Impact of Viral and Host Genetic Factors on Antiretroviral Treatment Outcome in South African HIV-1 subtype C infected AIDS patients Carole Lorraine Wallis A thesis submitted to the Faculty of Health Sciences, University of the Witwatersrand, in fulfillment of the requirements for the degree of Doctor of Philosophy Johannesburg, 2009 ii DECLARATION I, Carole Lorraine Wallis declare that this thesis is my own work. It is being submitted for the degree of Doctor of Philosophy in the University of the Witwatersrand, Johannesburg. It has not been submitted before for any degree or examination at this or any other University. ?????????.. ????..day of???????..2010 iii DEDICATION This thesis is dedicated to my family, my parents, Norman and Shirley, my sisters, Elizabeth and Lindsay, without their love, support and understanding this thesis would have not been possible. From them I have learnt that success is not a destination; but a journey. iv PUBLICATIONS & PRESENTATIONS ARISING FROM THIS STUDY Publications: Papers: 1. Wallis C.L., Bell C., Rubel D., Papathanasopoulos M.A., Venter F., Sanne I., Stevens W. 2007. Emerging HIV-1 Drug Resistance Patterns from two Johannesburg clinics on the South African ARV rollout program. Southern African HIV Medical Journal, June, 41-2. 2. Wallis C.L., Erasmus L., Varughese S., Ndiweni D., Stevens W. 2009. Surveillance of drug resistant mutations in HIV-1 subtype C children failing antiretroviral therapy. The Pediatric Infectious Disease Journal, 28, 1123-5. 3. Wallis C.L., Mellors J.W., Venter F., Sanne I., Stevens W. 2009. Varied HIV Drug Resistance Patterns Among Patients on Failing Antiretroviral Therapy in the South African National Roll-out Programme. In press, Journal of AIDS. 4. Wallis C.L., Papathanasopoulos M.A., Lakhi S., Karita E., Kamali A., Kaleebu P., Sanders E., Anzala O., Bekker L.G., Stevens G., Rinke de Wit T.F., Stevens W. 2009. Affordable in-house antiretroviral drug resistance assay with good performance in HIV-1 subtype C. In press, Journal of Virological Methods. Conference presentations: 1. Wallis C.L., Papathanasopoulos M.A., Sanne I., Stevens W. 2006. Monitoring HIV-1 Drug Resistance in South Africa. WITS Faculty of Health Science Research Day, Johannesburg, South Africa. v 2. Wallis C.L., Bell C., Boulme R., Papathanasopoulos M.A., Venter F., Sanne I., Stevens W. 2007. Emerging HIV-1 Drug Resistance Patterns from two clinics on the South African ARV rollout program, CROI, Los Angelos, USA. 3. Wallis C.L., Papathanasopoulos M.A., Rinke de Wit T.F., Stevens W. 2007. Subtype C specific In-house HIV-1 Drug Resistance Assay, 5th European HIV Drug Resistance Workshop, Cascais, Portugal. 4. Wallis C.L., Erasmus L., Varughese S., Ndiweni D., Stevens W. 2008. Surveillance of drug resistant mutations in HIV-1 subtype C children failing antiretroviral therapy. CROI, Boston, USA. 5. Wallis C.L., Stevens W., Venter F., Sanne I. 2008. Antiretroviral-Drug Resistance Patterns from patients failing the national roll-out programme in South Africa. Antiviral therapy 13 suppl 3: A164. 6. Wallis C.L., Sanne I., Venter F., Mellors J.W., Stevens W. 2009. Varied Drug Resistance Profiles following First-line Regimen Failure in the South Africa Antiretroviral Program. CROI, Montreal, Canada. 7. Wallis C.L., J.W. Mellors, W.D.F. Venter, Sanne I., Stevens W. 2009. Varied patterns of HIV-1 drug resistance among patients on failing first-line antiretroviral therapy in the South African national roll-out programme Antiviral Therapy 14 Suppl 1:A181. 8. Wallis C.L., Varughese S., Technau K., Stevens W. 2009. HIV drug resistant mutations in HIV-1 subtype C children failing antiretroviral therapy in South Africa Antiviral Therapy, 14 Suppl 1:A184. vi 9. Wallis C.L., Mellors J.W., Venter W.D.F, Sanne I., Stevens W. 2009. Protease inhibitor resistance is uncommon in patients on failing second-line lopinavir/r containing regimen in South Africa Antiviral Therapy; 14 Suppl 1:A183. 10. Wallis C.L., Papathanasopoulos M.A., Conradie F., Ive P., Orrell C., Zeinecker J., Sanne I., Wood R., McIntyre J., Stevens W. 2010. Early Switch based on virological failure reduces complexity of HIV-1 drug resistance. CROI, San Francisco, USA. vii ABSTRACT Background: The availability of highly active antiretroviral (ARV) treatment in the South African government sector has reduced the morbidity and mortality associated with HIV-1 infection. However, ARV drug resistance and toxicity are major obstacles to achieving and maintaining virus suppression, but there is no provision for ARV drug resistance testing in the public sector. To date, most studies of ARV drug resistance in HIV-1 reverse transcriptase (RT) and protease (PR), are based on sequence data from HIV-1 subtype B, whereas subtype C is the predominant circulating subtype in South Africa. Moreover, host genetic polymorphisms associated with ARV drug toxicity have not been investigated in South African populations. This study evaluated viral and host genetic factors associated with ARV treatment outcome in 812 ARV drug-naive South African AIDS participants enrolled on the CIPRA-SA study from Johannesburg and Cape Town. Methodology: An affordable in-house genotyping protocol (subtype C specific) was established and validated to monitor the emergence of ARV drug resistance. This assay was used to genotype all CIPRA-SA participants failing the first- and second-line ARV drug regimens. Allellic discrimination assays to identify the G1344A, A6986G, G516T and C3435T SNPs in CYP3A4, 3A5, 2B6 and MDR-1, respectively, associated with ARV metabolism and absorption were performed. Results: The in-house ARV drug resistance assay successfully genotyped 95% of patient samples, including non-C subtypes from 8 African sites. Treatment failure was experienced in 371 participants, mainly due to toxicity (n=134) or virological failure viii (n=83). Overall, CIPRA-SA participants with a lower CD4+ T-cell count at study onset were more likely to experience viral failure. Genotyping using the in-house assay revealed that 6 participants had ARV drug resistance mutations at study entry. Treatment failure of 58 participants was a result of ARV drug resistance mutations, whereas 19 had no known ARV drug resistance mutations. The most frequent mutations were M184V (67%) and K103N (50%). K65R was present (3%) and one participant harboured TAMs. Longitudinal genotypic analysis showed that NNRTI mutations accumulated at a rate of one per three months left on failing therapy. No PR mutations were detected amongst participants experiencing second-line failure. The four SNPs analysed occured in similar frequencies between a background and the CIPRA-SA cohort. Furthermore, no statistically significant association could be found between these four SNPs and viral failure and/or toxicity. Conclusion: Overall, HIV-1 subtype C-infected individuals receiving ARV therapy develop many of the known subtype B drug resistance mutations. However, the ARV drug resistance patterns in the closely monitored CIPRA-SA cohort were less complex compared to published data from the region, confirming that more frequent viral load monitoring, genotyping, and a virological failure cut-off value of 1000 RNA copies/ml ensure a better prognosis, and preserve future ARV treatment options. ix ACKNOWLEDGEMENTS ? I would like to thank my supervisors, Professor Wendy Stevens and Dr Maria Papathanasopoulos for their continual guidance, encouragement and support. ? National Institute of Health (NIH, USA) sponsored Comprehensive International Program of Research on AIDS (CIPRA) network, Grant U19 AI53217 ??Safeguard the Household?? study for funding and sample material. ? The National Health Laboratory Service (NHLS) and The Department of Molecular Medicine and Hematology, University of the Witwatersrand for funding. ? The staff of the genotyping laboratory, namely, Catherine Bell, Esrom Legadima, Lindiwe Skhosana and Christinah Mutuku for their support. ? Furthermore, I would like to thank the staff of the department of Molecular Medicine and Haematology for their encouragement and interest in my work, particularly Mrs Pamela Horsfield and Dr Lesley Scott. x TABLE OF CONTENTS PAGE Declaration ii Dedication iii Publications & Presentations iv-vi Abstract vii-viii Acknowledgements ix Table of Contents x-xii List of Figures xiii List of Tables xiv-xv Nomenclature xvi-xvii Preface xviii Chapter 1: Introduction 1-45 1.1. Background 1 1.2. Introduction to HIV 2-8 1.2.1. Structure of HIV-1 3-4 1.2.2. Lifecycle of HIV-1 5-8 1.2.2.1. Viral Attachment and Entry 6 1.2.2.2. Uncoating and Reverse Transcription 6 1.2.2.3. Viral Integration 7 1.2.2.4. Transcription and Translation 7 1.2.2.5. Assembly, Budding and Maturation 8 1.2.2.6. Consequences of the HIV-1 replication strategy 8 1.3. HIV-1 Disease Progression to AIDS 9-12 1.3.1. Acute Infection 9 1.3.2. Asymptomatic Phase 10 1.3.3. Symptomatic Phase and progression to AIDS 10 1.3.4. Initiation of highly active antiretroviral therapy 11 1.3.5. Factors influencing disease progression to AIDS 11 1.4. Antiretroviral Agents 13-26 1.4.1. Targeting viral entry 13 1.4.2. Targeting the Reverse Transcriptase (RT) Enzyme 13-17 1.4.3. Targeting the Integrase Enzyme 18-19 1.4.4. Targeting the Protease Enzyme 19-20 1.5. Factors Influencing Treatment Outcome 27-38 1.5.1. ARV drug Toxicity 28-29 1.5.2. Viral Factors 29-32 1.5.2.1. HIV-1 Drug Resistance 29-32 1.5.2.2. Diagnostic Assays to monitor for the development of HIV-1 drug resistance 32-33 1.5.3. Host Factors: 34-38 1.6. Guidelines for Monitoring HIV-1 Treatment Management 39-45 1.6.1. Developed Countries 39 1.6.2. Developing Countries 39-45 Chapter 2: Materials and Methods 46-68 xi 2.1. Participant samples used in this study 46-54 2.1.1. Patient Samples used in the Development of appropriate assays 48 2.1.1.1. Viral Factors 48 2.1.1.1.1. Routine Patient Samples for in-house HIV-1 drug resis-tance assay development 48 2.1.1.1.2. External Quality Assurance Panels for in- house HIV-1 drug resistance assay validation 48 2.1.1.2. Host Factors 49 2.1.1.2.1. Control Group for host genetic single nucleotide polymer-phisms (SNPs) study 49 2.1.2. CIPRA-SA cohort used for the Evaluation of viral and host genetic factors 49-54 2.1.2.1. Schedule of events for participants enrolled in the CIPRA-SA study 50 2.1.2.2. ARV drug Treatment Regimens 51-52 2.1.2.3. CIPRA-SA participants 52 2.1.2.4. Toxicity, adherence, virological and immunological failure 53-54 2.2. Development of an in-house assay for HIV-1 drug resistance testing 54-64 2.2.1. Extraction of viral RNA 54-55 2.2.1.1. Manual 54 2.2.1.2. Automated 55 2.2.2. Amplification of extracted viral RNA to cDNA 55-58 2.2.3. Dideoxy Sequencing 58 2.2.4. Analysis of Generated Sequences 59 2.2.5. ViroSeq Assay 59-60 2.2.6. Comparison of sequences obtained in the in-house and ViroSeq sequencing assays 61 2.2.7. Nucleotide sequence homology between the two assays 61-62 2.2.8. ARV drug resistance mutation profiles 62 2.2.9. Sequence Primer Mismatch analysis 62 2.2.10. Subtype and Phylogenetic Analysis 63 2.3. Viral Factors affecting ARV treatment outcome in the CIPRA-SA cohort. 63-64 2.3.1. Determination of HIV-1 ARV drug resistance in the CIPRA-SA cohort 63 2.3.2. Data Analysis 64 2.3.3. Emergence of HIV-1 ARV drug resistance mutations overtime 65 2.4. Assays to detect 4 host single nucleotide (SNPs) that impact on ARV metabolism and absorption 65-68 2.4.1. Genomic DNA extraction procedure 65 2.4.2. DNA Quantification 66 2.4.3. Identification of human genetic variants CYP3A4, 3A5, 2B6 and MDR-1 66-67 xii 2.4.4. Data Analysis 67-68 Chapter 3: Results 69-103 3.1. Development and Evaluation of an in-house HIV drug resistance assay 69-81 3.1.1. Viral RNA extraction 69-70 3.1.2. RT-PCR amplification of viral RNA 71-72 3.1.3. Cycle Sequencing and analysis 72-73 3.1.4. Full Validation of the in-house HIV-1 drug resistance assay on patient samples 73-79 3.1.5. In-house Validation with the EQA Panel Results 79-80 3.1.6. In-house Validation with non-subtype C samples 80-81 3.2. Emergence of HIV-1 drug resistance on the CIPRA-SA ?Safeguard the Household? project 82-93 3.2.1. Description of the CIPRA-SA Cohort 82-83 3.2.2. Baseline sequences of the virologically failing samples 83-85 3.2.3. HIV-1 ARV drug resistance at viral failure time point 86-90 3.2.4. Accumulation of mutations 90-93 3.3. Second-line failures on the CIPRA-SA cohort 94-96 3.3.1. Baseline Mutations of the second-line CIPRA-SA patients 94-95 3.3.2. Failure Mutations of the second-line CIPRA-SA patients 95-96 3.4. Characterisation of host polymorphisms in the CIPRA-SA cohort 97-103 Chapter 4: Discussion 104-128 Appendix A:Division of AIDs Table for Grading the Severity of Adult and Pediatric Adverse Events 129-150 Appendix B: Ethics Clearance Certificate and Consent Forms 151-164 Appendix C:Update of the Drug Resistance Mutations in HIV-1: December 2008 165-173 Appendix D: Viral Loads, Sequence Similarity, Mutation Patterns and Subtypes of the 90 samples used in the HIV-1 ARV drug resistance in-house validation. 174-179 Appendix E: Baseline CIPRA-SA demographics of the 83 patients that experience viral failure. 180-184 Appendix F: 83 CIPRA-SA patients with viral failure. 185-191 Appendix G: ViroSeq versus In-house Cost Analysis 192-193 Appendix H: Nurse management is not inferior to doctor management of antiretrovirals: The CIPRA South Africa randomized trial 194-219 References 220-251 xiii LIST OF FIGURES PAGE 1.1 HIV-1 group M subtype distribution. 3 1.2 Cross sectional representation of the structure of HIV-1. 4 1.3 The lifecycle of HIV-1. 5 1.4 HIV-1 disease progression from primary infection to AIDS. 12 1.5 Reverse Transcriptase enzyme. 15 1.6 Diagrammatic representation of the viral reverse transcriptase (RT) transcribing its RNA to cDNA prior to integration. 17 1.7 HIV-1 integrase enzyme. 18 1.8 HIV-1 protease enzyme. 20 2.1 Flow diagram of samples. 47 2.2 Graphic representation of the PCR and sequencing primers used in the in- house HIV-1 ARV drug resistance assay. 57 2.3 Alignment of two sequences 62 2.4 An example of a graphic representation of the allelic discrimination analysis software. 67 3.1 The 1.55kb fragment obtained with the in-house ARV drug resistance assay. 71 3.2 Subtype similarity plot for sample VAL087. 74 3.3 A radial phylogenetic tree was constructed from the 90 nucleotide alignments obtained from the in-house ARV HIV-1 ARV drug resistance assay, using neighbour-joining and the Kimura two-parameter distance matrix. 75 3.4 The ViroSeq chromatogram from patient VAL004. 78 3.5 Alignment of sequencing primers and patient sample sequence. 79 3.6 Diagrammatic representation of the CIPRA-SA patients with viral failure. 87 3.7 Frequency of the HIV-1 ARV drug resistance mutations associated with NRTI resistance in the 67 CIPRA-SA participants failing ARV therapy as a result of 2 consecutive viral loads greater than 1000 RNA copies/ml. 88 3.8 Distribution of NNRTI mutations from patients accessing a failing EFV- or NVP-containing regimens. 89 3.9 Development of NRTI and NNRTI mutations over time. 91 3.10 Accumulation of NNRTI mutations in NVP versus EVF exposed patients. 92 3.11 Accumulation of NNRTI mutations in NVP versus EFV-exposed patients, with previous MTCT. 92 3.12 Amino acid sequence of the 4 longitudinal sequences obtained from participant 236081. 93 3.13 Distribution of second-line baseline mutations prior to starting the second- line regimen. The M184V and K103N mutations are the most prevalent mutations. 95 3.14 Frequency of the CYP3A4 SNP G1344A in 82 HIV-1 negative samples. 98 3.15 Frequency of the CYP3A5 SNP A6986G in 75 HIV-1 negative samples. 99 3.16 Frequency of the CYP2B6 SNP G516T in 75 HIV-1 negative samples. 100 3.17 Frequency of the MDR-1 SNP C3435T, in 71 HIV-1 negative samples. 101 xiv LIST OF TABLES PAGE 1.1 All FDA approved ARVS 21-26 1.2 Examples of known polymorphisms, frequencies within ethnic groups, and enzymatic activity of cytochrome P450s. 38 2.1 CIPRA-SA Schedule of events 51 2.2 Demographics of 812 participants at the two CIPRA-SA sites. 52 2.3 Sequences of primers used for amplification and sequencing of nucleic acids. 57 3.1 Comparison of samples extracted using the manual ViroSeq extraction method versus the automated MagNaPure extraction method. 70 3.2 Sequence similarity between sequences obtained using the ViroSeq Amplification module and amplification with primers designed in-house. 72 3.3 Sequence homology for 45 patient samples obtained from comparison of ViroSeq and in-house sequencing primers. 73 3.4 ARV drug resistance mutation profiles and clinical significance of samples that successfully amplified using the in-house assay, but failed to amplify using the ViroSeq assay. 76 3.5 ARV drug resistance mutation profiles and clinical significance of samples that had differences in HIV-1 ARV drug resistance profiles. 77 3.6 Samples from the EQA panel that were sequenced with the ViroSeq and In-house assays, indicating subtype, mutation pattern and homology. 80 3.7 The number and (percentage) of primers which failed to amplify per subtype. 81 3.8 Distribution of subtype per African site. 81 3.9 Baseline characteristics of the CIPRA-SA Participants. 83 3.10 Baseline polymorphisms and mutations linked to HIV-1 ARV drug resistance of 22 CIPRA-SA participants who later experienced viral failure on the CIPRA-SA study. 85 3.11 Second-line outcome of the 61 patients accessing second-line regimen. 94 3.12 Second-line Baseline Demographics of the 61 patients that were switched to a second-line regimen. 95 3.13 Baseline and failure characteristics of the 21 participants that experienced failure on the second-line regimen. 96 3.14 Genotype frequencies of the 4 SNPs in the CIPRA-SA cohort and the HIV-1 negative control cohort. 102 3.15 Allele frequencies of the 4 genotypes examined from the patients that experience toxicity versus those that did not on the CIPRA- SA cohort. 102 3.16 Allele frequencies of the 4 genotypes examined from the patients 103 xv that experienced viral failure versus those that were virologically suppressed on the CIPRA-SA cohort. 4.1 A summary of the ARV drug resistance studies emerging from first-line failures in four African countries 123 D1 Viral Loads, Sequence Similarity, Mutation Patterns and Subtypes of the 90 samples used in the HIV-1 ARV drug resistance in-house validation. 175-179 E1 Baseline CIPRA-SA demographics of the 83 patients that experience viral failure. 181-184 F1 83 CIPRA-SA patients with viral failure. 186-191 G1 ViroSeq versus In-house Cost Analysis 193 xvi NOMENCLATURE 3TC-Lamivudine ABC=Abacavir ACTG-Adult AIDS Clinical Trial AIDS-Acquired Immunodeficiency Syndrome ALT-alanine aminotransferase ARV-antiretroviral AST-aspartate aminotransferase AZT-zidovudine CDC-Centre for Disease Control cDNA-complimentary DNA CPZ-chimpanzee CRF-circulating recombinant forms CYP450-cytochrome P450 d4T-stavudine DAIDs-Division of AIDS DART-Development of Antiretroviral Therapy in Africa ddC-zalcitabine ddI-didanosine DDT-Dithiothreitol DLV-delaviridine FBC=Full Blood Count EFV-efavirenz EI-entry inhibitors EQA-external quality assurance ETR-Etravarine FTC=Emtricitabine gp-glycoproteins gp120-glycoprotein 120 gp41-glycoprotein 41 HAART-highly active antiretroviral therapy HIV-Infection with Human Immunodeficiency Virus IAS-International AIDs Society Kaletra-lopinavir boosted with ritonavir KAVI-Kenya AIDs Vaccine Initiative LTR-long terminal repeat MDR-1-Multi-drug resistant type 1 MGPs-Magnetic Glass Particles xvii MuLV-Murine Moloney NA-Not Available ND-Not Done NHLS-National Health Laboratory Service NIH-National Institute of Health NNRTI-non- Nucleoside Reverse Transcriptase Inhibitors NRTI-Nucleoside Reverse Transcriptase Inhibitors NVP-nevirapine PBMCs-Peripheral Blood Mononuclear Cells p17-protein 17 p24-protein 24 PHRU-perinatal HIV research unit P-gp-P-glycoprotein PIs-Protease Inhibotors PR-protease RT-reverse transcriptase SGS-single genome sequencing SIV- Simian immunodeficiency virus SM-sooty mangabey SNPs-single nucleotide polymorphisms SOWETO-South West Township TAMs-thymidine analogue mutations TB-M. tuberculosis TNF=tenofovir UNAIDS-United Nations Program on HIV/AIDS UGT-UDP-glucuronosylatransferases V-valine Vpr-viral proteins R VQA-Virology Quality Assurance WHO-World Health Organization w-week xviii PREFACE Several events initiated and steered the direction of this study. At the time the study was planned (January, 2005), the South African government had just initiated the antiretroviral (ARV) roll-out program (April, 2004) and 50000 HIV-1 infected individuals were receiving ARV therapy. It was therefore envisaged that to support these treatment programs, affordable and appropriate laboratory monitoring is essential. Currently, the South Africa government has enrolled 870000 HIV-1 infected patients onto ARVs and a greater understanding of host genetic and viral factors that impact on ARV treatment outcome in South Africa is required. 1. Chapter 1: Introduction 1.1. Background Infection with Human Immunodeficiency Virus (HIV), the causative agent of Acquired Immunodeficiency Syndrome (AIDS) has resulted in a worldwide pandemic, with reports from the Joint World Health Organization (WHO) and the United Nations Program on HIV/AIDS (UNAIDs) estimating that a total of 33.4 million individuals worldwide were living with HIV infection by the end of 2008, with an additional 2.7 million newly infected during 2008 (UNAIDs, 2009). Furthermore, there were an estimated 2.0 million HIV/AIDS related deaths of which 1.7 million were adults during 2008 (UNAIDs, 2009). These staggering numbers ensure that the HIV-1 pandemic remains a serious public health challenge throughout the world. Although in some areas of the world, the HIV-1 epidemic appears to be on the decline, this is not the case in most of sub-Saharan Africa where the prevalence of HIV-1 is still increasing. Furthermore, 67% of all adults and children infected with HIV-1 reside in sub-Saharan Africa (UNAIDs, 2009). South Africa remains the epicenter of the HIV pandemic, with an estimated prevalence of 10.6% and 5.21 million people infected, with approximately one-fifth of reproductive South African women being HIV-1 positive (Statistics South Africa, 2009). 1 1.2. Introduction to HIV HIV exhibits remarkable genetic diversity, resulting in several different types and subtypes. HIV is divided into two distinct types namely, HIV-1 and HIV-2 (Centres for Disease Contol, 1982). HIV-1 accounts for the majority of infections globally, as a result of increased virulence and ease of transmission (Centres for Disease Contol, 1982); whereas HIV-2 is mainly concentrated in foci in West Africa and co-infection with HIV- 1 are common in these areas (Gottlieb et al., 2003). HIV-1 infection resulted from chimpanzee (SIVcpz)-to-human transmission, and HIV-2 infection resulted from sooty mangabey (SIVsm)-to-human transmission. HIV-1 is classified into three groups: the "major" group M, the "outlier" group O and the "new, or non M non O" group N, each group reflecting a different cross-species transmission. Both group O and N are restricted to west and central Africa and are extremely rare; whereas group M makes up approximately 90% of the infections worldwide (Wainberg, 2004). Group M is composed of nine subtypes (A, B, C, D, F, G, H, J and K), two sub-subtypes (A1, A2 and F1, F2) and 43 circulating recombinant forms (CRFs; see http://www.hivweb.lanl. gov/CRFs /CRFs.html for updates). In Europe, North and South America, most HIV-1 infections are with subtype B (Figure 1.1). By contrast, in Africa most subtypes are represented, with subtype A and D occurring in the highest frequency in central and eastern Africa and subtype C in Southern Africa (Papathanasopoulos et al., 2003; Figure 1.1). HIV-1 subtype C is responsible for over 50% of all infections worldwide (Buonaguro et al., 2007). 2 Figure 1.1: HIV-1 group M subtype distribution. Subtype B is found predominantly in North and South America, Europe and Australia; whereas subtype C is found predominantly in Southern and Eastern Africa and India (https://pathmicro.med.sc.edu/lecture/hiv6.htm). 1.2.1. Structure of HIV-1 HIV-1 is a retrovirus and belongs to the lentivirus genus. The virus is spherical and comprised of an envelope and the core. The envelope consists of a lipid bilayer, made up of approximately 72 viral envelope glycoprotein complexes (arranged as trimers) and different host derived proteins (Collier and Schwartz, 1999). Trimeric viral glycoproteins (gp) present in the lipid bilayer include the external glycoprotein 120 (gp120) and the transmembrane glycoprotein 41 (gp41). Below the lipid membrane is the matrix protein 17 (p17) containing the cone shaped viral capsid (p24; Gelderblom et al., 1998). The viral capsid surrounds two single-stranded HIV-1 RNA molecules, as well as viral 3 proteins necessary for replication, such as nucleoprotein p7-gag, p9-gag, the reverse transcriptase p51(RT), RNase H (p66), protease p15 (PR) and integrase p32. All the enzymes in the particle facilitate integration of viral genetic material into the host?s genome (Figure 1.2). The HIV-1 genome is approximately 9.7 kb and made up of two identical long terminal repeat (LTR) regions which flank three major genes gag, pol and env. There are a further 2 regulatory genes tat and rev, and 4 accessory genes vif, vpu, vpr and nef, which are not an absolute requirement for viral replication in vitro. Figure 1.2: Cross sectional representation of the structure of HIV-1. The lipid bilayer containing the gp41 and gp120 trimeric proteins, and the capsid which encompasses the two single stranded RNA molecules and viral enzymes (adapted from https://www.aidsfactsheet.com). 4 1.2.2. Lifecycle of HIV-1 HIV-1 has an extremely successful replication cycle, which takes approximately 2.5 days. Over ten billion HIV-1 particles can be produced and cleared each day in an average HIV-infected person. A schematic diagram of the viral life cycle is depicted in Figure 1.3 (Turner and Summers, 1999). Figure 1.3: The lifecycle of HIV-1. The HIV-1 lifecycle is depicted from 1) attachment, fusion and entry into the cellular cytoplasm to reverse transcription, integration into host DNA and assembly, budding and final maturation to make infectious virions. Modified from (Turner and Summers, 1999). 5 1.2.2.1. Viral Attachment and Entry Once the HIV-1 particle enters the body it infects T-lymphocytes and/or macrophages expressing the CD4 receptor (Dalgleish et al., 1984, Klatzmann et al., 1984) by binding of the viral envelope gp120 to the CD4 receptor (King, 1994). The gp120-CD4 interaction results in a conformational change in gp120 which exposes the gp120 coreceptor binding sites that are able to bind to either CCR5 or CXCR4, or both (Alkhatib et al., 1996, Dragic et al., 1996; Figure 1.3). The binding of the viral particle to the co-receptors results in further conformational changes in the envelope gp41. The gp41 forms a six helix bundle resulting in fusion of the viral and host membranes. 1.2.2.2. Uncoating and Reverse Transcription After fusion of the cellular and viral membranes, the HIV-1 core containing viral proteins enters the host cytoplasm (Turner and Summers, 1999; Figure 1.3). The viral capsid disintegrates releasing the single-stranded viral RNA and the viral enzymes: RT, integrase and PR. The RT transcribes the single-stranded RNA into complementary DNA (cDNA), and the viral RNA is degraded through the RNase H activity. The RT is extremely error-prone, introducing mistakes with each replication cycle (estimated misincorporation rate of 3x10-5 per base per replication cycle), which give rise to numerous quasispecies circulating within the same patient. 6 1.2.2.3. Viral Integration In the cytoplasm, integrase binds to specific sequences located at the ends of the viral DNA. This binding ?recruits? viral proteins such as Vpr (viral proteins R) and host cellular factors which form the preintegration complex. The integrase enzyme then excises two nucleotides from the 3? ends of the viral DNA (3? end processing) in preparation for strand transfer. The preintegration complex then moves into the nucleus by the aid of cellular co-factors, where it integrates into the host DNA. Integrase nicks the host DNA, strand transfer takes place and the host DNA repair mechanisms join the viral and host DNA together (Fish et al., 2010). 1.2.2.4. Transcription and Translation The integrated viral DNA either becomes latent or is transcribed into at least 30 mRNA species (Peterlin and Trono, 2003). The transcribed mRNA is spliced several different ways and moved into the cytoplasm were it encodes for the early regulatory proteins Tat and Rev. This facilitates the production of the remainder of the HIV-1 proteins. The alternative splicing patterns ensure all the structural and accessory components that are required for infectious virions are produced. The viral proteins (at least 16) are all translated within the cytoplasm, and some undergo post-translational modifications such as glycosylation and myristolation. The viral protease partially cleaves the Gag and Gag- Pol polyprotein, while host cellular proteases cleave the gp160 into the gp120 and gp41 components (Peterlin and Trono, 2003). 7 1.2.2.5. Assembly, Budding and Maturation All the viral proteins then travel to the plasma membrane where immature virions assemble in cholesterol rich lipid rafts and start budding. Gag is pivotal in assembly of the virions by recruiting the required host and viral factors. As each new virus buds from the host cell, it takes away with it the host cell?s outer lipid membrane, within which the viral gp120 and gp41 is embedded. Once the virion is released, complete processing of the Gag protein by the viral protease is required to make a mature infectious HIV particle capable of infecting another CD4+ T-cell (Turner and Summers, 1999). 1.2.2.6. Consequences of the HIV-1 replication strategy The short replication cycle, high numbers of virions produced daily and the error prone RT lead to the rapid evolution of HIV-1 (high genetic diversity). At least one error is introduced per virion during each replication cycle. Thus genomes or quasispecies with each possible mutation are generated daily. This ultimately allows HIV-1 to escape host immune surveillance, establish antiretroviral (ARV) drug resistant variants, affect accurate diagnoses and impact on the development of effective ARV drugs, microbicides and HIV-1 vaccines. 8 1.3. HIV-1 Disease Progression to AIDS Adults generally acquire HIV-1 by sexual transmission, blood transfusions and sharing of intravenous needles for drug usage. In infants, transmission can occur vertically from mother to child in utero, during birth, or through breastfeeding. The 3 major stages of HIV-1 disease progression to AIDS are shown in Figure 1.4a. 1.3.1. Acute Infection The acute phase of infection can last up to six months post transmission. During this stage the virus infects CD4+ T-cells and results in a rapid depletion of the memory CD4+ T-cells, in the gut-associated lymphoid tissue of the gastrointestinal tract (Brenchley et al., 2004, Guadalupe et al., 2003, Veazey et al., 2001). This depletion results in a loss of most of the mucosal CD4+ memory T-cells, which is thought to contribute to the disease progression to AIDS (Douek et al., 2006). Furthermore, there is a high level of viral replication (measured as viral load; RNA copies/ml) as there is no or limited host immune control. There is an initial depletion of peripheral CD4+ T-cells, but as the host immune system becomes activated (particularly the anti HIV-1 CD8+ cytotoxic T lymphocytes) it is able to control the viral replication, resulting in a rapid decline of viral load and restoration of the CD4+ T-cell counts. Furthermore, proviral DNA integrated into host DNA persists as viral reservoirs in resting CD4+ T-cells (Chun et al., 1995). At least 50% of new infections (transmissions) occur during the acute phase. 9 1.3.2. Asymptomatic Phase The viral load reaches a set point, which is indicative of the rate of disease progression to AIDS (Fauci et al., 1996). This phase can last for up to ten years and during this time the patient generally has no symptoms, but the virus continues to replicate at low levels and infects CD4+ T-cells. Over time, the immune system loses the battle against HIV-1, and CD4 + T-cells gradually decline. 1.3.3. Symptomatic Phase and progression to AIDS CD4+ T-cell depletion is characterized by the emergence of opportunistic infections. When the CD4+ T-cell counts reach a critical level the individual is diagnosed with AIDS. Without the initiation of ARV therapy, people die within 2 years of an AIDS diagnosis. AIDS is classified by the Centre for Disease Control (CDC) as a positive HIV-1 test and fewer than 200 CD4+ T-cells per microlitre, or the development of any 26 opportunistic infections (common opportunistic infections such as: Pneumocystis jiroveci pneumonia; Mycobacterium avium complex; cytomegalovirus, M. tuberculosis (TB), toxoplasmosis; cryptosporidiosis and human papillomavirus or cancers that affect HIV-1 positive individuals (AIDS defining diseases; Figure 1.4a; http://www.cdc.gov/hiv/ resources/brochures/livingwithhiv.htm). 10 1.3.4. Initiation of highly active antiretroviral therapy When an AIDS diagnosis is made, highly active antiretroviral therapy (HAART) consisting of a combination of three antiretrovirals is introduced to slow or reverse the progression to AIDS and death. If HAART is successful it can effectively suppress viral replication and reduce the viral load to below detectable limits of commercially available assays (Figure 1.4b) within an average of 12 weeks (Fauci et al., 1996). This viral suppression can be maintained with optimal treatment and compliance for several years, however, in some cases viral rebound can occur during HAART. 1.3.5. Factors influencing disease progression to AIDS: Disease progression to AIDS can vary between individuals and can be as a result of host and viral genetic differences, age, co-infection with other microbes and the virulence of the virus which has infected an individual. There have been reported cases of patients that progress to AIDS within a short period of time after infection and these are known as rapid progressors, moreover, there are individuals which appear to remain healthy for an extended period of time after infection and are known as long-term non-progressors (5%), and there are a group with spontaneous control that maintain a viral load of less than 50 RNA copies/ml and have been termed elite controllers (1 in 300; http://www.elitecontrollers.org). 11 Figure 1.4 HIV-1 disease progression from primary infection to AIDS. a) in the absence of HAART; b) with the intervention of HAART, however, viral rebound can occur as a result of several different factors (Adapted from Fauci et al., 1996). 12 1.4. Antiretroviral Agents Extensive analysis of the HIV-1 lifecycle has resulted in the identification of several drug targets, namely, 1) viral entry (entry inhibitors [EI] such as Fusion Inhibitors and CCR5 coreceptor antagonists); 2) viral replication (Nucleoside Reverse Transcriptase Inhibitors [NRTIs] and non -NRTIs [NNRTIs]); 3) integration (Integrase inhibitors) and 4) viral processing (Protease Inhibitors [PIs]; Table 1.1). 1.4.1. Targeting viral entry Viral entry is a multistep process encompassing attachment, coreceptor binding and fusion. US Food and Drug Administrator (FDA) approved entry inhibitors include Enfuvirtide (T-20; fusion inhibitor), a synthetic peptide which competitively binds to the six helix bundle in gp41, thereby preventing the conformation changes required for fusion of the viral and cellular membranes, and Maraviroc (CCR5 coreceptor antagonist), a small molecule which binds to CCR5, thereby preventing binding of gp120 to the coreceptor. ARV drug resistance to entry inhibitors has been reported (Olson and Maddon, 2003). 1.4.2. Targeting the Reverse Transcriptase (RT) Enzyme The RT enzyme is used by HIV-1 to transcribe single stranded viral RNA into viral cDNA in the cytoplasm (Figure 1.3). A functional RT is a heterodimer comprised of two subunits; p66 and p51. The p66 is made up of the N and C-terminal polymerase and 13 RNase H domains, respectively. The p51 is processed by proteolytic cleavage of p66 and corresponds to the N-terminal domain of p66. The RT crystal structure has been compared to a right hand, which contains three subdomains, namely, fingers, palm and thumb (Figure 1.5). The p66 subunit has three catalytic residues which are exposed in nucleic acid binding. The DNA/RNA-dependent DNA polymerase activity is catalysed by the p66. The thumb (made up of two alpha helices) and the fingers hold the nucleic acid in place over the palm, which contains the polymerase active site (Jacobo-Molina et al., 1993, Kohlstaedt et al., 1992). As mentioned previously, the RT enzyme is extremely error prone resulting in a high level of incorrectly incorporated bases. These errors constitute either polymorphisms or mutations, which may change the amino acid sequence of the virus, and result in a conformational or charge change in the proteins produced. This in turn can result in the development of resistance to ARV drugs targeting the RT enzyme. The majority of currently used antiretroviral therapies (zidovudine [AZT], didanosine [ddI], ddC [zalcitabine], stavuidine [d4T] and Lamivudine [3TC]; Table 1 .1) are nucleoside analogues that competitively inhibit RT activity. By contrast, the non- nucleoside, non-competitive RT inhibitors including efavirenz (EFV) and nevirapine (NVP) act by irreversibly binding to the enzyme. 14 Figure 1.5: Reverse Transcriptase enzyme. The RT enzyme is in the shape of a hand with the ?palm? containing the catalytic site, and the ?thumb? and fingers hold the DNA in place during replication (http://www.biochem.ucl.ac.uk/bsm/xtal/teach/repl/rt.html). These two classes of drugs which target the RT enzyme, nucleoside/nucleotide reverse transcriptase inhibitors (NRTIs) and non-nucleoside reverse transcriptase inhibitors (NNRTIs) make up the majority of regimens used in HIV-1 treatment (see Table 1.1 for US FDA approved NRTIs and NNRTIs). NRTIs are essentially modified nucleotides/sides that when incorporated into the replicating strand result in chain termination. During ARV drug pressure the HIV-1 RT is able to develop resistance to these drugs by generating mutations. The genetic pathways to develop resistance to NRTIs can occur in two ways. Firstly, RT-residues that encode amino acids on the tips of the fingers (Figure 1.5) that come into direct contact with the dNTPs or NRTIs can mutate. These mutations affect the rate of binding and incorporation of nucleotides. Primary mutations associated with this type of 15 resistance are K65R, L74V, Y115F, M184V/I and Q151M and its associated mutations. Primary mutations are amino acid substitutions in critical positions of the enzyme that cause an immediate decrease in susceptibility to the drug, ultimately leading to virological failure. Further work performed on the M184V mechanism of resistance has shown that the mutation results in a steric hindrance to the correct binding of both 3TC and FTC to the active site of the RT (Sarafianos et al., 1999, Schinazi et al., 1993). The second mechanism of resistance towards NRTIs is an increased rate of excision of the NRTIs (Arion et al., 1998). This process is driven by adenosine triphosphate (ATP) and is caused by thymidine analogue mutations (TAMs) that occur close to the triphosphate binding site. As the number of TAMs such as M41L, D67N, K70E, L210W, T215Y/F, K219Q/E/N/K increase in the RT, the level of resistance increases. The NNRTIs (Table 1.1) are molecules which have a high affinity for the hydrophobic pocket of the RT enzyme (as described above; Figure 1.6). This results in the NNRTIs binding to the pocket, thereby inhibiting replication. Resistance develops when mutations occur in the hydrophobic pocket, which changes the overall charge of the protein and results in a decreased binding of the NNRTIs (Figure 1.6). The mutations that develop in the hydrophobic pocket result in cross-resistance to all first-generation NNRTIs (Table 1.1). Recently a second generation NNRTIs, Etravarine (ETR) has been released which unlike the first generation NNRTIs, is a highly flexible molecule resulting in a high genetic barrier to resistance. ETR is susceptible to viruses with the K103N mutation, which results in cross resistance to both EFV and NVP. The level of 16 susceptibility is determined using a weighted scoring system for each mutation (Lazzarin et al., 2007, Madruga et al., 2007). Interestingly, the hydrophibic pocket of the RT enzyme has been found to be poorly conserved across different HIV-1 groups, resulting in HIV-1 group O being naturally resistant to the first-generation NNRTIs (Descamps et al., 1997). The impact of the variation in the RT hydrophobic pocket of different groups on second-generation NNRTIs is unknown. Figure 1.6: Diagrammatic representation of the viral reverse transcriptase (RT) transcribing its RNA to cDNA prior to integration (a). When a non-nucleotide reverse transcriptase (NNRTIs) is introduced it binds to the hydrophobic pocket of the RT resulting in inhibition of the polymerization of the cDNA (b). However, the RT can develop mutations which result in a change of charge or configuration resulting in the NNRTIs being unable to bind (c; http://www.thebodypro.com/thebody/images /nnrti_ fig1.gif). a) b) c) 17 1.4.3. Targeting the Integrase Enzyme Once HIV-1 has infected the host cell and replicated the viral RNA into cDNA, the viral DNA is integrated into the host DNA (Figure 1.3). These steps are catalysed by the integrase enzyme. The integrase enzyme consists of three domains, namely, a catalytic core and the C- and N-terminal domains. All three domains are required for DNA integration, with the catalytic core being the initiator in the integration process (Figure 1.7). The C-terminus binds the host and viral DNA while the function of the N-terminus is still unknown (Fish et al., 2009). Figure 1.7: HIV -1 integrase enzyme. The catalytic site is represented by green, with the flanking C and N terminals in pink. (Image from http://www.web.chemistry. gatech.edu/~williams/ bCourse_Information/6521/protein/images/haller.gif). There is only one US FDA approved ARV in this class, Raltegravir, a strand transfer inhibitor; which prevents viral cDNA integration into the host genome. Resistance C- and N- terminals 18 develops as a result of amino acid changes in the catalytic site. Second-generation integrase inhibitors are currently being investigated, which are active against some raltegravir mutants (Cooper et al., 2008, Steigbigel et al., 2008). An additional class of integrase inhibitors (quinolones) is being investigated which blocks both 3? processing and strand transfer, however, these have not yet reached clinical trials (Thibant et al., 2009). 1.4.4. Targeting the Protease Enzyme The PR enzyme in HIV-1 is responsible for cleaving the newly transcribed viral Gag and Gag-Pol polyproteins to functional proteins essential for viral assembly (Figure 1.3). The PR enzyme is a homodimer consisting of two identical chains, referred to as A and B. These two chains are mirror images and are stabilized by the aliphatic residues in the hydrophobic core. This hydrophobic core surrounds the electronegative active site of the enzyme (Figure 1.8). There is a beta hairpin loop which covers the active site, which is flexible and allows substrate access to the active site by folding the glycine rich tips into the hydrophobic pocket. PR undergoes a conformational change as the cleft of the active site tightens around the neutral or positively charged substrate (Scott and Schiffer, 2000). This conformational change ensures proper cleavage of the substrate. 19 Figure 1.8: HIV -1 protease enzyme. The green represents the identical chains A and B which surround the hydrophobic active site (red arrow) (Modified from http://www.udel.edu/ chem/bahnson/chem645/websites/Mays/activesite.jpg) PIs (Table 1.1) are a powerful class of drugs which bind more tightly to the active site of the PR enzyme than the natural substrates and act as preferred substrates. They are therefore competitive enzyme inhibitors, resulting in the PR enzyme being unable to cleave polyproteins, thus reducing the amount of mature virions that are produced. Interestingly, HAART regimens that include PIs are often boosted by low-levels of ritonavir. Resistance to this class of inhibitors is similar to that of NNRTIs with mutations developing in the active site and glycine tips prohibiting the binding of the PIs. PIs have a high genetic barrier for resistance, and require an accumulation of major mutations to lose complete susceptibility to the PIs. 20 T ab le 1. 1: A ll FD A app ro ve d A R V S . In fo rm at io n ad op te d an d in co rp or at ed fr om C lin ic al C ar e O pt io ns (h tt p: // w w w .c lin ic al op ti on s. co m /H IV /) Dr ug C la ss B ra nd N am e G en er ic N am e A bb re - vi at io n M an uf ac t- ur er M od e of In hi bi ti on B as e A ct iv at io n R eq ui re d M et ab ol ol is ed /C at ab ol is m by A dv er se E ve nt s G en et ic B ar ri er M od e of re si st an ce M ut at io ns (P I- m aj or ) M ut at io ns (P I- m in or ) R ev er se T ra ns cr ip ta se I n hi b io tr s N uc le os id e R ev er se T ra ns cr ip ta se I nh ib it or s (N R T Is ) R et ro vi r Z id ov ud in e A Z T G la xo S m it hK li n e C ha in T er m in at i on Py ri m id in e Y es U nd er go ce llu la r ph os ph or yl at i on an d ca ta ly si s N au se a, he ad ac he , ch an ge s in b od y fa t, an em ia a nd bo ne m ar ro w su pp re ss io n H ig h ex ci si on M 41 L , D 67 N , K 70 R , L 21 0W , T 21 5Y /F , T 21 9Q /E N A V id ex D id an os in e dd I B ri st ol -M ye rs Sq ui bb C ha in T er m in at i on Pu ri ne Y es U nd er go ce llu la r ph os ph or yl at i on an d ca ta ly si s D ia rr he a, he ad ac he s, vo m iti ng , ra sh , pe ri ph er al ne ur op at hy , pa nc re at it is an d la ct ic a ci do si s H ig h di st in gu is h dN T P ve rs us m od if ie d ba se s K 65 R , L 74 V N A H iv id za lc ita bi ne dd C R oc he C ha in T er m in at i on Py ri m id in e Y es di sc on ti nu ed di sc on ti nu ed H ig h di sc on ti n ue d di sc on ti nu e d N A Z er it St av ud in e d4 T B ri st ol -M ye rs Sq ui bb C ha in T er m in at i on Py ri m id in e Y es U nd er go ce llu la r ph os ph or yl at i on an d ca ta ly si s Pe ri ph er al ne ur op at hy , la ct ic a ci do si s H ig h ex ci si on M 41 L , D 67 N , K 70 R , L 21 0W , T 21 5Y /F , T 21 9Q /E N A 21 T ab le 1. 1: A ll FD A app ro ve d A R V S . In fo rm at io n ad op te d an d in co rp or at ed fr om C lin ic al C ar e O pt io ns (h tt p: // w w w .c lin ic al op ti on s. co m /H IV /) E pi vi r L am iv ud in e 3T C G la xo S m it hK li n e C ha in T er m in at i on Py ri m id in e Y es U nd er go ce llu la r ph os ph or yl at i on an d ca ta ly si s H ea da ch e, N au se a, vo m iti ng , m al ai se , fa ti qu e, sl ee pl es sn es s, an or ex ia , di zz in es s, ra sh , de pr es si on , an em ia , ne ut ro pe ni a, in cr ea se am yl as e H ig h di st in gu is h dN T P ve rs us m od if ie d ba se s K 65 R , M 18 4V /I N A Z ia ge n A ba ca vi r A B C G la xo S m it hK li n e C ha in T er m in at i on Pu ri ne Y es U nd er go ce llu la r ph os ph or yl at i on an d ca ta ly si s hy pe rs en si ti vi ty H ig h di st in gu is h dN T P ve rs us m od if ie d ba se s K 65 R , L 74 V , Y 11 5F , M 18 4V N A V ir ea d T en of ov ir T N F G ile ad S ci en ce s C ha in T er m in at i on Pu ri ne N O U nd er go ce llu la r ph os ph or yl at i on an d ca ta ly si s R en al a nd M il d ga st ro in te st in al ad ve rs e ev en ts H ig h di st in gu is h dN T P ve rs us m od if ie d ba se s K 65 R , K 70 E N A E m tr iv a E m tr ic ita bi ne FT C G ile ad S ci en ce s C ha in T er m in at i on Py ri m id in e Y es U nd er go ce llu la r ph os ph or yl at i on an d ca ta ly si s H ig h di st in gu is h dN T P ve rs us m od if ie d ba se s K 65 R , M 18 4V /I N A 22 T ab le 1. 1: A ll FD A app ro ve d A R V S . In fo rm at io n ad op te d an d in co rp or at ed fr om C lin ic al C ar e O pt io ns (h tt p: // w w w .c lin ic al op ti on s. co m /H IV /) No n- N uc le os id e R ev er se T ra ns cr ip ta se I nh ib it or s (N N R T Is ) Fi rs t G en er at io n N N R T I V ir am un e N ev ir ap in e N V P B oe hr in ge r In ge lh ei m B in ds to ac ti ve Po ck et N A N O H ep at ic - C Y P3 A 4 R as h, fe ve r, po te nt ia l fo r hy pe rs en si ti vi ty re ac ti on L ow C ha ng e in c ha rg e of th e hy dr op ho bi c po ck et L 10 0I , K 10 3N , V 10 6A /M , V 10 8I , Y 18 1C /I , Y 18 8C /L /H , G 19 0A N A R es cr ip to r D el av ir di ne D L V P fi ze r B in ds to ac ti ve Po ck et N A N O H ep at ic - C Y P3 A 4, C Y P2 D 6 R as h L ow C ha ng e in c ha rg e of th e hy dr op ho bi c po ck et K 10 3N , V 10 6M , Y 18 1C , Y 18 8L , P2 36 L N A Su st iv a E fa vi re nz E F V B ri st ol -M ye rs Sq ui bb B in ds to ac ti ve Po ck et N A N O H ep at ic - C Y P2 B 6 C en tr al N er vo us Sy st em , R as h, T et ra ge ne ic L ow C ha ng e in c ha rg e of th e hy dr op ho bi c po ck et L 10 0I , K 10 3N , V 10 6M , V 10 8I , Y 18 1C /I , Y 18 8L , G 19 0S /A , P2 25 H N A Se co nd G en er at io n N N R T I In te le nc e E tr av ir in e E T R T ib ot ec B in ds to ac ti ve Po ck et N A N O H ep at ic - C Y P3 A 4, C Y P2 C 9, C Y P2 C 19 R as h, po te nt ia l fo r hy pe rs en si ti vi ty re ac ti on H ig h C ha ng e in c ha rg e of th e hy dr op ho bi c po ck et W ei gh te d Sc or in g Sy st em N A 23 T ab le 1. 1: A ll FD A app ro ve d A R V S . In fo rm at io n ad op te d an d in co rp or at ed fr om C lin ic al C ar e O pt io ns (h tt p: // w w w .c lin ic al op ti on s. co m /H IV /) Pr ot ea se I nh ib it or s (P Is ) Fo rt ov as e/ In vi ra se Sa qu in av ir SQ V R oc he B in ds to ac ti ve Po ck et N A N O H ep at ic - C Y P3 A 4 D ia rr ah ea , na us ea , dy sp ep si a, ab do m in al pa in , dy sl ip id em ia H ig h C ha ng e in c ha rg e of th e hy dr op ho bi c po ck et G 48 V , L 90 M 10 , 24 , 54 , 62 , 71 , 73 , 77 , 8 2, 8 4 N or vi r R ito na vi r- us ed in lo w co nc . to b oo st PI m et ab ol is m R T V A bb ot t B in ds to ac ti ve Po ck et N A N O H ep at ic - C Y P3 A 4 D ys li pi de m ia , G I ad ve rs e ev en ts H ig h C ha ng e in c ha rg e of th e hy dr op ho bi c po ck et N A N A C ri xi va n Su lf at e In di na vi r ID V M E R C K B in ds to ac ti ve Po ck et N A N O H ep at ic - C Y P3 A 4 K id ne y st on es , hy pe rb ili ru bi ne m ia , G I ad ve rs e ev en ts , in su li n re si st an ce H ig h C ha ng e in c ha rg e of th e hy dr op ho bi c po ck et M 46 I/ L , V 82 A /F / T , I 84 V 10 , 20 , 24 , 32 , 36 , 54 , 71 , 73 , 76 , 77 , 9 0 V ir ac ep t N el fi na vi r N F V A go ur o n Ph ar m a ce ut ic a ls B in ds to ac ti ve Po ck et N A N O H ep at ic - C Y P3 A 4 G I ad ve rs e ev en ts H ig h C ha ng e in c ha rg e of th e hy dr op ho bi c po ck et D 30 N , L 90 M 10 , 36 , 46 , 71 , 77 , 82 , 84 , 8 8 K al et ra L op in av ir /r it o na vi r L P V / r A bb ot t B in ds to ac ti ve Po ck et N A N O H ep at ic - C Y P3 A 4 G I ad ve rs e ev en ts , hy pe rt ri gl yc er id em ia H ig h C ha ng e in c ha rg e of th e hy dr op ho bi c po ck et V 32 I, I4 7V /A , V 82 A /F / T /S 10 , 20 , 24 , 33 , 46 , 50 , 53 , 54 , 63 , 71 , 73 , 76 , 84 , 9 0 24 T ab le 1. 1: A ll FD A app ro ve d A R V S . In fo rm at io n ad op te d an d in co rp or at ed fr om C lin ic al C ar e O pt io ns (h tt p: // w w w .c lin ic al op ti on s. co m /H IV /) R ey at az A ta za na vi r A T V B ri st ol - M ye rs Sq ui bb B in ds to ac ti ve Po ck et N A N O H ep at ic - C Y P3 A 4 H yp er bi li ru bi ne m ia H ig h C ha ng e in c ha rg e of th e hy dr op ho bi c po ck et I5 0L , I8 4V , N 88 S 10 , 16 , 20 , 24 , 32 , 33 , 34 , 36 , 46 , 48 , 53 , 54 , 60 , 62 , 64 , 71 , 73 , 82 , 85 , 9 0, 9 3 L ex iv a Fo sa m pr en av i r FP V G la xo S m it hK l in e B in ds to ac ti ve Po ck et N A N O H ep at ic - C Y P3 A 4 G I ad ve rs e ev en ts , hy pe rl ip id em ia , r as h H ig h C ha ng e in c ha rg e of th e hy dr op ho bi c po ck et I5 0V , I8 4V 10 , 32 , 46 , 47 , 54 , 73 , 76 , 8 2, 9 0 A pt iv us T ip ra na vi r T PV B in ds to ac ti ve Po ck et N A N O H ep at ic - C Y P3 A 4 G I ad ve rs e ev en ts , in tr ac ra ni al he m or rh ag e, dy sl ip id em ia H ig h C ha ng e in c ha rg e of th e hy dr op ho bi c po ck et L 33 F, Q 58 E , T 74 P 10 , 13 , 20 , 35 , 36 , 43 , 46 , 54 , 69 , 83 , 9 0 Pr ez is ta D ar un av ir D R V T ib ot ec B in ds to ac ti ve Po ck et N A N O H ep at ic - C Y P3 A 4 R as h H ig h C ha ng e in c ha rg e of th e hy dr op ho bi c po ck et A cc um ul at e ov er 3 m aj or m ut at io ns N A In te gr as e In hi bi to r Is en tr es s R al te gr av ir R A L M E R C K B in ds to ac ti ve Po ck et N A N O H ep at ic - U G T 1A 1 rh ab do m yo ly si s or m yo pa th y L ow C ha ng e in c ha rg e of th e hy dr op ho bi c po ck et Y 14 3R /H /C , Q 14 8H /K /R , N 15 5H N A 25 T ab le 1. 1: A ll FD A app ro ve d A R V S . In fo rm at io n ad op te d an d in co rp or at ed fr om C lin ic al C ar e O pt io ns (h tt p: // w w w .c lin ic al op ti on s. co m /H IV /) Fu si on I nh ib it or Fu ze on (T -2 0) E nf uv ir it id e E N F R oc he N A N O H ep at ic - ex ac t m ec ha ni sm un kn ow n Pe ri ph er al N eu ro pa th y, In so m ni a, de pr es si on , dy sp no ea , hy pe rs en si ti vi ty , hy po te ns io n D is ru pt s fu si on N A E nt ry I nh ib it or Se lz en tr y M ar av ir oc M V C B lo ck s C C R 5 co - re ce pt or N A N O U nk no w n D is ru pt s bi nd in g of C C R 5 an d H IV C XC R 4 us ag e N A 26 1.5. Factors Influencing Treatment Outcome There are several factors which can contribute to ARV treatment outcome. The overall outcome of ARV treatment is dependent on the interaction of the following factors: drug- drug interactions, non-compliance, environmental factors, ARV drug toxicity and an array of either viral or host genetic factors (Boulle et al., 2007, Carr and Cooper, 2000, Johnson et al., 2008, Haas et al., 2004, Haas et al., 2003, Rotger et al., 2005, Rotger et al., 2007). Drug-drug interactions can lead to insufficient drug bioavailability to adequately suppress viral replication. For example, drug interactions with concomitant therapy, in particular anti-tubercular drugs (Kashuba, 2005, Spradling et al., 2002) can alter the circulating concentration of ARV drugs. Non-compliance, as a result of complicated dosage requirements, adverse side effects or non-adherence leads to virological failure. Non-compliance can be monitored by clinical algorithms such as pill-count or treatment diaries, or in the laboratory by directly measuring the concentrations of PIs or NNRTIs in the patient?s peripheral circulation and indirectly via continued virological suppression. Environmental factors such as alcohol consumption and recreational drug usage via non- adherence may impact on treatment outcome. Other factors that may contribute to altered drug concentrations in the local South African environment include the use of traditional remedies such as St. John?s Wort and milk thistle (Henderson et al., 2002). Low drug concentrations result in continued viral replication, whereas high drug concentrations can lead to ARV toxicity in humans, both of these scenarios resulting in ARV treatment failure. 27 1.5.1. ARV drug Toxicity ARV drug toxicities are the most common cause of treatment failure. ARV drug toxicity can be acute or chronic and can result in several different complications (See Table 1.1). Examples of acute complications are lactic acidosis, hepatic toxicity (commonly associated with the use of d4T and ddI; (Boubaker et al., 2001, Carr and Cooper, 2000, Carr et al., 2000) and pancreatitis. Chronic toxicity related complications such as metabolic complications, diabetes, altered fat distribution, and myopathies (Carpentier et al., 2005, Grinspoon and Carr, 2005) are also observed. These toxicities can contribute to non-compliance and often result in a change of ARV treatment regimens. Interestingly, drug toxicities have been shown to occur in 16.5% of South Africa patients accessing similar regimens to those prescribed in the national roll-out programme (Boulle et al., 2007, Rosen et al., 2008, Wood et al., 2009). ARV drug toxicity is diagnosed by a combination of clinical and laboratory markers. Laboratory markers are routinely used to investigate pancreatic function (triglycerides and lipase); liver function (total bilirubin, aspartate aminotransferase [AST] and alanine aminotransferase [ALT]); renal function (creatinine) and lactate l evels when lactic acidosis is suspected. Toxicity can be graded using systems such as the Adult AIDS Clinical Trial (ACTG) adverse events table (Appendix A). ARV drug toxicity is generally considered relevant when the ALT, AST or creatinine levels are greater than grade 2. All grades of lipase and lactate levels are classified as adverse events. All other 28 laboratory markers must be greater than grade 3 to be considered clinically relevant, necessitating treatment switches. 1.5.2. Viral Factors 1.5.2.1. HIV-1 Drug Resistance Viral factors contributing to ARV treatment outcome are a direct result of the poor proof- reading capability of the HIV-1 RT enzyme during replication (see section on Lifecycle of HIV-1). As mentioned previously this results in either polymorphisms or mutations which reduce the efficacy of the ARV drugs. To date, most data looking at viral factors linked to treatment failure during ARV therapy has been generated from studies of patients infected with HIV-1 subtype B, or in vitro drug susceptibility assays using HIV-1 subtype B viral isolates. The emergence of HIV-1 genetic variants with mutations conferring resistance to the above mentioned ARV compounds (EIs, RTIs, Integrase Inhibitors and PIs) have been mapped to several genes in the viral genome. These substitutions are classified into primary mutations, leading to several-fold decreases in sensitivity to one or more ARV drugs, and secondary mutations, which may not result in significant decreases to ARV drug sensitivity but are associated with restoration of the original viral fitness in the presence of the inhibitors (Quinones-Mateu et al., 2008). Several HIV-1 databases constantly maintain and update detailed lists of known mutations conferring ARV drug resistance (genotypic), the degree of drug resistance associated with specific mutations (phenotypic) as well as providing algorithms for 29 predicting drug resistance (http://www.hiv.lanl.gov; www.hivdb.stanford.edu). For example, in HIV-1 subtype B the presence of T215Y confers resistance to d4T, as well as cross-resistance to AZT (Table 1.1) and tenofovir. By contrast, the presence of M184V causes resistance to Lamivudine (Table 1.1), but enhances susceptibility to AZT, d4T and tenofovir (Johnson et al., 2008). Furthermore, the presence of either the K103N or Y188L mutation can substantially reduce the clinical use of all currently available NNRTIs. Unlike the V108I and P225H which both confer resistance to EFV in combination with other NNRTI-associated mutations (Clavel et al., 2004; Table 1.1). Emerging data suggests that ARV drug resistance profiles for non-B subtypes vary, and in many instances the known subtype B profiles should not be directly extrapolated to other HIV groups/subtypes. In vitro data have indicated that HIV-1 group O viruses, as well as HIV-2, are naturally resistant to NNRTIs (Descamps et al., 1997, Witvrouw et al., 1999). There are also indications of variation in drug susceptibility within HIV-1 group M. For example, some HIV-1 subtype G strains are less susceptible to PIs (Descamps et al., 1997). In HIV-1 subtype C, which is responsible for over 50% of new infections worldwide, the presence of naturally occurring polymorphisms which have been classified as minor mutations in HIV-1 subtpye B PR, for example, M36I and L63P, could impact on the efficiency of PI against subtype C (Kantor, 2006). The clinical relevance of this for HIV-1 subtype C infected patients remains unclear, and further in vivo and in vitro studies are necessary to delineate how these naturally occurring polymorphisms can affect treatment outcome. These polymorphisms may result in a predisposed resistance to the ARV or result in novel mutations (Grossman et al., 2004). 30 In the case of novel mutations, the amino acid valine (V) occurs at codon 106 in both subtype B and C RT, however, as a result of a natural polymorphism at a nucleotide level, a subtype C patient treated with EFV has a 50% chance of developing the V106M mutation. This mutation has never been reported in subtype B infected patients on EFV. By contrast, they are likely to develop the V106A mutation under NVP pressure (Brenner et al., 2003, Morris et al., 2003). The K65R has recently been shown to occur in higher frequencies in the RT of HIV-1 subtype C patients administered d4T compared to HIV-1 subtype B (Hosseinipour et al., 2009, Orrell et al., 2009, Wallis et al., 2010). Recently, a study showed that this is a result of a homopolymeric region surrounding codon 65 resulting in the enzyme pausing and an increased frequency of the K65R mutation (Coutsinos et al., 2009). Furthermore, studies have shown that even within one subtype there can be different primary mutations, both leading to resistance. For example, a genotypic study evaluating and comparing the frequency and patterns of PR mutations from HIV-1 subtype C infected patients in Botswana and Ethiopia showed that subtype C viruses from Botswana developed Nelfinavir resistance (D30N) via a different mutation pathway than those from Ethiopia (L90M; Grossman et al., 2004). A comparison of two clinical trials using single dose NVP to prevent mother to child transmission, namely the HIVNET 012 and NVAZ, indicated that the prevalence of the K103N drug resistance mutation in the RT of HIV-1 subtype C (69.2%) was significantly higher than that of subtype A (19.4%) or subtype D (36.1%; Eshleman et al., 2005b). Moreover, NVP resistance was more frequent in 31 subtype C infected infants from Malawi (87%) versus subtype A or D infected infants from Uganda (46%; Eshleman et al., 2005a). 1.5.2.2. Diagnostic Assays to monitor for the development of HIV-1 drug resistance The emergence of HIV-1 drug resistance during HAART can be monitored in the laboratory through phenotypic and genotypic assays. Phenotypic assays are based on growing the HIV-1 primary virus isolates from the patient or pseudoviruses in the presence of different levels of ARVs. The amount of virus present is quantified and the level of susceptibility of the virus to each ARV is determined, as compared to a baseline sample or reference virus. Although phenotype testing gives a direct measure of resistance, it does not take into account the discrepancies that could arise from differences in metabolism of the ARVs between individuals (Shao et al., 2003). The tests are extremely expensive, time consuming, require highly skilled staff and as a result of the high risk to laboratory staff, need to be performed in bio-safety level 3 laboratories. This has resulted in population based sequencing assays (genotyping) becoming the gold standard. These assays are based on the generation of the PR, RT, Integrase or gp160 sequences followed by comparison to a consensus sequence to determine if there are any differences. Differences at codons linked to drug resistance are called mutations, and linked to the level of resistance for each ARV. There are currently two commercially available and FDA approved assays for monitoring ARV drug resistance to the RTIs and 32 PIs: ViroSeqTM HIV-1 Genotyping Assay version 2.0 (Celera Diagnostics, Alameda, CA, USA) and TruGene (Siemens Health Diagnostics, Deerfield, IL, USA). Both methodologies use population based sequencing and detect the presence of more than one nucleotide in the same sequence chromatogram position at proportions greater than 20%, reflecting the presence of quasispecies. These methods are fast, safe and reproducible. However, the commercially available assays are still expensive ($ 400 per test) and perform poorly with non-subtype B samples (Engelbrecht et al., 2007). Alternatively, there are more sensitive point mutation assays (not FDA approved) which can only detect a single known mutation at a time. These probes/primers are highly dependent on sequence similarity to ensure accurate detection (Beck et al., 2002, Palmer et al., 2003, Wallis et al., 2005). However, the sequence variability of HIV-1 poses numerous challenges for the implementation of these types of assays in different geographic regions. Novel sequencing technologies that detect minority variants such as, single genome sequencing (SGS; Kearney et al., 2008, Palmer et al., 2005) and more recently pyrosequencing have been developed (Varghese et al., 2009). Both these methodologies are prohibitively expensive ($750); require a huge initial capital outlay and highly skilled staff. Furthermore, studies are only beginning to emerge which indicate the clinical significance of detecting minority variants (Le et al., 2009, Varghese et al., 2009). 33 1.5.3. Host Factors: There are numerous host factors that have been linked to HIV-1 disease progression and treatment outcome (Carrington and O'Brien, 2003, Fellay et al., 2007, Gao et al. , 2001, Gatanaga et al., 2007, Thomas et al., 2009, Torno et al., 2008). However, for the purposes of this review, only the host genetic factors linked to metabolism and absorption of ARVs used in the South African roll-out program are discussed below. NRTIs are not metabolized but undergo a complex homostatic relationship of activation through several phosphorylating and dephosphorylating steps once in the cell (Balzarini, 1994, Stein and Moore, 2001). All other classes of ARVs are metabolized by enzymes known as cytochrome P450 (CYP450) and UDP-glucuronosylatransferases (UGT) in the gastro- intestinal tract (Haas, 2005, Haas et al., 2005, Mutlib et al., 1999, Ward et al., 2003). Genetic polymorphisms in CYP450 and UGT in different population groups have been linked to variations in metabolism of PIs and NNRTIs. The CYP450 superfamily is involved in transforming these compounds into reactive, electrophilic and water-soluble products (Lin and Lu, 1998). CYP450 enzymes are located in high concentrations in enterocytes and hepatocytes. The CYP450 enzymes 3A4/5, 2B6, 2C9, 2C19, 1A2, and 2D6 are induced and/or inhibited by the following ARVs: the NNRTIs-EFV, NVP or the PIs ritonavir, nelfinavir, indinovir amprenavir and saquinavir. Furthermore, the same enzymes are responsible for metabolizing these drugs. Enterocytes primarily contain CYP3A4/5 and hepatocytes contain all CYP450 enzymes (Lin and Lu, 1998). 34 CYP enzyme activity is exquisitely sensitive to environmental, chemical, and genetic influence. Both EFV and NVP act as inducers of CYP3A4, 5, 7 and CYP2B6 (Erickson et al., 1999, Fichtenbaum and Gerber, 2002, Hesse et al., 2001); whereas delaviridine (DLV) inhibits CYP3A4. Other PIs have mixed effects on CYP enzyme activity. CYP3A5*3 is the most frequent polymorphism of CYP3A5, the presence of which results in no protein expression and thus no enzymatic activity (Table 1.2). Moreover, when expressed, CYP3A5 represents at least 50% of the total hepatic CYP3A content, making it the most important genetic contributor to inter-individual differences in CYP3A- dependent drug clearance (Kuehl et al., 2001). CYP3A5 is more frequently expressed in livers of African Americans (60%) than in Caucasians (33%; Kuehl et al., 2001). Genetic variations have also been found to contribute to the expression and activity of CYP enzymes (see Table 1.2; Hustert et al., 2001, Kuehl et al., 2001, Givens et al., 2003). These polymorphisms can cause large inter-individual variability in ARV drug exposure and might account for the differences in drug response between different ethnic groups. For example, the CYP2B6 516TT genotype (conferring lower CYP2B6 activity) was associated with greater EFV exposure in a Swiss HIV Cohort Study (Rotger et al., 2005). This genotype is also found in greater frequency in African American and Ghanaian populations (Klein et al., 2005). 35 The CYP2B6 function can be impaired by single nucleotide polymorphisms (SNPs) present in the gene. Studies have shown that SNPs in CYP2A6 result in a decrease in EFV metabolism (di Iulio et al., 2009, Kwara et al., 2009b). Furthermore, EFV toxicity has been linked to the presence of SNPs in CYP2A6 and CYP2B6 (Wood et al., 2009). EFV dose adjustments in individuals with the genotype 516TT have been found to be beneficial (Gatanaga et al., 2007, Torno et al., 2008). However, recently it has been demonstrated that the UGT 2B7*1 and *2 alleles impact on the c oncentration of EFV in individuals (Kwara et al., 2009a), as a direct result of the glucuronidation process of UGT2B7 (Belanger et al., 2009). Absorption of ARVs into cells can occur either via passive diffusion (in the case of NRTIs) or active cell mediated transport (Hediger et al., 2004, Haas et al., 2003). Currently, over 350 transporters have been identified including those from the ATP binding cassette family (for example: MDR-1, MRP-4, MRP-5, MRP-8; Borst et al., 2007, Guo et al., 2003). SNPs in the transmembrane protein P-glycoprotein (P-gp) encoded by the multi-drug-resistance transporter (MDR-1) gene located on chromosome 7 have been linked to altered absorption of ARVs, particularly PIs (Pan et al., 2007, Shaik et al., 2007). Specific SNPs linked to absorption of ARVs are MDR-1 1236, 2677 and 3435. Most importantly, numerous studies have associated the MDR-1 C3435T polymorphism with P-gp expression (Zhu et al., 2004). A study by Saitoh et al., 2005 that evaluated P-gp polymorphisms in infants receiving HAART consisting of nelfinavir, EFV and an NRTIs, revealed that infants with the MDR-1-3435 CT genotype had a more rapid virologic response compared to those patients with the CC genotype. 36 By contrast, Haas et al., 2004 showed the MDR-1-3435 TT genotype was present in 20% of African Americans compared to 3% of Caucasians (Haas et al., 2004). This genotype has been linked to increased plasma and intracellular exposure of EFV, and increased plasma concentrations of NVP (Hasse et al., 2005, Rodriguez-Novoa et al., 2005, Rotger et al., 2005). 37 Table 1.2: Examples of known polymorphisms, frequencies within ethnic groups, and enzymatic activity of cytochrome P450s. Polymorphism Mutation Frequency (%) Enz ymatic Activity Caucasi an African Japanese Chinese Other CYP3A4*1 Wild-type 21 ND ND ND ND Decreased CYP3A4*2 Unknown 2.7 0 ND ND ND Unknown CYP3A4*3 Unknown 2 0 ND ND ND Unknown CYP3A4*4 Unknown 0 ND ND ND ND Decreased CYP3A4*5 Unknown 0 ND ND ND ND Decreased CYP3A4*6 Frameshift 0 ND ND ND ND Decreased CYP3A4*1A Unknown 8 59 ND ND 78 Senegalese 81 Ghana Decreased CYP3A4*1B (1) A290G 4-5 54-82 ND ND ND Increased CYP3A5*1 (2,3,4,) A698 4.9-5.6 ND 2.8 25 40Asian Increased CYP3A5*2 (3) C27289A 1-1.9 ND 0 0 0 Asian Unknown CYP3A5*3 (1,2,3, 4) 698G 70-76 77.6 74-93 76 60 Asian No Protein CYP3A5*4 ND 0 ND 0 0.5 ND Unknown CYP3A5*5 ND 0 ND 0.4 0.5 ND Unknown CYP3A5*6 (1,2) G14690A 0.1 10-22 0 0 0 Asian No Protein CYP3A5*7 ND 10-22 ND ND ND Unknown CYP3A5*3B C3705T; 3709-10ins G ND ND ND ND ND Unknown 3A7*1 Wildtype 92 38 Tanzan ia ND 72 83 Saudi Mainly expressed in infants 3A7*2 (5) 7*1/5*3 8 62 Tanzan ia ND 28 17 Saudi Increased (Mainly expressed in infants) 2B6*1 Wildtype 16 ND 68 ND ND ND 2B6*2 (6) C64T 5.3 ND 4.7 ND ND Unknown 2B6*3 (6) C777A 0.5 ND 0 ND ND Decreased 2B6*4 (6) A785G 4-32 ND 9.3 ND ND Decreased 2B6*5 (6,7) C1459T 9-14 ND 1.1 ND 0.5 Mongolian Decreased (In Females) 2B6*6 (6,7,8) G516T; A785G 16.4-25 ND 16.4 ND 20 Mongolian Decreased (associated with increase of EFV concentra- tion) 2B6*7 G516T; A785G; C1459T 3 ND 0 ND ND Decreased 1(Atanasova et al., 2005), 2(Kuehl et al., 2001),3(Hustert et al., 2001),4(Givens et al., 2003),5(Rodriguez- Antona et al., 2005),6(Lang et al., 2001),7(Davaalkham et al., 2009),8(Rotger et al., 2005),^ND=Not Done 38 1.6. Guidelines for Monitoring HIV-1 Treatment Management 1.6.1. Developed Countries In developed countries, patients are initiated onto HAART when their CD4+ T-cell count is 350 cells/mm3; however, this is dependent on the patient and recommendations are for patients to initiate HAART when they become diagnosed. Prior to initiation of ARVs, it is recommended that HIV-1 drug resistance testing is performed to aid in optimal ARV choice (Hirsch et al., 2008). The International AIDs Society (IAS)-USA and European AIDS Clinical Society guidelines recommend PI-based regimens initially and three to four monthly viral loads and CD4+ T-cell/counts (Hammer et al., 2008, Reiss et al., 2009). When viral suppression is achieved, CD4+ T-cell monitoring can be done less frequently (6 monthly). Viral failure is determined as an increase in viral load above 500 RNA copies/ml on two consecutive visits and the possibility of non-adherence or the presence of HIV-1 drug resistance is investigated (Hirsch et al., 2008, Reiss et al., 2009). 1.6.2. Developing Countries The recently published WHO guidelines for HIV-1 management and care have amended the immunological start point from 200cells/mm3 to 350cells/mm3, irrespective of clinical symptoms (WHO, 2009). The drug regimens recommended for first-line have also been changed to remove d4T, as a result of the disfiguring and potentially life threatening toxicity of this drug. It has been recommended that developing countries move towards 39 replacing d4T with AZT or TNF, depending on the cost implication in each country. Modifications to the time to switch from first- to second-line regimens (if available in country) have been made, recommending a switch in ARV drug regimen if the patient has a viral load of 5000 RNA copies/ml (when viral load monitoring is available). Second- line regimens should contain a PI and an NRTI-backbone as several studies have shown that PI monotherapy is linked to reduced viral suppression and an increase in viral rebound (Arribas et al., 2005, Cameron et al., 2008, Delfraissy et al., 2008, Escobar et al., 2006). Finally it has been recommended that developing countries begin to consider the development of third-line regimens. Currently, however, in developing countries ARV treatment monitoring is generally determined by immunological failure (CD4+ T-cell count) and most do not have second- or third-line regimens available. In contrast, the South African government initiated the comprehensive HIV/AIDS treatment plan which started providing access to AIDS patients with a CD4+ T-cell counts <200 cells/ mm3 to ARV drugs in April 2004. The regimen includes first-line: d4T (can be substituted for AZT if toxicity occurs), 3TC, NVP or EFV and ddI, AZT and Kaletra. These guidelines were revised to form the HIV and AIDS and STI strategic Plan for 2007-2011 (http://www.doh.gov.za/ docs/misc/stratplan-f.html). The South African President announced on World AIDS day (1st December 2009) that from April 2010 AIDS patients would be initiated on ARVs at 350 cells/mm3. 40 Despite these advances, numerous challenges still face the Strategic Plan. For example, the first-line regimen still contains d4T, but recommendations have been made to change this to AZT or TNF. The appropriate cut-off to determine virological failure has not yet been established, and currently in South Africa this level is 5000 RNA copies/ml, but recent consensus is to change this to 1000 RNA copies/ml. No provisions to monitor for the emergence of ARV drug resistance have been made. Other limitations and difficulties have been encountered with this programme, for example, the initial cost of both procurement of the ARVs drugs and implementation of the diagnostic assays required to monitor disease progression. Increasing access to ARVs and diagnostic assay for monitoring HIV disease progression in remote areas of South Africa has also been very difficult and resource draining. Despite these obstacles, mid-year 2009 national statistics revealed that although approximately 870 000 HIV-1 infected adults and children were receiving HAART, but an additional 1 630 000 South Africans are still in need (Statistics South Africa, 2009). Currently, the national ARV roll-out program has provision to perform routine chemistry and haematology tests such as liver and kidney function and lactose levels to monitor for adverse events associated with the ARVs prescribed (Table 1.1). The ARV roll-out programme also monitors the patients and viral response to the ARV drugs by performing CD4+ T-cell counts and viral load monitoring. To date, monitoring of the above mentioned parameters have identified approximately 10% of patients enrolled from mid 2004 to present have failed the first-line regimen as a result of either non-compliance, 41 possible emergence of viral resistance or ARV toxicity (Professor F. Venter personal communication). However, there are still no guidelines in South Africa (or any developing country) that recommend the use of HIV-1 ARV drug resistance testing at initiation (screen for transmitted drug resistance or resistance from mother-to-child-transmission [ MTCT] programmes) or at virological failure (see Table 1.1 for mutations associated with ARVs prescribed in the South African 1st and 2nd line regimens). This consideration in mainly based on the high cost of the assay, high cost of initial outlay to implement these tests and the level of skilled staff required. As a result there is currently limited HIV-1 drug resistance data available in South Africa. A small study investigating ARV drug resistance mutations that develop from preventing MTCT programmes show that in 53 infants whose mothers received single dose NVP at birth, 45.3% developed HIV-1 ARV drug resistance mutations which confer resistance to NVP and EFV, namely, Y181C (75%), K103N (25%), and Y188C (12%; (Martinson et al., 2007). Further studies have shown that the drug resistance mutations that appear in women after single dose NVP, K103N and Y181C, can persist in low levels for over a year after exposure (Loubser et al., 2006, Palmer et al., 2006). Three studies have reported on the ARV drug resistance mutations occurring on the national ARV roll-out programmes and have shown that the mutation profiles are similar to those observed in HIV-1 subtype B (Marconi et al., 2008, Orrell et al., 2009, Wallis et al., 2010). The major mutations found in these cohorts were M184V, K103N and V106M. 42 Interestingly, these studies observed a higher than expected frequency of the K65R mutation in these predominantly HIV-1 subtype C infected cohorts, compared to what has been observed in HIV-1 subtype B, a result of subtype C specific nucleotide polymorphisms around this codon (Coutsinos et al., 2009). Furthermore, a study by Wallis et al., 2010, looking at 226 patients on a failing first-line regimen in South Africa found that 11% of patients had more than 3 TAMs, this is in contrast to the 56% of patients with 3 or more TAMs reported from Malawi first-line failure data emerging from 94 patients on a failing first-line regimen (Hosseinipour et al., 2009). The increased frequency of TAMs in the Malawi study is attributed to an extended duration on a failing regimen prior to HIV-1 drug resistance testing or other factors. In contrast to data from HIV-1 subtype B patients with a longer duration on a failing regimen (Kuritzkes et al., 2004, Wallis et al., 2009b) showed that TAMs occurred in a higher frequency in the AZT- than the d4T-containing regimens. Although the South African national ARV roll-out programme is well designed to treat HIV-1 infected patients, the overall data collection between the clinic and laboratory is disjointed, making it difficult to link the clinical and laboratory data. This has resulted in limitations of overall data analysis on treatment outcome and this is why the Comprehensive International Programme of Research in AIDs in South Africa (CIPRA- SA) program with its careful longitudinal monitoring of patients on ARV treatment represents a good opportunity to study these factors. The CIPRA-SA ?Safeguard the household? study is a controlled randomised study of ARV therapy in a resource poor 43 setting, with the primary objective of evaluating the care given by primary health care workers and doctors. The first-line and second-line regimens are the same as the national ARV roll-out program allowing for a unique opportunity to examine the effects of the South African ARV roll-out programme in a well monitored cohort. This study has two study sites, the Chris Hani Baragwanath site situated in Soweto, Johannesburg and the Masiphumelele site in a poor stable community on the outskirts of Cape Town. Preliminary data from the government ARV roll-out program indicates that HIV-1 infected South African patients have a rapid virological response to HAART (Lisgaris et al., 2005), while approximately 10% fail therapy each year. It is an intriguing possibility that the frequency and presence of polymorphisms in both CYPs and MDR-1 influences response to HAART in this population. Thus the CIPRA-SA study offers the perfect cohort to investigate the impact of both viral and host genetics on ARV treatment outcome. The overall objective of this study was to determine the impact of viral and host genetics factors on antiretroviral treatment outcome in South African HIV-1 Subtype C infected patients receiving HAART in a well-defined cohort, with the aim of guiding future government programs. This was achieved by setting the following Secondary Objectives: 1. To develop a validated, affordable HIV-1 ARV drug resistance assay to monitor the development of ARV drug resistance on the CIPRA-SA cohort 44 2. To identify patients with virological failure on the CIPRA-SA study and establish the presence/absence of known ARV drug resistance mutations. 3. To establish the pharmacogenetic background with respect to cytochromes P450 and MDR-1 polymorphisms in the study cohort, as compared to a control cohort. 4. To correlate host genetic profiles (identified polymorphisms) to ARV treatment outcome (toxicity and viral failure). 45 2. Chapter 2: Materials and Methods 2.1. Participant samples used in this study A total of 2335 participant samples were used for various analyses throughout the course of this study (Figure 2.1). Two hundred and ninety HIV-1 positive samples and 10 samples from two external quality assurance (EQA) panels were used to develop and validate the in- house HIV-1 drug resistance assay. One thousand two hundred and twenty three HIV-1 negative samples were used to set up the assays for host genetics, and determine the background frequency of these single nucleotide polymorphisms (SNPs; Figure 2.1a). Subsequently, the newly validated and established assays were used with 812 HIV-1 positive participants from the CIPRA-SA ?Safeguard the household? cohort to determine viral and host parameters associated with ARV metabolism and absorption (Figure 2.1b). Ethical clearance for the use of patient sample material was obtained through the human ethics committee of the University of the Witwatersrand, Johannesburg, South Africa using the ethics clearance number: M-061025 (Appendix B). 46 a) b) Figure 2.1: Flow diagram of samples a) used in the development of the appropriate assays; b) used in the evaluation of the host and genetic factors on the CIPRA-SA cohort. 47 2.1.1. Patient Samples used in the Development of appropriate assays 2.1.1.1. Viral Factors 2.1.1.1.1. Routine Patient Samples for in-house HIV-1 drug resistance assay development Two hundred and ninety patient samples sent for routine HIV-1 testing were used in the development and validation of the in-house HIV-1 ARV drug resistance assay (section 2.2). One hundred and fifty six samples were obtained from patients accessing the national antiretroviral roll-out program that were sent for routine viral load (n=21) or HIV-1 drug resistance testing (n=135) as they appeared to be failing either the first (3TC, d4T, NVP/EFV) or second (AZT, ddI, Kaletra) line ARV drug regimens. All samples selected had a viral load greater than 1000 RNA copies/ml. A further, 134 samples from patients recently infected with HIV-1 that were sent for routine HIV-1 drug resistance testing and subtyping from countries throughout Africa were used to evaluate the effectiveness of the in- house assay on non-C subtypes circulating in the region. 2.1.1.1.2. External Quality Assurance Panels for in-house HIV-1 drug resistance assay validation Ten well-characterised plasma samples with a range of viral loads (3557-57005 RNA copies/ml) and a variety of HIV-1 subtypes were obtained from the National Institutes of Health (NIH) Division of AIDS (DAIDS) Virology Quality Assessment Program (VQA) Laboratory, Rush Institute, USA (http://www.hanc.info/labs/Pages/VQA.aspx; (Huang et al., 2005) and used to validate the in-house drug resistance assay (section 2.2). 48 2.1.1.2. Host Factors 2.1.1.2.1. Control Group for host genetic single nucleotide polymorphisms (SNPs) study One thousand, two hundred and twenty three anonymous, unlinked HIV-1 negative samples, sent for routine HIV-1 DNA testing in the PCR laboratory, National Health Laboratory Service (NHLS), Johannesburg, were randomly selected and processed in a blinded fashion as a control population because little data is available on the frequencies of certain of the cytochrome P450 (CYP450) and Multi-drug resistant type 1 (MDR-1) polymorphisms in the South African population. Thus, at the time of study design, the sample numbers required to determine statistically significant frequencies were unknown. For the purposes of this study, we assumed the prevalence of 15% occurrence in the population (http://www.ncbi.nlm .nih.gov/SNP/), thus an estimated minimum sample size of 1 223 individuals is sufficient to measure the true occurrence with 0.02 margin of error with 95% confidence intervals. The use of a control group is required to ensure there is no biased selection of a certain SNP examined in the HIV-1 positive patient group. 2.1.2. CIPRA-SA cohort used for the Evaluation of viral and host genetic factors Eight hundred and twelve participants from the CIPRA-SA ?Safeguard the household? study were used to investigate specific viral and host factors that may impact on ARV treatment outcome. The CIPRA-SA project is an NIH funded study (CIPRA grant: U19 AI53217-01, Principal Investigator Prof J McIntyre) which allowed for the establishment of this cohort to investigate whether HIV-1 related care provided by primary health care nurses was non- 49 inferior to doctors in a resource constrained environment. Subjects were eligible to participate in the CIPRA-SA study if they were HIV-1 positive, had a CD4+ T-cell count below 350 cells/mm3 and were ARV treatment naive (excluding previous single dose EFV that may have been administered to prevent MTCT). There were two clinic sites involved in this study, namely, the perinatal HIV research unit (PHRU), Chris Hani Baragwanath in South West Township (SOWETO) and Masiphumelele in the Cape region. The Chris Hani Baragwanath site was chosen because of the high HIV-1 prevalence in SOWETO. SOWETO was established in the 1930?s and borders the mining belt of Johannesburg. The population has been overwhelmingly black and consists of approximately 1.3 million people. Masiphumelele was established in 1997 and is situated on the outskirts of Cape Town. It is a poor, stable community with about 10500 residents. The HIV clinic in Masiphumelele was established in 2000 and designed as a primary health care clinic, with a focus on medical care for women and children. 2.1.2.1. Schedule of events for participants enrolled in the CIPRA-SA study: Participants presenting at each clinic were screened by the primary health care sisters or doctors, and only enrolled in the study if they were HIV-1 positive, had either a severe CDC category B AIDS defining illness or history of a CDC category B/C illness or a CD4+ T-cell count of less than 350cells/mm3, were ARV drug-na?ve, willing to give w ritten informed consent and met all other study inclusion criteria. All 812 participants enrolled in the study were then subjected to physical examinations and blood draws (for laboratory tests and sample storage) as outlined in Table 2.1. The participants that met these criteria were started on ARV therapy as described in section 2.1.2.2. 50 Table 2.1: CIPRA-SA Schedule of events Phase 1 Visits Screening PreEntry Basel ine- W0* W 2 W4 W 8 W 12 Every 12 weeks until study completed Phase I Terminati on Visit HIV ELISA X Pregnancy Test (for all females of child bearing potential) X X X X X X As Needed Assess for Symptoms of Tuberculosis X X X X X X X Hepatitis B Surface Antigen X Biochemistry/FBC ^ X X [X] X X X X Reflex Test (if indicated) if on NVP& HIV-1 Viral Load X X X X X X X CD4+ T -cell Count X X X X X X X Dried Blood Spots X X X Pill Count/syrup measurement X X X X X Compliance/ Adherence Discussion X [X] X X X X X if on NVP Resource Utilization X X X X X X X X Well Being Questionnaire X X X X X 24 weekly after week 12 Dispense Study Drugs X X X X X Virological Resistance Testing X WHEN CLINICALLY OR VIROLOGICALLY INDICATED X Pharmacokinetics Sample (trough) X X X X X X Plasma/ PBMC % Storage X [X] X X X X if on NVP *w=week; ^=Full Blood Count; &NVP=Nevirapine; %PBMC=Peripheral Blood Mononuclear Cell 2.1.2.2. ARV drug Treatment Regimens The first-line regimen of the CIPRA-SA study contained d4T, 3TC and EFV for adults over the age of 16 years. However, if the woman was of child-bearing age and unwilling to use two forms of contraception, EFV was replaced by NVP. Lopinavir boosted with ritonavir 51 (Kaletra) replaced both EFV and NVP if the woman was pregnant when therapy was initiated. Furthermore, a one drug switch was permitted if drug toxicity was observed (section 2.1.4.4 below). The second-line regimen for participants not receiving TB-treatment consisted of a combination of AZT, ddI and Kaletra. Participants that required TB-treatment in either first- or second-line regimen were given an EFV-based regimen or were withdrawn from the protocol. 2.1.2.3. CIPRA-SA participants: The 812 participants were enrolled into the CIPRA-SA study from the two sites over a period of 2 years (Feb 2005-Jan 2007). Participants were monitored longitudinally for a minimum period of 96 weeks (actual follow up was dependent on patient failure), up to a maximum of 3.5 years from baseline. The demographic data of the CIPRA-SA participants is shown in Table 2.2. The participants were randomized into two arms (primary health care sister vs. doctor monitoring) and monitored three monthly to determine whether HIV management from primary health care workers was non-inferior to doctors. Table 2.2: Demographics of 812 participants at the two CIPRA-SA sites. Site Number of participants randomized Male (%) Female (%) Johannesburg 449 126 (28.1 %) 323 (71.9 %) Masiphumelele 363 113 (31.1 %) 250 (68.9 %) Total 812 239 (29.4 %) 573 (70.6 %) 52 2.1.2.4. Toxicity, adherence, virological and immunological failure: Toxicity (laboratory adverse events) noted at any of the visits were graded according to the DAIDs table for Grading the Severity of Adult and Pediatric Adverse Events (http://rcc.tech- res-intl.com, Appendix A). All laboratory indicators recorded above Grade 3 were reported as adverse events to the CIPRA-SA safety team, which took appropriate action. Adherence monitoring was performed at every scheduled visit. This was done by pill counting and adherence was determined as a percentage of number of pills taken/total pills prescribed. A percentage greater than 90% was considered satisfactory adherence. Participants with adherence less than this underwent re-counselling. Virologic failure was defined by either of the following criteria: 1) A less than 1.5 log drop in viral load measurements from baseline to week 12 or 2) Two consecutive viral load measurements of greater than 1000 RNA copies/mL after week 24 If viral failure was experienced, participants were switched to the PIs-based second-line regimen. Immunological Failure was defined as a CD4+ T-cell drop of 15% from study entry with a viral load between 400 and 1000 RNA copies/ml. If immunological failure was experienced participants were switched to the PIs-based second-line regimen. 53 Whole blood was collected in EDTA and Heparin tubes and centrifuged, according to standard protocols (www.aactg.org/) to isolate plasma and peripheral blood mononuclear cells (PBMCs). The processed plasma and PBMCs were stored at -70oC and -150oC until used. 2.2. Development of an in-house assay for HIV-1 drug resistance testing An RT-PCR and sequencing method to amplify the subtype C pol region implicated in ARV drug resistance was designed and optimized, and compared to the gold standard ViroSeq assay. Ninety of the 290 HIV-1 positive samples selected from samples sent for routine drug resistance were assessed using the new method as well as the gold standard ViroSeq. 2.2.1. Extraction of viral RNA 2.2.1.1. Manual Briefly, 500ul of plasma was centrifuged for 1 hour at 23000xg at 4?C, to pellet the HIV -1 viral particles. The viral pellet was resuspended in 600ul lysis buffer to lyse the viral particles and release the HIV-1 RNA. The RNA was purified by centrifugation using two 600ul washes using isopropanol and cold 70% ethanol, respectively and the supernatant discarded. The RNA pellet was eluted in 50ul elution buffer containing RNase inhibitors to ensure intact RNA was obtained. The eluted RNA was stored at -70?C, until used. 54 2.2.1.2. Automated Viral RNA was extracted from plasma separated from whole blood collected in EDTA tubes using the Roche MagNa Pure LC instrument (Roche, Mannheim, Germany) and the MagNA Pure LC Total Nucleic Acid Isolation Kit (Roche, Mannheim, Germany), according to manufacturer?s instructions. Briefly, 200ul of plasma was aliquoted into the sample cartridge and placed onto the MagNa Pure analyser where the samples were lysed, proteins digested using proteinase K and the nucleic acids were bound to the silica surface of the Magnetic Glass Particles (MGPs) allowing for them to be magnetically separated. Unbound debris was removed from the beads with several washing steps and the isolated nucleic acids eluted in 100ul of elution buffer. The extracted RNA was stored at -70oC until used in all other experiments (unless otherwise indicated). Fifteen samples were used to compare the manual and automated extraction samples. The automated extraction system allows for 32 samples (30 test samples and 2 controls) to be isolated in 90 minutes. The use of an automated system allows for an increase in throughput, improved purity of the isolated sample and decreases the risk of cross-contamination. 2.2.2. Amplification of extracted viral RNA to cDNA An RT-PCR protocol was designed and optimized to amplify the 1.55 kB required pol region from extracted viral RNA. Amplification and sequencing primers were designed against sequences from the Los Alamos Database (www.hiv.lanl.gov/) and aligned against HIV-1 subtype C sequences to ensure there was a high homology between the primers and the HIV- 1 subtype C sequences. Two PCR primers spanning nucleotides 2047 to 3594 according to 55 the HXB2 sequence , and five sequencing primers which result in the generation of fully bidirectional sequences were designed (Figure 2.2). These five sequencing primers ensure sequencing primer coverage according to the HXB2 sequence from nucleotide 1912 to 3576 (PR1-99 and RT1-240; with primer CWCS5 a back-up for primer CWCS4). The extracted viral RNA was used to generate HIV-1 cDNA using the in-house RT-PCR protocol described below. Extracted viral RNA was synthesized into cDNA using the reverse primer CWR1 (Table 2.3) and the Expand RT kit (Roche, Mannheim, Germany). Briefly, 2.5mM of the reverse primer CWR1 (Table 2.3, Figure 2.2) and 8ul of viral RNA were added together and incubated for 10 minutes at 65oC in the GeneAmp? PCR System 2700, (Applied Biosystems, Singapore). The samples were removed from the thermocycler and placed on ice. A mastermix containing 1mM dNTP (AB gene, Surrey, United Kingdom), 20U Protector RNase Inhibitor (Roche Mannheim, Germany), 10mM Dithiothreitol (DTT), 1x Expand RT buffer and 50U Expand RT (Roche Mannheim, Germany) were added to make a total volume of 20ul. The total volume of 20ul was incubated at 42oC for 60 minutes in the GeneAmp? PCR System 2700, (Applied Biosystems, Singapore). PCR amplification was performed using primers CWR1 and CWF1 (Table 2.3, Figure 2.2), 20ul of synthesized cDNA and the Expand High FidelityPLUSkit (Roche, Mannheim, Germany). This reaction was carried out in a total volume of 50ul containing 20ul cDNA, 0.4mM dNTPs (AB gene, Surrey, United Kingdom), 0.8umol of primers CWR1 and CWF1, 1xExpand High FidelityPLUSreaction buffer with 1.5mM MgCl2 and 2.5U Expand High FidelityPLUSenzyme blend (Roche, Mannheim, Germany). The cycling conditions consisted of an initial denaturation step of 94oC for 2 minutes, followed by 10 cycles of 94oC for 30 56 seconds, 54.5oC for 30 seconds and 72oC for 2 minutes, followed by 35 cycles of 94oC for 30 seconds, 55oC for 30 seconds and 72oC for 2 minutes increased by 10 seconds each cycle, and a final elongation step of 72oC for 10 minutes in the GeneAmp? PCR System 2700, (Applied Biosystems, Singapore). The PCR step was validated on 6 samples. Figure 2.2: Graphic representation of the PCR and sequencing primers used in the in - house HIV-1 ARV drug resistance assay. An amplicon of approximately 1.55kb is generated in the amplification step. The sequencing primers CWCS1-5 ensure a 1.25kb sequence with bidirectional coverage. The forward primers (CWF1, CWCS1 and CWCS2) are represented by the green forward arrow. The reverse primers (CWR1, CWCS3-5) are presented by the red arrows. Position 1-204 and 204 to 1563 on the blue line are the gag and pol genes, respectively. Table 2.3: Sequences of primers used for amplification and sequencing of nucleic acids Name Direction Sequence Location against the p o l gene Position on HXB2 Use CWR1 Reverse 5?-GCA TAC TTY CCT GTT TTC AG-3? RT349-355 3610-3594 RT and PCR CWF1 Forward 5?-GAA GGA CAC CAA ATG AAA GAY TG-3? 68codons before PR1 2047-2066 PCR CWCS1 Forward 5?-CCTCAAATCACTCTTTGGC-3? PR1-8 2253-2271 Sequencing CWCS2 Reverse 5?-AGAACTCAAGACTTTTGGG-3? RT83-89 2796-2814 Sequencing CWCS3 Forward 5?-TGCTGGGTGTGGTATTC-3? RT93-99 2846-2830 Sequencing CWCS4 Reverse 5?-TCCCTGTTCTCTGCCAATTC-3? RT300-308 3472-3453 Sequencing CWCS5 Reverse 5?-TGGTAAATTTGATATGTCCATTG-3? RT336-343 3577-3555 Sequencing Excess primers and buffers were removed from the 50ul of generated amplicon using microconcentrators, according to manufactures instructions (Celera Diagnostics, CA, USA). The PCR product was analyzed and quantified on a 2% agarose gel containing 30pmol ethidium bromide (Sigma, USA) in a 1xTAE buffer (Fermentas Life Sciences, Lithuania) and viewed under a UV transilluminator. The size and concentration of the DNA fragment was 57 identified by comparing it to a DNA Mass Ladder (MassRulerTM DNA ladder, Mix, ready-to- use Fermentas Life Sciences, Lithuania). 2.2.3. Dideoxy Sequencing The samples were diluted according to their concentration and dideoxy (chain termination) sequencing performed. Cycle sequencing was performed using a final volume of 0.16uMol of one of the five primers CWCS1-5 (Table 2.3, Figure 2.2), 13ul of PCR product (section 2.2.2), 0.5x BigDye? Terminator v1.1/3.1 Sequencing Buffer and 0.5x Ready Reaction Premix from the ABI PRISM? BigDye? Terminator version 3.1 cycle sequencing kit (Applied Biosystems, Foster City, CA, USA). This reaction was carried out in a total volume of 20ul. The cycling conditions consisted of an initial denaturation step of 96oC for 1 minute, followed by 25 cycles of 96oC for 10 seconds, 55oC for 5 seconds and 60oC for 4 minutes on a GeneAmp? PCR System 2700, (Applied Biosystems, Singapore). After cycle sequencing, unincorporated ddNTPs were removed by adding 80ul of 80% isopropanol (MERCK, Wadeville, Gauteng, South Africa) to each sample. Incubation for 15 minutes at room temperature was followed by a centrifugation step to pellet the sequence amplicon (45 minutes at 4000xg). The plate was immediately inverted to remove the supernatant by centrifugation for 1 minute at 700xg. To the dried pellet 20ul of Hi-DiTM Formamide (Applied Biosystems, Warrington, UK) was added. The sequencing step was optimized using 50 samples. 58 2.2.4. Analysis of Generated Sequences The DNA fragments now labeled with four different fluorescent dyes (one for each base; generated in sections 2.2.3) were loaded onto the ABI PRISM? 3100 Genetic Analyzer (Applied Biosystems, HITACHI, Foster City, USA). The sequence information was processed by the ABI PRISM ? 3100 Data Collection Software version 1.1 (Applied Biosystems, Foster City, USA). The sequence data was obtained from the ABI3100 genetic analyser and data was edited using the Sequencing analysis 3.3 program (Applied Biosystems, Foster City, USA), and the complete sequences encompassing the pol region of interest were assembled and manually edited using Sequencher version 4.7 (Genecodes, Ann Arbor, MI). Sequence data was submitted to the Stanford Database (http://hivdb.stanford.edu/index.html) to generate an HIV-1 ARV drug resistance report. 2.2.5. ViroSeq Assay The patient plasma obtained from section 2.1 and 2.2 were sequenced using the ViroSeqTM HIV-1 Genotyping System Version 2.0, Pack 1 (Celera Diagnostics, Alameda, CA, USA), as per manufacturers? protocol. Viral RNA was extracted for each of the samples as described in section 2.2.1.1. Twenty microliters of HIV-1 cDNA were generated from the isolated viral RNA using 10ul of reaction mix (Murine Moloney [ MuLV] reverse transcriptase, RNase Inhibitor and RT mix containing a specific reverse primer of unknown sequence) and 10ul of RNA. The 20ul of 59 cDNA was subsequently used as a PCR template, and added to 30ul of amplification mixture (AmpliTaq Gold, dUTP/UNG and a PCR mix containing HIV-1 specific primers, of unknown sequence). The PCR reaction was used to generate an approximately 1.8kb fragment including the coding sequence for HIV-1 protease (the entire protein, amino acids 1-99) and part of the HIV-1 reverse transcriptase (amino acids 1-324). The amplicon was purified using columns provided in the ViroSeq kit, as per manufacturer?s instructions. Twelve microlitres of primer mix was added to 8ul of appropriately diluted amplicon. Seven sequencing reactions were set up for each sample, and included 4 sense (A, B, C, D) and 3 anti-sense (F, G, H) primers. The cycling conditions were: 96oC for 10 minutes; 50oC for 5 seconds, 60oC for 4 minutes for 25 cycles (GeneAmp? PCR System 2700, Applied Biosystems, Singapore). After cycle sequencing unincorporated ddNTPs were removed as per the method described in section 2.2.3. The sequences obtained were assembled and analyzed on the ViroSeqTM HIV-1 Genotyping System Software Version 2.7 (Applied Biosystems, Foster City, USA). Manual reviewing and editing was performed, while the generated sequence was compared to a reference sequence. Once manual editing was completed the following files were saved: 1) FASTA file, containing the actual sequence; 2) GT file, containing a mutation list and 3) a report showing the mutations and ARV drugs no longer effective for the patient. The FASTA file was submitted to the REGA subtyping tool version 2 (http://dbpartners.stanford.edu /RegaSubtyping/). 60 2.2.6. Comparison of sequences obtained in the in-house and ViroSeq sequencing assays The data generated from the ViroSeq and in-house assays were analyzed and compared to determine 1) assay sensitivity by comparing the participant viral load ranges amplified by each method; 2) nucleotide sequence homology between the two assays and 3) assay accuracy by comparison of the HIV-1 ARV drug resistance mutation profiles generated by the two methods to ensure the same clinical information was obtained. 2.2.7. Nucleotide sequence homology between the two assays Nucleotide sequences generated from each of the samples by the two methodologies were aligned by the Clustal W method (http://www.ebi.ac.uk/clustalw/) to determine nucleotide mismatches between the two overlapping sequences. The mismatches were divided into two categories: partial and complete mismatch. A partial mismatch was classified as a mixture of two of more bases observed in one sequence, whereas only one of the bases was observed in the other sequence (Figure 2.3). A complete mismatch was classified as two different nucleotides at the same position on the two different sequences (Figure 2.3). Sequence similarity between the sequences obtained from the ?in-house? and ViroSeq assays were compared using a Hamming distance, this was done by: [Total number of differ ences/Total overlapping sequence length]x100 and represented as a percentage. The closer the Hamming distance is to 100 the stronger the sequence similarity (Hamming, 1950). 61 A) TAAAAAAGAAGGATRGTACTAAGTGGAGAAAATTAGTAGATTTCAGGGAACTCAATAAAA TAAAAAAGAAGGATAGTACTAAGTGGAGAAAATTAGTAGATTTCAGGGAACTCAATAAAA ** * ** * ** * ** * ** * * ** * ** * ** * ** * ** * ** * ** * ** * ** * ** * ** * ** * ** * ** * * B) ACTTCAGGAAATATACTGCATTCACCATACCTAGTATAAACAATGAAACACCAGGGATTA ACTTCAGGAAATATACTGCATTCCCCATACCTAGTATAAACAATGAAACACCAGGGATTA ** * ** * ** * ** * ** * ** * ** * ** * * ** * ** * ** * ** * ** * ** * ** * ** * ** * ** * ** * * Figure 2.3: Alignment of two sequences, the asterisks represent sequences that are completely homologous, the yellow highlighted bases represent a partial mismatch in A and a complete mismatch in B. 2.2.8. ARV drug resistance mutation profiles Mutation profiles of the sequences obtained from the in-house and ViroSeq methods were compared using HIV-1 drug resistance results obtained from the Stanford Database. The resistance reports generated were compared and samples that were not concordant in their mutation patterns had their chromatograms re-analysed. 2.2.9. Sequence Primer Mismatch analysis This analysis was only performed for the in-house assay, as the primer sequences for the ViroSeq assay are proprietary knowledge and thus unknown. Sequences generated using the in-house assay not completely bidirectional were aligned to the primer that failed in an attempt to identify potential primer sequence mismatches The sample and oligonucleotide primer sequences (CWCS1-5; Table 2.3) were aligned using Clustal W (http://www.ebi.ac.uk/Tools/clustalw2/index.html). 62 2.2.10. Subtype and Phylogenetic Analysis Sequences generated were subtyped using the published REGA subtyping tool version 2 (http://dbpartners.stanford.edu/RegaSubtyping/). Sequences were aligned with reference sequences from HVI-1 subtype A to K (www.hiv.lanl.gov/), using Clustal X (version 1.83; http://www.ebi.ac.uk/Tools/clustalX ). Neighbor-joining phylogenetic tree analysis was performed in MEGA version 4 (Tamura et al., 2007), using the Kimura two parameter model, to verify the REGA subtyping results. The stability of the nodes was assessed by bootstrap analysis (100 replicates), and bootstrap values greater than 70% were considered significant. 2.3. Viral Factors affecting ARV treatment outcome in the CIPRA-SA cohort. 2.3.1. Determination of HIV-1 ARV drug resistance in the CIPRA-SA cohort Viruses from patients failing ARV therapy (section 2.1.2) were sequenced using the newly developed in-house assay described in section 2.2 to determine if virological failure was attributable to the presence of ARV drug resistance mutations. Mutations were classified according to the IAS-USA mutation list (Johnson et al., 2008). All participants demonstrating failure of a first-line regimen had their baseline samples sequenced to determine if HIV-1 drug resistance was present prior to the initiation of therapy. The failure sample was then sequenced to determine if the development of resistance contributed to viral failure. 63 2.3.2. Data Analysis Subtype and phylogenetic analysis was performed as per section 2.2.8 and section 2.2.10. Statisitcal analysis was performed using Statistica version 8 (StatSoft Inc, Tulsa, OK, USA). The frequencies of the major and minor mutations were determined by dividing the total number of mutations over the total size of the cohort analysed. A non-linearized multivariate analysis (Mardia, 1967) was performed to determine if gender, age, viral load, CD4+ T-cell at baseline were linked to ARV treatment outcome with a 95% confidence level. The difference in frequency of the mutations associated with EFV and NVP exposure were compared using a non-parametric chi-Squared or Fishers Exact test (depending on the cohort size) with a 95% confidence level. A p-value of <0.05 was considered significant. 2.3.3. Emergence of HIV-1 ARV drug resistance mutations overtime Samples classified with virological failure as a result of HIV-1 drug resistance mutations (section 2.3.1) had any additional time-points with viral loads greater than 1000 copies/ml prior to failure sequenced using the in-house assay (section 2.2). All serial sequences obtained from each patient were aligned and compared, to determine how mutation patterns evolved over time. 64 2.4. Assays to detect 4 host single nucleotide (SNPs) that impact on ARV metabolism and absorption 2.4.1. Genomic DNA extraction procedure Genomic DNA was extracted from stored week 4 baseline PBMCs from 248 CIPRA-SA participants that consented for host genetic studies, and the 1223 control populations. Stored week 4 PBMCs were used because it did not compromise other potential studies. The PBMCs were defrosted and 100ul aliquoted (approximately 1 x106 cells) in a 1.5ml STARTAC tube. The cells were concentrated by centrifugation for 10 minutes at 2000g. The supernatant was removed and the cell pellet re-suspended in a total volume of 300ul of lysis buffer from the MagNaPure LC DNA Isolation Kit 1 (Roche Applied Science, Mannheim, Germany) and left at room temperature for 10minutes. The DNA was extracted using 200ul of the re-suspended cell pellets as per manufacturer?s instructions. The DNA from the 1223 HIV-1 negative controls were extracted from 100ul of whole blood using the MagNaPure LC DNA Isolation Kit 1 (Roche Applied Science, Mannheim, Germany), as per manufacturers instruction, and once HIV-1 negative status had been confirmed using the Roche Amplicor DNA version 1.5 (Roche Applied Science, Mannheim, Germany). 65 2.4.2. DNA Quantification The quantity and quality of extracted DNA was determined using the Thermo Scientific NanoDropTM Spectrophotometer (Thermo Fisher Scientific, MA, USA). Once the quantity of DNA was determined it was diluted to 25ng/ul using distilled water and 20ul aliquoted into one well per sample in a 96 well plate. The DNA samples were left at room temperature for 24 hours, to lyophilize. 2.4.3. Identification of human genetic variants CYP3A4, 3A5, 2B6 and MDR-1 Genotyping of each participant for the presence of SNPs in their CYP3A4, 3A5, 2B6 and MDR-1 genes was performed using fluorescently labeled minor groove binding (MGB) allele-specific probes purchased from the Assay-on-Demand TaqMan? SNP genotyping Assays (Applied Biosystems, https://products.appliedbiosystems.com). Participants were genotyped for CYP3A4 (1344G>T, 001_1344), CYP3A5 (6986 G>A, rs776746), CYP2B6 (516 G>T, rs3745274) and MDR -1 (3435 C>T, rs1045642). Amplification was performed using allele specific probes that were 5?fluorescently tagged with 6-FAM and VIC (Assay-on-Demand TaqMan? SNP genotyping Assays, Applied Biosystems, https://products.appliedbiosystems.com), 20ul of lyophilized DNA and 1xTaqMan? Universal PCR Master Mix, No AmpErase? UNG (Applied Biosystems, Foster City, USA) to a total volume of 20ul. The cycling conditions consisted of an initial denaturation step of 95oC for 10 minutes, followed by 50 cycles of 92oC for 15 seconds and a 66 combined annealing and extension step for 1 minute at 60oC. All amplification reactions were performed on the ABI 9700 real-time machine (Applied Biosystems, Foster City, USA). Post analysis was performed using the allelic discrimination analysis option on the SDS version 2.3 sequence detection software (Figure 2.4; Applied Biosystems, Foster City, USA). Figure 2.4: An example of a graphic representation of the allelic discrimination analysis software. This allows for easy identification of the 2 homozygous alleles (red and blue) and the 1 heterozygous allele (green). This clustering is determined by the fluorescence recorded in each well (sourced from examples in the SDS version 2.3 software, sequence detection systems, Applied Biosystems, Foster City, USA). 2.4.4. Data Analysis Statistical analysis was performed using Statistica version 8 (StatSoft Inc, Tulsa, OK, USA). The frequencies of the genotypes of the four SNPs were determined by dividing the total number of genetic variations over the total size of the cohort analysed. The difference in 67 frequency of the genotypes for each SNP was compared using a non-parametric chi-Squared or Fishers Exact test (depending on the cohort size) with a 95% confidence level. A non- linearised univariate analysis was performed to determine if SNP genotype was linked to ARV drug toxicity or viral failure. 68 3. Chapter 3: Results 3.1. Development and Evaluation of an in-house HIV drug resistance assay An optimised protocol to monitor the emergence of HIV-1 ARV drug resistance in a predominantly HIV-1 subtype C infected population was established. Overall, the protocol entailed an automated extraction of viral RNA and an in-house RT initiated PCR sequencing using the newly designed HIV-1 subtype C specific primers. 3.1.1. Viral RNA extraction A comparison of the HIV-1 ARV drug resistance profiles obtained from the manual and automated extraction methods on 15 randomly selected patient samples are shown in Table 3.1. The mutation profiles on the resistance reports generated using the Stanford database for all 15 samples were shown to be 100% homologous for 11/15 (73%) samples. Samples 4, 7, 9 and 10 had different mutation patterns when using the automated extraction versus the manual (number of disagreeing mutations ranging from 1-3). In patient 4 (96% sequence homology), 2 of the 3 differences in the HIV-1 ARV drug resistance mutations were as a result of partial mismatches and 1 was due to a complete mismatch. In all 4 cases, more mutations were detected by automated extraction. The difference in ARV drug resistance profiles may be attributed to improved sample extraction when using the automated MagNaPure extraction method. Thus, the automated extraction method was selected for use 69 in all subsequent experiments since in a routine laboratory setting it is advantageous to have an automated extraction step that increases the sample throughput and reduces hand on time. Table 3.1: Comparison of samples extracted using the manual ViroSeq extraction method versus the automated MagNaPure extraction method and amplified using ViroSeq . For each sample, the column for the HIV-1 ARV drug resistance profiles has the manual extraction method results (ViroSeq) above the automated extraction (In-house). Differences in mutation patterns are highlighted in bold. Sample number Viral Load (RNA copies/ml) HIV-1 ARV* drug resistance profiles Number of disagreeing mutations Sequence Similarity 1 2300 ViroSeq K65R, T69I, V75I, F77L, F116Y, V118I, Q151M, Y181C, G190A, K20R, M36I 0 98% In-house K65R, T69I, V75I, F77L, F116Y, V118I, Q151M, Y181C, G190A, K20R, M36I 2 2400 ViroSeq M184V, K103N, M36I 0 99% In-house M184V, K103N, M36I 3 5500 ViroSeq A62V, M184V, K103N, V106M, M36I, L63P 0 99% In-house A62V, M184V, K103N, V106M, M36I, L63P 4 9200 ViroSeq M184V, K103N, Y181C, M36I, L63P 3 96% In-house T69N, V75I/A/T, M184V, K103N, V106M, Y181C, M36I, L63P 5 11000 ViroSeq M184V, K101E, V106M, G190A, M36I 0 99% In-house M184V, K101E, V106M, G190A, M36I 6 37000 ViroSeq M184V, V108I, Y181C, K20M, M36I 0 98% In-house M184V, V108I, Y181C, K20M, M36I 7 38000 ViroSeq K65R, K219R, K103N, Y181C, G190A, K20R, M36I, L63P 1 99% In-house K65R, L74V , K219R, K103N, Y181C, G190A, K20R, M36I, L63P 8 53000 ViroSeq M184V, K103N, V108I, P225H, K20R, M36I, L63P 0 99% In-house M184V, K103N, V108I, P225H, K20R, M36I, L63P 9 92000 ViroSeq M36I, L63P 1 99% In-house D67G , M36I, L63P 10 130000 ViroSeq V75I/A/T, M184V, V106M, Y188C, K20R, M36I 1 96% In-house V75I/A/T, M184V, K103N , V106M, Y188C, K20R, M36I 11 150000 ViroSeq M36I 0 99% In-house M36I 12 600000 ViroSeq Q151M, V106M, G190A, M36I 0 99% In-house Q151M, V106M, G190A, M36I 13 670000 ViroSeq M36I, L63P 0 99% In-house M36I, L63P 14 800000 ViroSeq L10I, M36I 0 99% In-house L10I, M36I 15 Unknown ViroSeq M36I 0 99% In-house M36I *ARV=antiretroviral 70 3.1.2. RT-PCR amplification of viral RNA An RT-PCR protocol for HIV-1 subtype C specific amplification of an approximately 1.55kb fragment encompassing the entire PR region and most of the RT was successfully established (Figure 3.1). As a result of decreased amplification of the HIV-1 subtype C samples on the ViroSeq Assay (Engelbrecht et al., 2007), the ViroSeq amplification step was substituted with the in-house amplification step, while using the ViroSeq extraction and sequencing methods. Results from 6 patient samples of this initial validation are shown in Table 3.2. The mutation profiles on the resistance reports from all six samples were shown to be exactly the same when using the two amplification methods (overall sequence similarity 97-99%). In addition, the RT-PCR protocol was shown to successfully amplify 100% of all HIV-1 subtype C samples (section 3.1.4). Figure 3.1: The 1.55kb fragment obtained with the in -house ARV drug resistance assay. Lane 1-7 are HIV-1 subtype C samples with viral loads ranging from 1990-42800 RNA copies/ml, lane 8 is the positive control and lane 9 is the negative control. The molecular mass ladder is shown in lane 10. Samples 3 and 7 did not amplify and had viral loads 170000 and 185000 RNA copies/ml, respectively. 1 2 3 4 5 6 7 8 9 10 1500 10000 500 71 Table 3.2: Sequence similarity between sequences obtained using the ViroSeq Amplification module and amplification with primers designed in-house. Sample Sequence Similarity (%) Complete Mismatch of bases Number of disagreeing Mutations HIVDR1672 99% 0 0 HIVDR1674 99% 0 0 HIVDR1793 99% 0 0 HIVDR2269 99% 0 0 HIVDR3591 97% 0 0 HIVDR3696 99% 0 0 Average Similarity 98.7% 0 0 3.1.3. Cycle Sequencing and analysis The performance of the newly designed in-house sequencing primers on 45 previously genotyped samples (26 manual and 19 automated extractions) were compared to the ViroSeq primers (Table 3.3). The percentage homologies ranged from 92% to 99.77% compared to 98.92% to 100% for the manual and automated extractions, respectively. Differences were mainly a result of partial mismatches. 72 Table 3.3: Sequence homology for 45 patient samples obtained from comparison of ViroSeq and in-house sequencing primers. Sample Name (Manual) Sequence Similarity Sample Name (Automated) Sequence Similarity HIVDRMAN01 96.00% HIVDRAUTO27 99.38% HIVDRMAN02 97.00% HIVDRAUTO28 99.62% HIVDRMAN03 92.00% HIVDRAUTO29 99.78% HIVDRMAN04 96.00% HIVDRAUTO30 99.69% HIVDRMAN05 99.00% HIVDRAUTO31 99.46% HIVDRMAN06 98.80% HIVDRAUTO32 99.23% HIVDRMAN07 98.92% HIVDRAUTO33 99.16% HIVDRMAN08 99.36% HIVDRAUTO34 99.39% HIVDRMAN10 99.43% HIVDRAUTO35 99.69% HIVDRMAN11 99.77% HIVDRAUTO36 99.00% HIVDRMAN12 99.62% HIVDRAUTO37 99.54% HIVDRMAN13 99.13% HIVDRAUTO38 99.77% HIVDRMAN14 99.38% HIVDRAUTO39 100.00% HIVDRMAN15 99.77% HIVDRAUTO40 99.31% HIVDRMAN16 99.70% HIVDRAUTO41 99.16% HIVDRMAN17 99.04% HIVDRAUTO42 99.31% HIVDRMAN19 99.39% HIVDRAUTO43 99.46% HIVDRMAN20 99.53% HIVDRAUTO44 99.39% HIVDRMAN21 99.38% HIVDRAUTO45 98.92% HIVDRMAN22 95.00% HIVDRMAN23 99.00% HIVDRMAN24 92.00% HIVDRMAN25 98.00% HIVDRMAN26 98.00% 3.1.4. Full Validation of the in-house HIV-1 drug resistance assay on patient samples Ninety previously genotyped patient samples, with viral loads ranging from 1300 to 1.6million RNA copies/ml, were used to successfully validate the in-house HIV-1 ARV drug- resistance assay. All 90 samples were successfully amplified using the in-house HIV-1 ARV drug resistance amplification step (Appendix D), whereas 9 of the 90 samples (10%) were 73 unable to be amplified using the ViroSeq methodology. The subtype distribution was as expected with 96.7% (n=87) of the samples being classified as HIV-1 subtype C (as determined by REGA). An example of REGA subtyping is shown in Figure 3.2. Phylogenetic tree analysis of all 90 sequences was performed using reference sequences from HIV-1 subtype A to K (www.hiv.lanl.gov; Figure 3.3). Table 3.4 shows the HIV-1 ARV drug resistance mutation patterns of the 9 samples obtained using the in-house HIV-1 ARV drug resistance assay that could not be amplified using ViroSeq. Five of the 9 had significant HIV- 1 ARV drug resistance mutations. These 9 samples had viral loads ranging from 2300 to 627000 RNA copies/ml, indicating that primer mismatch in the amplification step rather than a low viral load were likely responsible for the lack of amplification, but this could not be unbundled further due to proprietary information. All 9 of these samples were HIV-1 subtype C. Figure 3.2: Subtype similarity plot for sample VAL087. The sample was classified as subtype A using the REGA HIV Subtyping tool version 2. Subtype was determined using a significance threshold of 0.8 (http://dbpartners.stanford.edu/RegaSubtyping/). 74 Figure 3.3: A radial phylogenetic tree was constructed f rom the 90 nucleotide alignments obtained from the in-house ARV HIV-1 ARV drug resistance assay, using neighbour-joining and the Kimura two -parameter distance matrix. Only bootstrap values of 70% or higher are shown. Sample VAL087 clusters with the representative subtypeA1 sequences (blue); and samples VAL066 and VA090 cluster with representative subtype B sequences (red); the remaining 87 sequences cluster with the subtype C representative sequences (numbers not shown due to size constraints). The scale represented the number of nucleotide changes between the sequences compared for every 1000 bases. 75 Table 3.4: ARV drug resistance mutation profiles and clinical significance of samples that successfully amplified using the in-house assay, but failed to amplify using the ViroSeq assay. Patient Name Viral load (RNA copies/ml) NRTIs Mutations Clinical Significance NNRTIs Mutations Clinical Significance Subtype VAL076 2300 D67N, M184V High-level resistance to 3TC* and FTC & and low level resistance to ABC# and ddI^ K101E, K103N, V108I, G190A High-level resistance to EFV2 and NVP3 C VAL077 2400 D67N, K70R, M184V High-level resistance to 3TC and FTC and low level resistance to ABC, d4T$ , AZT@ and ddI Y188L, G190A, K238T High-level resistance to EFV and NVP C VAL078 7400 M184V High-level resistance to 3TC and FTC K103R, V106M, V179D, M230L High-level resistance to EFV and NVP C VAL079 14000 K65R, M184V High-level resistance to 3TC, ABC and FTC and intermediate resistance ddI, TNF1 and d4T None None C VAL080 32000 V118I, M184V High-level resistance to 3TC, and FTC None None C VAL081 42000 None None None None C VAL082 150000 K65R, D67N, T69I, K70R, M184V High-level resistance to 3TC, ABC and FTC, intermediate resistance to d4t, ddI and TNF and low level resistance to AZT K101P, K103N, Y318F High-level resistance to EFV and NVP C VAL083 627000 V75I, M184V High-level resistance to 3TC, and FTC, low level resistance to ddI and ABC V106M, F227L High-level resistance to EFV and NVP C VAL084 unknown None None None None C *3TC=Lamivudine; &FTC=Emtricitabine; # ABC=Abacavir; ^ddI=didanosine; $ d4T=stavudine; @ AZT=Zidovudine; 1TNF=tenofovir; 2EFV=Efavirenz; 3 NVP=Nevirapine The 81 samples that were successfully amplified using both HIV-1 ARV drug resistance assays were found to have an average sequence homology of 99.20%. Detailed phylogenetic analysis revealed that sequences clustered with their partners from the two different sequencing methods and no contamination was observed (results not shown). Seventy-six of the 81 samples were found to have identical HIV-1 ARV drug resistance mutation profiles generated by the two assays. Of the 5 that were different 4 had additional mutations that were present in mixtures (Table 3.5; Appendix D). An example is shown in Figure 3.4. 76 Table 3.5: ARV drug resistance mutation profiles and clinical significance of samples that had differences in HIV-1 ARV drug resistance profiles. Patient Name Viral Load (RNA copies/ml) HIV-1 ARV Drug Resistance Profiles Number of Disagreeing mutations Sequence Similarity Clinical Significance Subtype VAL002 10000 ViroSeq D67G,K70R, M184V, K219Q, V106M, V179D,T215I/T 1 98.92 None C In-house D67G,K70R, M184V, K219Q, V106M, V179D VAL003 36000 ViroSeq D67N, K70R, M184V, K219E, A98G, K103N, V106M, Y188C, V108I/V 1 99.45 None C In-house D67N, K70R, M184V, K219E, A98G, K103N, V106M, Y188C VAL004 77000 ViroSeq T74S, M184V, K103N, P225H, V108I/V 1 98.5 None C In-house T74S, M184V, K103N, P225H VAL005 300000 ViroSeq L10I, K103N, V106M, L100L/I 1 99.11 None C In-house L10I, K103N, V106M VAL085 84000 ViroSeq D67N, M184V, T215F, L100I, K103N, H221I, K70R 3 99.05 None C In-house D67N, M184V, T215F, L100I, K103N, H221I, T215F, P225H 77 Figure 3.4: The ViroSeq chromatogram from patient VAL004 (a) indicates a mixed population at codon 108 (boxed) of the RT, resulting in a partial mutation V108V/I. This is not observed in the in-house sequence (highlighted; b). Of the 5 in-house sequencing primers, CWCS1 was found to successfully sequence 90 out of 90 samples, CWCS2 was unable to sequence 12 of the 90 samples (13.33%), CWCS3 was unable to sequence 7 of the 90 samples (7.77%), CWCS4 was unable to sequence 3 of the 90 sequences (3.33%) and CWCS5 was unable to sequence 2 of the 90 samples (2.22%). Sequence primer mismatch analysis was only performed for the in-house assay as the primer sequences for ViroSeq are unknown. Although a primer may have not successfully sequenced a sample, sequences obtained from neighbouring primers from each sample were available. This allowed for the sequence primer mismatch analysis against the sequences obtained from the samples (Figure 3.5). However, CWCS5 could not be aligned as it binds at the 3?end of the PCR amplicon, and CWCS2 sequences did not extend that far. 78 a)Primer CWCS2 -------------------------------------------AGAACTCAAGACTTTTGGG--------------------------- VAL081 ATTTCAGGGAACTCAATAAAAGAACTCAAGACTTTTGTGAGGTTCAATTAGG Subtype C VAL086 ATTTCAGGGAACTCAATAAAAGAACTCAAGATTTTTGGGAGGTTCAATTAGG Subtype C VAL061 ATTTCAGGGAACTTAATAAAAGAACTCAAGACTTTTGTGAAGTCCAATTAGG Subtype C VAL069 ATTTCAGGGAACTTAATAAAAGAACTCAAGACTTTTCAGAAGTTCAATTAGG Subtype C VAL002 ATTTCAGGGAACTCAATAAAAGAACTCAAGACTTTTCTGAAGTTCAATTAGG Subtype C VAL050 ATTTCAGGGAACTCAATAAGAGAACTCAGGATTTTTGGGAAGTTCAGTTAGG Subtype C VAL064 ATTTTAGGGAACTCAATAAAAGGACTCAGGATTTTTGGGAAGTMCAGTTAGG Subtype C VAL058 ATTTCAGAGAACTTAAYAAAAGAACTCAAGATTTCTGGGAAGTTCAATTAGG Subtype C VAL082 ATTTCAGGGAACTCAATAAAAGAACTCAAGATTTCTGGGAAGTTCAATTAGG Subtype C VAL079 ATTTCAGGGAACTCAATAAAAGAACCCAAGACTTTTCGGAAGTTCAATTAGG Subtype C VAL020 ATTTCAGGGAACTCAATAAAAGAACTCAAGAATTTAGTGAAGTTCAATTAGG Subtype C b)Primer CWCS3 ---------------------------------------GAATACCACACCCAGCA------------------------------------- VAL050 TTTTGGGAAGTTCAGTTAGGAATACCACACCCAGCAGGGTTAAAAAAGAAAA Subtype C VAL052 TTTTGGGAAGTTCAATTAGGAATACCACACCCAGCAGGGTTAAAAAAGAAAA Subtype C VAL060 TTTTGGGAGGTTCAATTAGGAATACCACACCCAGCAGGGTTAAAAAAGAAAA Subtype C VAL036 TTTTGGGAGGTTCAATTAGGAATACCACATCCAGCAGGGTTAAAAAAGAAAA Subtype C VAL054 TTTTGGGAGATTCAATTAGGAATACCACACCCATCAGGGTTAAAAAAGAACA Subtype C VAL065 TTTTGGGAAGTTCAACTAGGAATACCACATCCAGCAGGGTTAGWAAAGAAAA Subtype C VAL087 TTTTGGGAAGTTCAATTAGGAATACCGCATCCAGCGGGCTTAAAAAAGAAAA Subtype A1 c)Primer CWCS4 ---------------------------------------------------------------------GAATTGGCAGAGAACAGGGA VAL010 ACATAGTACCACTAACTGAAGAAGCRGAATTAGAATTAGCAGAAAACAGGGA Subtype C VAL057 ACATAGTACCACTAACTGAAGAAGCAGAATTAGAATTAGCAGAGAATAGGGA Subtype C VAL066 AAGTAATACAATTAACAGAAGAAGCAGAGCTAGAACTAGCTGA-AACAGGGA Subtype B Figure 3.5 Alignment of sequencing primers and patient sample sequence. The majority of the samples had mismatches with the primers which could influence primer binding. Two of the samples which had mismatches were subtype B (VAL066) and A1 (VAL087). 3.1.5. In-house Validation with the EQA Panel Results A comparison of performance of the in-house ARV HIV-1 drug resistance assay to ViroSeq with two VQA panels provided by the NIH resistance genotyping EQA Scheme is shown in Table 3.6. The mutation patterns for the 3 subtype C samples were identical using the IAS- USA mutation list (Johnson et al., 2008). In addition, the in-house HIV-1 ARV drug resistance assay gave identical patterns for 6 of 7 non-C subtypes when compared to the ViroSeq results. The VQA certified the in-house HIV-1 ARV drug resistance assay, and this assay was subsequently used to genotype patients on the CIPRA-SA cohort (section 3.2). 79 Table 3.6: Samples from the EQA panel that were sequenced with the ViroSeq and In-house assays, indicating subtype, mutation pattern and homology Sample Number Viral load (RNA copies/ml) Subtype Number of Disagreeing Mutations VQA012g01 17775 C 0 VQA012g02 35450 B 0 VQA012g03 18525 B 2 VQA012g04 40500 B 0 VQA012g05 12580 C 0 VQA013g01 27810 A1 0 VQA013g02 148282 C 0 VQA013g03 24238 F 0 VQA013g04 3557 B 0 VQA013g05 57005 A2 0 3.1.6. In-house Validation with non-subtype C samples The in-house assay was also evaluated on 134 patient samples obtained from eight African sites (Kigali, Lusaka, Copperbelt, MRC Uganda, Kemri, Cape Town, Kenya AIDs Vaccine Initiative [KAVI] and Entebbe). HIV -1 viral RNA loads of these patients ranged between 1 230 and 720 000 RNA copies/ml using the COBAS amplicor version 1.5 (Roche Diagnostics, Mannheim, Germany). One hundred and eighteen samples were successfully amplified using the in-house HIV-1 ARV drug resistance assay. Of the 118 samples sequenced with the in- house assay, 14 did not have bidirectional sequencing data; as a result of the primers used in cycle sequencing failing to amplify (Table 3.7). Subtype analysis using REGA revealed that across all eight sites the subtype distribution was 56.49% subtype C, 29.77% subtype A1, 4.58% subtype D and 11.84% were unassigned. The subtype distribution per site was as expected with the majority of subtype C samples occurring in sites situated in Southern Africa and the Eastern African sites containing predominantly subtype A, D and several unassigned subtypes (Table 3.8). 80 Table 3.7: The number and (percentage) of primers which failed to amplify per subtype. Subtype CWCS1 CWCS2 CWCS3 CWCS4 CWCS5 A1 0 6 (15%) 6 (15%) 0 2 (5%) C 1 (1%) 2 (3%) 2(3%) 1 (1%) 4 (5%) D 0 0 0 1 (17%) 1 (17%) NA 0 0 0 1 (8%) 0 Sixteen samples that could not be amplified using the in-house assay; were successfully amplified using the ViroSeq assay. The 16 samples were found to have the following subtypes: subtype A1 n=8 (Kigali, Kemri, Entebbe); subtype C n=4 (Copperbelt and Lusaka); subtype D n=1 (Entebbe); and 2 subtypes were unassigned. Table 3.8: Distribution of subtype per African site Site (N) Subtype C Subtype A1 Subtype D Unassigned Kigali (24) 8.33% 83.33% 0.00% 8.33% Lusaka (76) 97.26% 0.00% 0.00% 2.74% Masaka (12) 0.00% 33.33% 33.33% 33.33% Kemri (13) 0.00% 84.62% 0.00% 15.38% Cape Town (1) 100.00% 0.00% 0.00% 0.00% KAVI (2) 0.00% 50.00% 0.00% 50.00% Entebbe (6) 0.00% 50.00% 33.33% 16.67% Of the 134 samples 1 had the K103N mutation and two had the polymorphic I85V non- polymorphic PR mutation. 81 3.2. Emergence of HIV-1 drug resistance on the CIPRA-SA ?Safeguard the Household? project 3.2.1. Description of the CIPRA-SA Cohort A total of 812 ARV naive participants were enrolled on the CIPRA-SA cohort, from 2 different geographical regions during 2005-2007. All 812 participants were older than 18 years of age and had no active opportunistic infection at time of enrolment. Seventy percent of the cohort was female (n=569) and 99% of the patients were of African descent. Five hundred and seventeen participants (64%) had CD4+ T-cell counts less than 200 cells/mm3, with the remaining having CD4+ T-cell counts below 350 cells/mm3. The median baseline CD4+ T-cell and mean log viral load was 167 cells/mm3 and 5.65 copies/ml, respectively. Thirty five percent of participants enrolled in the study had a CDC stage C classification, defined by CD4+ T-cell count, symptomatic conditions attributed to HIV-1 infection or a defect in cell-mediated immunity. Of the 812 participants a total of 371 (45.7%) experienced treatment failure, defined by toxicity (n=134; 16.5%), virological failure (n=83; 10.2%), withdrawal of consent (n=39; 4.8%), defaulted (n=70; 8.62%), lost to follow-up (n=24; 2.96%) or death (n=21; 2.59%). Of the 83 patients that failed as a result of viral rebound, 54 of the 449 enrolled (n=12%) were from the Johannesburg site and 29 of the 363 enrolled (8%) were from the Cape Town site. The increased number of failures at the Johannesburg site may reflect a difference in adherence levels between the two sites. The majority of the patients on a failing regimen were receiving d4T, 3TC, EFV (49 of 83) followed by 22 on d4T, 3TC, NVP. Twelve patients (pregnant at time of study entry) were on a PI-based regimen at time of failure (n=3; 82 d4T, 3TC, NLF and n=9; d4T, 3TC, lopnavir/ritonavir). All 83 patients were of African descent. To ascertain possible associations with virological failure, baseline CD4+ T-cell counts and viral loads were compared between the viral failure group and the remainder of the CIPRA- SA cohort (Appendix E; Table 3.9). This comparison found that baseline viral load did not impact on subsequent virological failure (p=0.7781), whereas a lower CD4+ T-cell count at the time of therapy initiation were more likely to experience viral failure (p=0.0321). Of the 83 patients experiencing virological failure, 75% (n=62) had a CD4+ T-cell count less than 200 cells/mm3. Age (p=0.3033) and gender (p=0.5395) did not appear to impact on viral outcome. Table 3.9 : Baseline characteristics of the CIPRA-SA Participants * Variable All Patients (n=812) Viral Failure (n=83) p -values Gender-number (%) Female 573 (70.6%) 62 (74.6) 0.5395 Male 239 (29.4%) 21 (25.3) Mean Age ? year 33.2 (10-61) 32.3 (0-53) 0.3033 Median CD4+ T -cell count (cells/mm 3) 167 (2-734) 147 (16-354) 0.0321 Mean baseline HIV-1 RNA log 10 copies/ml 5.65 (49- >750000copies/ml) 5.6 (399- >750000 copies/ml) 0.7781 *Percentages may not total 100 because of rounding. 3.2.2. Baseline sequences of the virologically failing samples Of the 83 participants experiencing viral failure, 12 were not available for analysis (no amplification n=5; no storage n=7). The remaining 71 baseline samples were successfully sequenced and analysed for HIV-1 ARV drug resistance mutations (Appendix E). Six of the 83 71 participants were found to harbour resistance at time of study entry (Table 3.10), five of which were female. Of the six samples, 2 had mutations that resulted in reduced susceptibility to NNRTIs (K103N: n=1; K103N and V106M: n=1), 1 with mutations that impact on NNRTIs and PIs susceptibility (G190A, K101E, M46V and Q58E) and 3 that had mutations that reduce PIs susceptibility (M46I: n=1; M46L: n=1; Q58E: n=1; Table 3.10). All 3 of these participants with NNRTIs mutations were female, but only one (135671) had reported previous NVP exposure to prevent two separate cases of mother-to-child- transmission at the end of 2002 (36 months prior to study entry) and 2005 (1 month prior to study entry). Participant 266571 with the M46L mutation had also had previous NVP exposure in mid 2003 (36 months prior to study entry). Seventeen participants had HIV-1 subtype C polymorphisms that in combination with other mutations result in resistance. The T74S HIV-1 subtype C polymorphism was observed in 10 of the 71 baseline samples (14%); one of these had the K103N mutation (Table 3.10). Two patients had the A71T polymorphism (3%) and one patient had the L10I mutation. The E138A and V179D polymorphism was observed in three and two participants, respectively (Table 3.10). The I85V polymorphism was observed in one participant. 84 T ab le 3 .10 : B as el in e po ly m or ph is m s an d m ut at io ns l ink ed t o H IV -1 A R V d rug r es is ta nc e of 22 C IP R A -S A p ar ti ci pa nt s w ho l at er e xp er ie nc ed vi ra l f ai lu re o n th e C IP R A -S A s tu dy . P at ie nt N am e G en de r P ro te as e R ev er se T ra n sc ri pt as e C od on 10 C od on 46 C od on 58 C od on 71 C od on 74 C od on 85 C od on 10 1 C od on 10 3 C od on 10 6 C od on 13 8 C od on 17 9 C od on 19 0 13567 1 Fe m al e T 74 S K 103 N 13701 1 Fe m al e Q 58 E 16512 1 Fe m al e M 46 V Q 58 E K 101 E K 103 R G 190 A 16562 1 Fe m al e K 103 N V 106 M /V E 138 A 16693 1 M al e M 46 I 26657 1 Fe m al e M 46 L 13531 1 M al e T 74 S 13543 1 Fe m al e I85 V I 13564 1 Fe m al e T 74 S 13589 1 Fe m al e E 138 A 13594 1 Fe m al e T 74 S 13684 1 Fe m al e A 71 T 16535 1 Fe m al e T 74 S 16596 1 M al e A 71 T 16614 1 M al e L 10 I 16681 1 Fe m al e T 74 S 16691 1 Fe m al e E 138 A V 179 D 23641 1 M al e T 74 S V 179 D 26565 1 Fe m al e T 74 S 26595 1 M al e T 74 S 26626 2 Fe m al e K 103 R 26666 1 Fe m al e T 74 S 85 3.2.3. HIV-1 ARV drug resistance at viral failure time point Of the 83 patients experiencing viral failure, 12 were considered failing as a result of not having a 1.5 log drop in viral load from study entry to week 12 and the remaining 71 as a result of two consecutive viral loads greater than 1000 copies/ml (Figure 3.6). Six samples for participants experiencing viral failure were not available for analysis (no amplification n=4; no stored samples n=2). Of the 77 samples available for analysis, 56 had ARV drug resistance mutations, while 21 had no known mutations (Appendix F). Results were analysed according to whether patients failed due to a less than 1.5 log drop by week 12 or two consecutive viral loads greater than 1000 RNA copies/ml (Figure 3.6). Of the 10 patient samples available for analysis failing at week 12, 50% (n=5) were female, 2 of which had received prior MTCT. Eight of the 10 (80%) patients were on a failing d4T, 3TC, EFV regimen; whereas the remaining 2 were on a PIs-based regimen (d4T, 3TC, LPV/r n=2). At baseline none of these patients had mutations that would have resulted in reduced susceptibility to the regimen they were accessing. There were no NRTIs mutations present at failure in any of the 10 patients analysed. Of the 8 failing on the d4T, 3TC, EFV regimen, 2 had NNRTIs mutations (135891-K103N and E138A-and had previous NVP exposure and 165461-K103N and V106M-with no known previous NVP-exposure). Of the 2 patients accessing a failing PIs-based regimen no PIs-associated mutations were observed and one female patient (136101) reported as having no previous MTCT exposure had 3 NNRTIs mutations (K103N, V106A and Y188C). 86 Figure 3.6: Diagrammatic representation of the CIPRA-SA patients with viral failure. Participants on a PIs-based regimen are represented by a black asterisks, if they were also exposed to NVP to prevent mother-to-child-transmission the asterisks is red. Of the 67 participants on a failing ARV therapy as a result of 2 consecutive viral loads greater than 1000 RNA copies/ml, all were accessing the same NRTIs-backbone consisting of d4T and 3TC with either EFV (n=40, 60%), NVP (n=20, 30%), LPV/r (n=5, 7%) and NLF (n=2, 3%). Of the 67 participants on a failing ARV therapy as a result of two consecutive viral loads greater than 1000 RNA copies/ml, all were accessing the same NRTIs-backbone consisting of d4T and 3TC with either EFV (n=41; 57.7%), NVP (n=22; 31.0%), LPV/r (n=6, 8.5%) and NLF (n=2, 2.8%). The M184V mutation was the most prevalent NRTIs mutation occurring in 67% (n=45) of the participants (Figure 3.7) followed by the K65R mutation (3%). Eighteen percent (n=12) of the participants had no known or previously described mutations. 87 Figure 3.7: Frequency of the HIV -1 ARV drug resistance mutations associated with NRTIs resistance in the 67 CIPRA -SA participants failing ARV therapy as a result of 2 consecutive viral loads greater than 1000 RNA copies/ml. Of the 63 participant accessing an NNRTIs based regimen, 60 were successfully amplified and differences in mutation profiles were observed between the EFV and the NVP-containing regimens (Figure 3.8). The Y181C mutation only occurred in the patients accessing a failing NVP-containing regimen (40%). As expected, the K103N mutation was more frequent (p=0.1432) with EFV (n=60%) than NVP (40%). The V106M mutation occurred at a higher frequency in subjects on EFV (18%) than NVP (10%), but this difference was not significant (p=0.4431).The V106A mutation only occurred in the NVP-containing regimen (10%). EFV appeared to select for a wider range of mutations in the RT region compared to NVP (Figure 3.8). Of the 20 NNRTIs resistance mutations detected; 8 were associated with both EFV and NVP therapy (Figure 3.8). 88 F ig ur e 3. 8: D is tr ib u ti on o f N N R T I m u ta ti on s fr om p at ie nt s ac ce ss in g a fa ili ng E F V - or N V P -c on ta in in g re gi m en s. 89 Of the 8 subjects failing a PIs-containing regimen, none had known resistance mutations to any PIs. Within the 6 participants failing lopinavir/r, 4 had no other mutations associated with resistance, one had the M184V mutation and one sample failed to amplify. Of the 2 failing NLF and NRTIs-based regimens both were female, with previous NVP-exposure and harboured NNRTIs mutations (participant 135641-K103N, V106M and participant 135241- K103N). Well known naturally occurring HIV-1 subtype C PR polymorphisms were observed in patients experiencing virological failure. The T74S polymorphism was observed in 13% of patients. Mutations resulting in PIs resistance were observed in 3 patients, none of which were exposed to a protease inhibitor, but these mutations were present at baseline (section 3.2.2). 3.2.4. Accumulation of mutations Additional resistance testing was performed on 34 of the patients experiencing virological failure that had sequential visits with detectable viral loads. Two of the patients were accessing a PIs-based regimen and were not analysed further. Nine of the 32 patients had 3 sequential visits and the remainder had 2 sequential visits. One patient had the K103N mutation at study entry (baseline). The NRTIs mutations were found to increase in number from the first detectable viral load to the second visit 1-12 weeks later (Figure 3.9). This increase was due to the development of the M184V mutation. NNRTIs mutations were found 90 to increase as the patient was left on a failing regimen and on average for every 3 months left on a failing regimen an additional NNRTIs mutation was observed (Figure 3.9). Figure 3.9: Development of NRTIs and NNRTIs mutations over time. The NRTIs backbone was common for all 32 patients, but the 32 patients analysed either had EFV- or NVP exposure. Patients exposed to NVP- were found to have a greater increase of mutations overtime, compared to EFV-exposed patients (Figure 3.10). However, the variety of NNRTIs mutations in EFV-exposed (n=11) was greater than the NVP-exposed (n=8). 91 Figure 3.10: Accumulation of NNRTIs mutations in NVP- versus EVF- exposed patients. A small sub-set of patients had previous MTCT exposure (n=12) prior to the onset of the CIPRA-SA study. The number of mutations that occurred increased in the EFV- versus the NVP-exposed patients, with a greater variety of NNRTIs mutations occurring in patients exposed to EFV (n=8) compared to NVP (n=4; Figure 3.11). No association with the pattern of NNRTIs mutations developing was observed. Figure 3.11: Accumulation of NNRTIs mutations in NVP- versus EFV-exposed patients, with previous MTCT. 92 Amino acid sequences from participants with longitudinal visits were aligned at the change in amino acids compared. Figure 3.12 is representative of the analysis performed. This patient had no mutations present at baseline and successfully suppressed the virus for 22 months. At the first detectable viral load since suppression only the K103N (yellow) mutation was present. Six months later the M184V (blue) and V108I (green) mutations had developed followed three months later by P225H (purple). No additional amino acid changes that are not associated with HIV-1 ARV drug resistance occurred during these nine months of viral failure. * 9 0 * 11 0 * CP50739 (week 0) : KLVDFRELNKRTQDFWEV Q LGIPHPAGLKK K KSVT V LDVGDAYFSVPLDE : 1 2 2 CP61906(week96) : .................. . ........... N ................... : 122 CP63892(week120) : .................. . ........... N .... I .............. : 122 CP64620(week132) : .................. . ...... . .... N .... I .............. : 122 13 0 * 15 0 * 17 0 CP50739(week 0) : NFRKYTAFTIPSTNNETPGIRYQYNVLPQGWKGSPAIF QC SMT K ILE P FR : 172 CP61906 (week96) : ...................................... .. ... . ... . .. : 172 CP63892 (week120) : ...................................... .. ... . ... . .. : 172 CP64620 (w eek132) : ...................................... .. ... . ... . .. : 172 * 19 0 * 21 0 * CP50739(week 0) : A Q NPEIVIYQY M DDLY V GSDLEIGQHRAKIEELR KH LLKWGLTTPDKKHQ : 222 CP61906 (week96) : . . .............. . ................. .. .............. : 222 CP63892 (week120) : . . ......... V .... . ................. .. .............. : 222 CP64620 (week1 32) : . . ......... V .... . ................. .. .............. : 222 360 * 380 * 400 CP50739 (week 0) : KE P PFLWMGYE L HPDKWTVQPIQLPEKDSWTVNDIQKLVGKLNWASQIYP : 272 CP61906 (week96) : ........... . ...................................... : 272 CP63892 (week120) : ........... . ...................................... : 272 CP64620 (week132) : .. H ........ . ...................................... : 272 Figure 3.12: Amino acid sequence of the 4 longitudinal sequences obtained from participant 236081. The highlighted amino acids represent HIV-1 ARV drug resistance mutation (Yellow-K103N; Green-V108I; Blue-M184V and Purple-P225H). 93 3.3. Second-line failures on the CIPRA-SA cohort 3.3.1. Baseline Mutations of the second-line CIPRA-SA patients Sixty one of the 812 participants that experienced treatment failure (toxicity: n=20; viral failure: n=41) on the first-line of CIPRA-SA were changed to the second-line drug regimen (Table 3.11). Of the 21 participants that did not achieve viral control on second-line the baseline median age was 36 years, 76% (n=16) were female, with a mean second-line baseline viral load of 373000 RNA copies/ml. There was no statistically significant difference between the age, gender and second-line entry viral loads of the participants who subsequently virologically suppressed versus those that did not on the second-line regimen (Table 3.12). The second-line baseline resistance was examined and showed that the most prevalent mutation was M184V (60%), followed by K103N (30%; Figure 3.13). Of the 61 samples accessing the second-line regimen (past 4 weeks) treatment outcome on the second- line regimen was classified into 3 different groups: a) viral suppression; b) viral rebound or c) no viral suppression (Table 3.11). Table 3.11: Second-line outcome of the 61 patients accessing second-line regimen Second-line viral outcome Suppression Rebound No Suppression Total Reason for switch to second -line Toxicity 16 3 1 20 Two consecutive VL > 1000 copies/ml after week 24 22 6 9 37 Less than1.5log drop in VL by week 12 2 0 2 4 Total 40 9 12 61 *VL -viral load 94 Table 3.12: Second-line Baseline Demographics of the 61 patients that were switched to a second-line regimen. Participants that suppressed on second- line Participants that did not suppressed or rebound on second- line p-value Age year 35 (24-55) 36 (21-51) 0.0688 Gender-Female % 80% 76% 0.4854 Viral Load (RNA copies/ml) 61800 (399->750000) 37300 (399-335000) 0.2066 Figure 3.13: Distribution of second-line baseline mutations prior to starting the second- line regimen. The M184V and K103N mutations are the most prevalent mutations. 3.3.2. Failure Mutations of the second-line CIPRA-SA patients Twenty one participants failed the second-line regimen, 12 of whom never achieved viral suppression at any stage of second-line therapy. No PIs or NRTIs mutations were observed in all 21 patients. Four participants had NNRTIs mutations (Table 3.13), with the most frequent being K103N (n=4; 19%). Of the 9 participants that experienced viral rebound, 3 95 had experienced toxicity to the first-line regimen, and had no mutations present at second-line failure. Table 3.13: Baseline and failure characteristics of the 21 participants that experienced failure on the second-line regimen. *Not Available Participant Name Reason for failure Baseline Resistance Time since regimen change Outcome on Second-line A98G K103N P225H K103R 265842 Toxicity NA* 5 Never Suppressed 1 1 1 165461 <1.5LOG DROP K103N 4 Never Suppressed 1 135381 <1.5LOG DROP NONE 7 Never Suppressed 266262 VL>1000 M184V, K103E, V108I, Y181C 7 Never Suppressed 1 235681 VL>1000 K103N 8 Never Suppressed 1 136611 VL>1000 V106M, Y188C 10 Never Suppressed 135941 VL>1000 K103N 11 Never Suppressed 265641 VL>1000 M184V 6 Never Suppressed 266571 VL>1000 NA 7 Never Suppressed 136251 VL>1000 NA 9 Never Suppressed 136801 VL>1000 NONE 8 Never Suppressed 135101 VL>1000 NONE 8 Never Suppressed 165671 TOXICITY NA 17 Rebound 235051 TOXICITY NA 44 Rebound 166741 TOXICITY NA 7 Rebound 235491 VL>1000 M184V 11 Rebound 1 165831 VL>1000 NONE 3 Rebound 137111 VL>1000 M184V, V106A, F227L 9 Rebound 135311 VL>1000 I47V, M184V, K103N 17 Rebound 135671 VL>1000 M184V, K103N, V108I 14 Rebound 137011 VL>1000 Q58E, G190A 6 Rebound 96 3.4. Characterisation of host polymorphisms in the CIPRA-SA cohort A total of 1471 (1223 HIV-1 negative samples and 248 from the CIPRA-SA cohort) DNA preparations were isolated and successfully used for SNP analysis of the four polymorphisms of interest in CYP3A4, 3A5, 2B6 and MDR-1. A total of 248 out of the 812 CIPRA-SA participants were consented for host genetic analysis, 85 of which experienced treatment failure for the following reasons: 41 toxicities, 31 viral failure, 5 deaths, 6 defaulted on the clinical schedule, 2 lost to follow-up and 1 withdrew consent from the study. The participant that withdrew consent was removed from the analysis. The participants that failed as a result of death, default on clinical schedule or were lost to follow-up were included in the genotypic frequencies analysis, but were not linked to treatment, as the small size of each of these sub- sets would have no statistical power. An example of the allelic discrimination plots for the CYP3A4, G1344A genotype is represented in Figure 3.14. The Y-axis represents the wild-type 1344GG genotype which occurs in the majority of samples genotyped in this study, with a wildtype genotypic frequency of 44.2% and 60.2% for the control and CIPRA-SA groups, respectively (Table 3.14). Figure 3.15 represents the allelic discrimination plots for the CYP3A5 A6986G allele. The homozygous genotype 6986GG, which occur in the majority of the samples genotyped (X -axis), were present at a genotypic frequency of 64.4% and 70.5% for control and CIPRA- SA group, respectively (Table 3.14). The allelic discrimination plots for the CYP2B6, G516T allele, are represented in Figure 3.16. The homozygous variant 516TT occurs in the minority of the samples genotyped, at a genotypic frequency of 15.78% and 13.3% for the control and CIPRA-SA groups respectively (Table 3.14). Finally, the allelic discrimination 97 plots for the MDR-1 C3435T are depicted in Figure 3.17. The homozygous wild-type 3435CC (Y-axis) was present at genotypic frequencies of 80.8% and 79.5% for the control and CIPRA-SA groups, respectively. Figure 3.14: Frequency of the CYP3A4 SNP G1344A in 82 HIV -1 negative samples. Samples with the homozygous variant genotypes (A) are represented by the red dots on the x- axis, the homozygous wild-type genotypes (G) are represented by the blue dots and heterozygous genotypes (GA) are represented by the green dots. Samples that failed to amplify or no template controls are indicated by the X?s. 98 Figure 3.15: Frequency of the CYP3A5 SNP A6986G in 75 HIV -1 negative samples. Samples with the homozygous variant genotype (G) are represented by the red dots on the x- axis, the homozygous wild-type genotypes (A) are represented by the blue dots and heterozygous genotypes (AG) are represented by the green dots. No template controls are indicated by the X?s. 99 Figure 3.16: Frequency of the CYP2B6 SNP G516T in 75 HIV -1 negative samples. Samples with the homozygous variant genotypes (T) are represented by the blue dots on the y-axis, the homozygous wild-type genotypes (G) are represented by the red dots on the y-axis and heterozygous genotypes (GT) are represented by the green dots. Samples that failed to amplify and no template controls are indicated by the X and square boxes, respectively. 100 Figure 3.17: Frequency of the MDR -1 SNP C3435T, in 71 HIV -1 negative samples. Samples with the homozygous variant genotypes (T) are represented by the red dots on the x- axis, the homozygous wild-type genotypes (C) are represented by the blue dots and heterozygous genotypes (CT) are represented by the green dots. Samples that failed to amplify and no template controls are indicated by the X and square boxes, respectively. 101 The frequencies of the four genetic variants examined in the CIPRA-SA cohort and the HIV- 1 negative control groups were compared between the two groups using a Chi-squared test (Table 3.14). Overall, there were no significant differences in SNP frequencies between the control and CIPRA-SA case population. Table 3.14: Genotype frequencies of the 4 SNPs in the CIPRA-SA cohort and the HIV-1 negative control cohort. CYP3A4 CYP3A5 CYP2B6 MDR-1 G1344A A6986G G516T C3435T CIPRA Control CIPRA Control CIPRA Control CIPRA Control Homozygous Wild-Type 60.2% 44.2% 76.5% 64.4% 49.7% 38.9% 79.5% 80.8% Heterozygous 37.1% 50.3% 22.5% 32.6% 37.0% 45.4% 17.1% 17.8% Homozygous Variant 2.7% 5.5% 0.9% 3.0% 13.3% 15.7% 3.4% 1.4% p -value 0.145 0.140 0.180 0.690 A univariate analysis was performed to determine if there was any correlation between the allelic frequencies of participants that experienced ARV-related toxicity (n=41) versus those that did not (n=206; Table 3.15). There was no statistically significant association between the four genotypes examined and development of toxicity. Similarly, univariate analysis of allelic frequencies and viral failure (n=31) showed no statistically significant differences (Table 3.16). Table 3.15: Allele frequencies of the 4 genotypes examined from the patients that experience toxicity versus those that did not on the CIPRA-SA cohort. CYP3A4 CYP3A5 CYP2B6 MDR-1 G1344A A6986G G516T C3435T Toxicity No Toxicity Toxicity No Toxicity Toxicity No Toxicity Toxicity No Toxicity Wildtype 96% 98% 100% 99% 90% 84% 92% 97% Variant 3% 2% 0% 1% 10% 14% 8% 3% p -value 0.6506 0.3161 0.3841 0.1210 102 Table 3.16: Allele frequencies of the 4 genotypes examined from the patients that experienced viral failure versus those that were virologically suppressed on the CIPRA-SA cohort. CYP3A4 CYP3A5 CYP2B6 MDR-1 G1344A A6986G G516T C3435T Viral Failure No Viral Failure Viral Failure No Viral Failure Viral Failure No Viral Failure Viral Failure No Viral Failure Wildtype 95% 98% 100% 99% 83% 87% 96% 97% Variant 5% 2% 0% 1% 17% 13% 4% 3% p -value 0.2484 0.3161 0.4283 0.7004 Because CYP2B6 has been linked to EFV toxicity and or failure, a univariate analysis between participants receiving an EFV-containing regimen and outcome was performed to determine if there was any correlation. No correlation was found between the G516T genotype and outcome (p=0.9501). 103 4. Chapter 4: Discussion Antiretroviral therapy has greatly improved the life-span of HIV-1 infected individuals. However, treatment failure does occur and is often a result of toxicity, poor-tolerability, non- adherence or the development of ARV drug resistance. This study focused on the development and/or establishment of assays to evaluate viral (development of HIV-1 drug resistance) and host factors (4 SNPs associated with ARV metabolism and absorption) associated with ARV treatment outcome, and the longitudinal monitoring of these viral factors in the CIPRA-SA cohort. Overall, the ARV drug resistance mutations described in a predominantly HIV-1 subtype C infected South African population were similar to those described amongst other subtype C infected cohorts throughout Africa (Marconi et al., 2008, Orrell et al., 2009, Wallis et al., 2010) and India (Kandathil et al., 2009, Vidya et al., 2009) , as well as HIV-1 subtype B infected patients. Furthermore, this study revealed that more frequent clinical monitoring and switching of ARV drug regimens when a participant had greater than 1000 RNA copies/ml resulted in less complex ARV drug resistance patterns, which is beneficial for future treatment options. Due to the lower than anticipated number of participants failing ARV treatment and the total size of the CIPRA-SA cohort, no statistically significant association could be made between the four host genetic factors examined and ARV treatment outcome. The implementation of the South African national ARV roll-out program, and the associated emergence of HIV-1 ARV drug resistance, has driven the need for the development of an affordable HIV-1 subtype C specific ARV drug resistance assay. Results of this study confirmed the establishment of a validated; more affordable and subtype robust assay to 104 monitor ARV drug resistance. The use of an automated extraction method resulted in a more efficient isolation of minority quasispecies, which were detected as mixtures in the sequence chromatograms in the in-house HIV-1 ARV drug resistance assay in some patients. Detection of these extra mutations/polymorphisms did not alter the patient?s ARV drug resistance profiles, however, their presence may influence future treatment options. Moreover, the automated extraction method allowed for increased sample throughput (30 test samples and 2 controls to be isolated in 90 minutes) making the test suitable for the South African ARV roll-out program (approximately 870 000 patients on ARVs by end 2009). The use of an automated extraction method is in contrast with other commercial and in-house methodologies, which use manual extraction methods (Eshleman et al., 2004, Saravanan et al., 2009). RT-initiated amplification and sequencing was successful for 95% of all samples, and included 156 South African patient plasma samples (not dependent on viral load), 118 of the 134 patient plasma samples from 8 African sites and 10 EQA patient samples. The pol amplification and sequencing success rates are higher than those reported on commercially available assays (Eshleman et al., 2004), which could be attributed to the use of subtype C specific PCR primers. It should be noted that all currently available assays (commercial and in-house assays) are unable to amplify 100% of patient samples tested, mainly due to the high genetic variability of HIV-1 (Engelbrecht et al., 2007, Eshleman et al., 2004). All of the 90 South African patient samples, with viral loads ranging from 1300 to 1.6 million RNA copies/ml, were successfully amplified using the in-house HIV-1 ARV drug resistance assay, whereas nine of the 90 samples (10%) could not be amplified using the ViroSeq 105 method (2300-627000 RNA copies/ml; section 3.1.4, Appendix D, Table D1). None of the samples below 1000 RNA copies/ml were tested in either assay. This is not a limitation to the study as treatment switches in patients in resource constrained countries are not conducted below this level. Of significance, seven of the nine samples that failed to amplify on ViroSeq, had mutations that resulted in resistance to both NRTIs and NNRTIs, indicating the clinical importance of analysing these samples (Table 3.4). The subtype distribution was as expected with 96.7% of the samples being classified as HIV-1 subtype C. Two of the three remaining samples were classified as HIV-1 subtype B and one as sub-subtype A1. The presence of non-C subtypes in South Africa has been reported previously (Papathanasopoulos et al., 2003). HIV-1 subtype B is prevalent in North America and Europe, while sub-subtype A1 predominates in East Africa (Papathanasopoulos et al., 2003). It is likely that these patients did not originate from South Africa, or alternatively were infected by individuals originating from countries, where these subtypes are prevalent. The use of only 5 primers to generate a fully bidirectional sequence with coverage of PR 1-99 and RT 1-240 increases the number of samples that can be sequenced on one 96 well plate (19 samples as opposed to 13 using ViroSeq), thereby improving assay cost-effectiveness. The robustness of the in-house ARV drug resistance assay was further demonstrated by the amplification and sequencing of 118 of the 134 HIV-1 samples from newly infected patients from eight African sites. If necessary, subtype-specific or degenerate primers can be designed for implementation of this assay format for different geographic regions. Phylogenetic analysis revealed that the samples from the eight African sites were infected with different subtypes, unique or circulating recombinant forms expected in that region. For example, samples from Kigali, Rwanda were predominantly sub-subtype A1, followed by subtype C (Table 3.8; http://www.hiv.lanl.gov). This demonstrated that the newly developed 106 in-house ARV drug resistance assay can be used for HIV-1 subtypes other than subtype C. Future work should focus on improving the performance of this assay with non HIV-1 subtype C samples. It is highly likely that the one patient with the K103N mutation which causes high level resistance to all NNRTIs (Johnson et al., 2008) was infected with an ARV drug resistant virus, since this cohort was comprised of recently infected individuals. This reaffirms that the newly developed in-house ARV drug resistance assay can be used for surveillance studies to monitor the frequency of transmitted ARV drug resistant viruses. The in-house ARV drug resistance assay successfully amplified all samples in the VQA panels and the external analysis revealed a high sequence homology compared to sites participating in the panels. Most importantly, the mutation patterns were comparable to other laboratories enrolled in the proficiency program, resulting in the newly established in-house ARV drug resistance assay being certified by the NIH VQA. Four of the VQA samples were subtype B and future evaluation of this subtype using the in-house assay is required. It is becoming increasingly evident that the cost of monitoring patients on ARVs far exceeds the cost to treat, with recent studies from Uganda and Zimbabwe showing the cost to monitor one patient per year is equivalent to treating six HIV-1 infected individuals (Medina-Lara et al., 2009, Mugyenyi et al., 2009). These costs currently exclude the price of resistance testing where commercially available ARV drug resistance assays cost approximately R2700. Such prices are not prohibitive in resource rich countries and ARV drug resistance testing is used in routine patient monitoring. However, the current costs in the developing world make the ARV drug resistance monitoring of patients on HAART impossible. The newly developed assay is cheaper than the commercially available ViroSeq and costs R1300 107 (Appendix G). However, it should be noted that although the in-house ARV drug resistance assay costs 60% of the commercially available genotyping kits available in South Africa, the initial outlay for setting up a laboratory to perform sequencing is expensive as a result of the specialized equipment and skilled personnel required. Moreover, the ongoing costs linked to equipment maintenance may limit its widespread use. Numerous studies worldwide have shown that the type and complexity of the emerging ARV drug resistance patterns are linked to time of initiation of treatment with respect to CD4+ T- cell count (Kitahata et al., 2009, Moore et al., 2009, Sterne et al., 2009), choice of ARV regimen, HIV-1 subtype (Morris et al., 2003), and duration on a failing regimen (Doualla- Bell et al., 2009, Hosseinipour et al., 2009, Johannessen et al., 2009, Marconi et al., 2008, Orrell et al., 2009, Wallis et al., 2010). Since one of the objectives of the CIPRA-SA study was to set-up a closely monitored cohort that was followed longitudinally from ARV initiation and throughout ARV treatment, it has provided a unique opportunity to evaluate factors linked to the development of ARV drug mutation patterns emerging from HIV-1 subtype C infected patients experiencing treatment failure. Furthermore, the data obtained from this study can be compared to data emerging from patients failing on similar drug regimens in the region, following different available guidelines (WHO- and national- guidelines throughout Africa). The in-house ARV drug resistance assay was thus used to analyse participants failing HAART on the CIPRA-SA cohort. Overall, the CIPRA-SA study enrolled 812 participants from two sites who had CD4+ T-cell counts less than 350 cells/mm3. The participants were representative of the demographics of patients presenting to government ARV clinics as they were predominantly female and of 108 childbearing age. The inclusion criteria of participants enrolled onto CIPRA-SA cohort was different from patients on the national-roll program. In particular, one major difference between the CIPRA-SA and public sector cohorts was that CIPRA-SA participants were initiated onto ARV treatment with CD4+ T-cell counts of 350 cells/mm3 or below, unlike the public sector which initiates HAART in patients who have CD4+ T-cell counts of 200 cells/mm3 or below. The CIPRA-SA initiation criteria at the time (2005), was in line with international practices, and subsequently several studies which have shown the sooner a patient begins ARV therapy the better the prognosis (developing AIDS and dying; Kitahata et al., 2009, Moore et al., 2009, Sterne et al., 2009). Even though the initiation criteria of CIPRA-SA was less than a CD4+ T-cell count of 350 cells/mm3, the majority of the participants (63.7%) enrolled had CD4+ T-cell counts less than 200 cells/mm3, and 31% had CD4+ T-cell counts between 200 and 350 cells/mm3. This is reflective of the fact that most individuals do not know their HIV status in South Africa, and only seek treatment when presenting with opportunistic infections and their CD4+ T-cell counts are generally well below the entry criteria of this study. The CIPRA-SA study had a mortality rate of 2.5% which is in line with studies linking mortality to treatment outcome, which have shown that, 1.4% of patients initiating ARV therapy at CD4+ T-cell counts less than 350 cells/mm3 die. In contrast, 3.7% of patients who initiate ARV therapy at CD4+ T-cell counts less than 200 cells/mm3 are expected to die (Sterne et al., 2009). This data provides compelling evidence for initiation of ARV treatment and higher CD4+ T-cell counts to ensure a better prognosis. The South African government recently announced (1 December 2009) that the entry criteria for the government roll-out program will be adjusted to 350 cells/mm3 as of April 2010. This change of initiation criteria 109 was partly driven by results obtained from the CIPRA-SA study. The CIPRA-SA data has thus provided a baseline from which future comparisons can be made. The choice of ARV regimen in the CIPRA-SA cohort mirrored that of the public sector and consisted of 2 NRTIs supported by an NNRTIs (first-lines) or PIs (second-line). NRTIs are the choice of backbone of these regimens as a result of their intracellular persistence allowing for constant viral inhibition. Resistance data from 55 of the 67 participants experiencing viral failure (defined as two viral loads greater than 1000 RNA copies/ml) in this study found that 82% of patients failed with known NRTIs and/or NNRTIs mutations (Figure 3.6). As expected the M184V mutation was observed at the highest frequency, followed by the K103N mutation (Figures 3.7 and 3.8). Thus, these participants were resistant to both classes of ARVS (NRTIs and NNRTIs) prescribed in the first-line regimen. The virus from participants with the M184V mutation are expected to have an increased susceptibility to AZT present in the second-line regimen. Similarly, the presence of NNRTIs mutations, such as K103N and V106M, do not impact on ARVs present in the second-line regimen. These results are similar to those observed in resource rich countries where NRTIs and NNRTIs regimens have been used (Gallant et al., 2006, Gulick et al., 2004, Margot et al., 2006). These results indicate that overall, the ARV resistance patterns emerging in HIV-1 subtype C infected individuals are in line with what was expected from this ARV drug combination and may allow for lessons learnt elsewhere to be used in South Africa. Stavudine (d4T) was one of the two NRTIs used in the first-line regimen for participants recruited onto the CIPRA-SA study. The choice of this drug in Africa is largely based on cost considerations and not the toxic side-effects (Rosen et al., 2008). One hundred and thirty 110 four (16.5%) CIPRA-SA participants failed the first-line regimen as a result of toxicity (Wood et al., 2009, Appendix H), most of which were adverse events linked to d4T (Appendix A). These findings are similar to other studies in South Africa, which investigated toxicity in patients accessing the national ARV first-line regimen. (Boulle et al., 2007) found that amongst 560 of the 2679 (21%) patients that failed treatment due to toxicity, the major contributor was d4T. Furthermore, although toxicity was mainly observed early on in ARV therapy, side effects accumulated over time in participants on d4T, resulting in AZT being substituted for d4T (Boulle et al., 2007). Similarly, participants in CIPRA-SA were substituted to AZT in the event of d4T toxicities. Results from several studies (Boulle et al., 2007, Rosen et al., 2008) as well as CIPRA-SA contributed to the recommendation of removing d4T from the South African roll-out program and substituting it with a more tolerable drug like TNF. As mentioned previously, the M184V mutation was the most frequently observed NRTIs mutation in the CIPRA-SA cohort (67%) and is linked to the presence of 3TC in the first-line regimen. Similar findings have been shown in three other studies looking at mutations emerging from the South African ARV roll-out program, in Johannesburg, Cape Town and Durban (Table 4.1; Marconi et al., 2008, Orrell et al., 2009, Wallis et al., 2010). Table 4.1 summarises published data on mutation patterns from first-line failures in the region, as compared to the CIPRA-SA cohort. Although the emergence of the M184V mutation results in decreased susceptibility to the first-line regimen, it results in increased sensitivity to AZT, one of the NRTIs present in the second-line regimen, thereby increasing the effectiveness of the second-line regimens. 111 In the CIPRA-SA study the NNRTIs of choice were either NVP or EFV in the first-line regimen and mirrored the national ARV roll-out program. The resistance data from this study showed that the Y181C mutation only occurred in participants on the NVP-containing regimen (40%) and was not observed in patients accessing EFV. The V106A mutation (10%) was only observed in participants on a failing NVP-containing regimen and the V106M mutation was more frequent in participants on the EFV-containing arm (18%) than the NVP- containing arm (10%) of CIPRA-SA. Furthermore, in the CIPRA-SA study, EFV was found to select for a wider range of mutations in the RT area investigated than NVP. Of interest was the frequency of the K103N mutation, which occurred in 60% of participants on EFV versus 40% of participants on NVP in the CIPRA-SA study. The difference in mutations selected by EFV and NVP could have an impact on the second generation NNRTIs, etravirine (ETR; in future treatment regimens). Etravirine is less effective in the presence of viruses with the Y181C mutation which is selected by NVP and not EFV. EFV commonly selects for the K103N mutation that does not affect responses to the more flexible second generation NNRTIs-ETR (Lazzarin et al., 2007, Madruga et al., 2007). Since ETR is being considered for incorporation into future second- or third-line regimens, this difference in mutation patterns may impact on whether EFV or NVP is used in future first-line regimens (Stevens et al., 2009). These findings of the NNRTIs mutation patterns are the same as those observed in the South African public sector (Wallis et al., 2010). Apart from ARV regimen choice, the HIV-1 subtype plays a subtle role in the patterns of resistance mutations observed. As shown above, the CIPRA-SA resistance patterns (high frequency of M184V, K103N and V106M; Figure 3.7 and 3.8) are similar to those generated in HIV-1 subtype B (Kantor et al., 2002). However, differences were observed and are a result of different amino acid and nucleotide combinations at codons in RT or PR linked to 112 HIV-1 drug resistance. For example, the T74S minor PI resistance mutation was found in 13% of patients on the CIPRA-SA cohort. This mutation was observed in samples from participants at both study entry (Table 3.10) and viral failure (Appendix F, Table F.1), confirming this is a naturally occurring HIV-1 subtype C polymorphism. The presence of these polymorphisms in HIV-1 subtype C have been noted in other studies (Cane et al., 2001, Grossman et al., 2001), and may have possible effects on PI usage in second-line regimens and requires further investigation. The V106M mutation was found to occur in 18% and 10% of patients in the CIPRA-SA cohort accessing EFV- and NVP-containing regimens, respectively. The V106A mutation was less common and only occurred in 10% of viral failure samples in the CIPRA-SA cohort. Similar results have been observed for the V106M mutation in other HIV-1 subtype C samples from patients accessing a failing EFV- or NVP-containing regimen (Morris et al., 2003). Moreover, the V106M mutation has rarely been seen in HIV-1 subtype B patients accessing EFV or NVP-based regimens (Martinez-Cajas et al., 2009). The frequency of the V106M mutation in HIV-1 subtype C is a direct result of the occurrence of a silent polymorphism at the nucleotide level in this subtype. Of importance the V106M and V106A mutations result in different levels of resistance to NNRTIs. The presence of V106M results in cross-resistance to all first-generation NNRTIs and reduced susceptibility to second- generation NNRTIs (Brenner et al., 2003). Whereas, V106A only results in a 30-fold increase in resistance to NVP and a 2.5-fold increase in resistance to EFV and DLV (Shafer, 2004). These differences could have an impact on NNRTIs used in subsequent regimens. 113 The K103N mutation was the most frequent NNRTIs mutation in the CIPRA-SA cohort, occurring in 50% of all participants. This high frequency is similar to a study by (Flys et al., 2006) which showed that the K103N mutation occurs in higher levels in Ugandan women infected with HIV-1 subtypes C and D versus subtype A. The reason for this difference amongst subtypes is still not completely understood and requires further investigation. As K103N does not impact on the effectiveness of ETR, the presence of this mutation may be advantageous if ETR is used in third-line regimens. The second most frequent NRTIs mutation observed in the CIPRA-SA cohort was the K65R mutation (3%). This is in contrast to HIV-1 subtype B infected patients accessing d4T, where for example, the K65R mutation was observed in only two of 301 (0.7%) patients accessing d4T (Margot et al., 2006). Studies from countries with predominantly HIV-1 subtype C infections have confirmed that the K65R mutation commonly occurs as a consequence of ARV drug regimens containing d4T (Table 4.1; Hosseinipour et al., 2009, Orrell et al., 2009, Wallis et al., 2009b). Similarly, in vitro cell culture studies have revealed that the K65R mutation appears more rapidly in HIV-1 subtype C viral isolates compared to subtype B, CRF01_AE, CRF02_AG, G, and HIV -2 isolates (Brenner et al., 2006, Doualla-Bell et al., 2006, Sungkanuparph et al., 2007). Despite the more rapid appearance of K65R in HIV-1 subtype C isolates, there is no difference between the levels of resistance to TDF, abacavir (ABC), 3TC, and ddI and other subtypes (Brenner et al., 2006). Initially, the occurrence of the K65R mutation was attributed to the longer time patients were left on a failing regimen. However, recent data has linked this increase to the homopolymeric region surrounding codon 65 (Coutsinos et al., 2009). This poly-A region results in the RT enzyme pausing during cDNA synthesis and thereby increasing the chances of incorrect nucleotide incorporation. A major problem with the higher frequency of the K65R mutation seen in 114 HIV-1 subtype C is that it results in cross-resistance to most NRTIs (Johnson et al., 2008) and has consequences for the subsequent use of most NRTIs, especially TDF in second-line regimens. Furthermore, because TDF is being investigated for use in pre-exposure prophylaxis (PREP) the emergence of the K65R mutation and the implications this may have on PREP needs to be further investigated. The other major difference between clinical criteria used on the CIPRA-SA study and the public sector cohorts was the definition of viral failure. In the CIPRA-SA cohort, participants were classified as experiencing virological failure by two consecutive viral loads greater than 1000 RNA copies/ml. This is unlike the South African national roll-out programme which switches at two consecutive viral loads greater than 5000 RNA copies/ml. By contrast, the WHO recommendations (prior to 1 December 2009) advised switching ARV treatment at viral loads greater than 10000 RNA copies/ml. Furthermore, some African countries which do not have access to viral load measurements use CD4+ T-cell counts (immunological failure) and/or clinical criteria to switch. The early switching in the CIPRA-SA cohort were in line with several studies which have shown that the earlier ARV therapy is switched when a patient is failing, the less complex the mutation patterns associated with HIV-1 drug resistance. Results from this study confirmed these findings, and highlight the differences between African countries using different criteria for ARV regimen switching. Overall, 82% of participants experiencing viral failure harboured ARV drug resistance mutations and 62.7% had resistance to NRTIs and NNRTIs on the CIPRA-SA cohort. Both these percentages are lower than results from all other published studies from the region. For example, the Malawi study which accessed ARV drug resistance mutation patterns in patients 115 that were switched on immunological and/or clinical criteria found that 95% of the patients had mutations associated with ARV drug resistance, 94% of which had resistance to NRTIs and NNRTIs (Hosseinipour et al., 2009). Ongoing viral replication and frequency of ARV drug resistance mutations that occur as a result of different switch criteria among countries will have an impact on the use of NRTIs and second-generation NNRTIs in future ARV drug regimens. Similarly, the M184V mutation occurred at a lower frequency in participants (67.2%) with viral failure on the CIPRA-SA cohort. This frequency is considerably lower than resistance data emerging from Malawi, with a reported M184V prevalence of 81% (Table 4.1; Hosseinipour et al., 2009). The higher percentage in Malawi is possibly attributed to the switch criteria being dependent on immunological and clinical considerations, versus virological failure. Furthermore, the M184V frequency in CIPRA-SA was lower than those reported in two other South African studies from patients on failing regimens on the South African roll-out programme. Frequencies of 78% and 74% in Cape Town (Orrell et al., 2009) and Johannesburg (Wallis et al., 2009b), respectively were reported. The higher frequency of the M184V in patients from the government sector is likely due to viral load levels of 5000 RNA copies/ml being used as the definition of virological failure. Findings from the CIPRA- SA study are supported by similar M184V frequencies (64.3%) amongst patients from the government sector in Durban, where a viral load cut-off of 1000 RNA copies/ml was used to define viral failure (Marconi et al., 2008). Moreover, analysis of longitudinal samples examined on the CIPRA-SA cohort showed that the M184V mutation is the major NRTIs mutation which is present at early ARV drug failure, or is likely to emerge in patients within the first 3 months left on a failing ARV regimen (section 3.2.4). As mentioned previously, the implications for the increased frequency of M184V are beneficial for subsequent AZT 116 use; however, the emergence of this mutation may have an impact on future NRTIs still in development. Overall, the ARV drug mutation complexity, as defined by the occurrence of K65R, Q151M and TAMs was much lower than that observed in previous studies from the region. Although the predominant circulating subtype is the same for both countries, the K65R mutation occurred in 3% of the CIPRA-SA population, as compared to 19% in the Malawi study (Table 4.1; Hosseinipour et al., 2009) and the South African studies (Orrell et al., 2009, Wallis et al., 2010). This difference is most likely attributed to the length of time the Malawian patients were left on a failing ARV drug regimen (Table 4.1). Furthermore, only one CIPRA-SA participant had three TAMs on a failing first-line regimen. This is in complete contrast to all other published studies from the region which report levels of 23% to 56% (Hosseinipour et al., 2009, Marconi et al., 2008, Orrell et al., 2009, Wallis et al., 2010). The Q151M mutation did not occur in CIPRA-SA study, but has been shown to occur in up to 19% of patients on a failing first-line regimen in the region. This increase of ARV drug resistance mutations has been described in patients from the USA (Hatano et al., 2006), where participants on a failing regimen for a median of 11.3 months and viral loads greater than 1000 RNA copies/ml demonstrated an increase in both drug-associated and non-drug associated mutations, resulting in a 0.5 fold decrease in susceptibility to all NRTIs, NNRTIs and PIs. Similarly, a study by (Cozzi-Lepri et al., 2007) showed that European participants left on a failing regimen (HIV viral load > 400 copies/ml) for 6 months had on average an increased accumulation of two mutations with an average loss of 1.25 active ARV drugs. Overall, different switch criteria used amongst different countries can result in a delayed ARV regimen switching, leading to the occurrence of more complex HIV-1 ARV drug resistance mutation patterns. These complex ARV drug resistance mutation patterns result in 117 reduced susceptibility to all currently available FDA approved NRTIs, resulting in the PIs being the only fully effective ARV drug in the current second-line regimen in South Africa. The longitudinal resistance data in this cohort demonstrated that the number of NNRTIs mutations increased with approximately one additional mutation for every month left on a failing ARV drug regimen (Figure 3.9). To the best of our knowledge this is the first report of the accumulation of NNRTIs ARV drug resistance mutations in HIV-1 subtype C. By contrast, resistance data for the development of TAMs in HIV-1 subtype B shows that TAMs increase at a slow rate of approximately 0.11 TAMs per year (Cozzi-Lepri et al., 2009, Goetz et al., 2006, Stevens, 2009). The more rapid accumulation of NNRTIs ARV drug resistance mutations may have an impact on the future use of second-generation NNRTIs and requires further investigation. Eighteen percent of the CIPRA-SA participants with virological failure had no known ARV drug resistance mutations present. This is similar to what has been observed in the South African national roll-out program (16%; Wallis et al., 2010). However, this is nearly twice as high as observed in the NORA cohort (in Uganda; DART Virology Group, 2006) within the Development of Antiretroviral Therapy on Africa study (DART, 10%; full ARV drug resistance patterns for DART are not yet available). The DART study is the largest clinical trial run in Africa investigating ARV therapy in HIV-1 infected individuals, where only the CD4+ T-cell counts are measured (samples were stored for further viral investigations). This difference between South Africa and Uganda is more than likely linked to differences in switch criteria (virological versus immunological). However, there may be minority variants with known ARV drug resistance mutations that are below the lower detection limits of the 118 in-house ARV drug resistance assay, and thus not detected, circulating within these patients that contributed to viral failure. Analysis of the minority variants using pyrosequencing in the CIPRA-SA cohort is planned. Overall, the subtype of the infecting virus, ARV drug choice and most importantly time of switch from the first-line regimens are essential components to ensuring there are optimal second- and third-line regimens available to patients. Furthermore, because NRTIs form the basis of most future regimens, the complexity of NRTIs ARV drug resistance mutations should be avoided. A study by (Riddler et al., 2008), has shown that NRTIs-sparing regimens are non-inferior, but patients have an increase in laboratory associated adverse events (Riddler et al., 2008). Data emerging from the South African second-line regimens indicate that failure to these regimens are more likely as a results of poor tolerability and non- adherence, as resistance to PIs is infrequently observed (Wallis et al., 2009a). Similarly, resistance patterns from the CIPRA-SA participants that accessed a failing first-line regimen indicated that they were susceptible to the NRTIs and the PIs prescribed in the second-line regimen. Of the patients that commenced the second-line, a high percentage of them never achieved full viral suppression, indicating either poor tolerability to ddI or lopinavir and/or non-adherence were the main causes of treatment failure. The ARV drug resistance profile data emerging from the CIPRA-SA study has formed a vital component in helping determine and strategize for appropriate treatment strategies and ARV choices for second- and third-line regimens in South Africa. The CIPRA-SA study has confirmed that the earlier patients are started on ARV drug therapy, the better their chances of a favourable treatment outcome. Furthermore, baseline viral load is not a predictor of 119 ARV outcome, and therefore performing this test as an ARV drug treatment initiator is not required. However, the more frequent viral load monitoring and its use in determining viral failure has implications for development of less complex ARV drug resistance mutation patterns. The data also shows that the introduction of ARV drug resistance testing at a patient management level would be beneficial after first-line failure as this would identify patients with no ARV drug resistance, ensuring they are not unnecessarily switched to a more expensive second-line regimen. The high cost of ARV drug resistance testing would therefore be recouped by the reduced number of patients switched to a more expensive second-line regimen. Additionally, the patients with no ARV drug resistance would be re-counselled to increase adherence and help ensure viral suppression and reduce viral transmission. Surveillance studies of ARV drug resistance mutation patterns like this one performed on the CIPRA-SA cohort are vital in ensuring appropriate preservation of existing and future ARV regimens, as recommended by the WHO (WHO, 2009). From this study, it is clear that the introduction of TNF into a second-line regimen after the use of d4T in the first-line regimen may be sub-optimal, as the K65R mutation occurs at a high frequency in these patients requiring a regimen switch. Therefore, the introduction of TNF into a first-line regimen would be more beneficial, from a toxicity point of view, and has recently been proposed as a change to the South African guidelines. Similarly, the use of AZT in the second-line regimen is appropriate as HIV-1 has increased susceptibility to AZT in the presence of the M184V mutation. If ARV drug regimen switching occurs when a patient has a lower viral load, the choice of NRTIs that can be used in the second-line regimen increases as there are fewer TAMs observed. Results from this study also show that second-generation NNRTIs would be more effective in patients on a failing EFV-based regimen rather than a NVP-based regimen, making it a promising option for third-line regimens. The results of the NNRTIs 120 resistance patterns also confirm that the earlier a patient is switched the less number of NNRTIs mutations have accumulated, ensuring second-generation NNRTIs can be used in later regimens. A small subset of second-line failures on CIPRA-SA had no resistance at the time of second-line failure, indicating that the tolerability and adherence of ARVs in the second-line is more than likely the reason for treatment failure. This highlights the need for better tolerated ARVs to be incorporated into second-line regimens, for example, the integrase inhibitor raltegravir may be a better choice than Kaletra, or a different PIs should be used to improve tolerability. Data from the CIPRA-SA study and from other studies performed in South Africa looking at the development of HIV-1 ARV drug resistance have shown that there is a continued need for sentinel ARV drug resistance surveillance studies at ARV treatment clinics. The information obtained from such studies will help monitor the emerging ARV drug resistance patterns from current national ARV roll-out programs, and help inform the suitability of future ARV drug regimens. Furthermore, data from developed countries shows that between 3.4% to 26% of new infections have viruses harbouring ARV drug resistance (Taiwo, 2009). As more South Africans are accessing ARV therapy, it is expected that transmitted HIV-1 drug resistance will also increase, and thus will need to be monitored. Although the newly developed in-house ARV drug resistance assay is cheaper than the commercially available assays, there is still a need to further reduce the costs associated with these assays. The CIPRA-SA data confirms that a higher CD4+ T-cell count at ARV drug treatment initiation result in a better prognosis. However, for long term monitoring of patients on ARVs, viral load testing is more beneficial than immunological monitoring. Several studies 121 including this study have shown that the ARV resistance patterns that emerge in patients failing therapy are less complex in patients monitored virologically than immunologically. The need for viral load monitoring is corroborated by a recent study from Malawi where 43% of patients who were classified as failing the first-line regimen on immunological or clinical grounds were in fact virologically suppressed (Hosseinipour et al., 2009) and did not require switching to a more expensive second-line regimen. This is contrary to the data emerging from the DART study which suggests that no laboratory monitoring is required for patients on ARV therapy (Medina-Lara et al., 2009). Results from the CIPRA-SA study also allude to the fact that viral monitoring should occur more frequently, however, the CIPRA-SA study was not powered to answer this question. A randomised control study needs to be performed to determine the optimal time points and frequency of viral load monitoring in patients on HAART. Having viral loads performed at three months after initiation of ARV therapy, may be beneficial in increasing adherence, as data on CIPRA-SA shows that 70% of participants with a less than a 1.5 log10 drop in viral load at week 12 (Figure 3.6) had no HIV-1 ARV drug resistance. 122 Table 4.1: A summary of the ARV drug resistance studies emerging from first-line failures in four African countries. Site Malawi (Hosseinip our et al., 2009) Tanzania (J ohannessen et al., 2009) Botswana (Doualla- Bell et al., 2009) South Africa Cape Town (Orrell et al., 2009) South Africa Johannesburg (Wallis et al., 2010) South Africa Durban (Marconi et al., 2008) South Africa CIPRA- SA Sample Size Clinical Sites 94 2 22 1 63 1 110 1 226 2 115 2 67 2 Indicator for treatment initiation CD4+ T- cell count <200 cells/mm3 or clinical staging CD4+ T-cell count <200 cells/mm3 or clinical staging Unknown CD4+ T-cell count <200 cells/mm3 CD4+ T-cell count <200 cells/mm3 CD4+ T-cell count <200 cells/mm3 CD4+ T- cell count <350 cells/mm3 Switch Criteria CD 4 cell count decrease >30% or WHO staging Viral load greater than 10 000 RNA copies/ml (n=9); in this study viral load > 1000 RNA copies/ml (n=14) Viral load greater than 400 RNA copies/ml Viral load greater than 5000 RNA copies/ml Viral load greater than 5000 or 1000 RNA copies/ml Viral load greater than 1000 RNA copies/ml Viral load greater than 1000 RNA copies/ml Frequency of Monitoring Irregular Unknown Unknown 6 monthly- viral load & CD4+ T-cell 6 monthly- viral load & CD4+ T-cell 6 monthly- viral load & CD4+ T-cell 3 monthly- viral load & CD4+ T-cell First Line Regimen d4T, 3TC, NVP (100%) d4T, 3TC, EFV (57.5%) AZT, 3TC, EFV (2.8%) d4T, 3TC, NVP (18.4%) AZT, 3TC, NVP (21.2%) ddI, d4T,NVP/E FV (41%) AZT, 3TC, NVP/EFV (59%) d4T, 3TC, EFV (67%) AZT, 3TC, EFV (16%) d4T, 3TC, EFV (65) AZT, 3TC, EFV (24%) d4T, 3TC, NVP (10%) AZT, 3TC, NVP (1%) d4T, 3TC, EFV (49%) AZT, 3TC, EFV (26%) d4T, 3TC, EFV (59%) d4T, 3TC, NVP (27%) d4T, 3TC, NLF (4%) d4T, 3TC, lopinavir/r (10%) Median Time on First-line (months) 36.5 (8-127) 22.3 (14-29.9) 9.3-26.9 Unknown Unknown 12 15 (3-33) % with failure & resistance 95% 82% 90% 85% 83% 83.5% 82% Subtypes: A B C D Other 100% 14% 0% 32% 36% 18% 100% 98% 96.5% 98% 100% M184V 81% 64% 50.5% 78% 72% 64.3% 67.2% NNRTI K103N V106M 93% 28% 6% 77% 27% 0% 87% 41.6% 23.5% 86% 55% 31% 78% 38% 17% Unknown 51% 19% 75% 50% 14% TAMS >3 56% 23% 5% TAMs I 48% TAMs II 59% 23% 11% 32.2% 1.5% K65R 19% 5% 7.7% 9% 4.5% 2.6% 3% Q151M 19% 0% 3.25% Unknown 2.5% 0.9% 0% NRTI+NNRTI 94% 64% Unknown 83% 73% 64.3% 63% 123 Aside from the emergence of HIV-1 drug resistance, toxicity and/or the ability to tolerate ARVs is essential in ensuring successful ARV drug treatment outcomes. This is achieved by ensuring the bioavailability of the ARVs in the treated individual is kept at optimal plasma or intracellular levels. Changes in ARV drug plasma concentration have been linked to either toxicity when there is an increase (Marzolini et al., 2001, Stahle et al., 2004) or viral failure when there is a decrease in the plasma concentration (Langmann et al., 2002, Marzolini et al., 2001, Stahle et al., 2004). Furthermore, studies have shown that the concentration of EFV in plasma can be different between individuals that are prescribed the same fixed dose, thus affecting ARV drug treatment outcome (Gatanaga et al., 2007, Gatanaga and Oka, 2009, van Luin et al., 2009). This variation in ARV drug concentrations has been associated with DNA sequence variants in human genes involved in ARV drug metabolism and absorption. At the time the CIPRA-SA study was initiated, four SNPs in CYP3A4, CYP3A5, CYP2B6 and MDR-1 had been associated with ARV drug metabolism and absorption (Haas et al., 2004). The NNRTI, EFV is known to be mainly metabolized by CYP2B6, with minor contributions from CYP3A4 and CYP3A5 (Desta et al., 2007, Ward et al., 2003). This study found that the 516TT genotype, linked to altered CYP2B6 function, occurred in a small percentage (13.3%; Table 3.14) of the control population examined and was similar to genotype frequencies observed elsewhere in South Africa (Parathyras et al., 2009). This is similar to other studies, which have shown that the 516TT allele occurs less frequently in African Americans, than European Americans (Ribaudo et al., 2006). Furthermore, the presence of the 516TT genotype has previously been linked to toxicity in patients accessing HAART (Rotger et al., 2005). However, dose optimisation in the presence of this genotype can reduce the central nervous system toxicities (Gatanaga et al., 2007, Gatanaga and Oka, 2009). Univariate analysis of all CIPRA-SA participants to determine if there was a link 124 between ARV drug treatment outcome and the presence of the 516TT genotype revealed that there was no association between the genotype and viral failure or toxicity. Studies have shown that the 516TT genotype is the major contributor to increased levels of EFV (Haas et al., 2004, Ribaudo et al., 2006, Rodriguez-Novoa et al., 2005, Rotger et al., 2005, Tsuchiya et al., 2004, Wang et al., 2006). To this end, the link between the CIPRA-SA participants accessing an EFV-based regimen and the 516TT genotype was examined. Results showed that there was no link between the 516TT genotype and treatment outcome (toxicity and viral failure) of these participants. It is possible that other SNPs present in enzymes which also metabolise EFV are responsible for treatment outcome in the CIPRA-SA participants. For example, recent studies have shown that CYP2A6 also plays a role in oxidising EFV (di Iulio et al., 2009, Kwara et al., 2009b) and that EFV undergoes glucuronidation metabolism by UGT2B7 (Kwara et al., 2008). Similarly, no association between the genotypes examined for CYP3A4 and CYP3A5 were found. This is similar to findings from another study, which has shown that the G1344A and A6986G SNPs do not link to ARV metabolism (Robertson et al., 2008). All participants on the CIPRA-SA study were accessing d4T and 3TC as part of the first-line regimen, and as discussed above, no association was found between any of the three metabolising SNPs examined in this study and treatment outcome. This is likely due to the fact that CYP450 does not contribute to metabolism of NRTIs, except AZT (Cretton and Sommadossi, 1993), which was not available in the first-line regimen. However, 3TC and d4T are both activated by a complex process of phosphorylation and intracellular catalysis by kinases (Arner and Eriksson, 1995, Shewach et al., 1993) and 5?nucleotidases (Hunsucker et al., 2005, Zimmermann, 1992) and this study did not examine any SNPs that may alter these enzymes function, since none have been described in the literature. Furthermore, although PIs 125 are metabolised by CYP450 (and other enzymes), the link between this could not be examined on the CIPRA-SA study as PIs were not prescribed in the first-line regimen, except if patients were pregnant. Thus due to the small numbers, no statistically significant association could be made. This study investigated one SNP that occurs in the gene MDR-1 (C3435T), which encodes for P-gp, a transporter linked to transportation of ARVs across the cellular membrane (Pan et al., 2007). The 3435TT genotype occurred in the minority of the CIPRA-SA participants and control group examined and is linked to a decreased level of expression on P-gp on the cellular membrane. As this genotype has previously been linked to decreased EFV and nelfinavir cellular concentrations (Fellay et al., 2002), because of a reduced transport across the cellular membrane, the association between this genotype and treatment outcome was examined. No association was found between virological failure and CIPRA-SA participants with the 3435TT genotype. Conversely, the 3435CC genotype has been associated with an increase in cellular EFV concentration and toxicity, however, no association between toxicity and the 3435CC genotype was found in the CIPRA-SA study. Studies have shown that there are over 350 transporters which are linked to the absorption of NRTIs, NNRTIs and PIs (Hediger et al., 2004) and this may be a reason why no association was found. Furthermore, other SNPs in MDR-1 (T129C and G2677A) have recently been linked to CD4+ T-cell recovery rates (Parathyras et al., 2009), which would impact on treatment outcome, however these could not be examined in this study. Future investigations into these other MDR-1 SNPs should be performed as emerging data shows that the CD4+ T-cell recovery rate in South African HIV-1 positive patients is slower than that observed in patients from Europe and the US (Lisgaris et al., 2005). 126 There are several limitations to the host genetic analyses performed in this study. Firstly, only 4 SNPs were examined and it has now been shown that there are a great number of pharmacogenetic and environmental factors that impact on ARV concentrations and subsequent ARV drug treatment outcome (Telenti and Zanger, 2007). Therefore, genome wide association studies of genetic variations, on microarrays for example, would undoubtedly be more beneficial and allow for linkage between different genetic variants to be made. There are several microarray technologies available which can either be used to detect up to 906600 SNPs in the human genome, or to determine differences in 949000 mRNA expression levels (Affymetrix Genome Wide Human SNP Array 6). Although, no association could be found between the host genetic variations examined in this study, it does not preclude that other SNPs can be associated with ARV drug metabolism and absorption in South African patients. Large scale genome wide association studies examining overall genetic variation and possible associations are needed to minimise the number of failure events due to adverse ARV drug reactions. Secondly, although the background frequency from each genotype was determined for the adequately sized control South African population, the size of the CIPRA-SA clinical cohort investigated was too small to reach statistical significance because only 248 of the 812 CIPRA-SA participants consented for host genetic studies. This became apparent only after the control group frequencies were established. However, even if the total 812 participants consent for SNP analysis, standard sample size calculations to achieve an 80% power to link the gene to treatment outcome showed this would have been an insufficient number. To achieve an 80% power using a gene frequency of 10%, a tripling in the total CIPRA-SA cohort (n=812) would have been required to ensure an accurate linkage of the SNPs to viral failure or toxicity outcome. Furthermore, the CYP3A4, 3A5 and MDR-1 homozygous 127 variants occurred in 5.5%, 3.0% and 1.4%, of the background population examined. These frequencies are below the 10% which was used in the standard sample size calculation performed. Similarly, the homozygous variant for CYP2B6 was found to occur in 15.7% of the background population and this would have required a 2.3 increase in the overall CIPRA- SA sample size, which equated to approximately 1868 participants. The background frequencies described here, however, provide a framework for better planned studies in the future. In conclusion, the study has shown that ARV drug treatment outcome in South Africa is dependent on the combination of time of initiation of treatment, ARV drug regimen chosen, HIV-1 subtype, duration on a failing regimen and individual genetic background. This is similar to other international studies. The higher the CD4+ T-cell count when commencing ARV therapy, the greater the chance of viral suppression. The overall resistance patterns are less complex when viral load is monitored more frequently and viral failure determined at 1000 RNA copies/ml. When viral failure is determined at a lower level, it is likely that patients who virologically fail due to non-adherence will be detected earlier. These patients can be re-counselled to prevent the emergence of ARV drug resistance attributed to non- adherence. This will ensure fewer patients are switched to the more expensive second-line regimen. In addition, the CIPRA-SA cohort has shown that the usage of d4T is linked to high levels of toxicity, and the development of the K65R mutation which impacts on most second- line NRTIs choices. HIV-1 subtype C natural sequence variation causes the unique development of mutations such as K65R and V106M, which result in different levels of ARV drug resistance and may impact on future treatment options. Overall, the results highlight the importance of frequent monitoring of virological parameters such as viral loads and ARV drug resistance in patients on ARV therapy, to preserve future ARV treatment options. 128 APPENDIX A 129 AP PEND I X A DIV I SIO N OF AIDS T AB L E FOR GRAD ING T HE S EVERIT Y OF ADUL T AND PED I AT RIC ADV ER SE EVENT S VERS IO N 1 .0 , DECE MBER, 200 4 ; CL AR IF I CAT IO N AUGUST 200 9 28 - D ec - 0 4 /C l arif ic ati on A u g 0 9 P ag e 1 of 2 1 V ers i on 1. 0 /C l ar if ic ati on 1 The Div i si on of AI DS Tabl e for Gradi ng the Sev eri t y of Adul t and Pedi at ri c Adv erse Ev ent s (?DAI DS AE Gradi ng Tabl e?) i s a descri ptiv e termi nol ogy whi ch can be ut ili zed f or Adv erse Ev ent (AE) reporti ng. A gradi ng (sev erit y) scal e i s prov i ded f or each AE ter m. Thi s cl arif icati on of t he DAI DS Tabl e for Gradi ng the S ev eri t y of Adult and Pedi at ri c AE?s prov i des addi t i on al ex pl anat i on of the DAI DS AE Gradi ng T abl e and cl arif i es som e of the param et ers. I . In stru cti on s and Cl ari fi cati on s Gradi ng Adul t and Pedi a tric AEs The DAI DS AE Gradi ng T abl e i ncl udes param et ers f or gradi ng bot h Adult and Pedi at ri c AEs. W hen a si ngl e set of param et ers i s not appropri at e for gradi ng specif i c types of AEs f or bot h Adul t and Pedi at ri c popul at i ons, separat e set s of param et ers f o r Adul t and/or Pedi at ri c popul ati ons (wi t h specif i ed respect iv e age ranges) are giv en i n the T abl e. If there i s no di sti nct i on i n the T abl e bet ween Adul t and Pedi at ri c v al ues f or a type of AE, then the si ngl e set of param et ers l i st ed i s to be used f or gra di ng the sev eri t y of bot h Adul t and Pedi at ric ev ent s of that type. No te: In the cl assi f i cat i on of adv erse ev ent s, the term ? severe ? i s not the sam e as ? seri ou s . ? Sev eri ty i s an i ndi cati on of the i nt ensi t y of a specif ic event (as i n mil d, m oderat e, or sev ere chest pai n). The term ? seri o u s ? rel at es to a parti ci pant / ev ent out com e or acti on cri t eri a , usual l y associ at ed wi t h ev ent s that pose a threat to a part ici pant ?s l if e or f uncti oni ng. Addenda 1 - 3 Gradi ng Tabl es f or Mi crobi ci de St udi es For prot ocol s i nv olv i ng topical appli cati on of product s to the f em al e genit al tract , m al e geni t al area or rect um , st rong consi derat i on shoul d be giv en to usi ng Appendi ces I - I II as the prim ary gradi ng scal es f or these area s. The prot ocol woul d need to specif i cal ly stat e tha t one or m ore of the Appendi ces woul d be prim ary (and thus take precedence ov er the m ai n Grading T abl e) for i t em s that are li st ed i n bot h the Appendi x and the m ai n Gradi ng T abl e. ? Addendum 1 - Fem al e Genit al Gradi ng Tabl e f or Use i n Microbi ci de St udi es - PDF ? Addendum 2 - Mal e Geni t al Gradi ng Tabl e f or Use i n Mi crobici de St udi es - PDF ? Addendum 3 - Rect al Gradi ng Tabl e for Use i n Mi crobici de St udi es - PDF Grade 5 For any AE where the out com e i s deat h, the sev erit y of the AE i s cl assi f i ed as Grade 5. Est im ati ng Sev eri t y Grade f or Param et ers Not Identif i ed i n the Tabl e In order to grade a cl i ni cal AE that i s not i dentif i ed i n the DAI DS AE gr adi ng tabl e, use the cat egory ?Est im ati ng Sev eri ty Grade? l ocat ed on Page 3. Det ermi ni ng Sev eri t y Grade for Param et ers ?Bet ween Grades? If the sev eri t y of a cl i ni cal AE coul d f al l under eit her one of two grades (e. g. , the sev erit y of an AE coul d be ei t her Grade 2 or Grade 3), sel ect the hi gher of the two grade s f or the AE. If a l aborat ory v al ue that i s graded as a m ult i pl e of the ULN or LLN f all s bet ween two grade s, sel ect the hi gher of the two grades f or the AE. For ex am pl e, Grade 1 i s 2. 5 x ULN and Grade 2 i s 2. 6 x ULN f or a param et er. If the l ab v al ue i s 2. 53 x ULN (whi ch i s bet ween the two grade s), the sev eri t y of thi s AE woul d be Grade 2, the hi gher of the two grade s. Val ues Bel ow Grade 1 Any l aborat ory v al ue that i s bet ween ei t her the LLN or ULN and Grade 1 shoul d not be graded . 130 AP PEND I X A DIV I SIO N OF AIDS T AB L E FOR GRAD ING T HE S EVERIT Y OF ADUL T AND PED I AT RIC ADV ER SE EVENT S VERS IO N 1 .0 , DECE MBER, 200 4 ; CL AR IF I CAT IO N AUGUST 200 9 28 - D ec - 0 4 /C l arif ic ati on A u g 0 9 P ag e 2 of 2 1 V ers i on 1. 0 /C l ar if ic ati on 1 Det ermi ni ng Sev eri t y Grade when Local Laborat ory Norm al Val ues Ov erl ap wi t h Grade 1 Ranges In these si t uat i ons, the sev erit y gradi ng i s based on the ranges i n the DAI DS AE Gradi ng Tabl e, ev en whe n there i s a ref erence to th e l ocal l ab LLN. F or example: Phosphat e, Serum, Low , Adult a nd Pediat ric > 14 years (Page 20 ) Grade 1 range is 2. 50 mg/ dL - < LLN. A part i cul ar l aborat ory?s norm al range for Phosphat e i s 2. 1 ? 3. 8 m g/ dL. A parti ci pant ?s act ual l ab v al ue i s 2. 5. In thi s case, the v al ue of 2. 5 exceeds the LLN f or the l ocal l ab, but wi ll be graded as Grade 1 per DAI DS AE Gradi ng Tabl e . . I I . Defi n i ti on s of terms used in th e T ab l e: Basi c Self - care Functi ons Adul t Activ iti es such a s bat hi ng, dressi ng, toil eti ng, transf er/m o v em ent , cont i nence, and feedi ng. Young Chi l dren Activ iti es that are age and cul t ural ly appropri at e (e. g., feedi ng sel f wi t h cul t ural ly appropri at e eati ng im pl em ent). LLN Lower l imit of norm al Medi cal Int erv enti on Use of pharm acol ogi c or bi ol ogic agent (s) f or treatm ent of an AE. NA Not Appli cabl e Operat iv e Int erv ent i on Surgi cal OR ot her i nv asiv e m echani cal procedures. ULN Upper l imit of norm al Usual Soci al & Functi onal Activ iti es Adul t Adapt iv e tasks and de si rabl e activ iti es, such as goi ng to wo rk, shop pi ng, cooki ng, use of transport ati on, pursui ng a hobby, et c. Young Chi l dren Activ iti es that are age and cul t ural ly appropri at e (e. g., soci al i nt eracti ons, pl ay activ iti es, l earni ng tasks, et c. ). 131 AP PEND I X A DIV I SIO N OF AIDS T AB L E FOR GRAD ING T HE S EVERIT Y OF ADUL T AND PED I AT RIC ADV ER SE EVENT S VERS IO N 1 .0 , DECE MBER, 200 4 ; CL AR IF I CAT IO N AUGUST 200 9 Basi c S elf - car e Fun cti ons ? Adu lt : Ac t i viti es s uc h as b at hi ng , d r es s ing , t oi l et in g, tr ans f er / m o vem en t, c on ti n enc e, an d f eed in g. B asi c S elf - car e Fu nct ion s ? Y oun g Chi ldr en : Ac t i viti es th at ar e ag e and c u ltu r al l y ap pr opr i at e ( e.g ., f eedi ng s elf wi th c u ltu r all y ap pr opri at e eat in g i m pl em en t). U sua l Soc ia l & Funct ion al Ac tiv itie s ? Adu lt : Ad ap ti ve t as k s an d d es ir ab l e ac t i viti es , s uc h as g oin g t o wor k, s h op pi ng, c ook in g, us e of tr ans p or t at i on, pu rs ui ng a h obb y, etc . U sua l So cia l & Fun cti on al Activ it ie s ? Y oung C hil dr en : Ac ti vit i es th at ar e ag e and c u ltu r al l y ap pr opr i at e ( e.g. , s oc i al in t er ac ti ons , pl ay ac ti vi ti es , l ear ni ng t as ks , etc .). 28 D ec 0 4/C l ar if ic ati on Au g 09 Page 3 of 21 V ers i on 1. 0/ C l arif ic at i on 1 PAR AMET ER GRADE 1 MI L D GRADE 2 MO DERAT E GRADE 3 SEVERE GRADE 4 PO TENTI ALLY LI FE - THREATENI NG EST IMAT I NG SEVERIT Y GRADE Cl i ni cal adver se event NO T i denti fi ed el sewh er e i n this DAI DS AE Gr adi ng Tabl e Sym pt om s causi ng no or minim al i nt erf er ence wi t h usual soci al & funct ional acti vi ti es Sym pt om s causi ng gr eat er than minim al i nt erf er ence wi t h usual soci al & functi onal acti vi ti es Sym pt om s causi ng i nabi lit y t o per f orm usual soci al & functi onal acti vi ti es Sym pt om s causi ng i nabi lit y t o per f orm basic sel f - car e funct i ons O R Medi cal or oper ati ve i nt er venti on indi cat ed t o pr event perm anent im pairm ent , per sist ent di sabil it y, or deat h SYST EMI C Acut e syst em i c al l er gi c reacti on Locali zed ur ti cari a (wheal s) wit h no m edi cal i nt er vent i on i ndi cat ed Locali zed ur ti cari a wit h m edi cal i nt er vent i on i ndi cat ed O R Mil d angi oed em a wi th no m edi cal i nt er vent i on i ndi cat ed G ener al i zed urt icari a O R Angi oedem a wit h m edi cal i nt er vent i on i ndi cat ed O R Sym pt om ati c mil d br onchospasm Acut e anaphylaxi s O R Li f e - t hr eat eni ng br onchospasm O R l aryngeal edem a Chi ll s Sym pt om s causi ng no or minim al i nt erf er ence wi t h usual soci al & funct ional acti vi ti es Sym pt om s causi ng gr eat er than minim al i nt erf er ence wi t h usual soci al & functi onal acti vi ti es Sym pt om s causi ng i nabi lit y t o per f orm usual soci al & functi onal acti vi ti es NA Fat igue Mal aise Sym pt om s ca usi ng no or minim al i nt erf er ence wi t h usual soci al & funct ional acti vi ti es Sym pt om s causi ng gr eat er than minim al i nt erf er ence wi t h usual soci al & functi onal acti vi ti es Sym pt om s causi ng i nabi lit y t o per f orm usual soci al & functi onal acti vi ti es I ncapacit at i n g f at i gue/ mal aise sym ptom s causing i nabil it y to per f orm basi c sel f - car e f unct ions Fever (nonaxi ll ar y) 37. 7 ? 38. 6 ?C 38. 7 ? 39. 3 ?C 39. 4 ? 40. 5 ?C > 40. 5 ?C Pai n (i ndi cat e body sit e) DO NO T use for pai n due to i nj ect ion (See I nj ecti on Si t e React i ons: I nj ec t ion sit e pai n) See al so Headache, Ar t hr al gia, and Myal gi a Pai n causi ng no or minim al i nt er f er ence wi t h usual soci al & funct ional acti vi ti es Pai n causi ng gr eat er t han mi nim al i nt erf er ence wi t h usual soci al & functi onal acti vi ti es Pai n causi ng i nabi lit y t o per f orm usual soci al & funct ional acti vi ti es Di sabl ing pai n causi ng i nabi lit y t o per f orm basic sel f - car e funct i ons O R Hospit al i zati on (ot her t han em er gency room vi si t) i ndi cat ed 132 AP PEND I X A DIV I SIO N OF AIDS T AB L E FOR GRAD ING T HE S EVERIT Y OF ADUL T AND PED I AT RIC ADV ER SE EVENT S VERS IO N 1 .0 , DECE MBER, 200 4 ; CL AR IF I CAT IO N AUGUST 200 9 Basi c S elf - car e Fun cti ons ? Adu lt : Ac t i viti es s uc h as b at hi ng , d r es s ing , t oi l et in g, tr ans f er / m o vem en t, c on ti n enc e, an d f eed in g. B asi c S elf - car e Fu nct ion s ? Y oun g Chi ldr en : Ac t i viti es th at ar e ag e and c u ltu r al l y ap pr opr i at e ( e.g ., f eedi ng s elf wi th c u ltu r all y ap pr opri at e eat in g i m pl em en t). U sua l Soc ia l & Funct ion al Ac tiv itie s ? Adu lt : Ad ap ti ve t as k s an d d es ir ab l e ac t i viti es , s uc h as g oin g t o wor k, s h op pi ng, c ook in g, us e of tr ans p or t at i on, pu rs ui ng a h obb y, etc . U sua l So cia l & Fun cti on al Activ it ie s ? Y oung C hil dr en : Ac ti vit i es th at ar e ag e and c u ltu r al l y ap pr opr i at e ( e.g. , s oc i al in t er ac ti ons , pl ay ac ti vi ti es , l ear ni ng t as ks , etc .). 28 D ec 0 4/C l ar if ic ati on Au g 09 Page 4 of 21 V ers i on 1. 0/ C l arif ic at i on 1 PAR AMET ER GRADE 1 MI L D GRADE 2 MO DERAT E GRADE 3 SEVERE GRADE 4 PO TENTI ALLY LI FE - THREATENI NG Uni nt enti onal wei ght l oss NA 5 ? 9% l oss in body wei ght f r om baseli ne 10 ? 19 % l oss i n body wei ght f r om baseli ne ? 20% l oss i n body wei ght f r om baseli ne O R Aggr essi ve i nt er vent i on i ndi cat ed [ e. g. , t ube f eedi ng or tot al par ent er al nut ri ti on (TPN)] I NF ECT IO N I nf ecti on (any ot her t han HI V inf ecti on) Locali zed, no syst em i c ant im icr o bial t r eatm ent i ndi cat ed AND Sym pt om s causing no or minim al i nt erf er ence wi t h usual soci al & funct ional acti vi ti es Syst em i c antim icr obi al t r eatm ent i ndi cat ed O R Sym pt om s causing gr eat er t han minim al i nt er f er ence wi t h usual soci al & funct ional acti vi ti es Sy st em i c antim icr obi al t r eatm ent i ndi cat ed AND Sym pt om s causing i nabi lit y t o per f orm usual soci al & functi onal acti vi ti es O R Oper at i ve i nt er venti on (ot her t han sim pl e i nci si on and dr ainage) i ndi cat ed Li f e - t hr eat eni ng consequences (e. g. , sept i c shock) I NJECT IO N SIT E REACT IO NS I nj ecti on si t e pai n (pain wi thout t ouchi ng) O r Tender n ess (pai n when ar ea i s touched) Pai n/ t ender ness causing no or minim al l im itati on of use of l im b Pai n/ t ender ness l im iti ng use of lim b O R Pai n/ t ender ness causing gr eat er t han minim al i nt er f er ence wi t h usual soci al & funct ional acti vi ti es Pai n/ t ender ness causing i nabil it y to per f orm usual soci al & funct ional acti vi ti es Pai n/ t ender ness causi ng i nabi lit y t o per f orm basic sel f - car e funct i on O R Hospit al i zati on (ot her t han em er gency room v i si t) i ndi cat ed f or managem ent of pai n/ t ender ness I nj ecti on si t e react ion (l ocal i zed) Adul t > 15 year s Eryt hem a O R Indur ati on of 5x5 cm ? 9x9 cm (or 25 cm 2 ? 81cm 2 ) Er yt hem a O R Indur ati on O R Edem a > 9 cm any di am et er (or > 81 cm 2 ) Ul cer ati on O R Second ar y i nf ect ion O R Phl ebi ti s O R St er il e abscess O R Dr ai nage Necr osi s (i nvol vi ng derm i s and deeper t issue) Pedi atr ic ? 15 year s Eryt hem a O R Indur ati on O R Edem a pr esent but ? 2. 5 cm di am et er Er yt hem a O R Indur ati on O R Edem a > 2.5 cm di am et er but < 50% surf ac e ar ea of the ext r em i t y segm ent (e. g., upper arm /thi gh) Er yt hem a O R Indur at ion O R Edem a i nvol vi ng ? 50% surf ace ar ea of the ext r em i t y segm ent (e. g., upper arm /thi gh) O R Ul cer at i on O R Secondar y i nf ect ion O R Phl ebi ti s O R St er il e abscess O R Dr ai nage Necr osi s (i nvol vi ng derm i s and deeper t issue) 133 AP PEND I X A DIV I SIO N OF AIDS T AB L E FOR GRAD ING T HE S EVERIT Y OF ADUL T AND PED I AT RIC ADV ER SE EVENT S VERS IO N 1 .0 , DECE MBER, 200 4 ; CL AR IF I CAT IO N AUGUST 200 9 Basi c S elf - car e Fun cti ons ? Adu lt : Ac t i viti es s uc h as b at hi ng , d r es s ing , t oi l et in g, tr ans f er / m o vem en t, c on ti n enc e, an d f eed in g. B asi c S elf - car e Fu nct ion s ? Y oun g Chi ldr en : Ac t i viti es th at ar e ag e and c u ltu r al l y ap pr opr i at e ( e.g ., f eedi ng s elf wi th c u ltu r all y ap pr opri at e eat in g i m pl em en t). U sua l Soc ia l & Funct ion al Ac tiv itie s ? Adu lt : Ad ap ti ve t as k s an d d es ir ab l e ac t i viti es , s uc h as g oin g t o wor k, s h op pi ng, c ook in g, us e of tr ans p or t at i on, pu rs ui ng a h obb y, etc . U sua l So cia l & Fun cti on al Activ it ie s ? Y oung C hil dr en : Ac ti vit i es th at ar e ag e and c u ltu r al l y ap pr opr i at e ( e.g. , s oc i al in t er ac ti ons , pl ay ac ti vi ti es , l ear ni ng t as ks , etc .). 28 D ec 0 4/C l ar if ic ati on Au g 09 Page 5 of 21 V ers i on 1. 0/ C l arif ic at i on 1 PAR AMET ER GRADE 1 MI L D GRADE 2 MO DERAT E GRADE 3 SEVERE GRADE 4 PO TENTI ALLY LI FE - THREATENI NG Pr uri ti s associ at ed wi t h i nj ecti on See al so Ski n: Pruri ti s (it chi ng - no ski n l esi ons) I t chi ng l ocali zed t o i nj ecti on sit e AND Rel i eved spont aneousl y or wi t h < 48 hour s t r eatm ent It chi ng beyond t he i nj ecti on sit e bu t not gener al i zed O R It chi ng l ocali zed t o i nj ecti on sit e requi ri ng ? 48 hour s tr eatm ent Gener al i zed it chi ng causing i nabil it y to per f orm usual soci al & funct ional acti vi ti es NA SKI N ? DERMAT O LO GI CAL Al opeci a Thi nni ng det ect abl e by st udy par ti ci pant (or by car egi ver f or young chil dr en and di sabl ed adult s) Thi nni ng or pat chy hair l oss det ect abl e by heal t h car e pr ovi der Com pl et e hair l oss NA Cut aneous reacti on ? rash Locali zed m acul ar rash Di ff use macul ar , macul opapular, or morbill if orm rash O R Tar get l es i ons Di ff use macul ar , macul opapular, or morbill if orm rash wit h vesi cl es or lim it ed num ber of bul lae O R Super f i ci al ulcer ati ons of mucous m em br ane l im it ed t o one sit e Ext ensi ve or gener ali zed bull ous l esi ons O R St evens - Johnson syndr om e O R Ul cer at i on of muc ous m em br ane i nvol vi ng t wo or mor e di st i nct mucosal si t es O R Toxi c epi derm al necr ol ysi s (TEN) Hyper pi gm ent ati on Sl i ght or l ocali zed Mar ked or gener al i zed NA NA Hypopi gm ent at ion Sl i ght or l ocali zed Mar ked or gener al i zed NA NA Pr uri ti s (it chi ng ? no ski n l esi ons) (See al so I nj ect i on Si t e Reacti ons: Pr uri ti s associ at ed wi t h i nj ecti on) I t chi ng causi ng no or minim al i nt er f er ence wi t h usual soci al & funct ional acti vi ti es I t chi ng causi ng gr eat er t han mi nim al i nt erf er ence wi t h usual soci al & functi onal acti vi t i es I t chi ng causi ng i nabili t y t o perf orm usual soci al & functi onal act ivit i es NA CARDI O VASCUL AR Car diac arr hyt hm i a (gener al ) (By ECG or physical exam ) Asym pt om at ic AND No i nt er venti on i ndi cat ed Asym pt om at ic AND Non - urgent m edi cal i nt er venti on indicat ed Sym pt om ati c, non - li f e - t hr eat eni ng AND Non - ur gent m edi cal i nt er venti on indicat ed Li f e - t hr eat eni ng ar r hyt hm ia O R Ur gent i nt er venti on indicat ed Car diac - i schem i a/ i nf ar ct i on NA NA Sym pt om ati c i schem i a (st abl e angi na) O R Test i ng consi st ent wit h i schem i a Unst abl e angi na O R Acut e myocar di al i nfar cti on 134 AP PEND I X A DIV I SIO N OF AIDS T AB L E FOR GRAD ING T HE S EVERIT Y OF ADUL T AND PED I AT RIC ADV ER SE EVENT S VERS IO N 1 .0 , DECE MBER, 200 4 ; CL AR IF I CAT IO N AUGUST 200 9 Basi c S elf - car e Fun cti ons ? Adu lt : Ac t i viti es s uc h as b at hi ng , d r es s ing , t oi l et in g, tr ans f er / m o vem en t, c on ti n enc e, an d f eed in g. B asi c S elf - car e Fu nct ion s ? Y oun g Chi ldr en : Ac t i viti es th at ar e ag e and c u ltu r al l y ap pr opr i at e ( e.g ., f eedi ng s elf wi th c u ltu r all y ap pr opri at e eat in g i m pl em en t). U sua l Soc ia l & Funct ion al Ac tiv itie s ? Adu lt : Ad ap ti ve t as k s an d d es ir ab l e ac t i viti es , s uc h as g oin g t o wor k, s h op pi ng, c ook in g, us e of tr ans p or t at i on, pu rs ui ng a h obb y, etc . U sua l So cia l & Fun cti on al Activ it ie s ? Y oung C hil dr en : Ac ti vit i es th at ar e ag e and c u ltu r al l y ap pr opr i at e ( e.g. , s oc i al in t er ac ti ons , pl ay ac ti vi ti es , l ear ni ng t as ks , etc .). 28 D ec 0 4/C l ar if ic ati on Au g 09 Page 6 of 21 V ers i on 1. 0/ C l arif ic at i on 1 PAR AMET ER GRADE 1 MI L D GRADE 2 MO DERAT E GRADE 3 SEVERE GRADE 4 PO TENTI ALLY LI FE - THREATENI NG Hem orr hage (signifi cant acut e bl ood l oss) NA Sym pt om ati c AND No tr ansf usi on i ndi cat ed Sym pt om ati c AND Tr ansf usi on of ? 2 uni ts packed RBCs (for chil dr en ? 10 cc/kg) i ndi cat ed Li f e - t hr eat eni ng hypot ension O R Tr an sf usi on of > 2 unit s packed RBCs (for chil dr en > 10 cc/ kg) i ndi cat ed Hyper t ensi on Adul t > 17 year s (wit h repeat t esti ng at sam e vi sit ) 140 ? 159 mm Hg syst oli c O R 90 ? 99 mm Hg di ast ol ic 160 ? 179 mm Hg syst oli c O R 100 ? 109 mm Hg di ast ol ic ? 180 mm Hg syst o li c O R ? 110 mm Hg di ast oli c Li f e - t hr eat eni ng consequences (e. g. , mal i gnant hyper t ensi on) O R Hospit ali zat i on i ndi cat ed (ot her t han em er gency room vi sit ) Cor r ect i on : i n Gr ade 2 to 160 - 179 fr om > 160 - 179 (syst oli c) and to ? 100 - 109 fr om > 100 - 109 ( di ast oli c) and in Gr ade 3 to ? 180 fr om > 180 (syst oli c) and to ? 110 f r om > 110 (di ast oli c) . Pedi atr ic ? 17 year s (wit h repeat t est i ng at sam e vi si t) NA 91 s t ? 94 th per centil e adj ust ed for age, hei ght , and gender (syst ol ic and/ or di ast ol ic) ? 95t h per c enti l e adj ust ed for age, hei ght, and gender (syst ol i c and/ or di ast oli c) Li f e - t hr eat eni ng consequences (e. g. , mal i gnant hyper t ensi on) O R Hospit ali zat i on i ndi cat ed (ot her t han em er gency room vi sit ) Hypot ensi on NA Sym pt om ati c, cor r ect ed wi th or al f l ui d repl a cem ent Sym pt om ati c, I V fl ui ds i ndi cat ed Shock requir i ng use of vasopr essor s or m echanical assist ance t o mai nt ain bl ood pr essur e Per i car di al eff usi on Asym pt om at ic, sm al l ef f usion requi ri ng no i nt er venti on Asym pt om at ic, moder at e or l ar ger ef f usion requi ri ng no i nt er venti on Ef f usi on wi t h non - l if e t hr eat eni ng physiol ogi c consequences O R Ef f usi on wi t h non - ur gent i nt er venti on indicat ed Li f e - t hr eat eni ng consequences (e. g. , t am ponade) O R Ur gent i nt er venti on indicat ed Pr ol onged PR i nt er val Adul t > 16 year s PR i nt er val 0. 21 ? 0. 25 sec PR i nt er val > 0.25 sec Type I I 2 nd degr ee AV bl ock O R Ventr icul ar pause > 3. 0 sec Com pl et e AV block Pediatric ? 16 year s 1 s t degr ee AV bl ock (PR > norm al f or age and rat e) Type I 2 nd degr ee AV bl ock Type I I 2 nd degr ee AV bl ock Com pl et e AV block 135 AP PEND I X A DIV I SIO N OF AIDS T AB L E FOR GRAD ING T HE S EVERIT Y OF ADUL T AND PED I AT RIC ADV ER SE EVENT S VERS IO N 1 .0 , DECE MBER, 200 4 ; CL AR IF I CAT IO N AUGUST 200 9 Basi c S elf - car e Fun cti ons ? Adu lt : Ac t i viti es s uc h as b at hi ng , d r es s ing , t oi l et in g, tr ans f er / m o vem en t, c on ti n enc e, an d f eed in g. B asi c S elf - car e Fu nct ion s ? Y oun g Chi ldr en : Ac t i viti es th at ar e ag e and c u ltu r al l y ap pr opr i at e ( e.g ., f eedi ng s elf wi th c u ltu r all y ap pr opri at e eat in g i m pl em en t). U sua l Soc ia l & Funct ion al Ac tiv itie s ? Adu lt : Ad ap ti ve t as k s an d d es ir ab l e ac t i viti es , s uc h as g oin g t o wor k, s h op pi ng, c ook in g, us e of tr ans p or t at i on, pu rs ui ng a h obb y, etc . U sua l So cia l & Fun cti on al Activ it ie s ? Y oung C hil dr en : Ac ti vit i es th at ar e ag e and c u ltu r al l y ap pr opr i at e ( e.g. , s oc i al in t er ac ti ons , pl ay ac ti vi ti es , l ear ni ng t as ks , etc .). 28 D ec 0 4/C l ar if ic ati on Au g 09 Page 7 of 21 V ers i on 1. 0/ C l arif ic at i on 1 PAR AMET ER GRADE 1 MI L D GRADE 2 MO DERAT E GRADE 3 SEVERE GRADE 4 PO TENTI ALLY LI FE - THREATENI NG Pr ol onged QTc Adul t > 16 year s Asym pt om at ic, Q Tc i nt er val 0.45 ? 0. 47 sec OR Incr ease i nt er val < 0. 03 sec above basel ine Asym pt om at ic, Q Tc i nt er val 0.48 ? 0. 49 sec OR Incr ease i n i nt er val 0.03 ? 0. 05 sec above baseli ne Asym pt om at ic, Q Tc i nt er val ? 0.50 sec OR Incr ease in i nt er val ? 0. 06 sec above basel i ne Li f e - t hr eat eni ng consequences, e. g. Tor sade de poi nt e s or ot her associ at ed ser i ous vent r icular dysr hyt hm ia Pediatric ? 16 year s Asym pt om at ic, Q Tc i nt er val 0.450 ? 0. 464 sec Asym pt om at ic, Q Tc i nt er val 0.465 ? 0. 479 sec Asym pt om at ic, Q Tc i nt er val ? 0.480 sec Li f e - t hr eat eni ng consequences, e. g. Tor sade de poi nt es or ot her associ at ed ser i ous vent r icular dysr hyt hm ia Thr om bosi s/ em bol ism NA Deep vei n t hr om bosi s AND No i nt er venti on i ndi cat ed (e. g., anti coagul at ion, l ysi s f ilt er , i nvasive pr ocedur e) Deep vei n t hr om bosi s AND Int er vent i on i ndi cat ed (e. g., anti coagul at ion, l ysi s f ilt er , i nvasive pr ocedur e) Em bol ic event (e. g., pulm onar y em boli sm , l if e - t hr eat eni ng t hr om bus) Vasovagal episode (associ at ed wit h a pr ocedur e of any ki nd) Pr esent wit hout l oss of consci ousness Pr esent wit h t ransi ent l oss of consci ousness NA NA Vent r i cul ar dysf uncti on (congesti ve hear t f ail ur e) NA Asym pt om at ic di agnosti c fi ndi ng AND i nt er venti on indicat ed New onset wit h sym pt om s O R W orseni ng sym ptom ati c congest ive hear t f ail ur e Li f e - t hr eat eni ng congest ive hear t f ail ur e G AST RO I NT EST I NAL Anor exi a Loss of appeti t e wi t hout decr eased or al i ntake Loss of appeti t e associ at ed wit h decr eased or al i nt ake wi t hout si gni fi cant wei ght l oss Loss of appeti t e associ at ed wit h si gni fi cant wei ght l oss Li f e - t hr eat eni ng consequences O R Aggr essi ve i nt er vent i on i ndi cat ed [ e. g. , t ube f eedi ng or tot al par ent er a l nut ri ti on (TPN)] Com m ent: Pl ease not e t hat, whil e t he gr adi ng scal e pr ovi ded f or Uni nt ent ional W ei ght Loss may be used as a gui deli ne when gr adi ng anor exi a, thi s i s not a requir em ent and shoul d not be used as a substit ut e f or cli nical j udgm ent . Ascit e s Asym pt om at ic Sym pt om ati c AND Int er venti on i ndicat ed (e. g., di ur et i cs or ther apeut i c par acent esi s) Sym pt om ati c despit e i nt er venti on Li f e - t hr eat eni ng consequences 136 AP PEND I X A DIV I SIO N OF AIDS T AB L E FOR GRAD ING T HE S EVERIT Y OF ADUL T AND PED I AT RIC ADV ER SE EVENT S VERS IO N 1 .0 , DECE MBER, 200 4 ; CL AR IF I CAT IO N AUGUST 200 9 Basi c S elf - car e Fun cti ons ? Adu lt : Ac t i viti es s uc h as b at hi ng , d r es s ing , t oi l et in g, tr ans f er / m o vem en t, c on ti n enc e, an d f eed in g. B asi c S elf - car e Fu nct ion s ? Y oun g Chi ldr en : Ac t i viti es th at ar e ag e and c u ltu r al l y ap pr opr i at e ( e.g ., f eedi ng s elf wi th c u ltu r all y ap pr opri at e eat in g i m pl em en t). U sua l Soc ia l & Funct ion al Ac tiv itie s ? Adu lt : Ad ap ti ve t as k s an d d es ir ab l e ac t i viti es , s uc h as g oin g t o wor k, s h op pi ng, c ook in g, us e of tr ans p or t at i on, pu rs ui ng a h obb y, etc . U sua l So cia l & Fun cti on al Activ it ie s ? Y oung C hil dr en : Ac ti vit i es th at ar e ag e and c u ltu r al l y ap pr opr i at e ( e.g. , s oc i al in t er ac ti ons , pl ay ac ti vi ti es , l ear ni ng t as ks , etc .). 28 D ec 0 4/C l ar if ic ati on Au g 09 Page 8 of 21 V ers i on 1. 0/ C l arif ic at i on 1 PAR AMET ER GRADE 1 MI L D GRADE 2 MO DERAT E GRADE 3 SEVERE GRADE 4 PO TENTI ALLY LI FE - THREATENI NG Chol ecystit is NA Sym pt om ati c AND Medi cal i nt er vent i on i ndi cat ed Radi ol ogi c, endoscopi c, or oper ati ve i nt er vent ion i ndi cat ed Li f e - t hr eat eni ng consequences (e. g. , sepsi s or per f or ati on) Consti pat i on NA Per si st ent consti pat ion requi ri ng regul ar use of di et ar y modi fi cati ons, l axat ives, or enem as O bst ipati on wi t h manual evacuat i on i ndi cat ed Li f e - t hr eat eni ng consequences (e. g. , obstr uct i on) Di arr hea Adul t and Pedi atr ic ? 1 year Transi ent or i nt erm itt ent epi sodes of unf orm ed st ools OR Increase of ? 3 st ool s over basel i ne per 24 - hour per i od Per si st ent epi sodes of unf orm ed t o wat er y st ool s O R Incr ease of 4 ? 6 st ool s over basel i ne per 24 - hour per i od Bl oody di arr hea O R Increase of ? 7 stools per 24 - hour per i o d O R IV flui d replacem ent i ndi cat ed Li f e - t hr eat eni ng consequences (e. g. , hypot ensive shock) Pedi atr ic < 1 year Li qui d st ools (m or e unf orm ed t han usual) but usual num ber of st ool s Li qui d st ools wi t h i ncr eased num ber of st ool s O R Mil d dehydr ati on Li qui d st ools wi t h moder at e dehydr ati on Li qui d st ools resul ti ng i n sever e dehydr ati on wit h aggr essive rehydr at ion i ndi cat ed O R Hypot ensive shock Dysphagi a - O dynophagi a Sym pt om ati c but abl e t o eat usual di et Sym pt om s causi ng al t er ed di et ar y i ntake wi t hout m edi cal i nt er venti on indicat ed Sym pt om s causi ng sever el y al t er ed di et ar y i ntake wit h m edi cal i nt er venti on indicat ed Li f e - t hr eat eni ng reduct ion i n oral int ake Mucosit is/st om at iti s ( cli ni cal exam ) I ndi cat e sit e (e. g., l arynx, or al ) See Geni t ouri nar y f or Vul vovagini t is See al so Dysphagia - O dynophagi a and Pr octit is Er yt hem a of the mucosa Pat chy pseudom em br anes or ul cer ati ons Conf luent pseudom em br anes or ul cer ati ons O R Mucosal bl eedi ng wit h mi nor t r aum a Ti ssue necr osis O R Di ff use spont aneous mucosal bl eedi ng O R Li f e - t hr eat eni ng consequences (e. g. , aspir ati on, choki ng) Nausea Tr ansi ent (< 24 hours) or i nt erm i tt ent nausea wi t h no or minim al i nt erf er ence wi t h or al i ntake Per si st ent nausea resul ti ng i n decr eased or al i ntake f or 24 ? 48 hour s Per si st ent nausea resul ti ng i n minim al or al i ntake f or > 48 hour s O R Aggr essive rehydr ati on i ndi cat ed (e. g., I V fl uids) Li f e - t hr eat eni ng consequences (e. g. , hypot ensive shock) 137 AP PEND I X A DIV I SIO N OF AIDS T AB L E FOR GRAD ING T HE S EVERIT Y OF ADUL T AND PED I AT RIC ADV ER SE EVENT S VERS IO N 1 .0 , DECE MBER, 200 4 ; CL AR IF I CAT IO N AUGUST 200 9 Basi c S elf - car e Fun cti ons ? Adu lt : Ac t i viti es s uc h as b at hi ng , d r es s ing , t oi l et in g, tr ans f er / m o vem en t, c on ti n enc e, an d f eed in g. B asi c S elf - car e Fu nct ion s ? Y oun g Chi ldr en : Ac t i viti es th at ar e ag e and c u ltu r al l y ap pr opr i at e ( e.g ., f eedi ng s elf wi th c u ltu r all y ap pr opri at e eat in g i m pl em en t). U sua l Soc ia l & Funct ion al Ac tiv itie s ? Adu lt : Ad ap ti ve t as k s an d d es ir ab l e ac t i viti es , s uc h as g oin g t o wor k, s h op pi ng, c ook in g, us e of tr ans p or t at i on, pu rs ui ng a h obb y, etc . U sua l So cia l & Fun cti on al Activ it ie s ? Y oung C hil dr en : Ac ti vit i es th at ar e ag e and c u ltu r al l y ap pr opr i at e ( e.g. , s oc i al in t er ac ti ons , pl ay ac ti vi ti es , l ear ni ng t as ks , etc .). 28 D ec 0 4/C l ar if ic ati on Au g 09 Page 9 of 21 V ers i on 1. 0/ C l arif ic at i on 1 PAR AMET ER GRADE 1 MI L D GRADE 2 MO DERAT E GRADE 3 SEVERE GRADE 4 PO TENTI ALLY LI FE - THREATENI NG Pancr eati ti s NA Sym pt om ati c AND Hospit al i zati on not i ndi cat ed (ot her t han em er gency room vi sit ) Sym pt om ati c AND Hospit al i zati on indicat ed (ot her t han em er gency room vi sit ) Li f e - t hr eat eni ng consequences (e. g. , ci rcul at or y f ail ur e, hem or r hage, sepsis) Pr octit is ( f uncti onal - sym pt om at ic ) Al so see Mucosit is/st om at iti s for cl ini cal exam Rect al di scom f or t AND No i nt er venti on i ndi cat ed Sym pt om s causi ng gr eat er than minim al i nt erf er ence wi t h usual soci al & functi onal acti vi ti es O R Medi cal i nt er venti on indicat ed Sym pt om s causi ng i nabi lit y t o per f orm usual soci al & functi onal acti vi ti es O R Oper at i ve i nt er venti on indi cat ed Li f e - t hr eat eni ng consequences (e. g. , per f or at ion) Vom i ti ng Tr ansi ent or i nt erm itt ent vom it i ng wi t h no or minim al i nt erf er ence wi t h or al i ntake Fr equent epi sodes of vom i ti ng wi t h no or mil d dehydr ati on Per si st ent vom iti ng resul ti ng i n ort host ati c h ypot ension O R Aggr essi ve rehydr at i on i ndi cat ed (e. g., I V fl ui ds) Li f e - t hr eat eni ng consequences (e. g. , hypot ensive shock) NEURO LO GI C Al t er at i on i n per sonali ty - behavi or or i n mood (e. g., agit ati on, anxi et y, depr essi on, mania, psychosi s) Al t er at i on causi ng no or minim al i nt erf er ence wi t h usual soci al & funct ional acti vi ti es Al t er at i on causi ng gr eat er than minim al i nt erf er ence wi t h usual soci al & functi onal acti vi ti es Al t er at i on causi ng i nabi lit y t o per f orm usual soci al & functi onal acti vi ti es Behavi or pot enti all y harm f ul t o self or ot her s (e. g., sui ci dal and hom i ci dal i deati on or at t em pt, acut e psychosi s) O R Causi ng i nabi lit y t o per f orm basic sel f - car e funct i ons Al t er ed Ment al Stat us For Dem enti a, see Cognit ive and behavi or al/ att ent ional di st ur bance (i n cl udi ng dem enti a and at t enti on def icit di sor der ) Changes causi ng no or minim al i nt erf er ence wi t h usual soci al & funct ional acti vi ti es Mi l d l et har gy or som nol ence causi ng gr eat er than minim al i nt erf er ence wi t h usual soci al & functi onal acti vi ti es Conf usi on, m em or y im pairm ent , l et har gy, or som nol ence causi ng i nabi lit y t o per f orm usual soci al & functi onal acti vi ti es Del i ri um O R obt undati on, O R com a At axi a Asym pt om at ic at axi a det ect abl e on exam O R Mi nim al ataxi a causing no or minim al i nt erf er ence wi t h usual s oci al & funct ional acti vi ti es Sym pt om ati c at axi a causing gr eat er t han minim al i nt er f er ence wi t h usual soci al & funct ional acti vi ti es Sym pt om ati c at axi a causing i nabil it y to per f orm usual soci al & funct ional acti vi ti es Di sabl ing at axi a causing i nabi lit y t o per f orm basic sel f - car e funct i ons 138 AP PEND I X A DIV I SIO N OF AIDS T AB L E FOR GRAD ING T HE S EVERIT Y OF ADUL T AND PED I AT RIC ADV ER SE EVENT S VERS IO N 1 .0 , DECE MBER, 200 4 ; CL AR IF I CAT IO N AUGUST 200 9 Basi c S elf - car e Fun cti ons ? Adu lt : Ac t i viti es s uc h as b at hi ng , d r es s ing , t oi l et in g, tr ans f er / m o vem en t, c on ti n enc e, an d f eed in g. B asi c S elf - car e Fu nct ion s ? Y oun g Chi ldr en : Ac t i viti es th at ar e ag e and c u ltu r al l y ap pr opr i at e ( e.g ., f eedi ng s elf wi th c u ltu r all y ap pr opri at e eat in g i m pl em en t). U sua l Soc ia l & Funct ion al Ac tiv itie s ? Adu lt : Ad ap ti ve t as k s an d d es ir ab l e ac t i viti es , s uc h as g oin g t o wor k, s h op pi ng, c ook in g, us e of tr ans p or t at i on, pu rs ui ng a h obb y, etc . U sua l So cia l & Fun cti on al Activ it ie s ? Y oung C hil dr en : Ac ti vit i es th at ar e ag e and c u ltu r al l y ap pr opr i at e ( e.g. , s oc i al in t er ac ti ons , pl ay ac ti vi ti es , l ear ni ng t as ks , etc .). 28 D ec 0 4/C l ar if ic ati on Au g 09 Page 10 of 21 V ers i on 1. 0/ C l arif ic at i on 1 PAR AMET ER GRADE 1 MI L D GRADE 2 MO DERAT E GRADE 3 SEVERE GRADE 4 PO TENTI ALLY LI FE - THREATENI NG Cognit ive and behavi or al/ att ent ional di st ur bance (i ncl udi ng dem enti a and at t enti on def icit di sor der ) Di sabi lit y causi ng no or minim al i nt erf er ence wi t h usual soci al & funct ional acti vi ti es O R Speci ali zed resour ces not i ndi cat ed Di sabi lit y causi ng gr eat er than minim al i nt erf er ence wi t h usual soci al & functi onal acti vi ti es O R Speci ali zed resour ces on par t - tim e basi s i ndi cat ed Di sabi lit y causi ng i nabi lit y t o per f orm usual soci al & functi onal acti vi ti es O R Speci ali zed resour ces on a full - t im e basi s i ndi cat ed Di sabi lit y causi ng i nabi lit y t o per f orm basic sel f - car e funct i ons O R Inst it ut i onali zati on i ndi cat ed CNS i schem i a (acut e) NA NA Tr ansi ent i schem i c at t ack Cer ebr al vascul ar acci dent (CVA, str oke) wi t h neur ol ogi cal defi ci t Dev el opm ent al del ay ? Pedi atr i c ? 16 year s Mi l d devel opm ent al del ay, ei t her mot or or cogniti ve, as det er m i ned by com pari son wit h a devel opm ent al scr eeni ng t ool appr opr iat e for the set t i ng Moder at e devel opm ent al del ay, ei t her mot or or cogniti ve, as det e r m i ned by com pari son wit h a devel opm ent al scr eeni ng t ool appr opr iat e for the set t i ng Sever e dev el opm ent al del ay, ei t her mot or or cogniti ve, as det erm i ned by com pari son wit h a devel opm ent al scr eeni ng t ool appr opr iat e for the set t i ng Dev el opm ent al regr essi on, eit her motor or cogni ti ve, as det er m i ned by com pari son wit h a devel opm ent al scr eeni ng t ool appr opr iat e for the set t i ng Headache Sym pt om s causi ng no or minim al i nt erf er ence wi t h usual soci al & funct ional acti vi ti es Sym pt om s causi ng gr eat er than minim a l i nt erf er ence wi t h usual soci al & functi onal acti vi ti es Sym pt om s causi ng i nabi lit y t o per f orm usual soci al & functi onal acti vi ti es Sym pt om s causi ng i nabi lit y t o per f orm basic sel f - car e funct i ons O R Hospit al i zati on indicat ed (ot her t han em er gency room vi si t ) O R Headache wi t h si gni fi cant im pairm ent of al er t ness or other neur ol ogi c f uncti on I nsom ni a NA Di ff icult y sl eepi ng causing gr eat er t han minim al i nt er f er ence wi t h usual soci al & funct ional acti vi ti es Di ff icult y sl eepi ng causing i nabil it y to per f orm usua l soci al & funct ional acti vi ti es Di sabl ing i nsom ni a causing i nabil it y to per f orm basi c sel f - car e f unct ions Neur om uscul ar weakness (i ncl udi ng myopat hy & neur opat hy) Asym pt om at ic wi t h decr eased st r engt h on exam O R Mi nim al muscl e weakness causing no or min im al i nt erf er ence wi t h usual soci al & funct ional acti vi ti es Muscl e weakness causing gr eat er t han minim al i nt er f er ence wi t h usual soci al & funct ional acti vi ti es Muscl e weakness causing i nabil it y to per f orm usual soci al & funct ional acti vi ti es Di sabl ing mus cl e weakness causi ng i nabi lit y t o per f orm basic sel f - car e funct i ons O R Respi r ator y muscl e weakness im pair ing vent i lati on 139 AP PEND I X A DIV I SIO N OF AIDS T AB L E FOR GRAD ING T HE S EVERIT Y OF ADUL T AND PED I AT RIC ADV ER SE EVENT S VERS IO N 1 .0 , DECE MBER, 200 4 ; CL AR IF I CAT IO N AUGUST 200 9 Basi c S elf - car e Fun cti ons ? Adu lt : Ac t i viti es s uc h as b at hi ng , d r es s ing , t oi l et in g, tr ans f er / m o vem en t, c on ti n enc e, an d f eed in g. B asi c S elf - car e Fu nct ion s ? Y oun g Chi ldr en : Ac t i viti es th at ar e ag e and c u ltu r al l y ap pr opr i at e ( e.g ., f eedi ng s elf wi th c u ltu r all y ap pr opri at e eat in g i m pl em en t). U sua l Soc ia l & Funct ion al Ac tiv itie s ? Adu lt : Ad ap ti ve t as k s an d d es ir ab l e ac t i viti es , s uc h as g oin g t o wor k, s h op pi ng, c ook in g, us e of tr ans p or t at i on, pu rs ui ng a h obb y, etc . U sua l So cia l & Fun cti on al Activ it ie s ? Y oung C hil dr en : Ac ti vit i es th at ar e ag e and c u ltu r al l y ap pr opr i at e ( e.g. , s oc i al in t er ac ti ons , pl ay ac ti vi ti es , l ear ni ng t as ks , etc .). 28 D ec 0 4/C l ar if ic ati on Au g 09 Page 11 of 21 V ers i on 1. 0/ C l arif ic at i on 1 PAR AMET ER GRADE 1 MI L D GRADE 2 MO DERAT E GRADE 3 SEVERE GRADE 4 PO TENTI ALLY LI FE - THREATENI NG Neur osensor y al t er at ion (i ncl udi ng par est hesi a and pai nf ul neur opat hy) Asym pt om at ic wi t h sensor y alt er ati on on exam or minim al par est h esi a causi ng no or minim al i nt erf er ence wi t h usual soci al & funct ional acti vi ti es Sensor y al t er at ion or par est hesi a causi ng gr eat er than minim al i nt erf er ence wi t h usual soci al & functi onal acti vi ti es Sensor y al t er at ion or par est hesi a causi ng i nabi lit y t o per f orm usual soci al & functi onal acti vi ti es Di sabl ing sensor y al t er at ion or par esthesi a causing i nabil it y to per f orm basi c sel f - car e f unct ions Sei zur e: ( new onset ) ? Adult ? 18 years See al so Sei zur e: (known pr e - exi sti ng sei zur e di sorder ) NA 1 sei zur e 2 ? 4 sei zur es Sei zur es of any ki nd whi ch ar e pr ol onged, repet i t ive (e. g., stat us epi l ept i cus), or di ff icult t o contr ol (e. g., ref r act ory epil epsy) Sei zur e: ( known pr e - exi sti ng sei zur e di sor der ) ? Adult ? 18 years For wor seni ng of exi sti ng epil epsy t he gr ades shoul d be based on an i ncr ease f r om pr evi ous l evel of contr ol t o any of these l evel s. NA Incr eased f r equency of pr e - exi st i ng sei zur es (non - r epet i ti ve) wit hout change i n sei zur e char act er O R Infr equent br eak - t hr ough sei zur es whil e on st abl e m edi cati on i n a pr evi ousl y contr oll ed sei zur e di sor der Change i n sei zur e char act er f rom baseli ne ei t her in dur at ion or quali ty (e. g., sever i t y or focal it y) Sei zur es of any k i nd whi ch ar e pr ol onged, repet i t ive (e. g., stat us epi l ept i cus), or di ff icult t o contr ol (e. g., ref r act ory epil epsy) Sei zur e ? Pediatric < 18 year s Sei zur e, gener al i zed onset wit h or wi t hout secondar y gener al i zat i on, lasti ng < 5 minut es wit h < 24 hour s po st i ct al st at e Sei zur e, gener al i zed onset wit h or wi t hout secondar y gener al i zat i on, lasti ng 5 ? 20 minut es wit h < 24 hour s post i ct al st at e Sei zur e, gener al i zed onset wit h or wi t hout secondar y gener al i zat i on, lasti ng > 20 mi nut es Sei zur e, gener al i zed on set wit h or wi t hout secondar y gener al i zat i on, requiri ng i ntubati on and sedati on Syncope (not associ at ed wit h a pr ocedur e) NA Pr esent NA NA Ver t i go Ver t i go causi ng no or minim al i nt er f er ence wi t h usual soci al & funct ional acti vi ti es Ver t i go causi ng gr eat e r than minim al i nt erf er ence wi t h usual soci al & functi onal acti vi ti es Ver t i go causi ng i nabil it y t o perf orm usual soci al & functi onal act ivit i es Di sabl ing ver ti go causing i nabil it y to per f orm basi c sel f - car e f unct ions 140 AP PEND I X A DIV I SIO N OF AIDS T AB L E FOR GRAD ING T HE S EVERIT Y OF ADUL T AND PED I AT RIC ADV ER SE EVENT S VERS IO N 1 .0 , DECE MBER, 200 4 ; CL AR IF I CAT IO N AUGUST 200 9 Basi c S elf - car e Fun cti ons ? Adu lt : Ac t i viti es s uc h as b at hi ng , d r es s ing , t oi l et in g, tr ans f er / m o vem en t, c on ti n enc e, an d f eed in g. B asi c S elf - car e Fu nct ion s ? Y oun g Chi ldr en : Ac t i viti es th at ar e ag e and c u ltu r al l y ap pr opr i at e ( e.g ., f eedi ng s elf wi th c u ltu r all y ap pr opri at e eat in g i m pl em en t). U sua l Soc ia l & Funct ion al Ac tiv itie s ? Adu lt : Ad ap ti ve t as k s an d d es ir ab l e ac t i viti es , s uc h as g oin g t o wor k, s h op pi ng, c ook in g, us e of tr ans p or t at i on, pu rs ui ng a h obb y, etc . U sua l So cia l & Fun cti on al Activ it ie s ? Y oung C hil dr en : Ac ti vit i es th at ar e ag e and c u ltu r al l y ap pr opr i at e ( e.g. , s oc i al in t er ac ti ons , pl ay ac ti vi ti es , l ear ni ng t as ks , etc .). 28 D ec 0 4/C l ar if ic ati on Au g 09 Page 12 of 21 V ers i on 1. 0/ C l arif ic at i on 1 PAR AMET ER GRADE 1 MI L D GRADE 2 MO DERAT E GRADE 3 SEVERE GRADE 4 PO TENTI ALLY LI FE - THREATENI NG RESPI RAT O RY Br onchospasm (acut e) FEV 1 or peak fl ow reduced t o 70 ? 80% FEV1 or peak fl ow 50 ? 69% FEV1 or peak fl ow 25 ? 49% Cyanosi s O R FEV1 or peak fl ow < 25% OR Int ubati on Dyspnea or respi r at ory di st r ess Adult ? 14 years Dyspnea on exer t i on wi t h no or minim al i nt erf er ence wi t h usual soci al & funct ional acti vi ti es Dyspnea on exer t i on causing gr eat er t han minim al i nt er f er ence wi t h usual soci al & funct ional acti vi ti es Dyspnea at rest causing i nabi lit y t o pe r f orm usual soci al & functi onal acti vi ti es Respi r ator y fail ur e wit h vent i lat or y support i ndi cat ed Pedi atr ic < 14 year s W heezi ng O R minim al i ncr ease i n respi r at or y rat e f or age Nasal fl ar i ng O R Int er cost al ret racti ons O R Pul se oxim et r y 90 ? 95% Dyspnea a t rest causing i nabi lit y t o per f orm usual soci al & functi onal acti vi ti es O R Pul se oxim et r y < 90% Respi r ator y fail ur e wit h vent i lat or y support i ndi cat ed MUSCUL OSKELET AL Ar t hr al gia See al so Art hrit is Joi nt pai n causi ng no or minim al i nt erf er ence wi t h usual soci al & funct ional acti vi ti es Joi nt pai n causi ng gr eat er than minim al i nt erf er ence wi t h usual soci al & functi onal acti vi ti es Joi nt pai n causi ng i nabi lit y t o per f orm usual soci al & functi onal acti vi ti es Di sabl ing j oi nt pai n causing i nabil it y to per f orm ba si c sel f - car e f unct ions Ar t hr iti s See al so Art hral gi a St if fness or j oi nt swel l i ng causi ng no or minim al i nt er f er ence wi t h usual soci al & funct ional acti vi ti es St if fness or j oi nt swel l i ng causi ng gr eat er than minim al i nt erf er ence wi t h usual soci al & functi onal acti vi ti es St if fness or j oi nt swel l i ng causi ng i nabi lit y t o per f orm usual soci al & functi onal acti vi ti es Di sabl ing j oi nt sti ff ness or swelli ng causi ng i nabi lit y t o per f orm basic sel f - car e funct i ons Bone Mi ner al Loss Adult ? 21 years BMD t - scor e - 2. 5 t o - 1. 0 BMD t - scor e < - 2. 5 Pat hol ogi cal f ractur e (i ncl udi ng l oss of ver t ebr al hei ght ) Pat hol ogi c fr act ur e causing li f e - t hr eat eni ng consequences Pedi atr ic < 21 year s BMD z - scor e - 2. 5 t o - 1. 0 BMD z - scor e < - 2. 5 Pat hol ogi cal f ractur e (i ncl udi ng l oss of ver t ebr al hei ght ) Pat hol ogi c fr act ur e causing li f e - t hr eat eni ng consequences Myal gi a ( non - i nj ecti on sit e ) Muscl e pai n causi ng no or minim al i nt erf er ence wi t h usual soci al & funct ional acti vi ti es Muscl e pai n causi ng gr eat er than minim al i nt erf er ence wi t h usual soci al & functi onal acti vi ti es Muscl e pai n causi ng i nabi lit y t o per f orm usual soci al & functi onal acti vi ti es Di sabl ing muscl e pai n causing i nabil it y to per f orm basi c sel f - car e f unct ions 141 AP PEND I X A DIV I SIO N OF AIDS T AB L E FOR GRAD ING T HE S EVERIT Y OF ADUL T AND PED I AT RIC ADV ER SE EVENT S VERS IO N 1 .0 , DECE MBER, 200 4 ; CL AR IF I CAT IO N AUGUST 200 9 Basi c S elf - car e Fun cti ons ? Adu lt : Ac t i viti es s uc h as b at hi ng , d r es s ing , t oi l et in g, tr ans f er / m o vem en t, c on ti n enc e, an d f eed in g. B asi c S elf - car e Fu nct ion s ? Y oun g Chi ldr en : Ac t i viti es th at ar e ag e and c u ltu r al l y ap pr opr i at e ( e.g ., f eedi ng s elf wi th c u ltu r all y ap pr opri at e eat in g i m pl em en t). U sua l Soc ia l & Funct ion al Ac tiv itie s ? Adu lt : Ad ap ti ve t as k s an d d es ir ab l e ac t i viti es , s uc h as g oin g t o wor k, s h op pi ng, c ook in g, us e of tr ans p or t at i on, pu rs ui ng a h obb y, etc . U sua l So cia l & Fun cti on al Activ it ie s ? Y oung C hil dr en : Ac ti vit i es th at ar e ag e and c u ltu r al l y ap pr opr i at e ( e.g. , s oc i al in t er ac ti ons , pl ay ac ti vi ti es , l ear ni ng t as ks , etc .). 28 D ec 0 4/C l ar if ic ati on Au g 09 Page 13 of 21 V ers i on 1. 0/ C l arif ic at i on 1 PAR AMET ER GRADE 1 MI L D GRADE 2 MO DERAT E GRADE 3 SEVERE GRADE 4 PO TENTI ALLY LI FE - THREATENI NG O st eonecr osi s NA Asym pt om at ic wi t h radiogr aphic f indings AND No oper at ive i nt er venti on indicat ed Sym pt om ati c bone pai n wi t h radiogr aphic f i ndi ngs O R Oper ati ve i nt er venti on indicat ed Di sabl ing bone pain wi th radiogr aphic f indings causing i nabil it y to per f orm basi c sel f - car e f unct ions G ENIT O URI NARY Cer vi citi s ( sym p t om s ) (For use i n st udi es eval uati ng t opi cal st udy agent s) For ot her cer vicit is see Inf ecti on: I nf ect ion (any other t han HI V i nf ecti on) Sym pt om s causi ng no or minim al i nt erf er ence wi t h usual soci al & funct ional acti vi ti es Sym pt om s causi ng gr eat er than minim al i nt erf er ence wi t h usual soci al & functi onal acti vi ti es Sym pt om s causi ng i nabi lit y t o per f orm usual soci al & functi onal acti vi ti es Sym pt om s causi ng i nabi lit y t o per f orm basic sel f - car e funct i ons Cer vi citi s ( cli ni cal exam ) (For use i n st udi es e val uati ng t opi cal st udy agent s) For ot her cer vicit is see Inf ecti on: I nf ect ion (any other t han HI V i nf ecti on) Mi nim al cer vical abnorm al iti es on exam i nati on (er yt hem a, mucopur ul ent di schar ge, or fri abi li ty) O R Epit hel ial di sr upti on < 25% of tot al surf ace Moder at e cer vi cal abnorm al iti es on exam i nati on (er yt hem a, mucopur ul ent di schar ge, or fri abi li ty) O R Epit hel ial di sr upti on of 25 ? 49% tot al sur f ace Sever e cer vi cal abnorm al iti es on exam i nati on (er ythem a, mucopur ul ent di schar ge, or fri abi li ty) O R Epit hel ia l di srupti on 50 ? 75% total sur face Epi thel i al di sr upti on > 75% tot al sur face I nt er - m enstr ual bl eedi ng (I MB) Spot ti ng obser ved by par ti ci pant O R Mi nim al bl ood obser ved duri ng cli nical or colposcopi c exam i nati on I nt er - m enstr ual bl eedi ng not gr eat er i n du r at i on or am ount t han usual m enstr ual cycl e Int er - m enstr ual bl eedi ng gr eat er in dur at ion or am ount t han usual m enst rual cycl e Hem orr hage wi th l if e - t hr eat eni ng hypot ension O R Oper at ive i nt er venti on indicat ed Ur i nar y tr act obstr uct i on (e. g., st one) NA Si gns or sym pt om s of ur i nar y t r act obstr uct i on wi t hout hydr onephr osis or renal dysfunct i on Si gns or sym pt om s of ur i nar y t r act obst r ucti on wi t h hydr onephr osis or renal dysfunct i on O bst r ucti on causi ng li f e - t hr eat eni ng consequences 142 AP PEND I X A DIV I SIO N OF AIDS T AB L E FOR GRAD ING T HE S EVERIT Y OF ADUL T AND PED I AT RIC ADV ER SE EVENT S VERS IO N 1 .0 , DECE MBER, 200 4 ; CL AR IF I CAT IO N AUGUST 200 9 Basi c S elf - car e Fun cti ons ? Adu lt : Ac t i viti es s uc h as b at hi ng , d r es s ing , t oi l et in g, tr ans f er / m o vem en t, c on ti n enc e, an d f eed in g. B asi c S elf - car e Fu nct ion s ? Y oun g Chi ldr en : Ac t i viti es th at ar e ag e and c u ltu r al l y ap pr opr i at e ( e.g ., f eedi ng s elf wi th c u ltu r all y ap pr opri at e eat in g i m pl em en t). U sua l Soc ia l & Funct ion al Ac tiv itie s ? Adu lt : Ad ap ti ve t as k s an d d es ir ab l e ac t i viti es , s uc h as g oin g t o wor k, s h op pi ng, c ook in g, us e of tr ans p or t at i on, pu rs ui ng a h obb y, etc . U sua l So cia l & Fun cti on al Activ it ie s ? Y oung C hil dr en : Ac ti vit i es th at ar e ag e and c u ltu r al l y ap pr opr i at e ( e.g. , s oc i al in t er ac ti ons , pl ay ac ti vi ti es , l ear ni ng t as ks , etc .). 28 D ec 0 4/C l ar if ic ati on Au g 09 Page 14 of 21 V ers i on 1. 0/ C l arif ic at i on 1 PAR AMET ER GRADE 1 MI L D GRADE 2 MO DERAT E GRADE 3 SEVERE GRADE 4 PO TENTI ALLY LI FE - THREATENI NG Vul vovaginit is ( sym pt om s ) (Us e i n st udi es eval uati ng t opi cal st udy agent s) For ot her vul vovagi ni ti s see Inf ecti on: I nf ect ion (any other t han HI V i nf ecti on) Sym pt om s causi ng no or minim al i nt erf er ence wi t h usual soci al & funct ional acti vi ti es Sym pt om s causi ng gr eat er than minim al i nt erf er ence wi t h usual soci al & functi onal acti vi ti es Sym pt om s causi ng i nabi lit y t o per f orm usual soci al & functi onal acti vi ti es Sym pt om s causi ng i nabi lit y t o per f orm basic sel f - car e funct i ons Vul vovaginit is ( cli ni cal exam ) (Use i n st udi es eval uati ng t opi cal st udy agent s) For ot her vul vovagi ni ti s see Inf ecti on: I nf ect ion (any other t han HI V i nf ecti on) Mi nim al vagi nal abnorm al iti es on exam i nati on O R Epi thel i al di sr upti on < 25% of tot al surf ace Moder at e vaginal abnorm al iti es on exam i nati on O R Epi thel i al di sr upti on of 25 - 49% tot al surf ace Sever e vagi nal abnorm al iti es on exam i nati on O R Epi thel i al di sr upti on 50 - 75% tot al surf ace Vagi nal per f or ati on O R Epi thel i al di sr upti on > 75% tot al sur face O CUL AR/ VI SUAL Uvei t i s Asym pt om at ic but det ect abl e on exam Sym pt om ati c ant er i or uvei t is O R Medi cal i nt er venti on indicat ed Post er i or or pan - uveit i s O R Oper at ive i nt er venti on indicat ed Di sabl ing visual l oss i n af f ect ed eye( s) Vi sual changes (fr om basel i ne) Vi sual changes causing no or minim al i nt erf er ence wi t h usu al soci al & funct ional acti vi ti es Vi sual changes causing gr eat er t han minim al i nt er f er ence wi t h usual soci al & funct ional acti vi ti es Vi sual changes causi ng i nabi lit y t o per f orm usual soci al & functi onal acti vi ti es Di sabl ing visual l oss i n af f ect ed eye( s) ENDO CRI NE/MET ABO LI C Abnorm al f at accum ulati on (e. g., back of neck, br east s, abdom en) Det ect abl e by st udy par ti ci pant (or by car egi ver f or young chil dr en and di sabl ed adult s) Det ect abl e on physi cal exam by healt h car e pr ovi der Di sfi guri ng O R Obvi ous change s on casual vi sual inspecti on NA 143 AP PEND I X A DIV I SIO N OF AIDS T AB L E FOR GRAD ING T HE S EVERIT Y OF ADUL T AND PED I AT RIC ADV ER SE EVENT S VERS IO N 1 .0 , DECE MBER, 200 4 ; CL AR IF I CAT IO N AUGUST 200 9 Basi c S elf - car e Fun cti ons ? Adu lt : Ac t i viti es s uc h as b at hi ng , d r es s ing , t oi l et in g, tr ans f er / m o vem en t, c on ti n enc e, an d f eed in g. B asi c S elf - car e Fu nct ion s ? Y oun g Chi ldr en : Ac t i viti es th at ar e ag e and c u ltu r al l y ap pr opr i at e ( e.g ., f eedi ng s elf wi th c u ltu r all y ap pr opri at e eat in g i m pl em en t). U sua l Soc ia l & Funct ion al Ac tiv itie s ? Adu lt : Ad ap ti ve t as k s an d d es ir ab l e ac t i viti es , s uc h as g oin g t o wor k, s h op pi ng, c ook in g, us e of tr ans p or t at i on, pu rs ui ng a h obb y, etc . U sua l So cia l & Fun cti on al Activ it ie s ? Y oung C hil dr en : Ac ti vit i es th at ar e ag e and c u ltu r al l y ap pr opr i at e ( e.g. , s oc i al in t er ac ti ons , pl ay ac ti vi ti es , l ear ni ng t as ks , etc .). 28 D ec 0 4/C l ar if ic ati on Au g 09 Page 15 of 21 V ers i on 1. 0/ C l arif ic at i on 1 PAR AMET ER GRADE 1 MI L D GRADE 2 MO DERAT E GRADE 3 SEVERE GRADE 4 PO TENTI ALLY LI FE - THREATENI NG Di abet es m elli t us NA New onset wit hout need t o i nit i at e m edi cat ion O R Modi fi cati on of cur r ent m edi cat ions t o regain gl ucose contr ol New onset wit h i ni ti at ion of m edi cati on i ndi cat ed O R Di abet es uncontr ol l ed despi t e t r eatm e nt modif i cati on Li f e - t hr eat eni ng consequences (e. g. , ket oaci dosis, hyper osm ol ar non - ket ot ic com a) Gynecom ast i a Det ect abl e by st udy par ti ci pant or car egi ver (for young chil dr en and di sabl ed adult s) Det ect abl e on physi cal exam by healt h car e pr ovi der Di sfi guri ng O R Obvi ous on casual vi sual i nspecti on NA Hyper t hyroi di sm Asym pt om at ic Sym pt om ati c causing gr eat er than minim al i nt erf er ence wi t h usual soci al & functi onal acti vi ti es O R Thyr oi d suppr essi on t her apy i ndi cat ed Sym pt om s causi ng i nabi lit y t o per f orm usual soci al & functi onal acti vi ti es O R Uncontr ol l ed despit e t r eatm ent modif i cati on Li f e - t hr eat eni ng consequences (e. g. , t hyroi d st orm ) Hypot hyr oi di sm Asym pt om at ic Sym pt om ati c causing gr eat er than minim al i nt erf er ence wi t h usual soci al & functi onal acti v i ti es O R Thyr oi d repl acem ent t her apy i ndi cat ed Sym pt om s causi ng i nabi lit y t o per f orm usual soci al & functi onal acti vi ti es O R Uncontr ol l ed despit e t r eatm ent modif i cati on Li f e - t hr eat eni ng consequences (e. g. , myxedem a com a) Li poat rophy (e. g., f at l oss f r om t he face, ext r em iti es, but tocks) Det ect abl e by st udy par ti ci pant (or by car egi ver f or young chil dr en and di sabl ed adult s) Det ect abl e on physi cal exam by healt h car e pr ovi der Di sfi guri ng O R Obvi ous on casual vi sual i nspecti on NA 144 AP PEND I X A DIV I SIO N OF AIDS T AB L E FOR GRAD ING T HE S EVERIT Y OF ADUL T AND PED I AT RIC ADV ER SE EVENT S VERS IO N 1 .0 , DECE MBER, 200 4 ; CL AR IF I CAT IO N AUGUST 200 9 ? Val u es ar e f or t er m i nf ants . Pr e t erm i nf ants s h ou ld b e as s es s ed us i ng l oc al n or m al r an g es . ? Us e ag e an d s ex ap pr opr i at e val u es ( e.g. , b il iru bi n). 28 D ec - 0 4/C l ar if ic ati on Au g 0 9 Page 16 of 21 V ers i on 1. 0/ C l ar if ic ati on 1 L ABO R AT O RY PAR AMET ER GRADE 1 MI L D GRADE 2 MO DERAT E GRADE 3 SEVERE GRADE 4 PO TENTI ALLY LI FE - THREATENI NG HEMAT OLO G Y Standard International Units are listed in italics Absol ut e CD4+ count ? Adult and Pedi at ri c > 13 year s ( HI V NEG ATI VE O NLY ) 300 ? 400/m m 3 300 ? 400/ ?L 200 ? 299/mm 3 200 ? 299/ ?L 100 ? 199/m m 3 100 ? 199/ ?L < 100/m m 3 < 100/ ?L Absol ut e lym phocyt e count ? Adult and Pedi at ri c > 13 year s ( HI V NEG ATI VE O NLY ) 600 ? 650/m m 3 0. 600 x 10 9 ? 0. 650 x 10 9 / L 500 ? 599/m m 3 0. 500 x 10 9 ? 0. 599 x 10 9 / L 350 ? 499/m m 3 0. 350 x 10 9 ? 0. 499 x 10 9 / L < 350/m m 3 < 0.350 x 10 9 / L Com m ent: Values in children ? 13 years are not given for the two parameters above because the absolute counts are variable. Absol ut e neut r ophil count (ANC ) Adul t and Pedi atr i c, > 7 days 1, 000 ? 1, 300/m m 3 1. 000 x 10 9 ? 1. 300 x 10 9 / L 750 ? 999/m m 3 0. 750 x 10 9 ? 0. 999 x 10 9 / L 500 ? 749/m m 3 0. 500 x 10 9 ? 0. 749 x 10 9 / L < 500/m m 3 < 0.500 x 10 9 / L Inf ant ? ? , 2 ? ? 7 days 1, 250 ? 1, 500/mm 3 1. 250 x 10 9 ? 1. 500 x 10 9 / L 1, 000 ? 1, 249/mm 3 1. 000 x 10 9 ? 1. 2 49 x 10 9 / L 750 ? 999/m m 3 0. 750 x 10 9 ? 0. 999 x 10 9 / L < 750/m m 3 < 0.750 x 10 9 / L Inf ant ? ? , ? 1 day 4, 000 ? 5, 000/mm 3 4. 000 x 10 9 ? 5. 000 x 10 9 / L 3, 000 ? 3, 999/mm 3 3. 000 x 10 9 ? 3. 999 x10 9 / L 1, 500 ? 2, 999/mm 3 1. 500 x 10 9 ? 2. 999 x 10 9 / L < 1,500/mm 3 < 1.500 x 10 9 / L Com m ent: Param et er changed f r om ?I nfant, < 1 day? t o ?I nf ant , ? 1 day? Fi bri nog en, decr eased 100 ? 200 mg/ dL 1. 00 ? 2. 00 g/ L O R 0. 75 ? 0. 99 x LLN 75 ? 99 mg/ dL 0. 75 ? 0. 99 g/ L OR 0. 50 ? 0. 74 x LLN 50 ? 74 mg/ dL 0. 50 ? 0. 74 g/ L OR 0. 25 ? 0. 49 x LLN < 50 m g/ dL < 0.50 g/ L OR < 0.25 x LLN O R Associ at ed wi t h gr oss bl eedi ng 145 AP PEND I X A DIV I SIO N OF AIDS T AB L E FOR GRAD ING T HE S EVERIT Y OF ADUL T AND PED I AT RIC ADV ER SE EVENT S VERS IO N 1 .0 , DECE MBER, 200 4 ; CL AR IF I CAT IO N AUGUST 200 9 ? Val u es ar e f or t er m i nf ants . Pr e t erm i nf ants s h ou ld b e as s es s ed us i ng l oc al n or m al r an g es . ? Us e ag e an d s ex ap pr opr i at e val u es ( e.g. , b il iru bi n). 28 D ec - 0 4/C l ar if ic ati on Au g 0 9 Page 17 of 21 V ers i on 1. 0/ C l ar if ic ati on 1 L ABO R AT O R Y PAR AMET ER GRADE 1 MI L D GRADE 2 MO DERAT E GRADE 3 SEVERE GRADE 4 PO TENTI ALLY LI FE - THREATENI NG Hem ogl obi n (Hgb) Com m ent: The Hgb val ues i n mm ol / L have changed because t he conver si on f act or used t o conver t g/ dL t o mm ol / L has been changed fr om 0. 155 t o 0. 6206 (the m ost comm only used conver si on f act or ). For gr adi ng Hgb resul t s obt ai ned by an anal yt ic m ethod wit h a conver si on f act or ot her t han 0. 6206, t he resul t must be conver t ed t o g/ dL usi ng t he appropri at e conver si on fact or f or that l ab. Adul t and Pedi atr i c ? 57 days ( HIV PO SIT IVE ON L Y ) 8. 5 ? 10. 0 g/ dL 5. 24 ? 6. 23 mmol/ L 7. 5 ? 8. 4 g/dL 4. 62 ? 5. 23 mmol / L 6. 50 ? 7. 4 g/ dL 4. 03 ? 4. 61 mmol/ L < 6.5 g/ dL < 4.03 mmol/ L Adul t and Pedi atr i c ? 57 days ( HI V NEG ATI VE O NLY ) 10. 0 ? 10. 9 g/ dL 6. 18 ? 6. 7 9 mmol/ L OR Any decr ease 2. 5 ? 3. 4 g/dL 1. 5 8 ? 2. 13 mmol/ L 9. 0 ? 9. 9 g/dL 5. 55 - 6. 17 mmol/ L OR Any decr ease 3. 5 ? 4. 4 g/dL 2. 14 ? 2. 7 8 mmol/ L 7. 0 ? 8. 9 g/dL 4. 34 - 5.5 4 mmol/ L OR Any decr ease ? 4. 5 g/ dL > 2.7 9 mmol/ L < 7.0 g/ dL < 4.34 mmol/ L Com m ent : The de cr ease i s a decr ease fr om basel i ne Inf ant ? ? , 36 ? 56 days ( HI V PO SI TI VE O R NEG ATI VE ) 8. 5 ? 9. 4 g/dL 5. 24 ? 5. 8 6 mmol/ L 7. 0 ? 8. 4 g/ dL 4. 31 ? 5. 2 3 mmol/ L 6. 0 ? 6. 9 g/dL 3. 72 ? 4. 30 mmol/ L < 6.00 g/ dL < 3. 72 mmol/ L Inf ant ? ? , 22 ? 35 days ( HI V PO SI TI VE O R NEG ATI VE ) 9. 5 ? 10. 5 g/ dL 5. 8 7 - 6.54 mmol/ L 8. 0 ? 9. 4 g/dL 4. 93 ? 5. 8 6 mmol/ L 7. 0 ? 7. 9 g/dL 4. 3 4 ? 4. 92 mmol/ L < 7.00 g/ dL < 4.3 4 mmol / L Inf ant ? ? , ? 21 days ( HI V PO SI TI VE O R NEG ATI VE ) 12. 0 ? 13. 0 g/ dL 7. 4 2 ? 8. 09 mmol/ L 10. 0 ? 11. 9 g/ dL 6. 1 8 ? 7. 41 m mol/ L 9. 0 ? 9. 9 g/dL 5. 5 9 - 6. 1 7 mmol/ L < 9.0 g/ dL < 5.5 9 mmol/ L Cor r ect i on : Par am et er changed fr om ?I nf ant < 21 days? to ?Inf ant ? 21 days? Int er nati onal Norm ali zed Rat i o of pr ot hrom bi n tim e (I NR) 1. 1 ? 1. 5 x ULN 1. 6 ? 2. 0 x ULN 2. 1 ? 3. 0 x ULN > 3.0 x ULN Met hem ogl obin 5. 0 ? 10. 0% 10. 1 ? 15. 0% 15. 1 ? 20. 0% > 20. 0% Pr ot hr om bi n Tim e (PT) 1. 1 ? 1. 25 x ULN 1. 26 ? 1. 50 x ULN 1. 51 ? 3. 00 x ULN > 3.00 x ULN Par ti al Thr om bopl asti n Tim e (PTT) 1. 1 ? 1. 66 x ULN 1. 67 ? 2. 33 x ULN 2. 34 ? 3. 00 x ULN > 3.00 x ULN Pl at el et s, decr eased 100, 000 ? 124, 999/mm 3 100. 000 x 10 9 ? 124. 999 x 10 9 / L 50, 000 ? 99, 999/m m 3 50. 000 x 10 9 ? 99. 999 x 10 9 / L 25, 000 ? 49, 999/m m 3 25. 000 x 10 9 ? 49. 999 x 10 9 / L < 25, 000/m m 3 < 25. 000 x 10 9 /L W BC, decr eased 2, 000 ? 2, 500/mm 3 2. 000 x 10 9 ? 2. 500 x 10 9 / L 1, 500 ? 1, 999/mm 3 1. 500 x 10 9 ? 1. 999 x 10 9 / L 1, 000 ? 1, 499/mm 3 1. 000 x 10 9 ? 1. 499 x 10 9 / L < 1,000/mm 3 < 1.000 x 10 9 / L 146 AP PEND I X A DIV I SIO N OF AIDS T AB L E FOR GRAD ING T HE S EVERIT Y OF ADUL T AND PED I AT RIC ADV ER SE EVENT S VERS IO N 1 .0 , DECE MBER, 200 4 ; CL AR IF I CAT IO N AUGUST 200 9 ? Val u es ar e f or t er m i nf ants . Pr e t erm i nf ants s h ou ld b e as s es s ed us i ng l oc al n or m al r an g es . ? Us e ag e an d s ex ap pr opr i at e val u es ( e.g. , b il iru bi n). 28 D ec - 0 4/C l ar if ic ati on Au g 0 9 Page 18 of 21 V ers i on 1. 0/ C l ar if ic ati on 1 L ABO R AT O RY PAR AMET ER GRADE 1 MI L D GRADE 2 MO DERAT E GRADE 3 SEVERE GRADE 4 PO TENTI ALLY LI FE - THREATENI NG CHEMI ST RI ES Standard International Units are listed in italics Aci dosi s NA pH < norm al , but ? 7. 3 pH < 7. 3 wit hout lif e - t hr eat eni ng consequences pH < 7. 3 wit h lif e - t hr eat eni ng consequences Al bum in, ser um , low 3. 0 g/ dL ? < LLN 30 g/ L ? < LLN 2. 0 ? 2. 9 g/dL 20 ? 29 g/ L < 2.0 g/ dL < 20 g/ L NA Al kal ine Phosphat ase 1. 25 ? 2. 5 x ULN ? 2. 6 ? 5. 0 x ULN ? 5. 1 ? 10. 0 x ULN ? > 10. 0 x ULN ? Al kal osi s NA pH > norm al , but ? 7. 5 pH > 7. 5 wit hout lif e - t hr eat eni ng consequences pH > 7. 5 wit h lif e - t hr eat eni ng consequences ALT (SG PT ) 1. 25 ? 2. 5 x ULN 2. 6 ? 5. 0 x ULN 5. 1 ? 10. 0 x ULN > 10. 0 x ULN AST (SGO T) 1. 25 ? 2. 5 x ULN 2. 6 ? 5. 0 x ULN 5. 1 ? 10. 0 x ULN > 10. 0 x ULN Bi car bonat e, ser um , l ow 16. 0 m Eq/ L ? < LLN 16. 0 mmol/ L ? < LLN 11. 0 ? 15. 9 mEq/L 11. 0 ? 15. 9 mmol/ L 8. 0 ? 10. 9 mEq/ L 8. 0 ? 10. 9 mmol/ L < 8.0 mEq/ L < 8.0 mmol/ L Com m ent: Som e l abor at ori es wi ll report t hi s val ue as Bi car bonat e (HCO 3 ) and ot her s as Total Car bon Di oxi de (CO 2 ) . These ar e the sam e t ests; val ues shoul d be gr aded accor di ng t o the ranges f or Bi car bonat e as l i st ed above . Bi lir ubin (Tot al) Adul t and Pedi atr i c > 14 days 1. 1 ? 1. 5 x ULN 1. 6 ? 2. 5 x ULN 2. 6 ? 5. 0 x ULN > 5.0 x ULN I nf ant ? ? , ? 14 days ( non - hem olyti c) NA 20. 0 ? 25. 0 mg/dL 342 ? 428 ?mo l/ L 25. 1 ? 30. 0 mg/dL 429 ? 513 ?mo l/ L > 30. 0 mg/ dL > 513. 0 ?mo l/ L I nf ant ? ? , ? 14 days ( hem olyti c) NA NA 20. 0 ? 25. 0 mg/dL 342 ? 428 ?mo l/ L > 25. 0 mg/ dL > 428 ?mo l/ L Cal ci um , ser um , hi gh Ad ul t and Pedi atr i c ? 7 days 10. 6 ? 11. 5 m g/ dL 2. 65 ? 2. 88 mmol/ L 11. 6 ? 12. 5 m g/ dL 2. 89 ? 3. 13 mmol/ L 12. 6 ? 13. 5 m g/ dL 3. 14 ? 3. 38 mmol/ L > 13. 5 mg/ dL > 3.38 mmol/ L Inf ant ? ? , < 7 days 11. 5 ? 12. 4 mg/dL 2. 88 ? 3. 10 mmol/ L 12. 5 ? 12. 9 mg/dL 3. 11 ? 3. 23 mmol/ L 13. 0 ? 13. 5 mg/dL 3. 245 ? 3. 38 mmol/ L > 13. 5 mg/ dL > 3.38 mmol/ L Cal ci um , ser um , low Adul t and Pedi atr i c ? 7 days 7. 8 ? 8. 4 mg/ dL 1. 95 ? 2. 10 mmol/ L 7. 0 ? 7. 7 mg/ dL 1. 75 ? 1. 94 mmol/ L 6. 1 ? 6. 9 mg/ dL 1. 53 ? 1. 74 mmol/ L < 6.1 mg/ dL < 1.53 m mol/ L I nf ant ? ? , < 7 days 6. 5 ? 7. 5 mg/ dL 1. 63 ? 1. 88 mmol/ L 6. 0 ? 6. 4 mg/ dL 1. 50 ? 1. 62 mmol/ L 5. 50 ? 5. 90 mg/dL 1. 38 ? 1. 51 mmol/ L < 5.50 mg/ dL < 1.38 mmol/ L Com m ent : Do not adj ust Cal ci um , ser um , l ow or Calcium , ser um , hi gh f or al bum in 147 AP PEND I X A DIV I SIO N OF AIDS T AB L E FOR GRAD ING T HE S EVERIT Y OF ADUL T AND PED I AT RIC ADV ER SE EVENT S VERS IO N 1 .0 , DECE MBER, 200 4 ; CL AR IF I CAT IO N AUGUST 200 9 ? Val u es ar e f or t er m i nf ants . Pr e t erm i nf ants s h ou ld b e as s es s ed us i ng l oc al n or m al r an g es . ? Us e ag e an d s ex ap pr opr i at e val u es ( e.g. , b il iru bi n). 28 D ec - 0 4/C l ar if ic ati on Au g 0 9 Page 19 of 21 V ers i on 1. 0/ C l ar if ic ati on 1 L ABO R AT O RY PAR AMET ER GRADE 1 MI L D GRADE 2 MO DERAT E GRADE 3 SEVERE GRADE 4 PO TENTI ALLY LI FE - THREATENI NG Car diac t roponi n I (cTnI) NA NA NA Level s consi st ent wi t h myocar di al i nf arcti on or unstabl e angi na as def i ned by the manuf act ur er Car diac t roponi n T (cTnT) NA N A NA ? 0. 20 ng/m L O R Level s consi st ent wi t h myocar di al i nf arcti on or unstabl e angi na as def i ned by the manuf act ur er Chol est er ol (f asti ng) Adult ? 18 years 200 ? 239 mg/ dL 5. 18 ? 6. 19 mmol/ L 240 ? 300 mg/ dL 6. 20 ? 7. 77 mmol/ L > 300 mg/ dL > 7.77 mmol/ L NA Pediatric < 18 years 170 ? 199 mg/ dL 4. 40 ? 5. 15 mmol/ L 200 ? 300 mg/ dL 5. 16 ? 7. 77 mmol/ L > 300 mg/ dL > 7.77 mmol/ L NA Cr eat i ne Ki nase 3. 0 ? 5. 9 x ULN ? 6. 0 ? 9. 9 x ULN ? 10. 0 ? 19. 9 x ULN ? ? 20. 0 x ULN ? Creat i ni ne 1. 1 ? 1. 3 x ULN ? 1. 4 ? 1. 8 x ULN ? 1. 9 ? 3. 4 x ULN ? ? 3. 5 x ULN ? L ABO R AT O RY PAR AMET ER GRADE 1 MI L D GRADE 2 MO DERAT E GRADE 3 SEVERE GRADE 4 PO TENTI ALLY LI FE - THREATENI NG Gl ucose, ser um , high Nonf ast ing 116 ? 160 mg/ dL 6. 44 ? 8. 88 mmol/ L 161 ? 250 mg/ dL 8. 89 ? 13. 88 mmol/ L 251 ? 500 mg/ dL 13. 89 ? 27.75 mmol/ L > 500 mg/ dL > 27. 75 mmol/ L Fasti ng 110 ? 125 mg/ dL 6. 11 ? 6. 94 mmol/ L 126 ? 250 mg/ dL 6. 95 ? 13. 88 mmol/ L 251 ? 500 mg/ dL 13. 89 ? 27.75 mmol/ L > 500 mg/ dL > 27. 75 mmol/ L Gl ucose, ser um , l ow Adul t and Pedi atr i c ? 1 month 55 ? 64 mg/ dL 3. 05 ? 3. 55 mmol/ L 40 ? 54 mg/ dL 2. 22 ? 3. 06 mmol/ L 30 ? 39 mg/ dL 1. 67 ? 2. 23 mmol/ L < 30 m g/ dL < 1.67 mmol/ L I nf ant ? ? , < 1 m ont h 50 ? 54 mg/ dL 2. 78 ? 3. 00 mmol/ L 40 ? 49 mg/ dL 2. 22 ? 2. 77 mmol/ L 30 ? 39 mg/ dL 1. 67 ? 2. 21 mmol/ L < 30 m g/ dL < 1.6 7 mmol/ L 148 AP PEND I X A DIV I SIO N OF AIDS T AB L E FOR GRAD ING T HE S EVERIT Y OF ADUL T AND PED I AT RIC ADV ER SE EVENT S VERS IO N 1 .0 , DECE MBER, 200 4 ; CL AR IF I CAT IO N AUGUST 200 9 ? Val u es ar e f or t er m i nf ants . Pr e t erm i nf ants s h ou ld b e as s es s ed us i ng l oc al n or m al r an g es . ? Us e ag e an d s ex ap pr opr i at e val u es ( e.g. , b il iru bi n). 28 D ec - 0 4/C l ar if ic ati on Au g 0 9 Page 20 of 21 V ers i on 1. 0/ C l ar if ic ati on 1 Lact at e ULN - < 2. 0 x ULN wi t hout aci dosi s ? 2. 0 x ULN wit hout aci dosis I ncr eased l act at e wi t h pH < 7. 3 wit hout lif e - t hr eat eni ng consequences Incr eased l act at e wi t h pH < 7. 3 wit h lif e - t hr eat eni ng consequences Com m ent: A dded ULN to Gr ade 1 par a m et er LDL chol est er ol (f asti ng) Adult ? 18 years 130 ? 159 mg/ dL 3. 37 ? 4. 12 mmol/ L 160 ? 190 mg/ dL 4. 13 ? 4. 90 mmol/ L ? 190 mg/ dL ? 4. 91 mmol/ L NA Pedi atr ic > 2 - < 18 year s 110 ? 129 mg/ dL 2. 85 ? 3. 34 mmol/ L 130 ? 189 mg/ dL 3. 35 ? 4. 90 mmol/ L ? 190 mg/ dL ? 4.91 mmol/L NA Li pase 1. 1 ? 1. 5 x ULN 1. 6 ? 3. 0 x ULN 3. 1 ? 5. 0 x ULN > 5.0 x ULN Magnesi um , ser um , l ow 1. 2 ? 1. 4 mEq/ L 0. 60 ? 0. 70 mmol/ L 0. 9 ? 1. 1 m Eq/ L 0. 45 ? 0. 59 mmol/ L 0. 6 ? 0. 8 m Eq/ L 0. 30 ? 0. 44 mmol/ L < 0.60 mEq/ L < 0.30 mmol/ L Pancr e ati c am yl ase 1. 1 ? 1. 5 x ULN 1. 6 ? 2. 0 x ULN 2. 1 ? 5. 0 x ULN > 5.0 x ULN Phosphat e, ser um , l ow Adul t and Pedi atr i c > 14 year s 2. 5 mg/ dL ? < LLN 0. 81 mmol/ L ? < LLN 2. 0 ? 2. 4 mg/ dL 0. 65 ? 0. 80 mmol/ L 1. 0 ? 1. 9 mg/ dL 0. 32 ? 0. 64 mmol/ L < 1.00 mg/ dL < 0.3 2 mmol/ L Pedi atr ic 1 year ? 14 year s 3. 0 ? 3. 5 mg/ dL 0. 97 ? 1. 13 mmol/ L 2. 5 ? 2. 9 mg/ dL 0. 81 ? 0. 96 mmol/ L 1. 5 ? 2. 4 mg/ dL 0. 48 ? 0. 80 mmol/ L < 1.50 mg/ dL < 0.48 mmol/ L Pedi atr ic < 1 year 3. 5 ? 4. 5 mg/ dL 1. 13 ? 1. 45 mmol/ L 2. 5 ? 3. 4 mg/ dL 0. 81 ? 1. 12 mmol/ L 1. 5 ? 2. 4 mg/ dL 0. 48 ? 0. 80 mmol/ L < 1.50 mg/ dL < 0.48 mmol/ L Pot assi um , ser um , hi gh 5. 6 ? 6. 0 m Eq/ L 5. 6 ? 6. 0 mmol/ L 6. 1 ? 6. 5 m Eq/ L 6. 1 ? 6. 5 mmol/ L 6. 6 ? 7. 0 m Eq/ L 6. 6 ? 7. 0 mmol/ L > 7.0 mEq/ L > 7.0 mmol/ L Pot assi um , ser um , l ow 3. 0 ? 3. 4 m Eq/ L 3. 0 ? 3. 4 mmol/ L 2. 5 ? 2. 9 m Eq/ L 2. 5 ? 2. 9 mmol/ L 2. 0 ? 2. 4 m Eq/ L 2. 0 ? 2. 4 mmol/ L < 2.0 mEq/ L < 2.0 mmol/ L Sodi um , ser um , hi gh 146 ? 150 mEq/ L 146 ? 150 mmol/ L 151 ? 154 mEq/ L 151 ? 154 mmol/ L 155 ? 159 mEq/ L 155 ? 159 mmol/ L ? 160 mEq/ L ? 160 mmol/ L So di um , ser um , l ow 130 ? 135 mEq/ L 130 ? 135 mmol/ L 125 ? 129 mEq/ L 125 ? 129 mmol/ L 121 ? 124 mEq/ L 121 ? 124 mmol/ L ? 120 mEq/ L ? 120 mmol/ L Tr i gl ycer i des (f asti ng) NA 500 ? 750 mg/ dL 5. 65 ? 8. 48 mmol/ L 751 ? 1,200 m g/ dL 8. 49 ? 13. 56 mmol/ L > 1,200 mg/ dL > 13. 56 mmol/ L 149 AP PEND I X A DIV I SIO N OF AIDS T AB L E FOR GRAD ING T HE S EVERIT Y OF ADUL T AND PED I AT RIC ADV ER SE EVENT S VERS IO N 1 .0 , DECE MBER, 200 4 ; CL AR IF I CAT IO N AUGUST 200 9 ? Val u es ar e f or t er m i nf ants . Pr e t erm i nf ants s h ou ld b e as s es s ed us i ng l oc al n or m al r an g es . ? Us e ag e an d s ex ap pr opr i at e val u es ( e.g. , b il iru bi n). 28 D ec - 0 4/C l ar if ic ati on Au g 0 9 Page 21 of 21 V ers i on 1. 0/ C l ar if ic ati on 1 L ABO R AT O RY PAR AMET ER GRADE 1 MI L D GRADE 2 MO DERAT E GRADE 3 SEVERE GRADE 4 PO TENTI ALLY LI FE - THREATENI NG Ur i c aci d 7. 5 ? 10. 0 mg/ dL 0. 45 ? 0. 59 mmol/ L 10. 1 ? 12. 0 mg/dL 0. 60 ? 0. 71 mmol/ L 12. 1 ? 15. 0 mg/dL 0. 72 ? 0. 89 mmol / L > 15. 0 mg/ dL > 0.89 mmol/ L URI NAL YSI S Standard International Units are listed in italics Hem at uri a (m icr oscopi c) 6 ? 10 RBC/ HPF > 10 RBC/ HPF G r oss, wi t h or wi thout cl ot s O R wit h RBC cast s Tr ansf usi on indicat ed Pr ot ei nuri a, random coll ect ion 1 + 2 ? 3 + 4 + NA Pr ot ei nuri a, 24 hour coll ecti on Adul t and Pedi atr i c ? 10 year s 200 ? 999 mg/ 24 h 0. 200 ? 0. 999 g/ d 1, 000 ? 1, 999 mg/ 24 h 1. 000 ? 1. 999 g/ d 2, 000 ? 3, 500 mg/ 24 h 2. 000 ? 3. 500 g/ d > 3,500 mg/ 24 h > 3.500 g/ d Pedi atr ic > 3 m o - < 10 year s 201 ? 499 mg/ m 2 / 24 h 0. 201 ? 0. 499 g/ d 500 ? 799 mg/ m 2 / 24 h 0. 500 ? 0. 799 g/ d 800 ? 1,000 mg/ m 2 / 24 h 0. 800 ? 1. 000 g/ d > 1,000 mg/ m 2 / 24 h > 1.000 g/ d 150 APPENDIX B 151 A p p end ix B: Inform e d conse nt for: I m pact of Vi ral and Host Gene ti c Factors on Anti re trov i ral Treatm e nt Out com e i n South Afri can HI V - 1 subty pe C infe cte d AI DS pati e nts 152 Appendix B: Informed consent for: Impact of Viral and Host Genetic Factors on Antiretroviral Treatment Outcome in South African HIV-1 subtype C infected AIDS patients Version 1.0 5 October 2006 English Page 1 of 3 INFORMED CONSENT CIPRA PROJECT 1 Information Sheet and Consent From Title of Research Project: Impact of Viral and Host Genetic Factors on Antiretroviral Treatment Outcome in South African HIV-1 subtype C infected AIDS patients GENOTYPING OF HOST GENETIC FACTORS We would like to perform genotyping (studying your genes) on a sample of your blood. We will tell you what this involves so you can decide if you will consent to genotyping. 1. What is the purpose of this genetic research? You are currently taking antiretroviral therapy as part of CIPRA Project 1. There are enzymes (proteins in the body, usually in the liver and bowel) that help to break down any drug that you take, including antiretrovirals. These enzymes differ in different groups of people and have not been well studied in South Africans. It is important to understand if these enzymes are different in our population as they affect how our bodies handle different antiretroviral drugs and may impact on interactions with other medications or on the side-effects your experience. We would like to study the following enzymes: ? Cytochrome P450 ? P-glycoprotein ? HLA expression ? Any published gene linked to HIV/AIDS, which will help in further understanding of the virus and its treatment and prevention. All genetic results will be treated confidentially and identified only by your study number (and not your name). 2. What do I gain from this research? You will not receive any direct benefit from this genetic research. 3. What are the risks associated with the procedure? You may experience some mild discomfort and minor bruising at the site of blood sampling. 4. What will happen to my blood sample? No extra blood will be required. A small amount of blood (about 4ml) taken at the week 4 visit will be used to study your genes. 153 Appendix B: Informed consent for: Impact of Viral and Host Genetic Factors on Antiretroviral Treatment Outcome in South African HIV-1 subtype C infected AIDS patients Version 1.0 5 October 2006 English Page 2 of 3 5. What will happen if I change my mind? You are free to change your mind at any time. If you change your mind about participating, you can withdraw your sample by making a request to the trial doctor/nurse. This will not effect your treatment on CIPRA in any way. 6. Will the information be kept confidential? All the findings of this research will be kept confidential in accordance with the standards followed by medical researchers in compliance with International Good Clinical Practice. 7. Will I know the results of the research project? This project is not performed in real-time, but as the results become available you may request your result from your doctor/nurse. These results may not be useful to you, as combined information from many people is needed to see if the enzymes in South Africans make a difference to how we break down our antiretrovirals. The results of the whole study will be made known to you once it is complete. 8. What are my rights? The trial sponsor will not sell or transfer ownership to other parties. The samples will be used only by CIPRA-SA employees and/or researchers working with CIPRA-SA, and only for the research described above. YOUR PARTICIPATION IN THIS RESEARCH PROJECT IS VOLUNTA RY. YOU MAY REFUSE TO PARTICIPATE IN THIS RESEARCH PROJECT IF YOU WISH. 154 Appendix B: Informed consent for: Impact of Viral and Host Genetic Factors on Antiretroviral Treatment Outcome in South African HIV-1 subtype C infected AIDS patients Version 1.0 5 October 2006 English Page 3 of 3 DOCUMENTATION OF THIS CONSENT: One copy of this consent document will be given to you and one copy will be kept as part of the records of this research project, separate from the data resulting from the research project. Study ID: Initials: Date of Birth: Trial Number: CIPRAZA001 Title of Research Project: Impact of Viral and Host Genetic Factors on Antiretroviral Treatment Outcome in South African HIV-1 subtype C infected AIDS patients Consent Form Agreement to participate in a clinical trial Your Consent Subject Initials 1. I confirm I have read and understand the genotyping information sheet and have the opportunity to ask questions. 2. I understand that my participation is voluntary and that I am free to withdraw at any time, without given reason, without my medical care or legal rights being affected 3. I agree to take part in the above project Name (print):____________________________________Date:___________________ Signed by Subject:________________________________Date:___________________ Study staff Name:_______________________________ Date:___________________ Signed by Study staff:____________________________ Date:___________________ Witness: Date: 155 Appendix B: Informed consent for: Impact of Viral and Host Genetic Factors on Antiretroviral Treatment Outcome in South African HIV-1 subtype C infected AIDS patients Version 1.0 5 October 2006 Xhosa Page 1 of 3 I MV UME ES E KE LWE ELW AZ I NI YE P RO J E KT HI YOK U - 1 YE - C IP R A Iph e ph a lo L wa zi ne Fo mu ye Mvu me Isih lok o se P r oj ek thi yoP ha ndo: Imp e mb e le lo yee Me ko zeV a yira si ne S ond li so Fu zo kwiZip h u mo zo Nya ng o ng eA nt ire t ro vira l eMza nt si Af rika kub ag u li beA IDS ab an o su le lo lwe HIV - 1 y o h lo bo olu ng aph an t si lwe - C UK UHLE L A IIJ I NI ZOF UZO ZE E ME KO ZE SO NDLI SOFUZO Sin q we ne la ukuq hu ba uh le lo lwee jin i zof u zo (u kup ho no no ng a iijin i za kho ) kwisa mp u lu ye ga zi la kh o. Siza ku ku xe le la uku ba oku kub an da kan ya nto n i uku ze wen ze isigq ib o sokub a uya ku vu ma ukub a kup ho no no ng we iijin i zof u zo. 1 . Yin toni inj ongo yolu pha ndo lwe e j ini zofuzo? Nje n ga ng o ku uth a th a un yan go nge - an t ire t ro vira l njen ge n xa len ye yeP ro jekt h i yo ku - 1 ye CIP RA . Ku kho ii - e nzyme (iip ro t in i emzimb e n i, nga ma xa ama n in zi kwisib ind i na se ma th un jin i ) ezin ce d isa ukwa h lu kan isa (u ku ca lu ca lu la ) na wup h i umch iza owu th at ha yo, ku qu ka ne e - an t ire t ro vira l. Ezi en zyme zah lukile ku maq e la ah luken e yo ab an tu ya ye azikap ho no no ng wa ng o ku kho lisa yo eMza nt si Af rika . Kub a lu le kile uku qo nd a ukub a ngab a ezi enzyme za h lu kil e kwisizwe set hu nje ng o ko zich ap ha ze la in d le la imizimb a ye th u ip ha t ha nga yo imich iza eh lu ken e yo ye - a nt ire t ro vira l yaye ino kub a ne mp e mb e le lo eku se ben zen i na man ye ama ye za okan ye kwizip hu mo ezing a lin de le kan ga ona zo. Sin q we ne la ukup ho non on ga ii - e n zyme ezila n d e layo : ? I - Cyt o ch ro me P45 0 ? I - P - g lyco p ro te in ? Imb o n a ka lo ye HLA ? Nayip h i ijin i epa pa sh iwe yo en xu lu me ne ne HIV / A IDS , eya kun ce da ekuq on de n i ngo kon ge ze le lwe yo nge va yira si no n ya ng o lwa yo not h in t e lo . Zo n ke izip h u mo zof u zo ziya ku g cin wa ziyimf ih lo ya ye zicho ng we kup he la ng en o mb o lo ya kho yo ph on on on go (ha yi ng ega ma lakho ). 2 . Yin toni endi ya kuyizuza kolu pha ndo? Awu na kuf u ma na na lup h i un ced o olun gq a lile yo ko lu ph an do lof u zo . 3. Ze ziphi iingx a k i eza ya ma niswa ne nk qubo? Un o ku ba no kun go n wa b i oku th ile oku zo lile yo no ku g ru zu ka o ku n cin ci kwin da wo yo kut ha th a isa mp u lu yega zi. 4 . Kuya kwe nzek a ntoni kwi sa mpu lu ya m ye ga zi ? A likh o iga zi elon ge ze le lwe yo eliya kuf un wa . Ubun ga kan an i obu n cin ci beg azi (ma lu ng a ne - 4 ml) ob ut ha t h we kut ye le lo lwe ve ki ye si - 4 lu ya ku se tyen ziswa ukup ho no no ng a iij in i za kh o zof u zo . 156 Appendix B: Informed consent for: Impact of Viral and Host Genetic Factors on Antiretroviral Treatment Outcome in South African HIV-1 subtype C infected AIDS patients Version 1.0 5 October 2006 Xhosa Page 2 of 3 5 . Kuya kwe nzek a ntoni xa ndij ik a ingqondo ya m? Ukh u lu le kile uku jika in gq on do yakho na n in i na. Uku ba ujika ing qo nd o ya kho ma lu ng a no ku t ha th a in xa xh eb a, un ga rho xisa isa mpu lu yakh o ngo kwen za isice lo kug q irha wo ling o/ umo ng ika zi. Oku akun a k u cha ph a ze la un yan go lwa kho kwiCIP RA na ng eyip h i na ind le la. 6 . Inga ba ulwa zi lu ya kugc inwa luyi mf ih lo? Zon ke iziph u mo zo lu phan do ziya ku g cin wa ziyimf ih lo ng okwe miga ng a th o ela nd e lwa yo nga ba ph an d i be zo n ya ngo uku th ob e la i - In t e rna t io na l Go od Clin ica l Pra ct ice (u ku ziPh at ha okuL un g ile yo kwe zo Nya ng o kwe Zizwe ng e zizwe ). 7 . Inga ba ndiza kuza zi iziphu mo ze pr oj ek thi yopha ndo? L e pro je kt h i ayiq hu t ywa ng e xe sha lo kwe n ya n i, ko d wa xa izip hu mo ziman e zif u man e ka ung en za isice lo se ziph u mo za kho ku gq irh a /u mo ng ika zi. Kun ge n ze ka uku ba ezi ziph u mo zin g ab ina lo un ced o ku we , njen go ko ulwa zi olud it yan isiwe yo lwab an t u ab an in zi luf u ne ka ukub on a uku ba in gab a ii - e n zyme ku be mi ba seMza n t si Af rika ze nza umh lu ko kwind le la ii - a n t iret ro vira l ze t hu za h lu kan iswa nga yo. Uya kwaziswa ng e zip hu mo zo p h on on on go lon ke xa lu g q ityiwe . 8. Ay in toni ama lunge lo am? Umxh a si wo lin go akan a ku th en g isa okan ye ad lu lise le ub u mn in i kwa man ye ama qe la . Iisa mp u lu ziya ku set yen ziswa ng ab a se be n zi ba kwa - CIP RA - S A kup he la kun ye/ okan ye aba ph an d i aba seb en za no - CIP RA - S A , ya ye ma lun ga no ph an do olu ch a zwe ng en t la kup he la. UK UT HAT H A K W AK HO INX AX HE B A K ULE PRO J E KT HI YOP HANDO KUNG O K UZIT HANDE L A. UNG AL AND UL A UK UT HAT HA INX AX HE B A K ULE PRO JE KT HI YOP HANDO X A UT HAND A. 157 Appendix B: Informed consent for: Impact of Viral and Host Genetic Factors on Antiretroviral Treatment Outcome in South African HIV-1 subtype C infected AIDS patients Version 1.0 5 October 2006 Xhosa Page 3 of 3 AM AX WE B HU ALE MV UME : Iko p i en ye ye li xwe bhu le mvu me iya kun ikwa wen a k ut h i ikop i en ye ig cin we nje ng en xen ye ye e re kh od i za le pro je kt h i yo ph and o , ng o kwa h luken e yo ne da ta eve la kwip ro je kt h i yop ha nd o. I - ID yoP hononongo: Oonobumba bok uqa la: Umh la wok uZa lwa : Inombo lo yoL ingo: CIP R AZ A0 0 1 Is ih lok o se P r oje k thi yoP ha ndo: Imp e mbe le l o yee Me ko ze Va yira si ne So nd li so Fu zo kwiZip hu mo zo Nya ngo nge A nt ire t ro vira l eMza n t si Af rika kub ag u li beA IDS aba no su le lo lwe HIV - 1 yo h lo bo olu ng aph an t si lwe - C Ifo mu ye Mvu me Imvu me l wa no yok utha tha inx ax he ba kulingo lwe zonya ngo Imvu me Ya k ho O onobumba bok uqa l a boMl ingwa 1. Nding q ina ukub a nd ilif u nd ile ya ye nd a liqo nda iphe ph a lo lwa zi lo p ho no no ng o lwe jin i yof u zo ya ye nd ilif u me ne ithub a lo kub u za imib u zo . 2. Ndiya qo nd a uku ba uku th at ha kwa m in xa xhe ba ku ng o ku zit ha nd e la ya ye nd ikhu lu le kile uku rho xa na n in i na, nga ph an d l e ko ku n ika isizat hu , nga ph an d le ko ku ch ap ha ze le ka kwe n ka t ha le lo ya m ye zo n ya ng o oka n ye ama lun ge lo am ase mth et h wen i 3. Ndiya vu ma uku th at ha in xa xh eb a kwip ro je kt h i enge n t la Iga ma (unga diba nis i): __ __ __ _ _ __ __ __ __ __ _ _ _ _ __ __ __ __ __ Umh la : __ ___ __ __ _ _ __ _ I sa y in we ngumLing wa : __ __ __ __ __ __ __ __ _ _ _ _ __ __ __ __ __ _ Umh la : __ ___ _ _ __ __ __ _ Iga ma le lungu le siT a fu soP hononongo: ___ ___ __ __ __ __ __ _ Umh la : __ ___ __ __ __ __ _ Isa y in we lilungu le s iT a fu soP hononongo: _____ __ __ __ __ __ _ Umh la : __ ___ __ __ __ __ _ Ingqina : ___ __ __ _ _ __ __ __ __ __ __ __ __ __ __ ____ __ __ __ __ _ _ _ Umh la : __ ___ __ __ __ __ _ 158 Appendix B: Informed consent for: Impact of Viral and Host Genetic Factors on Antiretroviral Treatment Outcome in South African HIV-1 subtype C infected AIDS patients Version 1.0 5 October 2006 Zulu Page 1 of 3 I MV UME EY AZ IS I WE YE CIP R A PRO J E CT 1 Iph e sha na le min in ing wan e nef o mu le mvu me Isih lok o se phr o j ek thi yoc wa ningo : A man d la emip hu me la yo kwe la sh wa ng e mith i elwa na mag cin we ezimp a win i zof u zo eg ciwa ne n i na ku lo wo one g ciwa ne ezig u lin i za se Nin g izimu Af rika ezine HIV - 1 sub t yp e C ezih la se lwe yiNg cu laza UK UHLO LW A KWE Z I MP AW U ZOFUZO K ULO WO ONE G CIW ANE Sitha nd a uku h lo la izimpa wu za kh o zof u zo e s amp u len i leg a zi la kho . Sizo ku t sh e la uku th i lo kh u kup ha th e len e na n i ukuze ukwa zi uku nq u ma uma ufun a uku n ikeza imvu me yo kuh lo la izi mp a wu zof u zo. 1 . Yin i inh lo so ya lo lu cwa ningo lwe zi mpa wu zofu zo ? Nje n ga man je use be n zisa imit h i elwa ne HIV njen ge ng xen ye ye CIP RA Pro je ct 1. Kun a ma - e n za yimu (a map h ro t he n i emzimb en i, ava me esib in d in i na se siswin i) asiza uku n co zu lu la no ma yimup h i umut h i owuseb en zisa yo , oku ban da kan ya ne mit h i elwa ne HIV . La ma - e n za yimu ayeh lu ka emaq en jin i eh lu ken e aban t u fu th i awa ka ze acu tshu ng u lwe kah le eNin g izimu Af rika. Ku ba lu le kile uku th i uq on d isise ukut h i la ma - en za yimu eh lu kile esib a lwen i se t hu sa ba n tu njen go ba an o mth e le la ek ut h in i imizimb a ye th u i yi se ben z is a ka n ja n i i mit h i eh lu kile elwa ne HIV no kut h i ing ab a na ma nd la eku h lan gan en i ne minye imit h i no ma ezif e n i eziq ha mu ka ece le n i oba na zo . Sit ha nd a ukucwa n in ga ama - en za yimu ala nd e la yo : ? Cyto ch ro me P45 0 ? P - g lycop ro te in ? HLA exp ressio n ? Noma yilu ph i uph a wu lof uzo olu xhu men e ne HIV / A IDS , olun ga siza ekuq on d isisen i kab an zi nga le li gciwa ne nokwe la sh wa kwa lo ka n ye no ku vin je lwa kwa lo . Yo n ke imiph u me la ep ha th e le ne ne zimp a wu zof uzo izo ph a th wa ngo ku yimf ih lo fu th i izo kwa ziwa kup he la nge no mbo lo ya kho yo cwan ing o (h ha yi ng eg a ma la kh o ). 2 . Ng izozuza ni nga lolu cwa ningo ? Ung eke uth o le uku siza ka la oku qo nd ile ku lo lu cwan in go lwe zi m p a wu zof u zo . 3. Yiz iph i iz ingozi eziha mb i sa na nok uzok we nziw a ? Un g ab a no ku ph at he ka ka b i oku n ca ne kan ye no kuh u zu ka okun can e ku le yo nda wo oku th et h we kuyo isa mpu la le ga zi . 4 . Kuzok we nzek a ni kusa mpula le ga zi la mi ? A likh o elinye iga zi elizo d in ge ka. Ig a zi elin can e (e lin g ab a ngu - 4 ml) elizo t ha t h wa e ku zen i kwa kho emtho la mp ilo ng e viki 4 lizo se t sh en zise lwa uku cwan ing a izimp a wu zof u zo . 159 Appendix B: Informed consent for: Impact of Viral and Host Genetic Factors on Antiretroviral Treatment Outcome in South African HIV-1 subtype C infected AIDS patients Version 1.0 5 October 2006 Zulu Page 2 of 3 5 . Kuzok we nzek a ni uma ngiguqula umqondo wa mi ? Ukh u lu le kile uku t h i un ga gu qu la umqo ndo wa kho no ma nin i. Uma ugu qu la umqo nd o wa kh o ngo kuh lan ga n ye la , ung ah o xisa isa mpu la le g a zi lakho ng o kwe n za isice lo ku do ko te la/ u mh le ng ika zi obh e ke ne no cwa n in go . Lo kh u ku ng eke ku kh in y ab e ze ukwe lash wa kwa kho ku CIP RA no ma nga yiph i ind le la. 6 . Imin in ingwa ne i zogc inwa iy im fih lo yin i ? Konke oku th o la ke le ku lo lu cwa n in go ku zo g cinwa ku yimf ih lo ngo kwe migo mo elan de lwa nga ba cwan in g i kwe zo kwe lap ha eha mb isa na ne - In t e rna t ion a l Goo d Clin ica l Pra ct ice. 7 . Ng izoya zi yin i imiphu me l a ye ph r oj e k thi yoc waningo ? L e ph ro je kt h i ayen ziwa ng esikh at h i sa ng e mpe la , ko d wa uma imiph u me la itho la ka la ung a yi ce la kud o ko te la /u mh len g ika zi wa kho . Le mip h u me la in ga h le in ga b i wu sizo ku we, nge n xa yo ku th i ulwa zi oku xu t sh iwe lwa ba nt u ab an in g i luyad in ge ka uku bo na uma ama - e n za yimu eNin g izimu A frika en za umeh lu ko ekut h in i siyico zu lu la kan ja n i imit h i ye th u elwa ne HI V . Uzo kwa ziswa ng a yo yo n k e imiph u me la ya lo lon ke ucwa n ing o uma se lu ph e lile . 8. Yima phi ama lunge lo engina wo ? A b axha si bo cwan ing o ba ng e ke ba th en g ise no ma bed lu lise le ukub a ng ab an ika zi kwa ba n ye aba n tu . Ama sa mp u la azo se t sh en ziswa nga ba se be n zi be CIP RA - S A ku ph e la kan ye /n o ma aba cwan in g i aba seb en zisan a n e CIP RA - SA , fu t h i lo kho ku zo kwen ziwa ma ye lan a no cwa n ing o olu cha zwe nge nh la kup he la . UK UHL ANG ANY E L A K W AK HO K ULE PHRO J EKT HI YOCW ANI NG O KUNG O K UZI K HE T HE L A. UNG E NQ AB A UK UHL ANG ANYE L A K ULE PHRO J E KT HI YOCW ANI NG O UMA UT HAND A. 160 Appendix B: Informed consent for: Impact of Viral and Host Genetic Factors on Antiretroviral Treatment Outcome in South African HIV-1 subtype C infected AIDS patients Version 1.0 5 October 2006 Zulu Page 3 of 3 I NCW AD I ENIK A UB UF AK AZI B ALE MV UME : Uzo n ikezwa ikho ph i eyo d wa ya le ncwa d i yemvu me be se ku th i en ye ikh op h i ig cin we nje ng en gxen ye ya ma re kh od i ale ph ro je kth i yo ku cwan in ga , end a we n i eh lu kile ku ne min in ing wan e ezo th o laka la kup h ro je kth i yo kucwa n ing a. I - ID yoc wa ningo : Ama n i sha li : Usuk u lok uza lwa : Inombo lo yoc wa ningo : CIP R AZ A0 0 1 Is ih lok o se P hr oj ek thi yoc wa ningo : A ma nd la emip hu me la yo kwe lash wa nge mit h i elwa na ma g cin we ezimpa win i zof u zo eg ciwan en i na ku lo wo one g ciwa ne ezig u lin i za se Ning izimu Af rika ezine HIV - 1 sub t yp e C ezih la se lwe yiNg cu laza Ifo mu le mvu me Is ivu me l wa no sok uhla nga nye la oc wa ningwe ni lok we la pha Imvu me ya k ho Ama n i sha li es igu li 1 . Ng iya q in ise kisa uku th i ng ilif un d ile, ng a liq on d isisa ip he sha na le min in ing wan e yo ku h lo la izimpa wu zof u zo f ut h i ng ib e ne t hu ba lo ku bu za imib u zo . 2 . Ng iya qo nd isisa uku t h i uku h lan ga nye la kwa mi ku ng o ku zikhe th e la no kut h i ng ikh u lu le kile ukup huma no ma nin i, nga ph an d le ko ku n ika isizat hu , nan ga ph an d le ko ku t h i ukwe la sh wa kwa mi no ma ama lu ng e lo ami ngo ku se mt he t h we n i akh inyab e ze ke . 3 . Ng iya vu ma ukuh lan ga n ye la eph ro je kt h in i en ge nh la . Iga ma (p h r int h ): __ __ __ __ __ __ __ __ __ __ __ __ __ _ _ __ __ Usuk u _ _ ___ __ __ __ _ _ __ __ _ Kusa yina Isigu l i : ___ __ __ __ __ __ __ __ __ __ __ ___ __ __ Usuk u : __ __ __ __ __ __ __ __ _ Iga ma lo mse be nzi oc wa ningwe n i : _ __ __ __ __ ___ __ __ Usuk u : __ __ __ __ __ __ __ __ _ Kusa yina umse be nzi oc wa ningwe ni : _ _ __ __ ___ __ __ Usuk u _ _ ___ __ __ __ __ __ __ _ Ufa k a zi : _ __ __ __ __ __ __ __ ___ __ __ __ __ __ __ __ __ __ __ Usuk u : __ __ __ __ __ __ __ __ __ 161 Appendix B: Informed consent for: Impact of Viral and Host Genetic Factors on Antiretroviral Treatment Outcome in South African HIV-1 subtype C infected AIDS patients Version 1.0 5 October 2006 Sesotho Page 1 of 3 P RO JE KE 1 YA CIP R A YA T UME LLO E BONT SHA NG K UT LWIS IS O Leq ep he la Le sed i Fo ro mo ya Tu me llo S e hlooho sa Proje ke ya Diphuputso: Tsh u shu me t so ya Ko kwan ah lo ko le Diph a tsa tsa Lef u t so Diph e th on g tsa Ka laf o ka Me ria na e Lwa nt sh an g Kokwan ah lo ko ya HIV ho ba ku d i ba Af rika Bo rwa ba na ng le HIV - 1 su b t yp e C ba nan g le tsh wae t so AIDS P HUP UT S O YA D IP HAT S A T S A LE F UT S O Re la ka t sa ho etsa ge no t yp in g (ph up ut so ya dip ha t sa tsa lef ut so ) ka disa mp o le tsa ha o tsa ma d i. Re tla o bo le lla ho re na ho ame ha en g e le ho re o ka etsa qet o ya ho re na o ka du me la ho etswa dip hu pu t so tse na tsa diph a tsa tsa lef u t so ( ge no t yp in g ) . 1 . More r o wa phuputso ena ya dipha tsa tsa le futso ke ofe ? Hon a jwa le o ntse o nwa me rian a e lwan t sh an g kokwa na h loko ya HIV e le ka ro lo ya Pro je ke 1 ya CIP R A. Ho na le di - e n zyme (d ip rot he ine mme le ng , ha ng a ta di seb et en g ka pa ka ma len g ) tse th usan g ho sila mo ria na leh a e le ofe oo o o nwang , ho aka re lle t swa le me ria na e lwa n t sh an g ko kwan ah lo ko ya HIV . Di - en zyme tse na di a fap an a ba th on g ba mef u t a e sa tsh wan en g mme ha ho e so etswe dipa t lisiso tse ba tsi ka tson a ho Ma af rika Bo rwa . Ke hab oh lo kwa ho re re utlwisise ha eb a di - en zyme t sen a di f apa ne ho ba ah i ba hab o ron a kaha di ama tse la eo mme le ya rona e seb e t sa nan g le me rian a e sa tsh wan en g e lwan t sh an g ko kwan ah lo ko ya HIV mme di ka nn a tsa ama ka mo o me ria na ena e ken a ken ana ng le me ria n a e me ng ka pa dit la mo ra o tseo o ka ba ng le tso na . Re la ka t sa ho fu pu t sa di - e n zyme tse lat e la ng : ? Cyt o ch ro me P45 0 ? P - g lycop ro te in ? HL A exp re ssion ? P h at sa ya lef u t so efe kap a efe eo ho sen g ho ha t isit swe dit la le ho ka yo na e ama na ng le HIV /A IDS , e tla th u sa ho utlwisisa ko kwana h lo ko ena hah o lwan yane le ka laf o le th ibe lo . Dip h et ho tso h le tse aman an g le dip ha t sa tsa lef ut so di tla bo lo kwa e le le kun u tu mme di tla tse jwa fee la k a no mo ro ya hao ya pa t lisiso (mme e sen g ka le b it so la hao ). 2 . Ke una mole mo ofe ka ho nk a karolo phuputso ng ena ? O ke ke wa una me le mo ka ko t lo loho ka ho nka ka ro lo phu pu t so ng en a ya diph at sa tsa lef u t so . 3 . Ke dik otsi dife tse te ng tse ama na ng le me k gwa e se be diswa ng? O ka nna wa utlwa bo h loko bo bon ye n ya ne kap a wa pe t la han ye n ya ne moo disa mpo le tsa ma d i di nku wen g ten g. 162 Appendix B: Informed consent for: Impact of Viral and Host Genetic Factors on Antiretroviral Treatment Outcome in South African HIV-1 subtype C infected AIDS patients Version 1.0 5 October 2006 Sesotho Page 2 of 3 4 . Ho t la etsa ha la ng ka disa mpole tsa ma di a ka ? Ha ho na ma d i a ma ng a tla hlo kah a la . Ket e lon g ya be ke 4 ho tla nku wa mad i a m an yen yan e (h o o e ka ban g 4 ml) a tla seb ed iset swa ho hlah lob a diph a tsa tsa ha o tsa lef u t so. 5 . Ho t la etsa ha la ng hae ba ke fe tola mohopolo? O na le bo lo ko lo h i ba ho f et o la moh op o lo wa hao nen g ka pa nen g . Hae ba o f et o la moh op o lo wa ha o ma ba p i le ho nka ka ro lo dipa t lisison g tsena , o ka hu la disa mp o le tsa mad i a ha o ka ho di kop a ho nga ka/ moo ki wa dip a t lisiso . Ho han g sen a se ke ke sa ama ka laf o ya ha o ka CIP RA . 6 . Na le se di le o le tla bolok wa e le le k unutu? Dip h et ho tsoh le tse sibo llwan g ha ho etswa pa t lisiso ena di tla bo lo kwa e le le kun u tu ho la t e la me la o e la te lwa ng ke baf up ut si ba me ria na ba tsa ma isan an g le In t e rna t io na l Go od Clin ica l Pra ct ice. 7 . Na ke tla tse ba diphe tho tsa proj ek e ena phuputso? Patlisiso ena ha e etswe ka na ko e itse ng ka kot lo lo ho , empa ha dip he t ho di ntse di fu man eh a, o ka di ko pa ho nga ka/ mo o ki wa ha o. Dip he t ho tsen a di ka nn a tsa se o thu se ka le t ho , kah a ho hlo kaha la le sed i le kop an en g la ba th o ba ba ng at a ho bon a ha eb a di - e n zyme ho Ma af rika Bo rwa di fa pa ne tse le ng eo di sila ng ka te ng meria n a e lwan t sh an g ko kwan ah lo ko ya HIV . Ha n g ha pa t lisiso en a e fed ile o tla tse b iswa dip het h o tsa yon a kaof e la . 8 . Ditok e lo tsa ka di dif e ? Motsh e he t si wa pa t lisiso en a a ke ke a re kisa kapa a fe t ise t sa dit o ke lo tsa ho ba le disa mp o le tse na ho ba t sh eh e tsi ba ban g. Ke ba seb et si le/ka pa baf u pu t si ba CIP RA - S A fe e la ba tla se be d isa disa mp o le tsa ha o, mme e tla ba fe e la ba ke ng sa dip hu pu t so ts e hla lo sit swe ng ka hod imo mon a. HO NK A K ARO LO HA HAO PHUP UT S O NG ENA HO ETS W A K A BOIT HAO P O . O KA NNA W A HAN A HO KOP ANE L A PHUP UT S O ENA HAE B A O B AT L A. 163 Appendix B: Informed consent for: Impact of Viral and Host Genetic Factors on Antiretroviral Treatment Outcome in South African HIV-1 subtype C infected AIDS patients Version 1.0 5 October 2006 Sesotho Page 3 of 3 T O KO MANE YA T UME LLO ENA: O tla fu wa ko p i e nn g we ya to ko man e en a ya tume llo mme ko p i e nn g we e tla bo lo kwa e le ka ro lo ya dit la le ho tsa pro je ke en a ya phu pu t so , e aroh an e le le se d i le bo ke llwa ng pro je ke ng ena ya ph up ut so . ID ya Pa tli si so: Dit lha k u tsa pe le tsa ma bit so: Le tsa ts i la T swa lo: No mor o ya Phuputso: CIP R AZ A0 0 1 Se hlooho sa More r o wa Pa tlisi so: Tsh u sh u met so ya Ko kwana h lo ko le Diph at sa tsa Lef u t so Diph e th ong tsa Ka laf o ka Me ria na e Lwa n tsha ng Ko kwa na h lo ko ya HIV ho ba kud i ba Af rika Bo rwa ba na ng le HIV - 1 sub t ype C ba na n g le tsh wae t so AIDS For omo ya T ume llo T ume lla no ya ho nka ka rolo phuputsong ya tli l inik i T ume llo ya Ha o Dit lha k u tsa pe le tsa ma bit so a Moh la hlobu wa 1 . Ke tiisa ho re ke ba d ile mme ke utlwisisa leqe ph e la le se d i le ma b ap i le diph up ut so tse na tsa diph a t sa tsa lef ut so (gen o t yp ing ) mme ke bile le mon yet la wa ho bot sa dipo t so . 2 . Ke a utlwis isa ho re ke nka ka ro lo pat lisiso ng ena ka bo it ha opo le ho re ke na le bo lo ko lo h i ba ho ikgu la ne ng kap a ne ng , ho sa hlo kaha le ho re ke f an e ka ma ba ka , mme ho sa ame h e tlh o ko me lo ya ka ya tsa bo ng a ka kap a dit o ke lo tsa ka tsa mo la o 3 . Ke a du me la ho re ke nka ka ro lo pro jeken g e ka ho d imo Leb it so (p rin ta ): __ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Le t sa t si: __ _ _ _ _ _ _ _ _ _ _ _ _ _ E sae nn we ke Mo h la h lo bu wa : __ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Le t sa t si: __ _ _ _ _ _ _ _ _ _ _ _ _ _ Leb it so la mo if o wa Dipa t lisiso __ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Le t sa t si: __ _ _ _ _ _ _ _ _ _ _ _ _ _ E sae nn we ke mo if o wa Dip a t lisiso : __ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Le t sa t si: __ _ _ _ _ _ _ _ _ _ _ _ _ _ Paki __ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Le t sa t si: __ _ _ _ _ _ _ _ _ _ _ _ _ _ 164 APPENDIX C 165 International AIDS Society?USA Topics in HIV Medicine 138 Update of the Drug Resistance Mutations in HIV-1: December 2008 Victoria A. Johnson, MD, Fran?oise Brun-V?zinet, MD, PhD, Bonaventura Clotet, MD, PhD, Huldrych F. G?nthard, MD, Daniel R. Kuritzkes, MD, Deenan Pillay, MD, PhD, Jonathan M. Schapiro, MD, and Douglas D. Richman, MD The International AIDS Society?USA (IAS?USA) Drug Resistance Mutations Group reviews new data on HIV-1 drug resistance that have been published or presented at recent scientific meetings to maintain a current list of mutations associated with antiretroviral drug re- sistance. This December 2008 version of the IAS?USA drug resistance muta- tions figures updates those published in this journal in March/April 2008 (Johnson VA, Brun-V?zinet F, Clotet B, et al, Top HIV Med, 2008;16:62-68). The compilation includes mutations that may contribute to a reduced virologic response to HIV-1 drugs. It should not be assumed that the list presented here is exhaustive. Drugs that have been approved by the US Food and Drug Administration (US FDA) as well as any drugs available in expanded ac- cess programs are included and listed in alphabetical order by drug class. The figures are designed for practitioners to use in identifying key mutations as- sociated with viral resistance to anti- retroviral drugs and in making thera- peutic decisions. Updates are posted periodically at www.iasusa.org. For more in-depth reading and an exten- sive reference list, see the 2008 IAS? USA panel recommendations for re- sistance testing (Hirsch MS, Gunthard HF, Schapiro JM, et al, Clin Infect Dis, 2008:47:266-285). The mutations listed have been identified by 1 or more of the follow- ing criteria: (1) in vitro passage experi- ments or validation of contribution to resistance by using site-directed mutagenesis; (2) susceptibility testing of laboratory or clinical isolates; (3) nucleotide sequencing of viruses from patients in whom the drug is failing; (4) correlation studies between genotype at baseline and virologic response in patients exposed to a drug. The avail- ability of more recently approved drugs that cannot be tested as monotherapy precludes assessment of the impact of resistance on antiretroviral activity that is not seriously confounded by activity of other drug components in the background regimen. Readers are encouraged to consult the literature and experts in the field for clarification or more information about specific mutations and their clinical impact. Polymorphisms associated with im- paired treatment responses that occur in wild-type viruses should not be used in epidemiologic analyses to identify transmitted HIV-1 drug resistance. In the context of making clinical decisions regarding antiretroviral ther- apy, evaluating the results of HIV-1 ge- notypic testing includes: (1) assessing whether the pattern or absence of a pattern in the mutations is consistent with the patient?s antiretroviral therapy history; (2) recognizing that in the ab- sence of drug (selection pressure), re- sistant strains may be present at levels below the limit of detection of the test (analyzing stored samples, collected under selection pressure, could be use- ful in this setting); and (3) recognizing that virologic failure of the first regi- men typically involves HIV-1 isolates with resistance to only 1 or 2 of the drugs in the regimen (in this setting, resistance most commonly develops to lamivudine or the nonnucleoside ana- logue reverse transcriptase inhibitors [NNRTIs]). The absence of detectable viral resistance after treatment failure may result from any combination of the following factors: the presence of drug- resistant minority viral populations, nonadherence to medications, labora- tory error, lack of current knowledge of the association of certain mutations with drug resistance, the occurrence of relevant mutations outside the regions targeted by routine resistance assays, drug-drug interactions leading to sub- therapeutic drug levels, and possibly compartmental issues, indicating that drugs may not reach optimal levels in specific cellular or tissue reservoirs. Current Revision This December 2008 update includes several changes to the list of drug re- sistance mutations for HIV-1, as shown on the figure bars. For etravirine, 3 new mutations were added?K101H, E138A, and M230L?and the muta- tions at positions L100, K101, and Y181 were changed to boldface to indicate their newer categorization as more important mutations because they are sufficient on their own to confer partial Author Affiliations: Dr Johnson (Group Chair), Birmingham Veterans Affairs Medical Center and the University of Alabama at Birmingham School of Medicine, Birmingham, AL; Dr Brun-V?zinet, H?pital Bichat-Claude Bernard, Paris, France; Dr Clotet, HIV Unit, Hospital Universitari Germans Trias i Pujol and Fundacio irsiCAIXA, Barcelona, Spain; Dr G?nthard, University Hospital, Zurich, Switzerland; Dr Kuritzkes, Harvard Medical School and Brigham and Women?s Hospital, Boston, MA; Dr Pillay, Department of Infection, University College London, and Centre for Infections, Health Protection Agency, United Kingdom; Dr Schapiro, Sheba Medical Center, Tel Aviv, Israel; Dr Richman (Group Vice-Chair), Veterans Affairs San Diego Healthcare System and the University of California San Diego, San Diego, CA. Appendix C 166 139 Special Contribution ? December 2008 Resistance Mutations Volume 16 Issue 5 December 2008 reduction in virologic response based on weighting factors identified through correlations with phenotype (see User Note m). Changes to the figure bar for ritonavir-boosted darunavir include the removal of G73S and addition of L74P. For ritonavir-boosted tiprana- vir, the representations for 3 existing mutations?at positions I47, Q58, and T74?were changed to boldface. Fi- nally, the mutations Y143R/H/C were added to the raltegravir figure bar. The IAS?USA Drug Resistance Mu- tations Group also undertook a com- prehensive revision of the user notes. The information in each note was re- viewed and updated as necessary. The references were updated as needed; citations to full papers replaced those to abstract presentations whenever possible. Mutations Panel The authors comprise the IAS?USA Drug Resistance Mutations Group, an independent, volunteer panel of experts charged with the goal of delivering ac- curate, unbiased, and evidence-based information on these mutations to prac- titioners. As for all IAS?USA panels, a rotation procedure is in place whereby 1 or 2 panel members periodically step down from panel participation and new members join. These rotations are de- signed to ensure that all IAS?USA ex- pert panels remain diverse in member affiliations and areas of expertise. Comments The IAS?USA Drug Resistance Muta- tions Group welcomes comments on the mutations figures and user notes. Please send your evidence-based comments, including relevant refer- ence citations, to the IAS?USA at res- istance2009''at''iasusa.org or by fax at 415-544-9401. Please include your name and institution. Reprint Requests The Drug Resistance Mutations Group welcomes interest in the mutations figures as an educational resource for practitioners and encourages dissemi- nation of the material to as broad an audience as possible. However, permis- sion is required to reprint the figures and no alterations in the content can be made. If you wish to reprint the mutations figures, please send your re- quest to the IAS?USA via e-mail or fax (see above). To ensure the integrity of the mu- tations figures, IAS?USA policy is to grant permission for only minor, pre- approved adaptations of the figures (eg, an adjustment in size). Minimal adaptations only will be considered; no alterations of the content of the fig- ures or user notes will be permitted. Please note that permission will be granted only for requests to reprint or adapt the most current version of the mutations figures as they are posted on the Web site (www.iasusa.org). Be- cause scientific understanding of HIV drug resistance evolves rapidly and the goal of the Drug Resistance Mutations Group is to maintain the most up-to- date compilation of mutations for HIV clinicians and researchers, publication of out-of-date figures is counterproduc- tive. If you have any questions about re- prints or adaptations, please contact us. Financial Disclosures: The authors disclose the following affiliations with commercial organizations that may have interests related to the content of this article: Dr Brun-V?zi- net has received grants and research support from GlaxoSmithKline, Tibotec Therapeutics, has served as a consultant to Merck & Co, Inc, Monogram Biosciences, Inc, and Tibotec Therapeutics, and has served as a paid lec- turer for Bristol-Myers Squibb, GlaxoSmith- Kline, and Tibotec Therapeutics. Dr Clotet has served on scientific and marketing advi- sory boards and has received honoraria for lectures from Abbott Laboratories, Boehring- er Ingelheim Pharmaceuticals, Inc, Merck Sharp & Dohme, Bristol-Myers Squibb, Gil- ead Sciences, Inc, GlaxoSmithKline, Pana- cos Pharmaceuticals, Inc, Pfizer Inc, Roche Pharmaceuticals, and Tibotec Therapeutics. Dr G?nthard has served as a scientific and medical advisor for Abbott Laboratories, Bristol-Myers Squibb, Boehringer Ingelheim Pharmaceuticals, Inc, GlaxoSmithKline, No- vartis Pharmaceuticals Corp, and Tibotec Therapeutics and has received unrestricted research and travel grants from Abbott Labo- ratories, Boehringer Ingelheim Pharmaceu- ticals, Inc, Bristol-Myers Squibb, Gilead Sci- ences, Merck Sharp & Dohme, and Roche Pharmaceuticals. Dr Johnson has received grant and research support from Agouron Pharmaceuticals, Bristol-Myers Squibb, GlaxoSmithKline, Monogram Biosciences, Inc, and Visible Genetics, Inc (later Bayer, now Siemens Medical Solutions Diagnos- tics); has served on the speaker?s bureaus or received honoraria from Abbott Laboratories, GlaxoSmithKline, and Monogram Bioscienc- es, Inc; and has served on medical or clini- cal advisory boards of Bristol-Myers Squibb, GlaxoSmithKline, Monogram Biosciences, Inc, and Virco Lab, Inc. Dr Kuritzkes has served as a consultant to and has received honoraria from Abbott Laboratories, Avexa Ltd, Boehringer Ingelheim Pharmaceuticals, Inc, Bristol-Myers Squibb, Gilead Sciences, Inc, GlaxoSmithKline, Human Genome Sci- ences, Inc, Idenix Pharmaceuticals, Inc, Merck & Co, Inc, Monogram Biosciences, Inc, Pfizer Inc, Roche Pharmaceuticals, Schering- Plough Corp, Siemens, and Trimeris, Inc and has received research grant support from GlaxoSmithKline, Human Genome Sciences, Inc, Merck & Co, Inc, and Schering-Plough Corp. Dr Pillay has served as a consultant to Boehringer Ingelheim Pharmaceuticals, Inc, Bristol-Myers Squibb, Gilead Sciences, Inc, and Roche Pharmaceuticals. Dr Schapiro has served as a consultant, advisor, or speaker for Abbott Laboratories, Ambrilia Biophar- ma, Inc, Bristol-Myers Squibb, Boehringer Ingelheim Pharmaceuticals, Inc, Gilead Sci- ences, Inc, GlaxoSmithKline, Merck & Co, Inc, Monogram Biosciences, Inc, Pfizer Inc, Roche Pharmaceuticals, Siemens, Tibotec Therapeutics, Virco Lab, Inc, and Virology Education; and has received research sup- port from GlaxoSmithKline, Monogram Bio- sciences, Inc, Roche Pharmaceuticals, and Tibotec Therapeutics. Dr Richman has served as a consultant to Anadys Pharmaceuticals, Inc, Biota, Bristol-Myers Squibb, Gilead Sci- ences, Inc, Idenix Pharmaceuticals, Inc, Merck & Co, Inc, Monogram Biosciences, Inc, Pfizer Inc, Roche Pharmaceuticals, and Tobi- ra Therapeutics, Inc. The International AIDS Society?USA has received grants in the past 3 years for selected continuing medical edu- cation activities that are pooled (ie, no single company supports any single effort) from Abbott Laboratories, Boehringer Ingelheim Pharmaceuticals, Inc, Bristol-Myers Squibb, Gilead Sciences, Inc, GlaxoSmithKline, Merck & Co, Inc, Roche Pharmaceuticals, Tibotec Therapeutics, and Pfizer Inc. Funding/Support: This work was funded by the IAS?USA. No private sector or govern- ment funding was used to support the effort. Panel members are not compensated. Appendix C 167 International AIDS Society?USA Topics in HIV Medicine 140 MUTATIONS IN THE REVERSE TRANSCRIPTASE GENE ASSOCIATED WITH RESISTANCE TO REVERSE TRANSCRIPTASE INHIBITORS Nucleoside and Nucleotide Analogue Reverse Transcriptase Inhibitors (nRTIs)a Nonnucleoside Analogue Reverse Transcriptase Inhibitors (NNRTIs)a,l Multi-nRTI Resistance: 69 Insertion Complexb (affects all nRTIs currently approved by the US FDA) Multi-nRTI Resistance: 151 Complexc (affects all nRTIs currently approved by the US FDA except tenofovir) Multi-nRTI Resistance: Thymidine Analogue-associated Mutationsd,e (TAMs; affect all nRTIs currently approved by the US FDA) Abacavirf,g Didanosineg,h Emtricitabine Lamivudine Stavudined,e,i,j Tenofovirk Zidovudined,e,i,j Etravirinem Efavirenz Nevirapine M 41 L M 41 L D 67 N K 65 R L 74 V K 65 R K 65 R K 65 R K 65 R L 74 V Y 115 F M 184 V M 184 V I M 184 V I A 62 V A 62 V V 75 I F 77 L F 116 Y Q 151 M K 70 R K 70 R M 41 L D 67 N K 70 R K 70 E M 41 L D 67 N K 70 R L 210 W T 215 Y F K 219 Q E L 210 W T 215 Y F K 219 Q E L 210 W T 215 Y F V 106 I E 138 A K 103 N V 106 M V 108 I G 190 S A G 190 S A M 230 L L 100 I L 100 I A 98 G V 90 I Y 181 C I Y 188 L K 103 N V 106 A M V 108 I G 190 A L 100 I Y 181 C I Y 188 C L H P 225 H K 219 Q E L 210 W T 215 Y F K 219 Q E t 69 Insert Y 181 C I V V 179 D F T K 101 E H P Appendix C 168 141 Special Contribution ? December 2008 Resistance Mutations Volume 16 Issue 5 December 2008 MUTATIONS IN THE PROTEASE GENE ASSOCIATED WITH RESISTANCE TO PROTEASE INHIBITORSn,o,p Atazanavir +/? ritonavirq Fosamprenavir/ ritonavir Darunavir/ ritonavirr Indinavir/ ritonavirs Lopinavir/ ritonavirt Nelfinavirs,u Saquinavir/ ritonavirs Tipranavir/ ritonavirv L 10 I F V C G 16 E K 20 R M I T V L 24 I V 32 I L 33 I F V L 33 F E 34 Q M 36 I L V M 46 I L G 48 V F 53 L Y D 60 E I 62 V I 54 L V M T A I 64 L M V A 71 V I T L G 73 C S T A V 82 A T F I I 93 L M I 85 V L 90 M I 84 V L 10 V I 13 V K 20 M R L 33 F E 35 G M 36 I M 46 L I 47 V K 43 T I 54 A M V Q 58 E H 69 K T 74 P V 82 L T N 83 D L 90 M I 84 V L 10 I R V L 24 I G 48 V I 62 V I 54 V L A 71 V T G 73 S V 77 I V 82 A F T S L 90 M I 84 V N 88 S L 10 F I D 30 N M 36 I M 46 I L A 71 V T V 77 I V 82 A F T S L 90 M I 84 V N 88 D S I 50 L L 10 F I R V K 20 M R L 24 I V 32 I L 33 F M 46 I L I 47 V A F 53 L I 54 V L A M T S L 63 P A 71 V T G 73 S V 82 A F T S L 90 M I 84 V I 50 V L 10 I R V K 20 M R L 24 I V 32 I M 36 I M 46 I L I 54 V A 71 V T G 73 S A V 77 I V 82 A F T L 90 M I 84 V L 10 F I R V V 32 I M 46 I L I 47 V I 54 L V M G 73 S V 82 A F S T L 90 M I 84 V I 50 V V 11 I V 32 I I 47 V I 54 M L T 74 P L 76 V L 76 V L 89 V I 84 V I 50 V L 76 V L 76 V MUTATIONS IN THE INTEGRASE GENE ASSOCIATED WITH RESISTANCE TO INTEGRASE INHIBITORS Raltegraviry N 155 H MUTATIONS IN THE ENVELOPE GENE ASSOCIATED WITH RESISTANCE TO ENTRY INHIBITORS Enfuvirtidew Maravirocx Q 148 H K R Y 143 R H C G 36 D S V 38 A M E Q 39 R Q 40 H N 42 T N 43 D I 37 V See User Note 90 54 L t M Amino acid, wild-type Amino acid position Major (boldface type; protease only)o Amino acid substitution conferring resistance Minor (lightface type; protease only)o Insertion MUTATIONS Amino acid abbreviations: A, alanine; C, cysteine; D, aspartate; E, glutamate; F, phenylalanine; G, glycine; H, histidine; I, isoleucine; K, lysine; L, leucine; M, methionine; N, asparagine; P, proline; Q, glutamine; R, arginine; S, serine; T, threonine; V, valine; W, tryptophan; Y, tyrosine. Appendix C 169 International AIDS Society?USA Topics in HIV Medicine 142 User Notes a. Numerous nucleoside (or nucleotide) analogue reverse transcriptase inhibitor (nRTI) mutations, like M41L, L210W, and T215Y, may lead to viral hypersuscepti- bility to the nonnucleoside analogue re- verse transcriptase inhibitors (NNRTIs), including etravirine,1 in nRTI-treated individuals. The presence of these muta- tions may improve subsequent virologic response to NNRTI-containing regimens (nevirapine or efavirenz) in NNRTI-naive individuals2-6 or with etravirine in some NNRTI-experienced individuals. b. The 69 insertion complex consists of a substitution at codon 69 (typically T69S) and an insertion of 2 or more amino acids (S-S, S-A, S-G, or others). The 69 insertion complex is associated with re- sistance to all nRTIs currently approved by the US FDA when present with 1 or more thymidine analogue?associated mutations (TAMs) at codons 41, 210, or 215.7 Some other amino acid changes from the wild-type T at codon 69 with- out the insertion may be associated with broad nRTI resistance. c. Tenofovir retains activity against the Q151M complex of mutations.7 d. Mutations known to be selected by thy- midine analogues (M41L, D67N, K70R, L210W, T215Y/F, and K219Q/E, termed TAMS) also confer reduced susceptibil- ity to all approved nRTIs.8 The degree to which cross-resistance is observed depends on the specific mutations and number of mutations involved.9-12 Muta- tions at the C-terminal reverse transcrip- tase domains (amino acids 293?560) outside of regions depicted on the figure bars may prove to be important for HIV-1 drug resistance. The clinical relevance of these in vitro findings remains unclear, and there is yet no evidence that they have a substantial impact in the absence of other, established mutations. Thus, they are not depicted on the figure bars. e. The E44D and the V118I mutations increase the level of resistance to zid- ovudine and stavudine in the presence of TAMs and correspondingly increase cross-resistance to other nRTIs. Their presence in the absence of other key mutations does not substantially alter resistance.13,14 Furthermore, V118I alone does not compromise response to nRTI- containing regimens.15 f. The M184V mutation alone does not appear to be associated with a reduced virologic response to abacavir in vivo.16,17 When present with 2 or 3 TAMs, M184V contributes to reduced susceptibility to abacavir and is associated with im- paired virologic response in vivo.17 The M184V mutation plus 4 or more TAMs results in no virologic response to abaca- vir in vivo.17 Slightly increased treatment responses to tenofovir are observed if M184V is present.7 g. The K65R mutation may be selected by didanosine or abacavir and is asso- ciated with decreased susceptibility to these drugs.16,18,19 The impact of K65R on clinical response to didanosine-con- taining triple-drug regimens remains un- clear. h. The presence of 3 of the following mu- tations?M41L, D67N, L210W, T215Y/F, K219Q/E?is associated with resistance to didanosine.20 The presence of K70R or M184V alone does not decrease virologic response to didanosine.21 i. The presence of M184V appears to de- lay or prevent emergence of TAMs.22 This effect may be overcome by an accumu- lation of TAMs or other mutations. j. The T215A/C/D/E/G/H/I/L/N/S/V substi- tutions are revertant mutations at codon 215 that confer increased risk of viro- logic failure of zidovudine or stavudine in antiretroviral-naive patients.23-25 The T215Y mutant may emerge quickly from 1 of these mutations in the presence of zidovudine or stavudine.26,27 k. The presence of K65R is associated with a reduced virologic response to te- nofovir.7 A reduced response also occurs in the presence of 3 or more TAMs inclu- sive of either M41L or L210W.7 Slightly in- creased treatment responses to tenofovir are observed when M184V is present.7 l. The sequential use of nevirapine and efavirenz (in either order) is not recom- mended because of cross-resistance be- tween these drugs.28 m. Resistance to etravirine has been extensively studied only in the context of coadministration with darunavir/rito- navir. In this context, mutations associ- ated with virologic outcome have been assessed and their relative weights (or magnitudes of impact) assigned. In ad- dition, phenotypic cutoff values have been calculated, and assessment of genotype-phenotype correlations from a large clinical database have determined relative importance of the various muta- tions. These 2 approaches are in agree- ment for many, but not all, mutations and weights.29-31 The single mutations Y181C/I/V, K101P, and L100I reduce but do not preclude clinical utility. The pres- ence of K103N does not affect etravirine response.32 Accumulation of several mutations results in greater reductions in susceptibility and virologic response than do single mutations.33 n. Often, numerous mutations are nec- essary to substantially impact virologic response to a ritonavir-boosted protease inhibitor (PI).34 When used as unboosted The International AIDS Society?USA (IAS?USA) Drug Resistance Mutations Group reviews new data on HIV-1 drug resistance that have been published or presented at recent scientific meetings to maintain a current list of mutations associated with antiretroviral drug resistance. The compilation includes mutations that may contribute to a reduced virologic response to HIV-1 drugs. It should not be assumed that the list presented here is exhaustive. Drugs that have been approved by the US Food and Drug Administration (FDA) as well as any drugs available in expanded access programs are included and listed in alphabetic order by drug class. The mutations listed have been identified by 1 or more of the following criteria: (1) in vitro passage experiments or validation of contribution to resistance by using site-directed mutagenesis; (2) susceptibility testing of laboratory or clinical isolates; (3) nucleotide sequencing of viruses from patients in whom the drug is failing; (4) correlation studies between genotype at baseline and virologic response in patients exposed to a drug. The availability of more recently approved drugs that cannot be tested as monotherapy precludes assessment of the impact of resistance on antiretroviral activity that is not seriously confounded by activity of other drug components in the background regimen. Readers are encouraged to consult the literature and experts in the field for clarification or more information about specific mutations and their clinical impact. Polymorphisms associated with impaired treatment responses that occur in wild-type viruses should not be used in epidemiologic analyses to identify transmitted HIV-1 drug resistance. Appendix C 170 143 Special Contribution ? December 2008 Resistance Mutations Volume 16 Issue 5 December 2008 agents, atazanavir, fosamprenavir, and saquinavir generally select the same mutations as the ritonavir-boosted drug regimen, although the relative frequency of mutations may differ. o. Resistance mutations in the protease gene are classified as ?major? or ?mi- nor.? Major mutations in the protease gene are defined as those selected first in the presence of the drug or those substantially reducing drug susceptibility. These mutations tend to be the primary contact residues for drug binding. Minor mutations generally emerge later than major mutations and by themselves do not have a sub- stantial effect on phenotype. They may improve replication of viruses containing major mutations. Some minor mutations are present as common polymorphic changes in HIV-1 nonsubtype-B clades. p. Ritonavir is not listed separately, as it is currently used only at low dose as a pharmacologic booster of other PIs. q. Many mutations are associated with atazanavir resistance. Their impacts dif- fer, with I50L, I84V, and N88S having the greatest effect. Higher atazanavir levels obtained with ritonavir boosting increase the number of mutations re- quired for loss of activity. The presence of M46I + L76V might increase suscep- tibility to atazanavir.35 r. Ritonavir-boosted darunavir correlates with baseline susceptibility and the pres- ence of several specific PI mutations. Re- ductions in response are associated with increasing numbers of the mutations in- dicated in the figure bar. Some of these mutations appear to have a greater ef- fect on susceptibility than others (eg, I50V vs V11I). A median darunavir phe- notypic fold-change greater than 10 (low clinical cutoff) occurs with 3 or more of the 2007 IAS?USA mutations listed for darunavir36 and is associated with a di- minished virologic response.37 s. The mutations depicted on the figure bar cannot be considered comprehen- sive because little relevant research has been reported in recent years to update the resistance and cross-resistance pat- terns for this drug. t. In PI-experienced patients, the accu- mulation of 6 or more of the mutations indicated on the figure bar is associ- ated with a reduced virologic response to lopinavir/ritonavir.38,39 The product information states that accumulation of 7 or 8 mutations confers resistance to the drug.40 However, there is emerging evidence that specific mutations, most notably I47A (and possibly I47V) and V32I, are associated with high-level re- sistance.41-43 The addition of L76V to 3 PI resistance?associated mutations sub- stantially increases resistance to lopina- vir/ritonavir.35 u. In some nonsubtype-B HIV-1, D30N is selected less frequently than are other PI mutations.44 v. Clinical correlates of resistance to tipranavir are limited by the paucity of clinical trials and observational studies of the drug. Lists of mutations associ- ated with accumulating resistance have been presented, with some conflicting results. In vitro studies and initial analy- sis of clinical data show mutations L33F, V82L/T, and I84V as having substantial contributions. Confirmatory studies are pending. A number of mutations (L24I, I50L/V, I54L, and L76V) are associated with decreased resistance in vitro and improved short-term virologic response if 2 or more are present. w. Resistance to enfuvirtide is associat- ed primarily with mutations in the first heptad repeat (HR1) region of the gp41 envelope gene. However, mutations or polymorphisms in other regions of the envelope (eg, the HR2 region or those yet to be identified) as well as corecep- tor usage and density may affect suscep- tibility to enfuvirtide.45-47 x. Maraviroc activity is limited to pa- tients with virus that uses only the CC chemokine receptor 5 (CCR5) for entry (R5 virus); viruses that use both CCR5 and the CXC chemokine receptor 4 (CXCR4) (termed dual/mixed or D/M) or only CXCR4 (X4) do not respond to maraviroc treatment. Virologic failure with maraviroc therapy frequently is associated with outgrowth of X4 virus that preexisted as a minority popula- tion below the level of assay detection. Mutations in the HIV-1 gp120 molecule that allow the virus to bind to the mara- viroc-bound form of CCR5 have been described in viruses from some patients whose virus remained R5 at the time of virologic failure. The resistance profile for maraviroc is too complex to be de- picted on the figure bar. The frequency and rate at which maraviroc resistance mutations emerge are not yet known. y. Raltegravir failure is associated with integrase mutations in at least 3 distinct genetic pathways defined by 2 or more mutations including (1) a signature (ma- jor) mutation at Q148H/K/R, N155H, or Y143R/H/C; and (2) 1 or more addi- tional minor mutations. Minor muta- tions described in the Q148H/K/R path- way include L74M + E138A, E138K, or G140S. The most common mutational pattern in this pathway is Q148H + G140S, which also confers the greatest loss of drug susceptibility. Mutations de- scribed in the N155H pathway include this major mutation plus either L74M, E92Q, T97A, E92Q + T97A, Y143H, G163K/R, V151I, or D232N.48 The Y143R/H/C mutation is uncommon.49-53 References to the User Notes 1. Picchio G, Vingerhoets J, Parkin N, Azijn H, de Bethune MP. Nucleoside-asso- ciated mutations cause hypersusceptibility to etravirine. [Abstract 23.] Antivir Ther. 2008;13(Suppl 3):A25. 2. Shulman NS, Bosch RJ, Mellors JW, Al- brecht MA, Katzenstein DA. Genetic cor- relates of efavirenz hypersusceptibility. AIDS. 2004;18:1781-1785. 3. Demeter LM, DeGruttola V, Lustgarten S, et al. Association of efavirenz hypersus- ceptibility with virologic response in ACTG 368, a randomized trial of abacavir (ABC) in combination with efavirenz (EFV) and indinavir (IDV) in HIV-infected subjects with prior nucleoside analog experience. HIV Clin Trials. 2008;9:11-25. 4. Haubrich RH, Kemper CA, Hellmann NS, et al. The clinical relevance of non- nucleoside reverse transcriptase inhibitor hypersusceptibility: a prospective cohort analysis. AIDS. 2002;16:F33-F40. 5. Tozzi V, Zaccarelli M, Narciso P, et al. Mu- tations in HIV-1 reverse transcriptase po- tentially associated with hypersusceptibil- ity to nonnucleoside reverse-transcriptase inhibitors: effect on response to efavirenz- based therapy in an urban observational cohort. J Infect Dis. 2004;189:1688-1695. 6. Katzenstein DA, Bosch RJ, Hellmann N, et al. Phenotypic susceptibility and viro- logical outcome in nucleoside-experienced patients receiving three or four antiretrovi- ral drugs. AIDS. 2003;17:821-830. 7. Miller MD, Margot N, Lu B, et al. Ge- notypic and phenotypic predictors of the magnitude of response to tenofovir disoproxil fumarate treatment in antiret- roviral-experienced patients. J Infect Dis. 2004;189:837-846. Appendix C 171 International AIDS Society?USA Topics in HIV Medicine 144 8. Whitcomb JM, Parkin NT, Chappey C, Hellman NS, Petropoulos CJ. Broad nucle- oside reverse-transcriptase inhibitor cross- resistance in human immunodeficiency virus type 1 clinical isolates. J Infect Dis. 2003;188:992-1000. 9. Larder BA, Kemp SD. Multiple muta- tions in HIV-1 reverse transcriptase confer high-level resistance to zidovudine (AZT). Science. 1989;246:1155-1158. 10. Kellam P, Boucher CA, Larder BA. Fifth mutation in human immunodeficiency vi- rus type 1 reverse transcriptase contrib- utes to the development of high-level re- sistance to zidovudine. Proc Natl Acad Sci USA. 1992;89:1934-1938. 11. Calvez V, Costagliola D, Descamps D, et al. Impact of stavudine phenotype and thymidine analogues mutations on viral response to stavudine plus lamivu- dine in ALTIS 2 ANRS trial. Antivir Ther. 2002;7:211-218. 12. Kuritzkes DR, Bassett RL, Hazelwood JD, et al. Rate of thymidine analogue resis- tance mutation accumulation with zidovu- dine- or stavudine-based regimens. JAIDS. 2004;36:600-603. 13. Romano L, Venturi G, Bloor S, et al. Broad nucleoside-analogue resistance im- plications for human immunodeficiency virus type 1 reverse-transcriptase muta- tions at codons 44 and 118. J Infect Dis. 2002;185:898-904. 14. Walter H, Schmidt B, Werwein M, Schwingel E, Korn K. Prediction of abaca- vir resistance from genotypic data: impact of zidovudine and lamivudine resistance in vitro and in vivo. Antimicrob Agents Che- mother. 2002;46:89-94. 15. Mihailidis C, Dunn D, Pillay D, Poz- niak A. Effect of isolated V118I muta- tion in reverse transcriptase on response to first-line antiretroviral therapy. AIDS. 2008;22:427-430. 16. Harrigan PR, Stone C, Griffin P, et al. Resistance profile of the human immuno- deficiency virus type 1 reverse transcrip- tase inhibitor abacavir (1592U89) after monotherapy and combination therapy. CNA2001 Investigative Group. J Infect Dis. 2000;181:912-920. 17. Lanier ER, Ait-Khaled M, Scott J, et al. Antiviral efficacy of abacavir in antiretrovi- ral therapy-experienced adults harbouring HIV-1 with specific patterns of resistance to nucleoside reverse transcriptase inhibi- tors. Antivir Ther. 2004;9:37-45. 18. Winters MA, Shafer RW, Jellinger RA, Mamtora G, Gingeras T, Merigan TC. Human immunodeficiency virus type 1 reverse transcriptase genotype and drug susceptibility changes in infected indi- viduals receiving dideoxyinosine mono- therapy for 1 to 2 years. Antimicrob Agents Chemother. 1997;41:757-762. 19. Svarovskaia ES, Margot NA, Bae AS, et al. Low-level K65R mutation in HIV-1 reverse transcriptase of treatment-experi- enced patients exposed to abacavir or di- danosine. JAIDS. 2007;46:174-180. 20. Marcelin AG, Flandre P, Pavie J, et al. Clinically relevant genotype interpretation of resistance to didanosine. Antimicrob Agents Chemother. 2005;49:1739-1744. 21. Molina JM, Marcelin AG, Pavie J, et al. Didanosine in HIV-1-infected patients ex- periencing failure of antiretroviral therapy: a randomized placebo-controlled trial. J In- fect Dis. 2005;191:840-847. 22. Kuritzkes DR, Quinn JB, Benoit SL, et al. Drug resistance and virologic response in NUCA 3001, a randomized trial of la- mivudine versus zidovudine versus zid- ovudine plus lamivudine in previously un- treated patients. AIDS. 1996;10:975-981. 23. Riva C, Violin M, Cozzi-Lepri A, et al. Transmitted virus with substitutions at po- sition 215 and risk of virological failure in antiretroviral-naive patients starting high- ly active antiretroviral therapy. [Abstract 124.] Antivir Ther. 2002;7:S103. 24. Chappey C, Wrin T, Deeks S, Petro- poulos CJ. Evolution of amino acid 215 in HIV-1 reverse transcriptase in response to intermittent drug selection. [Abstract 32.] Antivir Ther. 2003;8:S37. 25. Violin M, Cozzi-Lepri A, Velleca R, et al. Risk of failure in patients with 215 HIV- 1 revertants starting their first thymidine analog-containing highly active antiretro- viral therapy. AIDS. 2004;18:227-235. 26. Garcia-Lerma JG, MacInnes H, Ben- nett D, Weinstock H, Heneine W. Transmit- ted human immunodeficiency virus type 1 carrying the D67N or K219Q/E mutation evolves rapidly to zidovudine resistance in vitro and shows a high replicative fit- ness in the presence of zidovudine. J Virol. 2004;78:7545-7552. 27. Lanier ER, Ait-Khaled M, Craig C, Scott J, Vavro C. Effect of baseline 215D/C/S ?re- vertant? mutations on virological response to lamivudine/zidovudine-containing regi- mens and emergence of 215Y upon viro- logical failure. [Abstract 146.] Antivir Ther. 2002;7:S120. 28. Antinori A, Zaccarelli M, Cingolani A, et al. Cross-resistance among nonnucleo- side reverse transcriptase inhibitors limits recycling efavirenz after nevirapine failure. AIDS Res Hum Retroviruses. 2002;18:835- 838. 29. Benhamida J, Chappey C, Coakley E, Parkin NT. HIV-1 genotype algorithms for prediction of etravirine susceptibility: nov- el mutations and weighting factors iden- tified through correlations to phenotype. [Abstract 130.] Antivir Ther. 2008;13(Sup- pl 3):A142. 30. Coakley E, Chappey C, Benhamida J, et al. Biological and clinical cut-off analyses for etravirine in the PhenoSense HIV assay. [Abstract 122.] Antivir Ther. 2008;13(Suppl 3):A134. 31. Peeters M, Nijs S, Vingerhoets J, et al. Determination of phenotypic clinical cut- offs for etravirine: pooled week 24 results of the DUET-1 and DUET-2 trials. [Abstract 121.] Antivir Ther. 2008;13(Suppl 3):A133. 32. Etravirine [package insert]. Bridgewa- ter, NJ: Tibotec Therapeutics; 2008. 33. Vingerhoets J, Peeters M, Azijn H, et al. An update of the list of NNRTI muta- tions associated with decreased virologi- cal response to etravirine: multivariate analyses on the pooled DUET-1 and DUET- 2 clinical trial data. [Abstract 24.] Antivir Ther. 2008;13(Suppl 3):A26. 34. Hirsch MS, Gunthard HF, Schapiro JM, et al. Antiretroviral drug resistance testing in adult HIV-1 infection: 2008 recommenda- tions of an International AIDS Society-USA panel. Clin Infect Dis. 2008;47:266-285. 35. Norton M, Young T, Parkin N, et al. Prevalence, mutational patterns, and phe- notypic correlates of the L76V protease mutation in relation to LPV-associated mu- tations. [Abstract 854.] 15th Conference on Retroviruses and Opportunistic Infec- tions. February 3-6, 2008; Boston, MA. 36. Johnson VA, Brun-V?zinet F, Clotet B, et al. Update of the drug resistance mutations in HIV-1: 2007. Top HIV Med. 2007;15:119-125. 37. De Meyer S, Dierynck I, Lathouwers E, et al. Phenotypic and genotypic determi- nants of resistance to darunavir: analysis of data from treatment-experienced pa- tients in POWER 1, 2, 3 and DUET-1 and 2. [Abstract 31.] Antivir Ther. 2008;13(Suppl 3):A33. 38. Masquelier B, Breilh D, Neau D, et al. Human immunodeficiency virus type 1 genotypic and pharmacokinetic determi- nants of the virological response to lopina- vir-ritonavir-containing therapy in protease inhibitor-experienced patients. Antimicrob Agents Chemother. 2002;46:2926-2932. Appendix C 172 145 Special Contribution ? December 2008 Resistance Mutations Volume 16 Issue 5 December 2008 39. Kempf DJ, Isaacson JD, King MS, et al. Identification of genotypic changes in human immunodeficiency virus protease that correlate with reduced susceptibility to the protease inhibitor lopinavir among viral isolates from protease inhibitor-ex- perienced patients. J Virol. 2001;75:7462- 7469. 40. Lopinavir/ritonavir [package insert]. Abbott Park, IL: Abbott Laboratories; 2008. 41. Mo H, King MS, King K, Molla A, Brun S, Kempf DJ. Selection of resistance in pro- tease inhibitor-experienced, human im- munodeficiency virus type 1-infected sub- jects failing lopinavir- and ritonavir-based therapy: mutation patterns and baseline correlates. J Virol. 2005;79:3329-3338. 42. Friend J, Parkin N, Liegler T, Martin JN, Deeks SG. Isolated lopinavir resis- tance after virological rebound of a rito- navir/lopinavir-based regimen. AIDS. 2004;18:1965-1966. 43. Kagan RM, Shenderovich M, Heseltine PN, Ramnarayan K. Structural analysis of an HIV-1 protease I47A mutant resistant to the protease inhibitor lopinavir. Protein Sci. 2005;14:1870-1878. 44. Gonzalez LMF, Brindeiro RM, Aguiar RS, et al. Impact of nelfinavir resistance mutations on in vitro phenotype, fitness and replication capacity of HIV-1 with sub- type B and C proteases. [Abstract 56.] An- tivir Ther. 2004;9:S65. 45. Reeves JD, Gallo SA, Ahmad N, et al. Sensitivity of HIV-1 to entry inhibitors cor- relates with envelope/coreceptor affinity, receptor density, and fusion kinetics. Proc Natl Acad Sci USA. 2002;99:16249-16254. 46. Reeves JD, Miamidian JL, Biscone MJ, et al. Impact of mutations in the coreceptor binding site on human immunodeficiency virus type 1 fusion, infection, and entry inhibitor sensitivity. J Virol. 2004;78:5476- 5485. 47. Xu L, Pozniak A, Wildfire A, et al. Emergence and evolution of enfuvirtide resistance following long-term therapy involves heptad repeat 2 mutations with- in gp41. Antimicrob Agents Chemother. 2005;49:1113-1119. 48. Hazuda DF, Miller MD, Nguyen BY, Zhao J, for the P005 Study Team. Resis- tance to the HIV-integrase inhibitor ralte- gravir: analysis of protocol 005, a phase II study in patients with triple-class resis- tant HIV-1 infection. Antivir Ther. 2007;12: S10. 49. Miller MD, Danovich RM, Ke Y, et al. Longitudinal analysis of resistance to the HIV-1 integrase inhibitor raltegravir: re- sults from P005 a phase II study in treat- ment-experienced patients. [Abstract 6.] Antivir Ther. 2008;13:A8. 50. Fransen S, Gupta S, Danovich R, et al. Loss of raltegravir susceptibility in treated patients is conferred by multiple non-over- lapping genetic pathways. [Abstract 7.] Antivir Ther. 2008;13:A9. 51. Hatano H, Lampiris H, Huang W, et al. Virological and immunological outcomes in a cohort of patients failing integrase inhibitors. [Abstract 10.] Antivir Ther. 2008;13:A12. 52. Da Silva D, Pellegrin I, Anies G, et al. Mutational patterns in the HIV-1 integrase related to virological failures on raltegra- vir-containing regimens. [Abstract 12.] Antivir Ther. 2008;13:A14. 53. Ceccherini-Silberstein F, Armenia D, D?Arrigo R, et al. Virological response and resistance in multi-experienced patients treated with raltegravir. [Abstract 18.] An- tivir Ther. 2008;13:A20. Top HIV Med. 2008;16(5):138-145 ? 2008, International AIDS Society?USA Appendix C 173 APPENDIX D 174 Ta bl e D .1 : V ir al L oa ds , S equ en ce S im ila ri ty , M ut at io n Pa tt er ns a nd S ub ty pe s of th e 90 s am pl es u se d in th e H IV -1 A R V d ru g re si st an ce in -h ou se v al id at io n. T he y el lo w hi gh lig ht ed s am pl es h av e di ff er en t m ut at io n pa tt er ns f or V ir oS eq a nd th e in -h ou se a ss ay . T he p ur pl e hi gh lig ht ed s am pl es f ai le d to a m pl if y on V ir oS eq . P at ie nt N am e V ir al L oa d Se que nc e Si m il ar it y M utat io n P att er n P I- M aj or P I- M in or N R T I N N R T I Su bty pe V A L00 1 150 0 93 .6 5 sa m e A 62 V , M 184 V K 103 N , G 190 A C V A L00 2 1000 0 98 .9 2 V S T 21 5I /T D 67 G ,K 70 R , M 184 V , K 219 Q V 106 M , V 179 D C V A L00 3 3600 0 99 .4 5 V S V 108I /V D 67 N , K 70 R , M 184 V , K 21 9E A 98 G , K 103 N , V 106 M , Y 188 C C V A L00 4 7700 0 98 .5 V S V 108I /V T 74 S M 184 V K 103 N , P 225 H C V A L00 5 30000 0 99 .1 1 V S L 100I /L L 10 I K 103 N , V 106 M C V A L00 6 130 0 99 .2 8 sa m e D 67 N , K 70 R , K 21 9E K 103 N , V 106 M C V A L00 7 160 0 99 .7 7 sa m e K 103 N C V A L00 8 170 0 98 .8 1 sa m e D 67 N , K 70 R , M 184 V K 103 N , G 190 A C V A L00 9 200 0 99 .1 3 sa m e T 74 S M 184 V K 103 N , V 106 M C V A L01 0 250 0 99 .2 sa m e M 184 V V 106 M , Y 188 L C V A L01 1 390 0 98 .5 3 sa m e C V A L01 2 390 0 10 0 sa m e M 46I , I84 V L 10 F C V A L01 3 390 0 99 .3 8 sa m e M 184 V K 103 N C V A L01 4 430 0 99 .3 sa m e L 10 V , T 74 S M 184 V K 101 E , K 10 3R , V 106 M , G 190 A C V A L01 5 520 0 99 .1 3 sa m e A 62 V ,M 184 V K 101 E , V 10 6M C V A L01 6 540 0 99 .9 2 sa m e M 184 V Y 188 L C V A L01 7 550 0 99 .6 1 sa m e M 184 V , T 21 5Y G 190 S, M 230 L C V A L01 8 590 0 99 .4 5 sa m e M 184 V V 90I , K 10 1E , Y 181 C C V A L01 9 680 0 99 .7 6 sa m e D 67 N , M 184 V V 106 M , Y 188 C C V A L02 0 800 0 99 .2 3 sa m e D 67 N , T 69 N , K 70 R , V 11 8I , M 184 V , T 21 5F , K 219 Q A 98 G , K 101 E , K 103 R , V 106 M , F 227 L C V A L02 1 870 0 99 .8 4 sa m e M 184 V K 103 N C V A L02 2 970 0 99 .2 1 sa m e L 74 V , M 184 V K 103 N , P 225 H C V A L02 3 1000 0 99 .4 5 sa m e M 184 V K 103 N , Y 181 C C V A L02 4 1100 0 99 .3 4 sa m e M 184 V K 103 N , V 108 I C V A L02 5 1100 0 99 .6 8 sa m e M 184 V , T 21 5Y Y 181C C 175 Ta bl e D .1 : V ir al L oa ds , S equ en ce S im ila ri ty , M ut at io n Pa tt er ns a nd S ub ty pe s of th e 90 s am pl es u se d in th e H IV -1 A R V d ru g re si st an ce in -h ou se v al id at io n. T he y el lo w hi gh lig ht ed s am pl es h av e di ff er en t m ut at io n pa tt er ns f or V ir oS eq a nd th e in -h ou se a ss ay . T he p ur pl e hi gh lig ht ed s am pl es f ai le d to a m pl if y on V ir oS eq . P at ie nt N am e V ir al L oa d Se que nc e Si m il ar it y M utat io n P att er n P I- M aj or P I- M in or N R T I N N R T I Su bty pe V A L02 6 1200 0 99 .4 5 sa m e D 67 N , K 70 E , M 184 V V 106 M , H 221 Y , F 227 L C V A L02 7 1200 0 99 .7 7 sa m e K 70 R , M 184 V K 103 R , V 106 M , V 179 D C V A L02 8 1300 0 99 .7 5 sa m e L 23 F M 184 V K 103 N , V 108 I C V A L02 9 1400 0 99 .8 4 sa m e M 184 V V 108I , Y 181 C , H 221 Y C V A L03 0 1500 0 98 .7 2 sa m e M 184 V V 106 M , Y 188 L C V A L03 1 1900 0 99 .5 3 sa m e M 184 V , T 21 5F K 103 N , V 108 I C V A L03 2 1900 0 99 .2 9 sa m e C V A L03 3 2100 0 99 .3 6 sa m e K 103 N C V A L03 4 2100 0 99 .0 6 sa m e A 62 V , M 184 V , T 215 S V 106 M , G 190 A , M 23 0L C V A L03 5 2300 0 98 .9 9 sa m e M 41 L , D 67 N , K 70 R , M 184 V , T 215 F/ Y V 106 M , Y 188 L C V A L03 6 3800 0 99 .6 1 sa m e C V A L03 7 4900 0 99 .9 2 sa m e M 184 V K 101 E , V 10 6M , F 227 L C V A L03 8 5100 0 99 .1 sa m e M 184 V K 101 P, K 103 N C V A L03 9 6200 0 99 .6 8 sa m e V 118I K 103 N , E 13 8A C V A L04 0 6700 0 99 .7 6 sa m e V 118I , M 184 V V 106 M , Y 188 L C V A L04 1 7200 0 97 .7 9 sa m e M 184 V K 103 N , P 225 H C V A L04 2 7600 0 10 0 sa m e K 65 R , M 184 V L 100I , K 103 N , P 225 H C V A L04 3 7700 0 99 .1 3 sa m e Q 58 E K 103 N C V A L04 4 7700 0 99 .6 9 sa m e K 103 N , V 106 M , Y 18 8C C V A L04 5 7800 0 99 .1 9 sa m e V 11 I M 184 V V 106 M , V 179 D , F 227 L C V A L04 6 8500 0 99 .2 sa m e M 41 L , D 67 N , K 70 R , V 75 M , M 184 V , L 210 W , T 21 5F , K 219 E V 106 M , V 179 D , F 227 L C V A L04 7 9100 0 99 .6 1 sa m e L 10 I A 62 V , K 65 R , Y 115 F, M 184 V V 106 M , Y 188 C C V A L04 8 9500 0 99 .1 sa m e A 71 T M 184 V K 101 E , K 10 3R , V 17 9E , G 190 A , P 225 H C 176 Ta bl e D .1 : V ir al L oa ds , S equ en ce S im ila ri ty , M ut at io n Pa tt er ns a nd S ub ty pe s of th e 90 s am pl es u se d in th e H IV -1 A R V d ru g re si st an ce in -h ou se v al id at io n. T he y el lo w hi gh lig ht ed s am pl es h av e di ff er en t m ut at io n pa tt er ns f or V ir oS eq a nd th e in -h ou se a ss ay . T he p ur pl e hi gh lig ht ed s am pl es f ai le d to a m pl if y on V ir oS eq . P at ie nt N am e V ir al L oa d Se que nc e Si m il ar it y M utat io n P att er n P I- M aj or P I- M in or N R T I N N R T I Su bty pe V A L04 9 10800 0 99 .1 4 sa m e C V A L05 0 11000 0 99 .0 6 sa m e M 46I , I54 V ,L 76 V , V 82 A A 71 V , T 74 S M 184 V C V A L05 1 13000 0 99 .2 1 sa m e M 184 V K 103 N C V A L05 2 14000 0 99 .3 8 sa m e C V A L05 3 16000 0 98 .9 9 sa m e Q 58 E C V A L05 4 21000 0 99 .6 sa m e D 67 N , M 184 I, T 215 F K 103 N C V A L05 5 30000 0 99 .3 6 sa m e K 103 N C V A L05 6 31000 0 99 .2 9 sa m e K 103 N C V A L05 7 32000 0 99 .6 9 sa m e D 67 N , T 69 S, M 184 V K 101 E , V 10 6M , F 227 L C V A L05 8 35000 0 97 .8 5 sa m e T 74 S C V A L05 9 71000 0 98 .6 7 sa m e M 184 V K 103 N , G 190 A C V A L06 0 75000 0 99 .5 3 sa m e C V A L06 1 92000 0 99 .8 4 sa m e M 41 L , K 65 R , V 75 I K 103 N , V 106 M , V 179 D , Y 188 C C V A L06 2 120000 0 99 .1 2 sa m e M 41 L , E 44 D , D 67 N , T 69 D , L 74 V , M 184 V , L 210 W , T 215 Y K 103 N , V 179 E , M 230 L C V A L06 3 160000 0 99 .8 4 sa m e T 69 N Y 181C , G 190 A C V A L06 4 970000 0 99 .2 9 sa m e K 103 N C V A L06 5 un kn ow n 99 .1 3 sa m e M 41 L , D 67 N , M 184 V , T 215 Y K 101 E /V , Y 181 C , G 190 A C V A L06 6 un kn ow n 99 .4 3 sa m e A 71 T M 184 V K 103 N B V A L06 7 un kn ow n 97 .7 9 sa m e A 71 T C 177 Ta bl e D .1 : V ir al L oa ds , S equ en ce S im ila ri ty , M ut at io n Pa tt er ns a nd S ub ty pe s of th e 90 s am pl es u se d in th e H IV -1 A R V d ru g re si st an ce in -h ou se v al id at io n. T he y el lo w hi gh lig ht ed s am pl es h av e di ff er en t m ut at io n pa tt er ns f or V ir oS eq a nd th e in -h ou se a ss ay . T he p ur pl e hi gh lig ht ed s am pl es f ai le d to a m pl if y on V ir oS eq . P at ie nt N am e V ir al L oa d Se que nc e Si m il ar it y M utat io n P att er n P I- M aj or P I- M in or N R T I N N R T I Su bty pe V A L06 8 un kn ow n 99 .9 2 sa m e M 184 V C V A L06 9 un kn ow n 98 .3 8 sa m e M 184 V K 103 R , V 106 M , E 138 A , V 179 E , F 227 L C V A L07 0 un kn ow n 99 .2 1 sa m e C V A L07 1 un kn ow n 99 .6 8 sa m e A 71 T A 62 V , M 184 V K 101 E , V 10 6M , G 190 A C V A L07 2 1100 0 98 .1 7 sa m e M 184 V K 103 S, V 106 M C V A L07 3 un kn ow n 99 .2 sa m e M 184 V K 103 N , Y 188 L C V A L07 4 u nk no w n 98 .3 9 sa m e C V A L07 5 230 0 V S fa il ed V S fa il ed D 67 N , M 184 V K 101 E , K 10 3N , V 108 I, G 190 A C V A L07 6 240 0 V S fa il ed V S fa il ed D 67 N , K 70 R , M 184 V Y 188 L , G 19 0A , K 23 8T C V A L07 7 740 0 V S fa il ed V S fa il ed M 184 V K 103 R , V 106 M , V 179 D , M 230 L C V A L07 8 1400 0 V S fa il ed V S fa il ed K 65 R , M 184 V C V A L07 9 3200 0 V S fa il ed V S fa il ed V 118I , M 184 V C V A L08 0 4200 0 V S fa il ed V S fa il ed C V A L08 1 15000 0 V S fa il ed V S fa il ed K 65 R , D 67 N , T 69 I, K 70 R , F116 W , M 18 4V K 101 P, K 103 N , Y 318 F C V A L08 2 62700 0 V S fa il ed V S fa il ed V 75I , M 184 V V 106 M , F 227 L C V A L08 3 un kn ow n V S fa il ed V S fa il ed C V A L08 4 1700 0 10 0 sa m e A 62 V , M 184 V V 106 M , Y 188 C C V A L08 5 8400 0 99 .0 5 N o cl in ic al d if fe re nc e IN K 70 R & T 215 F V S P225 H D 67 N , M 184 V , T 215 F L 100I , K 103 N , H 221 I C 178 Ta bl e D .1 : V ir al L oa ds , S equ en ce S im ila ri ty , M ut at io n Pa tt er ns a nd S ub ty pe s of th e 90 s am pl es u se d in th e H IV -1 A R V d ru g re si st an ce in -h ou se v al id at io n. T he y el lo w hi gh lig ht ed s am pl es h av e di ff er en t m ut at io n pa tt er ns f or V ir oS eq a nd th e in -h ou se a ss ay . T he p ur pl e hi gh lig ht ed s am pl es f ai le d to a m pl if y on V ir oS eq . P at ie nt N am e V ir al L oa d Se que nc e Si m il ar it y M utat io n P att er n P I- M aj or P I- M in or N R T I N N R T I Su bty pe V A L08 6 23000 0 99 .3 sa m e M 46I , I54 V , L 76 V , V 82 A A 71 V , T 74 S M 184 V C V A L08 7 un kn ow n 99 .2 1 sa m e L 90 M A 71 V , T 74 S D 67 N , T 69 D , K 70 R , V 75 T , V 118I , K 219 Q E 138 A A V A L08 8 un kn ow n 99 .2 9 sa m e C V A L08 9 un kn ow n 99 .1 3 sa m e C V A L09 0 un kn ow n 99 .4 3 sa m e B 179 APPENDIX E 180 T ab le E .1 : B as el in e C IP R A -S A d em og ra ph ic s of t he 83 p at ie nt s th at e xp er ie nc e vi ra l f ai lu re . P at ie nt N am e In it ia ls R ef er en ce N um be r D at e O f B ir th G en de r V ir al L oa d A ge C D 4 P I* - m aj or P I- m in or N R T I^ N N R T I# C om m en ts 13501 1 K -M C P0505 B 4448 0 30 -A pr -7 6 Fe m al e 8, 99 0 29 26 0 N o St or ag e 13510 1 M -K C P0505 B 4453 1 14 -A ug -6 0 Fe m al e 28 ,50 0 45 26 2 13514 1 M T M C P0505 B 4447 6 16 -J un -7 6 Fe m al e 49 ,80 0 29 14 6 13524 1 B -S C P0505 B 4841 8 12 -A ug -0 5 Fe m al e 30 ,50 0 0 19 8 13531 1 PM M C P0505 B 4840 5 01 -F eb -5 7 M al e 65 ,40 0 48 11 5 T 74 S 13537 1 J- Q C P0505 B 4900 4 12 -M ay -8 0 M al e 12 ,50 0 25 31 8 T 74 S 13538 1 IZ M C P0505 B 4900 9 19 -J ul -7 3 M al e 21 ,60 0 32 31 3 N o am pl if ic at io n 13543 1 C -M C P0505 B 4900 1 12 -M ay -7 6 Fe m al e 39 ,40 0 29 20 1 I85 V I 13564 1 IT R C P0505 B 4992 5 16 -J ul -7 7 Fe m al e 110 ,0 00 28 18 1 T 74 S 13567 1 R T M C P0505 B 4990 4 15 -M ay -6 7 Fe m al e 74 ,40 0 38 12 3 T 74 S K 103 N 13577 1 H A T C P0505 B 5012 8 07 -J ul -5 6 M al e 16 ,60 0 50 20 8 13585 1 R SZ C P0505 B 4865 7 19 -A pr -6 3 M al e 122 ,0 00 43 23 5 13589 1 M PS C P0505 B 4867 2 15 -A ug -6 5 Fe m al e N D 1 41 31 1 E 138 A 13594 1 Q -S C P0505 B 4867 0 23 -M ay -8 1 Fe m al e 455 ,0 00 25 21 4 T 74 S 13610 1 N PM C P0505 B 5044 6 24 -D ec -7 5 Fe m al e 5, 18 0 31 13 7 N o am pl if ic at io n 13615 1 M SM C P0505 B 5068 8 24 -J un -7 7 Fe m al e 93 ,00 0 29 21 9 13625 1 D U S C P0505 B 4993 3 11 -J ul -7 4 Fe m al e 448 ,0 00 32 55 13635 1 N M B C P0505 B 5180 1 12 -M ay -7 7 Fe m al e 33 ,10 0 29 11 9 13661 1 B M R C P0505 B 5251 6 22 -M ay -6 9 M al e 168 ,0 00 37 19 1 N o St or ag e 13680 1 M A H C P0505 B 5285 8 01 -F eb -7 1 Fe m al e 24 ,50 0 35 21 4 13684 1 M E L C P0505 B 5308 7 15 -M ay -7 5 Fe m al e 135 ,0 00 31 14 8 A 71 T 13685 1 PT G C P0505 B 5249 0 17 -J ul -8 2 Fe m al e 298 ,0 00 24 91 181 T ab le E .1 : B as el in e C IP R A -S A d em og ra ph ic s of t he 83 p at ie nt s th at e xp er ie nc e vi ra l f ai lu re . P at ie nt N am e In it ia ls R ef er en ce N um be r D at e O f B ir th G en de r V ir al L oa d A ge C D 4 P I* - m aj or P I- m in or N R T I^ N N R T I# C om m en ts 13691 1 G T G C P0505 B 5250 3 16 -J an -6 7 Fe m al e 293 ,0 00 39 19 1 13701 1 L PR C P0505 B 5287 6 06 -M ar -7 9 Fe m al e 308 ,0 00 27 12 9 Q 58 E 13711 1 T JM C P0505 B 5286 9 21 -M ar -7 1 Fe m al e 468 ,0 00 35 21 3 16512 1 A -M C P0505 B 4447 9 02 -O ct -6 9 Fe m al e 678 ,0 00 36 22 4 M 46 V Q 58 E K 101 E K 103 R G 190 A 16513 1 J- N C P0505 B 4453 2 22 -D ec -6 5 M al e 80 ,40 0 40 16 8 16534 1 M PM C P0505 B 4828 8 02 -A ug -7 5 Fe m al e 37 ,00 0 30 14 8 N o St or ag e 16535 1 N C S C P0505 B 4901 0 28 -J an -8 5 Fe m al e 58 ,70 0 20 16 4 T 74 S 16546 1 M SD C P0505 B 4936 2 19 -J ul -6 7 Fe m al e 18 ,90 0 38 35 4 16553 1 B T M C P0505 B 4952 4 07 -S ep -6 9 Fe m al e 39 9 36 25 6 N o am pl if ic at io n 16562 1 T Q Q C P0505 B 4955 3 12 -D ec -7 0 Fe m al e 155 ,0 00 35 12 4 V 106 M /V E 138 A K 103 N 16578 1 IL T C P0505 B 5013 3 13 -J un -7 1 Fe m al e 249 ,0 00 35 12 3 16583 1 L Q C C P0505 B 4867 3 07 -M ay -7 8 Fe m al e 2, 89 0 28 16 2 16588 1 R M P C P0505 B 4865 9 12 -J an -8 4 Fe m al e 204 ,0 00 22 10 6 16596 1 JT T C P0505 B 5042 1 22 -S ep -7 0 M al e 58 ,20 0 36 19 4 A 71 T 16614 1 M L S C P0505 B 4992 1 29 -J an -7 3 M al e 218 ,0 00 33 11 8 L 10 I 16615 1 P- M C P0505 B 5119 0 07 -F eb -8 1 Fe m al e 70 ,30 0 25 61 16616 1 N H P C P0505 B 5119 3 15 -M ay -8 6 Fe m al e 609 ,0 00 20 17 7 16631 1 N T S C P0505 B 5045 3 10 -O ct -7 0 Fe m al e 152 ,0 00 36 87 N o am pl if ic at io n 16632 1 A N K C P0505 B 5180 2 25 -A pr -6 2 M al e 215 ,0 00 44 16 8 16635 1 E K P C P0505 B 5179 8 28 -J un -8 2 Fe m al e 293 ,0 00 24 10 9 182 T ab le E .1 : B as el in e C IP R A -S A d em og ra ph ic s of t he 83 p at ie nt s th at e xp er ie nc e vi ra l f ai lu re . P at ie nt N am e In it ia ls R ef er en ce N um be r D at e O f B ir th G en de r V ir al L oa d A ge C D 4 P I* - m aj or P I- m in or N R T I^ N N R T I# C om m en ts 16659 1 FN M C P0505 B 5253 4 25 -J an -7 1 Fe m al e 111 ,0 00 35 15 9 16681 1 T M A C P0505 B 5249 4 12 -M ar -7 8 Fe m al e 28 ,70 0 28 14 7 T 74 S 16683 1 SA L C P0505 B 5309 6 28 -J un -5 4 M al e 201 ,0 00 52 17 1 16687 1 M -F C P0505 B 5180 5 04 -F eb -8 1 Fe m al e 162 ,0 00 25 28 4 16689 1 W SM C P0505 B 5251 0 02 -J un -6 2 Fe m al e 138 ,0 00 44 10 1 16691 1 N H M C P0505 B 5307 9 08 -A ug -7 4 Fe m al e 25 ,20 0 32 18 8 V 179 D E 138 A 16693 1 SJ M C P0505 B 5275 8 23 -S ep -7 9 M al e 71 ,40 0 27 11 4 M 46 I 16694 1 L R M C P0505 B 5276 4 06 -D ec -7 0 Fe m al e 750 ,0 01 36 19 16695 1 N M Q C P0505 B 5251 1 07 -J un -8 4 Fe m al e 637 ,0 00 22 77 16696 1 N JO C P0505 B 5276 1 14 -N ov -7 1 Fe m al e 15 ,10 0 35 18 1 16698 1 PS M C P0505 B 5285 2 02 -N ov -7 7 Fe m al e 347 ,0 00 29 14 0 16704 1 FJ M C P0505 B 5288 6 09 -J an -7 6 Fe m al e 266 ,0 00 30 15 9 23514 1 Z -M C P0505 A 0024 9 16 -M ay -7 7 Fe m al e 4, 12 0, 00 0 28 12 2 23521 1 Z -M C P0505 A 0039 8 11 -J un -7 4 Fe m al e 94 ,80 0 31 21 6 23524 1 P- T C P0505 A 0040 7 25 -D ec -7 7 Fe m al e 854 ,0 00 28 13 8 23525 1 S- K C P0505 A 0040 4 15 -M ar -7 0 M al e 78 ,70 0 35 25 1 N o St or ag e 23528 1 SE N C P0505 A 0027 4 12 -F eb -6 8 M al e 7, 50 0, 00 1 37 65 23549 1 K -S C P0505 A 4803 4 20 -J un -6 7 M al e 1, 68 0, 00 0 38 54 23568 1 P- M C P0505 A 4912 6 25 -J ul -6 9 Fe m al e 287 ,0 00 36 15 3 23572 2 N -M C P0505 A 4803 0 26 -O ct -7 0 Fe m al e 750 ,0 01 36 N D 1 23580 1 I- G C P0505 A 4802 9 21 -J an -7 5 Fe m al e 210 ,0 00 31 12 7 N o am pl if ic at io n 23608 1 F- W C P0505 A 5073 9 28 -F eb -7 9 Fe m al e 292 ,0 00 27 25 1 N o St or ag e 183 T ab le E .1 : B as el in e C IP R A -S A d em og ra ph ic s of t he 83 p at ie nt s th at e xp er ie nc e vi ra l f ai lu re . P at ie nt N am e In it ia ls R ef er en ce N um be r D at e O f B ir th G en de r V ir al L oa d A ge C D 4 P I* - m aj or P I- m in or N R T I^ N N R T I# C om m en ts 23628 1 M -B C P0505 A 5076 4 25 -A pr -7 6 M al e 261 ,0 00 30 75 23641 1 L -G C P0505 A 5235 3 04 -A pr -7 4 M al e 99 ,90 0 32 90 T 74 S V 179 D 23661 1 N V Z C P0505 A 5592 4 05 -M ay -7 9 Fe m al e 379 ,0 00 27 16 23664 1 G -R C P0505 A 5570 7 12 -O ct -7 2 Fe m al e 478 ,0 00 34 13 5 26524 1 K V M C P0505 A 0040 2 09 -J ul -7 2 Fe m al e 945 ,0 00 33 20 26525 1 Z -L C P0505 A 0039 4 03 -J un -6 9 M al e 623 ,0 00 36 14 6 N o St or ag e 26545 1 C -N C P0505 A 0047 2 31 -M ay -6 6 Fe m al e 306 ,0 00 39 34 26555 1 B -G C P0505 A 0048 0 25 -J ul -8 5 Fe m al e 751 ,0 00 20 85 26564 1 M -V C P0505 A 4911 3 25 -D ec -5 8 Fe m al e 221 ,0 00 47 13 5 26565 1 B B K C P0505 A 4913 2 21 -J an -7 1 Fe m al e 24 ,80 0 34 22 5 T 74 S 26577 1 N -N C P0505 A 5034 1 15 -J un -7 6 M al e 30 ,40 0 30 70 26579 1 N -K C P0505 A 0047 1 28 -A pr -6 8 Fe m al e 107 ,0 00 38 18 3 N o St or ag e 26581 1 N -M C P0505 A 0039 6 05 -M ar -8 0 Fe m al e 139 ,0 00 26 12 2 26595 1 D -M C P0505 A 5074 0 19 -M ar -5 3 M al e 188 ,0 00 53 62 T 74 S 26601 1 N -M C P0505 A 5140 8 08 -A pr -7 8 Fe m al e 2, 26 0, 00 0 28 25 26626 1 P- X C P0505 A 5075 0 01 -J an -7 6 M al e 460 ,0 00 30 17 8 26626 2 N -X C P0505 A 5766 8 15 -S ep -8 7 Fe m al e 95 ,50 0 19 94 K 103 R 26657 1 B -M C P0505 A 5521 8 20 -J ul -7 6 Fe m al e 153 ,0 00 30 14 3 M 46 L 26666 1 N E M C P0505 A 5766 2 15 -S ep -8 0 Fe m al e 707 ,0 00 26 16 2 T 74 S *PI = Pr ot ea se Inh ib it or ; ^N R T I= N uc le os id e R ev er se T ra ns cr ip ta se I nh ib it or ; # N N R T I= N on -N R T I; 1 N D = N ot D on e 184 APPENDIX F 185 T ab le F .1 : 83 C IP R A -S A p at ie nt s w ith v ir al f ai lu re . P at ie nt N am e In it ia ls R eg im en D at e O f B ir th G en de r V ir al lo ad P I- m aj or P I- m in or N R T I N N R T I C om m en ts 13501 1 K -M d4 T -3 T C - E FV 30 -A pr -7 6 Fe m al e 13 ,00 0 K 103 N 13510 1 M -K d4 T -3 T C - E FV 14 -A ug -6 0 Fe m al e 9, 04 0 13514 1 M T M d4 T -3 T C - N V P 16 -J un -7 6 Fe m al e 11 ,40 0 13524 1 B -S d4 T -3 T C - N L F 12 -A ug -8 1 Fe m al e 1, 31 0 M 184 V K 103 N , Y 188 H 13531 1 PM M d4 T -3 T C - E FV 01 -F eb -5 7 M al e 8, 24 0 I47 V T 74 S M 184 V K 103 N 13537 1 J- Q d4 T -3 T C - E FV 12 -M ay -8 0 M al e 3, 06 0 T 74 S M 184 V 13538 1 IZ M d4 T -3 T C - E FV 19 -J ul -7 3 M al e 9, 81 0 13543 1 C -M d4 T -3 T C - N V P 12 -M ay -7 6 Fe m al e 4, 61 0 M 184 V K 103 N , G 190 A 13564 1 IT R d4 T -3 T C - N L F 16 -J ul -7 7 Fe m al e 15 ,90 0 T 74 S M 184 V K 103 N , V 106 M 13567 1 R T M d4 T -3 T C - E FV 15 -M ay -6 7 Fe m al e 1, 29 4 T 74 S M 184 V K 103 N , V 108 I, P 22 5H 13577 1 H A T d4 T -3 T C - E FV 02 -J ul -5 6 M al e 50 ,80 0 13585 1 R SZ d4 T -3 T C - E FV 19 -A pr -6 3 M al e 1, 11 0 V 90 I M 184 V K 103 N , K 101 E , K 238 N 13589 1 M PS d4 T -3 T C - E FV Fe m al e E 138 A , K 10 3N 13594 1 Q -S d4 T -3 T C - E FV 23 -M ay -8 1 Fe m al e 27 ,30 0 T 74 S K 103 N 13610 1 N PM d4 T -3 T C - L PV r 24 -D ec -7 5 Fe m al e 2, 90 0 V 118 I K 103 N /K , V 106 A /V , Y 188C /Y 186 T ab le F .1 : 83 C IP R A -S A p at ie nt s w ith v ir al f ai lu re . P at ie nt N am e In it ia ls R eg im en D at e O f B ir th G en de r V ir al lo ad P I- m aj or P I- m in or N R T I N N R T I C om m en ts 13615 1 M SM d4 T -3 T C - N V P 24 -J un -7 7 Fe m al e 40 ,60 0 M 184 V Y 181 C 13625 1 D U S d4 T -3 T C - N V P 11 -J un -7 4 Fe m al e 6, 84 0 N o am pl if ic at io n 13635 1 N M B d4 T -3 T C - N V P 12 -M ay -7 7 Fe m al e 1, 35 0 M 184 V Y 181 C 13661 1 B M R d4 T -3 T C - E FV 22 -M ay -6 9 M al e 14 ,70 0 V 106 M , Y 188 C 13680 1 M A H d4 T -3 T C - L PV r 01 -F eb -7 1 Fe m al e 8, 16 0 13684 1 M E L d4 T -3 T C - E FV 15 -M ay -7 5 Fe m al e 100 ,0 01 A 71 T 13685 1 PT G d4 T -3 T C - E FV 17 -J ul -8 2 Fe m al e 100 ,0 01 D 67 A , T 69 L 13691 1 G T G d4 T -3 T C - E FV 16 -J an -6 7 Fe m al e 42 ,60 0 K 103 N 13701 1 L PR d4 T -3 T C - N V P 06 -M ar -7 7 Fe m al e 7, 40 0 Q 58 E G 190 A 13711 1 T JM d4 T -3 T C - N V P 21 -M ar -7 1 Fe m al e 96 ,70 0 M 184 V V 106 A , F 227 L 16512 1 A -M d4 T -3 T C - E FV 02 -O ct -6 9 Fe m al e 4, 67 0 M 46 V , Q 58 E M 184 V K 103 S, G 190 A 16513 1 J- N d4 T -3 T C - E FV 22 -D ec -6 5 M al e 1, 03 0 M 184 V K 103 N , P 225 H 16534 1 M PM d4 T -3 T C - N V P 02 -A ug -7 5 Fe m al e 49 N o am pl if ic at io n 16535 1 N C S d4 T -3 T C - N V P 28 -J an -8 5 Fe m al e 25 ,20 0 16546 1 M SD d4 T -3 T C - E FV 19 -J ul -6 7 Fe m al e 46 ,80 0 L 10 V /L K 103 N /K , V 106 M /V 187 T ab le F .1 : 83 C IP R A -S A p at ie nt s w ith v ir al f ai lu re . P at ie nt N am e In it ia ls R eg im en D at e O f B ir th G en de r V ir al lo ad P I- m aj or P I- m in or N R T I N N R T I C om m en ts 16553 1 B T M d4 T -3 T C - E FV 07 -S ep -6 9 Fe m al e 3, 61 0 16562 1 T Q Q d4 T -3 T C - N V P 12 -D ec -7 0 Fe m al e 1, 22 0 M 184 V K 103 N , E 13 8A 16578 1 IL T d4 T -3 T C - E FV 13 -J un -7 1 Fe m al e 100 ,0 01 V 106 M , E 13 8A 16583 1 L Q C d4 T -3 T C - L PV r 07 -M ay -7 8 Fe m al e 23 ,80 0 A 71 V 16588 1 R M P d4 T -3 T C - N V P 12 -J an -8 4 Fe m al e 100 ,0 01 M 184 V K 103 N , Y 181 C 16596 1 JT T d4 T -3 T C - E FV 22 -S ep -7 0 M al e 50 ,60 0 A 71 T 16614 1 M L S d4 T -3 T C - E FV 29 -J an -7 3 M al e 67 ,40 0 L 10 I 16615 1 P- M d4 T -3 T C - N V P 07 -F eb -8 1 Fe m al e 6, 62 0 M 184 V K 103 N , Y 181 C 16616 1 N H P d4 T -3 T C - L PV r 15 -M ay -8 6 Fe m al e 609 ,0 00 16631 1 N T S d4 T -3 T C - L PV r 10 -O ct -7 0 Fe m al e 17 ,80 0 N o am pl if ic at io n 16632 1 A N K d4 T -3 T C - E FV 25 -A pr -6 2 M al e 2, 36 0 K 103 N 16635 1 E K P d4 T -3 T C - L PV r 28 -J un -8 2 Fe m al e 100 ,0 01 16659 1 FN M d4 T -3 T C - N V P 25 -J an -7 1 Fe m al e 3, 69 0 M 184 V K 103 N 16681 1 T M A d4 T -3 T C - N V P 12 -M ar -7 8 Fe m al e 55 ,80 0 T 74 S M 184 V V 108I , Y 181 C , H 221 Y 16683 1 SA L d4 T -3 T C - E FV 28 -J un -5 4 M al e 100 ,0 01 M 184 V K 103 N 188 T ab le F .1 : 83 C IP R A -S A p at ie nt s w ith v ir al f ai lu re . P at ie nt N am e In it ia ls R eg im en D at e O f B ir th G en de r V ir al lo ad P I- m aj or P I- m in or N R T I N N R T I C om m en ts 16687 1 M -F d4 T -3 T C - E FV 04 -F eb -8 1 Fe m al e 100 ,0 01 M 184 V K 101 E , P 225 H , K 103 N , V 108 I 16689 1 W SM d4 T -3 T C - E FV 02 -J un -6 2 Fe m al e 31 ,80 0 K 103 N 16691 1 N H M d4 T -3 T C - E FV 08 -A ug -7 4 Fe m al e 100 ,0 01 N O S T O R A G E 16693 1 SJ M d4 T -3 T C - E FV 23 -S ep -7 9 M al e 40 ,30 0 M 46 I K 103 N 16694 1 L R M d4 T -3 T C - N V P 06 -D ec -7 0 Fe m al e 100 ,0 01 M 184 V K 101 E , K 10 3N , V 106 M 16695 1 N M Q d4 T -3 T C - N V P 07 -J un -8 4 Fe m al e 3, 46 0 M 184 V K 103 N , K 238 N 16696 1 N JO d4 T -3 T C - N V P 14 -N ov -7 1 Fe m al e 20 ,60 0 M 184 V Y 181 C 16698 1 PS M d4 T -3 T C - N V P 02 -N ov -7 7 Fe m al e 1, 59 0 16704 1 FJ M d4 T -3 T C - E FV 09 -J an -7 6 Fe m al e 100 ,0 01 T 74 S, V 75 I M 184 V K 101 E , K 10 3N , G 190 A 23514 1 Z -M d4 T -3 T C - N V P 16 -M ay -7 7 Fe m al e 1, 50 0 M 184 V V 106 M , M 230 L 23521 1 Z -M d4 T -3 T C - N V P 11 -J un -7 4 Fe m al e 6, 10 0 M 184 V A 98 G , Y 181 C 23524 1 P- T d4 T -3 T C - E FV 25 -D ec -7 7 Fe m al e 69 5 M 184 V F227 L , G 190 A , V 106 M 23525 1 S- K d4 T -3 T C - E FV 15 -M ar -7 0 M al e 55 ,10 0 23528 1 SE N d4 T -3 T C - E FV 12 -F eb -6 8 M al e 100 ,0 01 M 184 V K 101 E , K 10 3N , G 190 A 23549 1 K -S d4 T -3 T C - E FV 20 -J un -6 7 M al e 78 ,20 0 M 184 V 189 T ab le F .1 : 83 C IP R A -S A p at ie nt s w ith v ir al f ai lu re . P at ie nt N am e In it ia ls R eg im en D at e O f B ir th G en de r V ir al lo ad P I- m aj or P I- m in or N R T I N N R T I C om m en ts 23568 1 P- M d4 T -3 T C - E FV 25 -J ul -6 9 Fe m al e 2, 29 0 K 103 N 23572 2 N -M d4 T -3 T C - E FV 26 -O ct -7 0 Fe m al e 29 ,40 0 M 184 V K 103 N , G 190 S 23580 1 I- G d4 T -3 T C - E FV 21 -J an -7 5 Fe m al e 1, 77 0 M 184 V K 103 N , P 225 H 23608 1 F- W d4 T -3 T C - E FV 28 -F eb -7 9 Fe m al e 10 ,70 0 M 184 V K 103 N , V 108 I, P 22 5H 23628 1 M -B d4 T -3 T C - E FV 25 -A pr -7 6 M al e 8, 71 0 M 184 V K 103 N , V 108 I, P 22 5H 23641 1 L -G d4 T -3 T C - E FV 04 -A pr -7 4 M al e 5, 59 0 T 74 S V 179 D 23661 1 N V Z d4 T -3 T C - E FV 05 -M ay -7 9 Fe m al e 2, 37 0 K 65 R , V 62 A K 103 N 23664 1 G -R d4 T -3 T C - E FV 12 -O ct -7 2 Fe m al e 3, 91 0 M 184 V , a 62 v V 106 M , Y 188 H 26524 1 K V M d4 T -3 T C - E FV 09 -J ul -7 2 Fe m al e 100 ,0 01 M 184 V V 106 M , G 190 A 26525 1 Z -L d4 T -3 T C - E FV 03 -J un -6 9 M al e 100 ,0 01 E 138 A 26545 1 C -N d4 T -3 T C - E FV 31 -M ay -6 6 Fe m al e 6, 06 0 D 67 N , K 70 R , M 184 V , K 219 E K 101 E , V 10 6M 26555 1 B -G d4 T -3 T C - N V P 25 -J ul -8 5 Fe m al e 100 ,0 01 V 106 A 26564 1 M -N d4 T -3 T C - E FV 25 -D ec -5 8 Fe m al e 51 ,70 0 M 184 V 26565 1 B B K d4 T -3 T C - N L F 21 -J an -7 1 Fe m al e 1, 91 0 N o am pl if ic at io n 26577 1 N -N d4 T -3 T C - E FV 15 -J un -7 6 M al e 24 ,70 0 M 184 V K 103 N , P 225 H 190 T ab le F .1 : 83 C IP R A -S A p at ie nt s w ith v ir al f ai lu re . P at ie nt N am e In it ia ls R eg im en D at e O f B ir th G en de r V ir al lo ad P I- m aj or P I- m in or N R T I N N R T I C om m en ts 26579 1 N -K d4 T -3 T C - L PV r 28 -A pr -6 8 Fe m al e 63 ,60 0 26581 1 N -M d4 T -3 T C - L PV r 05 -M ar -8 0 Fe m al e 2, 26 0 M 184 V E 138 A 26595 1 D -M d4 T -3 T C - E FV 19 -M ar -5 3 M al e 3, 48 0 T 74 S M 184 V K 103 N , M 230 L 26601 1 N -M d4 T -3 T C - E FV 08 -A pr -7 8 Fe m al e 21 ,00 0 K 65 R , M 184 V V 106 M , V 179 D 26626 1 P- X d4 T -3 T C - E FV 01 -J an -7 6 M al e 1, 70 0 M 184 V , D 67 G G 190 Q 26626 2 N -X d4 T -3 T C - N V P 15 -S ep -8 7 Fe m al e 8, 89 0 M 184 V K 103 E , V 10 8I , Y 18 1C 26657 1 B -M d4 T -3 T C - L PV r 20 -J ul -7 6 Fe m al e 7, 53 0 N o am pl if ic at io n 26666 1 N E M d4 T -3 T C - E FV 15 -S ep -8 0 Fe m al e 6, 52 0 T 74 S M 184 V K 103 N 191 APPENDIX G 192 Table G1: ViroSeq versus in-house cost analysis ViroSeq In?house Assuming Batch of 8 samples and 2 controls Assuming?Batch?of?6?samples?and?2?controls RNA Extraction Cost per Run RNA Extraction Cost per Run 1.5ml Startec Tubes R 11.20 MagNaPure?Kit R?422.19 Tips-1ml R 25.83 MagNaPure?Consumables/Run R?641.52 Tips-100ul R 19.38 2ml?Startec?Tubes R?8.80 Tips-10ul R 25.83 SABEX R?4.00 Isopropanol R 2.28 R 1,076.51 Centrifuge tubes (ppt, 15 ml) 8.76 RT-PCR Ethanol R 2.80 PCR tube R 5.98 Rnase Free Water R 10.00 RT Expand R 297.67 Labels R 2.50 Rnase Inhibitor R 30.89 Pasteur pippete (10ml ) R 11.57 dNTPs R?12.51 R 108.58 Primers R?1.56 RT-PCR Tips R?70.00 Tips-100ul R 32.29 R 418.61 Tips-10ul R 32.29 PCR 0.2ml PCR tubes R 5.15 PCR?plus?kit R?43.27 1.5ml Startec Tubes R 2.24 dNTPs R?6.26 R 71.97 Primers R?3.12 Purification and Quantification Tips R?140.00 Tips-1ml R 0.00 SABEX? R?0.40 Tips-100ul R 32.29 R 193.04 Tips-10ul R 51.67 Purification and Quantification 0.2ml PCR strips R 3.71 Tips-1ml R 0.00 Agarose R 30.16 Tips-100ul R 32.29 50xTAE R 40.20 Tips-10ul R 51.67 Ethidium bromide R 0.48 0.2ml PCR strips R 3.71 Rnase Free Water R 10.00 Agarose R 30.16 Polaroid R 30.00 50xTAE R 40.20 Labels R 2.50 Ethidium bromide R 0.48 1.5ml Startec Tubes R 11.20 Rnase Free Water R 10.00 R 212.21 Polaroid R 30.00 Labels R 2.50 1.5ml Startec Tubes R 11.20 R 212.21 Cycle Sequencing and Purifcation Cycle Sequencing and Purifcation Tips-1ml R 0.00 Primers R?12.48 Tips-100ul R 258.33 Big Dye Terminator R?1,200.00 Tips-10ul R 0.00 ViroSeq Pack 2 R?166.67 Isopropanol R 4.56 Tips-1ml R 0.00 Rnase Free Water R 5.00 Tips-100ul R 258.33 Centrifuge tubes (ppt, 15 ml) 8.76 Tips-10ul R 0.00 Reagent reservoir (50ml) R 22.78 Isopropanol R 4.56 Hi-Di Formamide R 8.00 Rnase Free Water R 5.00 1.5ml Startec Tubes R 28.00 Centrifuge tubes (ppt, 15 ml) 8.76 96 well plate R 71.75 Reagent reservoir (50ml) R 22.78 Pasteur pippete (10ml ) R 11.57 Hi-Di Formamide R 8.00 R 418.75 1.5ml Startec Tubes R 28.00 96 well plate R 71.75 Pasteur pippete (10ml ) R 11.57 R 1,797.90 Running Sequencer Running Sequencer Cappillary 50cm R 336.25 Cappillary 50cm R 336.25 Buffer R 30.56 Buffer R 30.56 POP-6 R 706.00 POP-6 R 706.00 Speta R 60.00 Speta R 60.00 Retainer R 100.00 Retainer R 100.00 Rnase Free Water R 5.00 Rnase Free Water R 5.00 Centrifuge tubes (ppt, 15 ml) R 8.76 Centrifuge tubes (ppt, 15 ml) R 8.76 R 1,232.81 R 1,232.81 General Running Costs of the Gentyping Laboratory (divided by 104 runs/year) Powder-free, (inner coated, latex) R 9.90 Powder-free, (inner coated, latex) R 9.90 Tissue R 6.42 Tissue R 6.42 RNAse away/250ml R 1.13 RNAse away/250ml R 1.13 De-ionised water R 41.00 De-ionised water R 41.00 Ethanol R 350.00 Ethanol R 350.00 Laboratory coat (blue, disposable) R 22.26 Laboratory coat (blue, disposable) R 22.26 Laboratory coat [Large, white, cotton] R 22.26 Laboratory coat [Large, white, cotton] R 22.26 Laboratory marker [wet and dry surfaces] R 10.95 Laboratory marker [wet and dry surfaces] R 10.95 Timer R 66.00 Timer R 66.00 Graduated Measuring cylinder R 26.75 Graduated Measuring cylinder R 26.75 Conical fask R 48.00 Conical fask R 48.00 Tube racks R 48.90 Tube racks R 48.90 70% Ethanol in spray bottle R 350.00 70% Ethanol in spray bottle R 350.00 10 % bleach (0,5 % sodium hypochlorite in spray bottle R 42.00 10 % bleach (0,5 % sodium hypochlorite in spray bottle R 42.00 Bottle spray R 34.29 Bottle spray R 34.29 R 1,079.86 R 1,079.86 Consumable Costs R 3,124.19 Total for 8 reaction R 6,010.95 ViroSeq Kit (Pack 1 and 2) R 13,000.00 Labour R 1,035.00 Total for 10 reactions R 16,124.19 Labour R 1,380.00 Cost for one sample R 2,188.02 Cost of one sample R?1,174.32 20% failure rate R 2,625.63 10% repeats R 117.43 Cost per test R 2,625.63 Cost per test R 1,291.76 193 APPENDIX H 194 Confidential: For Revie w Please review the Supplemental Files folder to review documents not compiled in the PDF. Nurse management is not inferior to doctor management of antiretroviral patients: The CIPRA South Africa randomized trial. Journal: New England Journal of Medicine Manuscript ID: Draft Article Type: Special Article Date Submitted by the Author: Complete List of Authors: Sanne, Ian; University of Witwatersrand, Helen Joseph Hospital Orrell, Catherine; University of Cape Town, Desmond Tutu HIV Foundation Fox, Matthew; Center for Global Health and Development Conradie, Francesca; University of Witwatersrand, Clinical HIV Research Unit Ive, Prudence; University of Witwatersrand, Clinical HIV Research Unit Zeineker, Jennifer; University of Cape Town, Desmond Tutu HIV Centre Cornell, Morna; University of Cape Town, Department of Public Health Heiberg, Christie; University of Cape Town, Desmond Tutu HIV Centre Ingram, Charlotte; University of Witwatersrand, Clinical HIV Research Unit Panchia, Ravindre; University of Witwatersrand, Clinical HIV Research Unit Rassool, Mohammed; University of Witwatersrand, Clinical HIV Research Unit Gonin, Rene; Westat Stevens, Wendy; University of Witwatesrand, Contract Laboratory Services Truter, Handre; University of Witwatersrand, Clinical HIV Research Unit Dehlinger, Marjorie; National Institute of Allergy and Infectious Diseases van der Horst, Charles; University of North Carolina, Medicine McIntyre, James; University of the Witwatersrand, Perinatal HIV Research Unit Wood, Robin; University of Cape Town, Desmond Tutu Research Confidential: Destroy when review is complete. Submitted to the New England Journal of Medicine 195 Confidential: For Revie w Keywords: HIV/AIDS < Infectious Disease, Health Care Delivery < Public Health, Policy, and Training Abstract: Introduction Combination antiretroviral therapy administered by experienced physicians is highly effective. However, due to the scarcity of doctors, continued expansion of antiretroviral therapy (ART) in resource-poor settings will require large-scale task shifting from doctors to other health providers. Methods A randomised comparative strategy trial of treatment outcomes of doctor-initiated and monitored ART and doctor-initiated and nurse- monitored ART was performed at two South African primary-care clinics using regimens of the South African national ART program. Results 812 HIV-positive adults were randomised to either doctor (n=408) or nurse monitored ART (n=404). At baseline patients were 70% female, 34.7% had prior AIDS diagnoses and the median CD4 cell count was 164 cells/mm3. After a median follow-up of 24.3 months, deaths (10 vs 11), virological failures (44 vs 39) and CD4 cell count gain (270 vs 248 cells/mm3), toxicity failures (68 vs 66) and program losses (70 vs 63) were similar in nurse and doctor arms respectively. 371 (46%) patients reached a protocol pre- defined composite endpoint of treatment failure incorporating mortality, viral failure, treatment-limiting toxicities and visit schedule adherence; 192 (47.5%) and 179 (43.9%) in the nurse and doctor arms respectively. The hazard ratio for composite failure was 1.09 (95%CI 0.89-1.33) which lay within the protocol-defined limits for non-inferiority. Conclusions Survival was similar in both strategy arms. Using a comprehensive composite endpoint of treatment outcomes, nurse-monitored ART was shown to be non-inferior to doctor monitored therapy. This study supports task shifting to appropriately trained nurses for monitoring antiretroviral therapy in low income settings. Page 1 of 23 Confidential: Destroy when review is complete. Submitted to the New England Journal of Medicine 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 196 Confidential: For Revie w 1 Nurse management is not inferior to doctor management of antiretroviral patients: The CIPRA South Africa randomized trial Ian Sanne1, Catherine Orrell2, Matthew Fox3, Francesca Conradie1, Prudence Ive1, Jennifer Zeinecker2, Morna Cornell2, Christie Heiberg2, Charlotte Ingram1, Ravindre Panchia1,Mohammed Rassool1, Rene Gonin4, Wendy Stevens1, Handr? Truter1, Marjorie Dehlinger5, Charles van der Horst6, James McIntyre1, Robin Wood2 for the CIPRA-SA Study Team. 1. University of the Witwatersrand, 2. University of Cape Town, 3. Center for Global Health and Development, Boston University, 4. Westat, Rockville, USA, 5. National Institute of Allergy and Infectious Diseases, 6. University of North Carolina. Corresponding author: Dr Catherine Orrell Email: catherine.orrell@hiv-research.org.za Phone: +27-21-650 6958 Fax: +27-21-6506963 Acknowledgements: Funding for the CIPRA-SA trial was by the Division of AIDS (DAIDS) of the National Institutes of Allergy and Infectious Diseases, the National Institutes of Health, through grant No 1U19AI53217- 01. Funding was also provided by the United States Agency for International Development (USAID) under the terms of agreement 674-A-00-08-00007-00 with Right to Care (RTC). The project was also supported by Awards K01AI083097 and P30-AI50410 from the National Institute of Allergy And Infectious Diseases. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Division of AIDS, the National Institute of Allergy and Infectious Diseases, the National Institutes of Health, USAID, or other parties. Page 2 of 23 Confidential: Destroy when review is complete. Submitted to the New England Journal of Medicine 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 197 Confidential: For Revie w 2 We would like to acknowledge the support of the Gauteng and Western Cape Provincial Health Authorities, the work of the CIPRA-SA Study Team (Sharlaa Badal-Faesen, Mildred Botile, Nastassja Choonilal, Jennipher Gelant, Janet Grab,Veronica Graham, Najma Hafejee, Lynda Hamber, Sindesh Harduth, Johean Hendricks, Colleen Herman, Mellissa Hero, Richard Kaplan, Nicola Killa, Daniella Klemp, Faisel Laher, Thandi Mabiletsa, Zanele Madlala, Ntombekaya Mafukuzela, Bontle Mahlatsi, Helgard Marias, Nomakhaya Mfundisi, Buang Motloba, Cindy Moyo, Mcebisi Mtshizana, Lundi Ncana, Kevin Newell, Sean Palmer, Deborah Pearce, Mary-Ann Potts, Daphne Radebe, Anne Reyneke, Anna Segeneco, Jennifer Sekgale, Jan Steyn, Pinky Thebe, Handre Truter, Diederik van Niekerk, Frieda Verheye-Dua, Karlien Voges, Helen Woolgar), the Endpoint Review Committee (Gary Maartens, David Spencer; Charles van der Horst), and especially the contribution of our patients. Page 3 of 23 Confidential: Destroy when review is complete. Submitted to the New England Journal of Medicine 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 198 Confidential: For Revie w 3 Abstract (words 249) Introduction Combination antiretroviral therapy administered by experienced physicians is highly effective. However, due to the scarcity of doctors, continued expansion of antiretroviral therapy (ART) in resource-poor settings will require large-scale task shifting from doctors to other health providers. Methods A randomised comparative strategy trial of treatment outcomes of doctor-initiated and monitored ART and doctor-initiated and nurse-monitored ART was performed at two South African primary-care clinics using regimens of the South African national ART program. Results 812 HIV-positive adults were randomised to either doctor (n=408) or nurse monitored ART (n=404). At baseline patients were 70% female, 34.7% had prior AIDS diagnoses and the median CD4 cell count was 164 cells/mm3. After a median follow-up of 24.3 months, deaths (10 vs 11), virological failures (44 vs 39) and CD4 cell count gain (270 vs 248 cells/mm3), toxicity failures (68 vs 66) and program losses (70 vs 63) were similar in nurse and doctor arms respectively. 371 (46%) patients reached a protocol pre-defined composite endpoint of treatment failure incorporating mortality, viral failure, treatment-limiting toxicities and visit schedule adherence; 192 (47.5%) and 179 (43.9%) in the nurse and doctor arms respectively. The hazard ratio for composite failure was 1.09 (95%CI 0.89-1.33) which lay within the protocol-defined limits for non-inferiority. Conclusions Survival was similar in both strategy arms. Using a comprehensive composite endpoint of treatment outcomes, nurse-monitored ART was shown to be non-inferior to doctor monitored therapy. This study supports task shifting to appropriately trained nurses for monitoring antiretroviral therapy in low income settings. Page 4 of 23 Confidential: Destroy when review is complete. Submitted to the New England Journal of Medicine 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 199 Confidential: For Revie w 4 INTRODUCTION (words 3010) Combination drug therapy has had a remarkable impact in reducing AIDS-related morbidity and mortality [1-3]. In industrialised countries antiretroviral management is administered by specialist physicians who prescribe from the full range of available antiretroviral drugs, supported by frequent laboratory monitoring including resistance testing [4,5]. Several studies in industrialised settings have demonstrated that outpatients cared for by a physician with HIV expertise have better outcomes, including quality of care and survival, [6-12] which may reflect the complexities of HIV infection and its management [4]. In contrast to the relatively small epidemic in resource rich countries, there are 22.4 million people living with HIV in sub-Saharan Africa [13] with an estimated 3.8 million in urgent need to treatment [14]. Globally, there is a shortage of 4.3 million health workers [15] and in South Africa there are only 17.4 medical practitioners per 100,000 people, largely concentrated in urban areas [16, 17] In contrast to the individualised approach to HIV care in developed countries, the World Health Organisation (WHO) has proposed a public-health approach to antiretroviral therapy (ART) to enable scaling-up access to treatment for large numbers of HIV-positive adults and children in developing countries [18]. An approach using standardised simplified treatment protocols and decentralised service delivery was developed to enable lower level health-care workers to deliver care [19]. Models of care have explored task shifting to clinical officers [20] and a combination of nurses and community workers [21]; however, nurse-led models of antiretroviral delivery have been one of the most widely implemented models of HIV care in poor-resourced African settings [22-24]. The HIV/AIDS strategic plan of South Africa, a medium income country with the world?s largest national antiretroviral therapy programme, envisions increasing reliance on nurses for monitoring of antiretroviral therapy [25]. With increasing deployment of nurses for HIV care there is an urgent need for operational research to determine if nurse-led models of care are safe and effective. We therefore conducted a prospective randomised controlled strategy trial comparing ?doctor-initiated-nurse- monitored? to the current standard of care, ?doctor-initiated-doctor-monitored? ART. Efficacy was assessed Page 5 of 23 Confidential: Destroy when review is complete. Submitted to the New England Journal of Medicine 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 200 Confidential: For Revie w 5 using a composite endpoint which reflected both treatment outcomes and patient management. Endpoint criteria included death, loss to follow up, viral suppression, drug interruptions due to toxicity and adherence to schedule of visits. METHODS The study was a community-based ART strategy trial performed as part of the Comprehensive International Program for Research in AIDS in South Africa (CIPRA-SA - NCT00255840) [26]. The trial was conducted at two primary healthcare sites in South African townships: Masiphumelele in Cape Town and Soweto in Johannesburg. Study Population The eligible study population consisted of HIV-1 infected antiretroviral drug na?ve adults (< 6 weeks) over 16 years with a CD4+ count <350 cells/mm3 or a prior AIDS-defining illness [27] and not in first trimester of pregnancy. Women who had received short course ART for prevention of mother to child transmission were not excluded. Screening laboratory investigations for renal function, liver enzymes and hematology were required to be less than grade 3 by the National Institutes of Health Division of AIDS toxicity grading scale [28]. An active opportunistic infection was exclusionary if the patient?s treatment status was not considered stable (i.e. treatment for > 7 days) or in the case of tuberculosis (TB) if the treatment had been for less than eight weeks (amended in October 2005 to < 2 weeks of TB treatment). Other exclusion criteria included; concomitant treatment with systemic myelosuppressive, neurotoxic, pancreatotoxic, hepatotoxic, or cytotoxic treatment within 30 days of randomization; acute hepatitis, intractable diarrhea (lasting > 6 weeks), bilateral peripheral neuropathy of grade 2 or higher and drug or alcohol abuse considered by the investigator to potentially interfere with study compliance. Page 6 of 23 Confidential: Destroy when review is complete. Submitted to the New England Journal of Medicine 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 201 Confidential: For Revie w 6 The study was approved at the institutional review boards of the University of Cape Town and University of the Witwatersrand, and written informed consent was obtained from all participants prior to the initiation of study procedures. Study Design The CIPRA-SA study was a prospective, unblinded, randomized controlled trial comparing two treatment monitoring strategies. Subjects were allocated to either receive their primary care from doctors (hereafter referred to as doctor arm) or from primary health care nurses (hereafter referred to as nurse arm). Participants were randomized 1:1 within sites in pre-defined blocks of six. The standard of care strategy (doctor) was consistent with the routine management of patients in the current South African ART program which is based on doctor initiated and monitored treatment [19]. The experimental nurse monitoring strategy utilized doctor-initiated primary health care nurse-monitored ART with participants aware of their randomized treatment assignment. To ensure that all procedures and overall study management conformed to the national [28], and NIH guidelines for research on human subjects [29], a clinical safety team was established consisting of research experienced clinicians. The clinical safety team was responsible for the recruitment of participants including consent, screening processes, initiating therapy and providing ongoing telephonic consultation support to study nurses and doctors. At each site the experimental arm (nurse) utilized two experienced primary health care nurses. Primary health care nurses are a nationally registered cadre of nurses who have undergone further training in primary health care. The control arm (doctor) consisted of two doctors at each site. Primary-care providers in both arms had limited or no prior experience with antiretroviral therapy. Both arms were supported by lay community counselors trained in treatment adherence counseling and a clinic nurse scheduled patient visits and performed Page 7 of 23 Confidential: Destroy when review is complete. Submitted to the New England Journal of Medicine 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 202 Confidential: For Revie w 7 routine clinic procedures. In order to limit contamination between randomized arms, routine visits were scheduled on different days. A pharmacist oversaw ordering and dispensing of antiretroviral drugs at each site. The primary study outcome was a composite end-point of possible treatment limiting events that may occur on first-line therapy. These included the following: 1) all-cause mortality, 2) loss-to-follow-up, 3) virologic failure, 4) toxicity failure, 5) withdrawn consent, 6) defaulting clinic schedule, and 7) HIV-disease progression. Virologic failure was defined as either a decline of < 1.5 log10 in viral load from baseline to 12 weeks of treatment (early failure), or two consecutive viral loads 4 weeks apart of >1000 copies/ml (late failure). Toxicity failure was defined as Grade 3 and 4 adverse events or other events requiring treatment interruption for more than 42 days [30]. However, single drug substitution as a result of drug related toxicity was not considered failure if treatment was interrupted for less than 42 days. Patients who missed three consecutive study visits and were not able to be contacted by the study team were defined as lost to follow-up. Defaulting clinic schedule was defined as missing three or more consecutive scheduled clinic appointments with a study visit window of seven days but able to be traced. Disease progression was defined by new AIDS-defining clinical events, as defined in the revised case definition of the Centers for Disease Control and Prevention [27]. Tuberculosis (TB) is hyperendemic in South Africa and therefore pulmonary TB was not included in the composite endpoint but was analyzed separately. Throughout the study, a data monitoring team reviewed data from all study visits to identify any default or loss- to-follow-up. An end-point review committee reviewed all events classified as death and toxicity failure to ascertain if the correct assignment to study regimen and procedure was undertaken. An independent data and safety monitoring board reviewed the safety and efficacy of the CIPRA-SA study at six monthly intervals. Page 8 of 23 Confidential: Destroy when review is complete. Submitted to the New England Journal of Medicine 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 203 Confidential: For Revie w 8 Antiretroviral therapy ART was provided and specified by the South African Department of Health. Regimens initially prescribed by the Clinical Safety Team [31] included a nucleoside backbone of stavudine and lamivudine, with a choice of efavirenz, nevirapine or lopinavir/ritonavir. The initial dose of stavudine was 40 mgs daily for individuals over 60 kgs, which was reduced to 30 mgs for all patients from mid 2007 in line with WHO recommendations [32]. Efavirenz was the preferred non-nucleoside for men and women not wishing to become pregnant and willing to maintain both barrier and hormonal contraception throughout the study. Nevirapine and lopinavir/ritonavir were prescribed to women of child bearing potential depending on whether their CD4+ lymphocyte count was above or less than 250 cells/mm3 respectively. Pregnant women, who were allowed to enroll after their first trimester, were prescribed either nelfinavir or lopinavir/ritonavir. Data collection and monitoring After consenting and randomization by the Clinical Safety Team, the primary-care provider of the assigned arm undertook responsibility for treatment initiation, adherence counseling and follow up visits. Patients were scheduled for study visits at baseline and then at weeks 2, 4, 8, 12, and 12 weekly thereafter. Clinical records were maintained by the primary-care providers in each arm. Study coordinators at each site extracted relevant study data into case report forms which were relayed to a central database using Datafax?. Statistical analysis and sample size The sample size was calculated based on an 18-month accrual and 96 weeks follow-up period with 80% power and alpha of 0.05. Non-inferiority of the nurse arm over the doctor arm for cumulative treatment failure was pre-specified as an upper 95% confidence limit for the hazard ratio that was below 1.40. An initial sample size of 850 subjects accounted for potential clustering of multiple enrolled subjects within households. As Page 9 of 23 Confidential: Destroy when review is complete. Submitted to the New England Journal of Medicine 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 204 Confidential: For Revie w 9 significant household clustering was not observed, enrollment was able to be discontinued after 812 subjects with no compromise of pre-established study power. Baseline differences in randomization groups were described using simple proportions for categorical variables and means and standard deviations for continuous variables. The primary analysis was an intention-to-treat analysis of any treatment failure using Cox proportional hazards regression. Differences in specific reasons for treatment failure (e.g. lost to follow-up, toxicity, death, etc.) were compared by treatment group using hazard ratios and 95% confidence intervals. Finally, differences in time to failure used Kaplan-Meier analyses. Group comparisons using the log-rank statistic, were considered significant if p-values were < 0.05. RESULTS The study enrolment flow diagram is shown in figure 1. Between February 2005 and January 2007, 917 subjects were screened for study enrolment, of whom 828 met eligibility criteria and 812 consented and were randomized. Of the 89 patients excluded from the study, 32 did not meet the ART initiation criteria, 22 had acute medical conditions, 18 were considered unsuitable by investigators or failed to return, 8 had laboratory results out of eligible range and 9 were unable to take oral medication or were on excluded medications. Study subjects were 99% black African and 70% were female. Four hundred and eight individuals were randomized to the nurse arm and 404 to the doctor arm. The median follow-up was 120 weeks (IQR 60-144) with no difference between the nurse and doctor arms (median 119 vs 120 weeks respectively).The total follow-up period was 815.7 patient years and 830.9 patient years for the nurse and doctor arms, respectively. Baseline characteristics together with prior antiretroviral exposure and initial regimens are shown for each study arm in table 1. The study cohort had a median age of 32 years and had advanced HIV-disease as manifested by 35% with prior AIDS, 57% with viral loads >100,000 copies per millilitre (cpm) and a median of 164 CD4 cell/mm3. Patients in the nurse arm were slightly more likely to be female (73% vs 68%) and be in CDC stage A (40% vs 35%) than patients in the doctor arm but differences were small and non-significant. Despite the slight Page 10 of 23 Confidential: Destroy when review is complete. Submitted to the New England Journal of Medicine 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 205 Confidential: For Revie w 10 preponderance of females in the nurse arm, prior exposure to antiretroviral prophylaxis as part of mother-to- child prophylaxis was evenly distributed between study arms. Most subjects commenced with non-nucleoside based therapy (92%) together with a nucleoside backbone of stavudine and lamivudine which reflected the prevailing South African national treatment guidelines. Cumulative treatment failure The primary study end-point of cumulative treatment failure was reached by 371 (45.7%) patients after a total of 1647 patient-years of follow-up. One hundred and ninety two (48%) of the subjects in the nurse arm reached the composite treatment failure endpoint and 179 (44%) in the doctor?s arm. Using proportional hazards regression there was a nine percent increased risk of failure in the nurse arm (Hazard Ratio = 1.09 (95% confidence interval 0.89-1.33). The hazard ratio and 95% confidence limits lie below the pre-defined study criterion for inferiority (1.4). The Kaplan-Meier estimated time to composite failure was similar for each arm (Figure 2). The hazard ratios for individual treatment failure parameters of the composite end-point are shown in Table 2. Deaths contributed 5.7% of the total events, viral failure 22.4%, toxicity failure 36% and protocol defined lost to follow up failure 36% of end-points. The subcategories of the composite endpoint hazard ratios are all closely distributed to 1.0 (0.92-1.15). There were no significant differences between study arms for Kaplan-Meier estimates of time to death, viral failure, toxicity failure and lost to follow up (Figure 2). Deaths A total of 21 deaths, 10 in nurse arm and 11 in the doctor arms, were included in the analysis. One further death was not included in the analysis as the participant had met a protocol defined end-point of toxicity failure before the death occurred. All the deaths were reviewed by a blinded end-point review committee to assign the cause Page 11 of 23 Confidential: Destroy when review is complete. Submitted to the New England Journal of Medicine 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 206 Confidential: For Revie w 11 of death as study related, treatment related, disease related or non-study related. Two deaths were assessed as due to lactic acidosis, related lactic acidosis and 2 deaths were considered to be non-study and non-HIV related. Immunology Immune response was not a component of the primary endpoint; however, CD4 cell count increases from base line were 155 cells (IQR 119-193) and 158 cells (IQR 125-169) at 1 year and 239 cells (IQR 217-290) and 220 cells (IQR 174-274) at 2 years for the nurse and doctor arms, respectively. Cumulative treatment failure was not impacted significantly by either low baseline CD4+ count <200 cells/mm3 nor high viral load > 100,000 cpm. However, there were a non-significant trends for increased failure in the nurse arm for individuals with CD4 cell count <200cells/mm3 (p=0.14) and with viral loads >100,000 copies/ml (p=0.09). Safety monitoring and toxicity: Grade 3 and 4 toxicities which occurred during the study are shown in table 3. The most frequent laboratory abnormalities were anemia and neutropenia, raised lactate and abnormal hepatic enzymes occurring at 10.2, 10.1 and 7.0 per 100 patient years respectively. The high frequency of hyperlactatemia resulted in a data safety monitoring board recommendation in 2007, for additional training and management of raised lactate. Grade 3 and 4 and dose limiting toxicities were more commonly reported in the doctor arm compared to the nurse arm (incidence rate of 55.5 vs 45.5 respectively). However, a retrospective review by the CIPRA clinical safety team of all laboratory investigations performed throughout the study was consistent with the equal distribution of laboratory defined adverse events between arms. Discussion: This study reports the findings of the first prospective, randomized, controlled study comparing of nurse versus doctor managed ART. Mortality, viral suppression, CD4 cell count response and a composite end-point reflecting multiple aspects of ART delivery, demonstrated that nurse monitored therapy was not inferior to Page 12 of 23 Confidential: Destroy when review is complete. Submitted to the New England Journal of Medicine 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 207 Confidential: For Revie w 12 doctor monitored therapy. These findings support observational data from other treatment programmes reporting successful use of task shifting in HIV care [33-41] and also for other disease management [42]. Expansion of ART services is urgently required in resource-poor countries in order to achieve universal access targets by 2010 [43] and further expansion will be needed with initiation of universal testing and treating strategies [44]. There was no difference in mortality, viral failure or immune recovery between the study arms although there was a non-significant trend in increased failure in the nurse arm for patients with advanced HIV disease. This study therefore strongly supports the strategy of ?task shifting? and indicates that HIV management by nurses can be safe and effective even for those patients commencing therapy with advanced HIV infection. Although both study strategies successfully managed drug related toxicities, the study does highlight a high frequency of lipomorphologic changes and lactate elevation associated with use of regimens including stavudine. Recent WHO guidelines have moved away from reliance on stavudine [45] however, it remains widely used in resource-poor HIV therapy programs [18]. In our study the overall drug toxicity frequency appeared to be lower than earlier reports of stavudine based toxicities which resulted in drug substitutions in excess of 20% after three year [46]. The dose reduction of stavudine to 30 mgs after the first year of the study which was in line with WHO recommendations [30] may have reduced drug limiting toxicities somewhat. However, two of the study deaths were due to hyperlactatemia, a recognised complication of stavudine use. Randomised controlled studies are frequently considered the ?gold standard? on which treatment policies should be based. However, there may be some caveats in applying trial findings to non-study settings and other populations. A strength of our study was that it was performed at urban and peri-urban primary care clinics in South African high-burdened communities where large scale task shifting will be required. Additionally, in order to limit the ?contamination? between the arms of the study, once the participants were randomised scheduled visits were booked for different days of the week, Page 13 of 23 Confidential: Destroy when review is complete. Submitted to the New England Journal of Medicine 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 208 Confidential: For Revie w 13 The study, however, did not necessarily replicate the typical conditions under which therapy is presently delivered in resource-poor settings. For instance, all the clinical staff in the study received protocol specific training in the conduct of ethical research including didactic clinical management and ongoing telephonic clinical support if required. However, widespread ?task shifting? will require increased training, a redefinition of scope of practice for nurses and a clinical support structure. It should be noted that the study design did not address ?nurse initiated? antiretroviral therapy because the prescription of licensed medication in South Africa is restricted to doctors. Implementation of nurse initiated therapy would therefore require additional changes to the existing legislation. However, the new national HIV strategic plan does envisage initiation of therapy by doctors together with wide scale task shifting to nurses for ongoing patient management [25]. In conclusion, nurses were shown to be non-inferior to doctors in monitoring a public health ART program in South Africa. The results of this study strongly support the expanded access to treatment using models of task shifting in primary health care. Page 14 of 23 Confidential: Destroy when review is complete. Submitted to the New England Journal of Medicine 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 209 Confidential: For Revie w 14 Figure 1: CONSORT study flow chart and participant disposition for the CIPRA-SA trial, a randomized trial of doctor vs. nurse monitored antiretroviral therapy in South Africa. En ro llm en t Al lo ca tio n Fo llo w -u p An aly sis Assessed for eligibility (N = 917) Randomized (N = 812) Excluded (N=105) Failed inclusion criteria (N=89) Refused to participate (N=16) Allocated to Nurse Arm (N = 408) Allocated to Doctor Arm (N = 404) Lost to Follow-up (N = 10) Discontinued Intervention (N = 53) Lost to Follow-up (N = 14) Discontinued Intervention (N = 56) Analyzed (N = 408) Excluded (N = 0) Analyzed (N = 404) Excluded (N = 0) Page 15 of 23 Confidential: Destroy when review is complete. Submitted to the New England Journal of Medicine 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 210 Confidential: For Revie w 15 Figure 2a: Kaplan-Meier curves of time to cumulative treatment failure by study arm among 812 subjects randomized to doctor or nurse monitored antiretroviral therapy in the CIPRA-SA trial in South Africa; Figure 2b-d: Kaplan-Meier curves of time to specific reasons for treatment failure by study arm among 812 subjects randomized to doctor or nurse monitored antiretroviral therapy in the CIPRA-SA trial in South Africa* * a) a Kaplan-Meier curve demonstrating the composite end-point of cumulative treatment failure. The primary health care nurse arm of the study is non-inferior to the doctor arm (log-rank p-value 0.4238). b) shows time to virologic failure stratified by treatment ARM (log-rank p-value = 0.5340); c) shows time to toxicity failure stratified by treatment ARM (log-rank p-value = 0.4678); d) shows time to loss to follow-up stratified by treatment ARM (log-rank p-value = 0.8358); Page 16 of 23 Confidential: Destroy when review is complete. Submitted to the New England Journal of Medicine 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 211 Confidential: For Revie w 16 Table 1: Baseline demographic and clinical characteristics of 812 subjects randomized to doctor or nurse monitored antiretroviral therapy in the CIPRA-SA trial in South Africa Nurse Arm Doctor Arm Total (N=404) (N=408) (N=812) Female 297 (73.5%) 276 (67.7%) 573 (70.6%) Age years median (IQR) 32.3 (28.0-36.6) 32.2 (28.0-37.4) 32.3 (28.0-37.1) BMI (kg/m2) (IQR) 23.5 (21.3-27.6) 23.5 (20.4-26.8) 23.5 (20.8-27.2) CDC Classification Class A (%) 160 (39.6%) 141 (34.6%) 301 (37.1%) Class B (%) 111 (27.5%) 118 (28.9%) 229 (28.2%) Class C (%) 133 (32.9%) 149 (36.5%) 282 (34.7%) CD4+ Count (cells/ml) <200 (%) 260 (64.4%) 257 (63.0%) 517 (63.7%) 200-350 (%) 119 (29.5%) 131 (32.1%) 250 (30.8%) 350-500 (%) 23 (5.7%) 18 (4.4%) 41 (5.1%) > 500 (%) 2 (0.5%) 2 (0.5%) 4 (0.5%) Median (IQR) 165 (105-235) 164 (110-225) 164 (109-229) Viral load (copies/ml) ? 100,000 (%) 181 (44.8%) 170 (41.7%) 351 (43.2%) > 100,000 (%) 223 (55.2%) 238 (58.3%) 461 (56.8%) Log10 mean viral load (std) 4.99 (0.75) 5.09 (0.73) 5.04 (0.74) Baseline regimen prescribed Stavudine, Lamivudine, Efavirenz 293 (72.5%) 304 (74.5%) 597 (73.5%) Stavudine, Lamivudine, Nevirapine 72 (17.8%) 81 (19.9%) 153 (18.8%) Stavudine, Lamivudine, Lopinavir/rtv ? 35 (8.7%) 20 (4.9%) 55 (6.8%) Stavudine, Lamivudine, Nelfinavir? 4 (1%) 3 (0.7%) 7 (0.9%) Prior exposure to antiretrovirals* Single Dose Nevirapine (%) 81 (20%) 86 (21.1%) 167 (20.6%) Zidovudine (%) 2 (0.5%) 4 (1.0%) 6 (0.7%) Nevirapine, Zidovudine (%) 14 (3.5%) 15 (3.7%) 29 (3.6%) Triple drug therapy (%) 1 (0.2%) 0 (0%) 1 (0.1%) ? ?Protease inhibitor containing regimens were prescribed to pregnant women or women of childbearing potential with CD4+ count >250 who were unable or unwilling to use both a barrier contraceptive and a progesterone contraceptive. These women could not receive either a Nevirapine or Efavirenz containing regimen * Prior exposure to antiretroviral therapy for prevention of transmission, either from mother-to-child or in post-sexual exposure prophylaxis was permitted by the protocol for up to 6 weeks of treatment. Page 17 of 23 Confidential: Destroy when review is complete. Submitted to the New England Journal of Medicine 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 212 Confidential: For Revie w 17 Table 2: Cumulative treatment failure (primary end-point) and accompanying reasons by study arm for 812 subjects randomized to doctor or nurse monitored antiretroviral therapy in the CIPRA-SA trial in South Africa? ?The two arms of the study were compared using a composite end-point or cumulative treatment failure. The composite consisted of each of the reasons listed below. ^ Early virologic failure was defined when a participant failed to demonstrate a serologic viral load decline of more than 1.5 logarithm within 12 weeks of initiating treatment. * Late virologic failure was defined as rebound in viral load from undetectable to more than 1000 copies/ml confirmed within one month. 0 2 4 6 8 1 0 1 2 0.1 1 10 Nurse Doctor Hazard Ratio (N=404) (N=408) (95% CI) CUMULATIVE FAILURE 192 (48%) 179 (44%) 1.09 (0.89-1.33) All Virologic Failure 44 (11%) 39 (10%) 1.15 (0.75-1.76) <1.5 Log drop VL^ 7 (2%) 6 (2%) 1.18 (0.40-3.51) 2 VL > 1000* 37 (9%) 33 (8%) 1.14 (0.71-1.82) Toxicity Failure 68 (17%) 66 (16%) 1.04 (0.74-1.45) All Loss** 70 (17%) 63 (15%) 1.13 (0.81-1.59) Withdrew Consent 18 (5%) 21 (5%) 0.87 (0.46-1.63) Default Clinic Schedule 38 (9%) 32 (8%) 1.21 (0.76-1.93) Lost to follow up 14 (4%) 10 (3%) 1.42 (0.63-3.20) Death 10 (3%) 11 (3%) 0.92 (0.39-2.17) Favors Nurse Arm Favors Doctor Arm **Any loss was defined as: 1) withdrawn consent was if the patient withdrew from participating in the study for whatever reason and represents in most cases a transfer away from the site to another geographic location and clinic; 2) defaulting clinic schedule was a protocol defined measure of adherence to the clinic schedule, any participant who missed three consecutive visits was considered to be defaulting; (3) Loss to follow-up was consider if a participant did not return to the clinic for three consecutive clinic visits and could not be traced. Page 18 of 23 Confidential: Destroy when review is complete. Submitted to the New England Journal of Medicine 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 213 Confidential: For Revie w 18 Table 3: Rate of laboratory and clinical dose limiting or Aids Clinical Trial Group grade three and four defined toxicities 30 by study arm among 812 subjects randomized to doctor or nurse monitored antiretroviral therapy in the CIPRA-SA trial in South Africa*? Nurse arm Doctor arm TOXICITY Event in 815.74 py Rate/ 100 py Event in 830.88 py Rate/ 100 py IRR (95% CI) p-value Laboratory: Haematology 62 7.6 106 13 0.60 (0.44 - 0.82) 0.0011 Biochemistry 1 0.1 2 0.2 0.51 (0.05 - 5.62) 0.5745 Liver 44 5.4 72 8.7 0.62 (0.43 - 0.91) 0.0124 Hyperlactataemia 80 9.8 87 10 0.94 (0.69 - 1.27) 0.6724 Pancreatic 4 0.5 4 0.5 1.02 (0.25 - 4.07) 0.9793 Renal 3 0.4 1 0.1 3.06 (0.32 - 29.4) 0.3085 Drug related rash 4 0.5 5 0.6 0.81 (0.22 - 3.03) 0.7598 Clinical HIV events: Tuberculosis 28 3.4 31 3.7 0.92 (0.55 - 1.53) 0.7490 Cervical dysplasia 1 0.1 4 0.5 0.25 (0.03 - 2.28) 0.1865 Neurologic 10 1.2 32 3.9 0.32 (0.16 - 0.65) 0.0009 Intestinal 8 1.0 7 0.8 1.16 (0.42 - 3.21) 0.7689 Skin 1 0.1 2 0.2 0.51 (0.05 - 5.62) 0.5745 Lipodystrophy, lipoatrophy 45 5.5 51 6.1 0.90 (0.60 - 1.34) 0.6015 Miscellaneous 23 2.8 23 2.8 1.02 (0.57 - 1.82) 0.9503 Clinical Non-HIV events: CNS 5 0.6 13 1.6 0.39 (0.14 - 1.10) 0.0648 Obstetric/gynaecology 10 1.2 7 0.8 1.46 (0.55 - 3.82) 0.4439 Miscellaneous 34 4.2 37 4.5 0.94 (0.59 - 1.49) 0.7806 * PHCN arm had 815.7 total person-years while the MO arm had 830.9 ? Active reporting of adverse events was undertaken by the primary care giving nurse or doctor, and a retrospective review by the study team of all laboratory adverse events greater than or equal to grade three was undertaken. Page 19 of 23 Confidential: Destroy when review is complete. Submitted to the New England Journal of Medicine 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 214 Confidential: For Revie w 19 References 1. Palella FJ Jr, Delaney KM, Moorman AC, et al. Declining morbidity and mortality among patients with advanced human immunodeficiency virus infection.HIV Outpatient Study Investigators. New England Journal of Medicine,1998, 338(13):853?860. 2. Egger M, May M, Ch?ne G, et al. Prognosis of HIV-1-infected patients starting highly active antiretroviral therapy: a collaborative analysis of prospective studies. The Lancet, 2002, 360(9340):1178. 3. Mocroft A, Brettle R, Kirk O, et al. Changes in the cause of death among HIV positive subjects across Europe: results from the EuroSIDA study.AIDS, 2002, 16(12):1663?1671. 4. Guidelines for the Use of Antiretroviral Agents in HIV-1-Infected Adults and Adolescents. November 3, 2008. Available at http://www.aidsinfo.nih.gov/ContentFiles/AdultandAdolescentGL.pdf. accessed 25th November 2009 5. British HIV Association guidelines for the treatment of HIV-1 infected adults with antiretroviral therapy. HIV Medicine 2008:9;561-608. 6. Kitahata MM, Van Rompaey SE, Shields AW. Physician experience in the care of HIV-infected persons is associated with earlier adoption of new antiretroviral therapy. J Acquir Immune Defic Syndr, 2000. 24(2):106- 14. 7. Landon BE, Wilson IB, McInnes K, et al. Physician specialization and the quality of care for human immunodeficiency virus infection. Arch Intern Med, 2005. 165(10):1133-9. 8. Delgado J, Heath KV, Yip B, et al. 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