IJID Regions 6 (2023) 62–67 Contents lists available at ScienceDirect IJID Regions journal homepage: www.elsevier.com/locate/ijregi Evaluating determinants of treatment outcomes among tuberculosis patients in the mining district of Butha Buthe, Lesotho Veranyuy D. Ngah 1 , Motlatsi Rangoanana 1 , Isaac Fwemba 1 , Llang Maama 2 , Sele Maphalale 3 , Mabatho Molete 3 , Retselisitsoe Ratikoane 3 , Modupe Ogunrombi 4 , Justine Daramola 5 , Peter S. Nyasulu 1 , 6 , ∗ 1 Division of Epidemiology and Biostatistics, Faculty of Medicine, and Health Sciences, Stellenbosch University, Cape Town, South Africa 2 Disease Control Directorate, National Tuberculosis Program, Ministry of Health Lesotho 3 District Health Management team Butha Buthe, Ministry of Health Lesotho National Tuberculosis Program, Ministry of Health Lesotho 4 Department of Clinical Pharmacology, Sefako Makgatho Health Sciences University, Pretoria South Africa 5 Department of Information Technology, Faculty of Informatics and Design, Cape Peninsula University of Technology 6 Division of Epidemiology & Biostatistics, School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa a r t i c l e i n f o Key Words: Tuberculosis Treatment Favourable Unfavourable outcomes a b s t r a c t Background: Before the COVID-19 pandemic, tuberculosis (TB) was the leading infectious cause of death glob- ally. In low- and middle-income countries (LMIC) including Lesotho, treatment outcome is lower than the rec- ommended rate and poor TB treatment outcomes remain a programmatic challenge. The aim of this study was to determine unfavourable treatment outcomes and associated risk factors among TB patients in Butha Buthe district. Methods: This was a retrospective record review of TB patients registered between January 2015 and December 2020. Data were collected from TB registers and patients’ files and entered Microsoft Excel 2012. Analysis was conducted using R and INLA statistical software. Descriptive statistics were presented as frequencies and percent- ages. The differences between groups were compared using Pearson’s X 2 test in bivariate analysis. Frailty Cox proportional hazards model was used to determine the risk of unfavourable outcomes among the variables. Results: A total of 1792 TB patients were enrolled in the study with about 70% males (1,257). Majority (71.7%) of the patients were between 20 and 59 years old, with 48% of the patients being unemployed. Almost a quarter of the patients (23.1%) had unfavourable outcomes with death (342 patients) being the most common unfavourable outcome. Our study has shown that patients older than 59 years, and unemployment increased the risk of having unfavourable treatment outcomes. Death was the most common unfavourable outcome followed by lost-to-follow up. We also observed that the patients in the initiation phase of treatment died at a faster rate compared to those in the continuation phase (p = 0.02). Conclusion: TB treatment programs should have efficient follow-up methods geared more toward elderly patients. Active case finding to identify population at risk should be part of a TB program which would improve early diagnosis and treatment initiation. Patients in the intensive phase of the treatment program should be monitored more closely to determine adverse drug effects and nutritional requirement to prevent death during this phase of treatment. B i v f c d a p P T 2 t o h R 2 B ackground Prior to the Covid-19 pandemic, tuberculosis (TB) was the leading nfectious cause of death worldwide despite the fact that it is a pre- entable and curable disease [ 1 , 2 ]. An estimated 100 000 more deaths rom TB were reported during the 2019/2020 period [ 1 , 3 ]. This increase ould be attributed to the interruption of TB care services due to lock- own measures during the peak of the Covid-19 pandemic [ 1 , 4 ]. Glob- ∗ Corresponding Author: Peter S. Nyasulu. E-mail address: pnyasulu@sun.ac.za (P.S. Nyasulu) . ttps://doi.org/10.1016/j.ijregi.2022.12.008 eceived 29 November 2022; Received in revised form 21 December 2022; Accepted 772-7076/© 2022 The Authors. Published by Elsevier Ltd on behalf of Internationa Y-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ) lly there was a decline in the incidence of TB disease in 2020 (127 cases er 100 000 population), with the World Health Organization (WHO) acific South-East Asia region having the highest percentage (43%) of B incident cases [1] . This is followed by the WHO Africa region with 5% of incident cases[1]. However, this decline was minimal compared o previous years, and as such the world did not meet the 2020 milestone f the End TB strategy. 23 December 2022 l Society for Infectious Diseases. This is an open access article under the CC https://doi.org/10.1016/j.ijregi.2022.12.008 http://www.ScienceDirect.com http://www.elsevier.com/locate/ijregi http://crossmark.crossref.org/dialog/?doi=10.1016/j.ijregi.2022.12.008&domain=pdf mailto:pnyasulu@sun.ac.za https://doi.org/10.1016/j.ijregi.2022.12.008 http://creativecommons.org/licenses/by-nc-nd/4.0/ V.D. Ngah, M. Rangoanana, I. Fwemba et al. IJID Regions 6 (2023) 62–67 h m a a t d c t a c a t t d t [ A p a m f s d m o a t u T B t M S r S n h K f h H s C R P w D p i p r m D R i t t t t f ( s i e T v f s T l m m n m d c w u [ ( d S s p w w p p b h a f v s R S T m a y b ( 4 o m i In sub-Saharan Africa, TB control remains one of the key public ealth challenges where treatment success rate is lower than that recom- ended by the WHO [ 5 , 6 ]. In this region, TB treatment outcome is still problem, with studies showing poor outcomes being positively associ- ted with lower social-economic status and health system factors within hese countries [7–9] . A study conducted in Karamoja, Uganda at 10 ifferent TB diagnostic and treatment units showed that drug stockouts ontributed to failure in treatment success [7] . Another study showed hat the distance travelled by patients to get to the health clinic was significant factor for unfavourable outcome as poor accessibility in- reased risk of missed treatment [9] . Drug resistant TB is another factor ffecting treatment outcome. The continuous mutation of the Mycobac- erium tuberculosis (Mtb) requires different innovative diagnostics and reatment techniques [10] . This poses a burden on the health system ue to cost, and adverse effects associated with drug resistant medica- ion [ 11 , 12 ]. The WHO Africa region carries the highest number of high TB burden 1 , 2 ]. Lesotho is one of the 16 high TB burden country in sub-Saharan frica, with a recent national TB incidence rate of 660 per 100 000 opulation [2] . It is classified as a lower middle income country with per capita income of US$967.23 [13] , and with mining as one of its ajor sources of economic activity and the main source of employment or the adult males and females. TB studies conducted in Southern Africa howed that the mining industry contributes heavily to the burden of TB isease in these countries [14–16] . Studies conducted in Lesotho have focused on drug resistant TB treat- ent regimens [ 17 , 18 ], as well as the burden, diagnosis and treatment f TB [19–21] . Other studies have looked at the knowledge, attitudes nd practices among patients and healthcare workers [ 22 , 23 ]. However here has been no study focusing on treatment outcomes, specifically nfavourable outcomes in a mining population in the last five years. his study aimed to model the unfavourable TB treatment outcomes in utha Buthe district, Lesotho. The results of this study would inform on he improvement of TB treatment programs in Lesotho. ethods tudy design This was a retrospective record review of patients on TB treatment egistered between January 2015 and December 2020. tudy setting The study was conducted in Butha Buthe , a district found in the orthern part of Lesotho. It has a total population of around 110 000 in- abitants covering an area of 1767 km 2 . It houses two diamond mines, ao and Liqhobong. The study was conducted in all of the 12 health acilities found in the Butha Buthe district. This included two district ospitals which served as referral hospitals (Butha Buthe Government ospital and Seboche Hospital] and 10 primary health clinics [Boiket- iso Clinic, Linakaneng Clinic, Makhunoane Clinic, Motete Clinic, Muela linic, Ngoajane Clinic, St Paul Clinic, Tsime Clinic, St Peters Clinic, and ampai Clinic). opulation of study The study population consisted of the patients in Butha Buthe who ere diagnosed with tuberculosis during the period of January 2015 to ecember 2020. Active and passive case finding through symptomatic atients reporting to the health facility and contact tracing were used to dentify TB patients during this period. To be included in the study, atients should have started TB treatment. Patients with incomplete ecords that could not be traced, such as dates of treatment commence- ent or end, were excluded from the analysis. 63 ata collection Data were abstracted from TB patients’ registers and medical records. esearch assistants trained in data collection visited all 12 health facil- ties gathering data. The following variables were considered impor- ant for this study: demographic information (age, sex, occupation), ype of TB diseases (pulmonary and extra-pulmonary TB), phase of reatment (initiation/phase 1 and continuous/phase 2), drug resistance, reatment contact, treatment outcome (cured, completed, failure, de- aulted/interrupted, lost to follow-up, death) and employment status unemployed, employed non-mine workers, mine workers). For this tudy ex-mine workers were grouped together with mine workers. This s because ex-mine workers were assumed to have the same level of xposures to mining as mine workers hence might have similar risk to B. We further classified employment as a binary variable [employed s unemployed] when determining the risk factors associated with un- avourable outcomes. Data collected were entered into a MS Excel 2010 preadsheet, cross-checked for errors, and validated. reatment outcomes TB treatment outcomes are defined per WHO TB treatment guide- ines as: “i) Cured: Patient who is sputum smear-negative in the last onth of treatment and on at least one previous sputum test; ii) Treat- ent completed: Patient who has completed treatment but who does ot meet the criteria to be classified as a cure or a failure; iii) Treat- ent failure: Patient who is sputum smear-positive at 5 months or later uring treatment, iv) Death: Patient who dies for any reason during the ourse of treatment; v) Defaulted/interrupted: Patient whose treatment as interrupted for two consecutive months or more; Lost to follow- p: Patient whose treatment has been interrupted and cannot be traced 24] . For this study, treatment outcomes were classified as “favourable ” Cured and completed) and “unfavourable outcomes ” (failure, death, efaulted/interrupted and lost to follow up). tatistical analysis Data processing and analysis were conducted using R, and INLA oftware packages [25] . Descriptive statistics was done with data ex- ressed as frequency and percentages. The differences between groups ere compared using Pearson’s X 2 test in bivariate analysis. Variables ith p < 0.05 were considered statistically significant. To determine the robability of unfavourable outcomes among variables, frailty Cox pro- ortional hazards model was conducted. The frailty model was used ecause this model considers within-group variability and accounts for eterogeneity as well as the time factor. We accounted for variability t the 12 different health facilities. We further conducted a sub-analysis or death as this was seen to be the most unfavourable outcome. Sur- ival analysis for the unfavourable outcome death was conducted as a econdary analysis for phase of treatment variables. esults ociodemographic characteristics Table 1 provides characteristics of the patients that were enrolled in B treatment. A total of 1,792 TB patients were enrolled in TB treat- ent in 12 health facilities with 70.1% (1,257) being males. The mean ge of the patients was 45.8 years, with an age range of 2 years to 94 ears. We categorized the patients into three age groups of 19 years and elow (71, 4.0%), 20 to 59 years (1285, 71.7%), 60 years and above 436, 24.3 %). Less than half of the patients were unemployed (n = 817, 5.6%) while 568 (31.7%) were mine workers and 407 (22.7%) had ther occupations. More than three quarters of the patients had pul- onary TB (n = 1,381, 77.1 %). Most patients were registered as being n the initiation phase of treatment (phase 1) (n = 1,157, 64.6%). Half http://www.lesotho-info.co.za/provinces/town/720 V.D. Ngah, M. Rangoanana, I. Fwemba et al. IJID Regions 6 (2023) 62–67 Table 1 Distribution of socio-demographic characteristics Characteristics N = 1,792 (%) Sex Female 535 29.9 Male 1,257 70.1 Age category ≤ 19Yrs 71 4.0 20-59Yrs 1,285 71.7 ≥ 60Yrs 436 24.3 Occupation Category Employed (non-mine workers) 407 22.7 Employed (mine workers) 568 31.7 Unemployed 817 45.6 Tuberculosis category Extrapulmonary TB 411 22.9 Pulmonary TB 1,381 77.1 Phase of treatment Phase 1 1,157 64.6 Phase 2 635 35.4 Treatment contact Community Health Worker 274 15.3 Family Member 887 49.5 Friend 162 9.0 Unreported 469 26.2 Drug Resistance Resistance 218 12.2 Susceptible 1,574 87.8 Figure 1. Distribution of unfavourable treatment outcomes o ( m a h T p B T 1 c c T n f u T A a s t a ( a p p t p t t c P t w h ( D V b m ( 9 ( t c m t S c 0 3 s D s d t p c y s a t p M b m A c w k f f the patients had a family member as their treatment contact person n = 887, 49.5%), and 26.2% (469) of the patients did not provide infor- ation on their treatment contact. Less than 10% of the patients had friend as their treatment contact (n = 162), and 274 (15.3%) reported aving a community health worker as their treatment contact. reatment outcomes Treatment outcome data were available for 1,781 patients. Eleven atients (0.6%) were transferred out from the 12 health facilities in utha Buthe, and we could not trace their treatment outcome data. hese patients were excluded from overall analysis of outcomes. Of the ,781 patients, 1,369 (76.9%) patients had favourable treatment out- omes. Among those with favourable outcomes, 655 (48.1%) of them ompleted their treatment and 714 (52.5%) were cured. Unfavourable B treatment outcomes were reported in 412 (23.1%) patients. Of this umber 4 (1%) patients defaulted treatment, 12 (2.9%) had treatment ailure and 54 (13.1%) were lost-to-follow up (LTF). The most common nfavourable outcome was death with 342 patients dying after starting B treatment, making up 83% of the unfavourable outcomes ( figure 1 ). 64 ssociation between demographic characteristics and treatment outcomes Table 2 depicts the differences between the outcome measures mong the demographic characteristics of the patients. There was no tatistically significant difference between male and female with regard o the treatment outcomes (p = 0.38). Patients who were 60 years and bove had significantly higher proportion of unfavourable outcomes p < 0.001). There was no statistically significant difference in outcomes mong the different occupation categories (P = 0.50). Patients who had ulmonary TB had better favourable outcomes (79.8%) as compared to atients who had extrapulmonary (20.2%) (p < 0.001). There was a sta- istically significant difference in outcomes between patients who had ulmonary TB and patients who had extrapulmonary TB (p < 0.001). Pa- ients in phase 1 had better favourable outcomes as compared to pa- ients in phase 2. There was a statistically significant difference in out- omes between patients who were in phase 1 and phase 2 (p < 0.001). atients who had their treatment contacts as family members had bet- er treatment outcomes as compared to other groups: community health orker, friend and unknown (p < 0.001). Patients with drug resistant TB ad more favourable outcomes than patients susceptible to treatment p < 0.02). eterminants of unfavourable TB treatment outcomes Table 3 shows the hazard ratios of unfavourable treatment outcomes. ariables with increased hazards of unfavourable outcomes included eing 60 years and older (HR = 2.81, 95%CI 1.82 – 4.33), unemploy- ent (HR = 1.25, 95%CI 1.03 – 1.51) and susceptibility to TB treatment HR = 1.93, 95% CI 1.36 – 2.74). Patients with pulmonary TB (HR 0.57, 5%CI 0.47 – 0.70), having a close relation as their treatment contact family member or friends) (HR = 0.58, 95%CI 0.46 - 0.74) and those in he second phase of treatment (HR = 0.13, 95%CI 0.09 - 0.19) signifi- antly decreased the risk of unfavorable treatment outcomes. Although ales were less likely to have unfavourable outcome, this was not sta- istically significant (HR = 0.8, 95%CI, 0.70 – 1.06). urvival probability of outcome death between phases of treatment Patients in phase 1 of treatment are seen to die at a very fast rate ompared to patients in the second phase of treatment right from day of treatment. Patients in phase 1 had a 50% survival rate at about 0 days (1 month) of treatment while patients in phase two had a 50% urvival rate at about 120 days (4 months) of treatment (p = 0.002). iscussion This study determined unfavourable treatment outcomes and its as- ociated factors among TB patients in Butha Buthe. We further con- ucted a survival analysis for the unfavourable death outcome between he phases of TB treatment. Our study found that almost a quarter of the atients, 23.1%, had unfavourable outcomes with death being the most ommon unfavourable outcome. Our study has shown that patients 60 ears and older, unemployment and drug susceptibility are factors that how an increased risk of having unfavourable treatment outcomes. We lso observed that the risk of dying was higher in patients who were in he initiation phase of the treatment. About 70% of the patients were men. A higher proportion of male TB atients has also been reported in other studies internationally [26–28] . any more men may be diagnosed with TB in this population, probably ecause this is a mining district with many migrant workers that are en who move into the district to work in the mines or worked in South frican mines. Other studies have shown that mines produce favourable onditions for TB infection and disease [16] . The majority of our patients ere aged between 20 and 59 years, which is the working age group also nown as the productive age group. This is in line with other reports rom other sub-Saharan countries [ 26 , 29 ]. The greater proportion of V.D. Ngah, M. Rangoanana, I. Fwemba et al. IJID Regions 6 (2023) 62–67 Figure 2. Survival probability plot between phases of treatment among patients who died Table 2 Bivariate analysis of TB outcomes among demographic characteristics Characteristics Favorable outcome Unfavorable outcomes P value N = 1369 (%) N = 423 (%) Sex: 0.381 Female 401 (29.3) 134 (31.7) Male 968 (70.7) 289 (68.3) Age category < 0.001 ≤ 19 years 49 (3.6) 22 (5.2) 20 – 59 years 1180 (86.2) 105 (24.8) ≥ 60 years 140 (10.2) 296 (70.0) Occupation category 0.506 Employed non-mine workers 317 (23.2) 90 (21.3) Mine worker 438 (32.0) 130 (30.7) Unemployed 614 (44.9) 203 (48.0) Tuberculosis category < 0.001 Extrapulmonary TB 277 (20.2) 134 (31.7) Pulmonary TB 1092 (79.8) 289 (68.3) Phase of treatment < 0.001 Phase 1 767 (56.0) 390 (92.2) Phase 2 602 (44.0) 33 (7.8) Treatment contact < 0.001 Community Health Worker 177 (12.9) 97 (22.9) Family Member 674 (49.2) 213 (50.4) Friend 137 (10.1) 25 (5.9) Unreported 381 (27.8) 88 (20.8) Drug Resistance 0.018 Resistance 181 (13.2) 37 (8.75) Susceptible 1188 (86.8) 386 (91.3) p s t e t E r r c f c i t t u c i l e r r d w o c atients in this age group could be explained due to influx of persons in earch for better economic opportunities. Unfavourable treatment outcomes were reported in 23.1% of the pa- ients, which is higher than the 13.1% stipulated by the WHO [5] . This quates to a favourable outcome of 76.9%. This favourable rate is lower han the 95.1% and the 87.8% reported in Mozambique and Southeast thiopia respectively over a five year period [ 28 , 30 ]. An approximate ate to that in our study of 78.1% over five years was reported in Nige- ia [26] , and a lower pooled estimated rate of 74.4% from 13 European ountries reported over 5 years [31] . Patients who were 60 years and above had a higher risk of un- avourable outcomes. Advanced age has been shown to be a signifi- ant risk factor for poor TB treatment outcomes [ 27 , 32–34 ]. A study n China specifically reported patients older than 60 years having up 65 o four times the odds of unfavourable treatment outcomes compared o younger patients [27] . Older patients would be more susceptible to nwanted treatment outcomes such as treatment failure and death be- ause of the gradual degeneration of their bodies including a waning mmune system [34] . The lack of family support among older persons iving on their own and the inability to access health services would nable treatment defaults and/or loss to follow-up [33] . Patients who were unemployed were observed to have a higher isk of unfavourable treatment outcomes. Similar findings have been eported internationally [35–37] . A six year retrospective study con- ucted in Thailand reported that unemployed pulmonary TB patients ere about 3 times significantly more at risk of unsuccessful treatment utcomes [37] . Unemployed patients do not have a stable source of in- ome, which is an indicator of poverty. Patients in our study with no V.D. Ngah, M. Rangoanana, I. Fwemba et al. IJID Regions 6 (2023) 62–67 Table 3 Frailty Cox proportional hazard model for unfavourable TB outcomes Characteristic Hazard Ratio (95% CI) Age category < 20yrs reference 20-59 yrs. 0.24 0.15 - 0.38 ≥ 60 yrs. 2.81 1.82 - 4.33 TB Category Extrapulmonary reference Pulmonary TB 0.57 0.47 – 0.70 Gender Female reference Male 0.86 0.70 – 1.06 Treatment Contact Community health worker reference Close relations 0.58 0.46 – 0.74 Employment status Employed reference Unemployed 1.25 1.03 – 1.51 Phase of treatment Phase 1 reference Phase 2 0.13 0.09 – 0.19 Drug Resistance Resistance reference Susceptible 1.93 1.36 – 2.74 s t o c b s t c c i f d w T m u t m [ C t h t f s t t T t w t c G b T o c t b w h v h i t w m o i C t o r p a t o t C a e t a t u fi p w u D E L D a s M a a M s t i A a f a H table source of income would probably not be able to afford nutrition o sustain TB treatment, which can lead to poor treatment adherence, r worse, dying from the side effects of the treatment. They also en- ounter challenges with funds for transport to treatment on a monthly asis, which leads to treatment defaulting. An interesting finding in our study was that patients without drug re- istant TB had almost twice the risk of unfavourable outcomes compared o patients with drug resistant TB. The treatment of drug resistant TB is omplex, long, and can sometimes lead to treatment failure or in worse ases death when the treatment becomes too toxic [ 12 , 38 ]. Our find- ngs are therefore contrary to other findings [ 39 , 40 ]. The explanation or these results could be because a majority of the patients in our study id not have drug-resistant TB [87.8%]. As such, most of the patients ith unfavourable outcome were probably those without drug resistant B. Although more than 70% of our patients were diagnosed with pul- onary TB, they were shown to have a significantly decreased risk of nfavourable outcomes compared to those with extrapulmonary TB. Ex- rapulmonary TB is very complex to diagnose and most times there is a isdiagnosis or late diagnosis when the symptoms are already advanced 41 , 42 ]. Late diagnosis and/or misdiagnosis could explain our findings. ontrary to our findings a retrospective cohort study in Benin of the na- ional TB program for one year showed that patients with pulmonary TB ad significantly higher odds of treatment failure and death compared o those with extrapulmonary TB [43] . Death was recorded among 342 [83%] of 412 patients with un- avourable treatment outcomes. This finding is in line with several other tudies conducted in sub-Saharan Africa in which death was reported as he most common unfavourable outcome [ 9 , 28 , 30 , 44 ]. It was observed hat patients seemed to die at a faster rate during the initiation phase of B treatment. Higher rate of death at the start of treatment could be due o late diagnosis, when the disease is already at an advanced stage. This ould be common in the case of extrapulmonary TB, which is difficult o diagnose. The initiation phase of TB treatment is quite intense and ould be harsh on some patients, especially on those with poor nutrition. iven that most patients in our population are unemployed, they proba- ly lack the proper nutrition for their bodies to cope with the treatment. his could be another reason for the high death rate during this phase f treatment. The other reason could be side effects of the treatment onsidering that the immune system of such patients might have been oo weakened by other comorbidities. 66 Our findings are not without limitations. Although data was collected y trained data captures and measures were taken to ensure data entry as as accurate as possible, this was a retrospective review of data from ospital records. As such, the reliability of the data cannot be 100% alidated. Data on level of education, marital status, smoking, and alco- ol consumption are socio-economic variables that were not available n patient’s records. These could introduce bias when assessing risk fac- ors associated with unfavourable conditions. A strength of our study as that we were able to obtain over 95% of all data with very minimal issing data. As such we can conclude that our finding of unfavourable utcomes seemed to occur across clinics in the Butha Buthe district and s useful for future TB programs in this district. onclusion and recommendations To our knowledge, this is the first study evaluating unfavourable TB reatment outcomes and its associated risk factors in the mining district f Butha Buthe, Lesotho. Our study reports an unfavourable outcome ate higher than that set forth by the WHO. The study also revealed that atients 60 years and older are at a higher risk of unfavourable outcomes nd that a majority of patients died during the initiation phase of the reatment. We therefore recommend that for TB treatment programs, lder persons should be prioritized and be assigned a treatment contact hat will follow up with them throughout the course of their treatment. ontact tracing should be intensified and scaled up to identify patients t risk and assess them for TB signs and symptoms. This would improve arly diagnosis for prompt treatment and reduce death in the initia- ion phase of treatment. The follow up of patients on treatment should lso be prioritized in the TB program. Community members should be rained as community health workers who will be dedicated to follow p with patients on treatment to reduce loss to follow up. From our ndings, it is unclear how service delivery is organized and provided to atients who are unemployed. Further research on delivery of services ould be advantageous in improving TB treatment programs for the nemployed. eclarations Ethical Approval: This study was approved by the Human Research thics Committee of Stellenbosch University, and the Ministry of Health esotho. Written permission was obtained from the health facilities. ata was analysed anonymously as patient identifiers were not collected Author Contributions : V.D.N, M.R. and PSN.: conceptualization nd study design; V.D.N., M.R., L.M., S.M., M.M. and R. R.: data acqui- ition. V.D.N, M.R, PSN and I.F: statistical analysis. N.V.D., M.R., I.F., .O. and P.S.N: drafting of manuscript. V.D.N., M.R., I.F., M.O., J.D. nd P.S.N. review and revision the manuscript. All authors read and pproved the final version of the manuscript. Research funding : This work was carried out through funding from RC South Africa Availability of data : Dataset used and/or analysed in the current tudy are available upon reasonable request from the corresponding au- hor. Consent for publication: Not applicable Competing Interest : The authors declare that they have no compet- ng interest cknowledgements We thank the Butha Buthe district health managers for giving us ccess to the various health facilities. The health staff of the health acilities who accommodated us during the process of data collection nd were ready to assist with all our queries. We also thank Ministry of ealth: Disease Control Directorate for their support. V.D. Ngah, M. Rangoanana, I. Fwemba et al. IJID Regions 6 (2023) 62–67 R [ [ [ [ [ [ [ [ [ [ [ [ [ [ [ [ [ [ [ [ [ [ [ [ [ [ [ [ [ [ [ [ [ [ [ eferences [1] World Health Organization. Global tuberculosis report. 2021 Available from: https://www.who.int/publications/i/item/9789240037021 [Accessed 2022 April 4]. 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Pan Afr Med J 2019; 32 (1) . https://www.who.int/publications/i/item/9789240037021 https://apps.who.int/iris/handle/10665/341980 http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0003 http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0004 https://www.who.int/publications/i/item/WHO-HTM-TB-2015.19 https://stoptb.org/assets/documents/resources/publications/acsm/909090_PDF_LR.pdf http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0007 http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0008 http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0009 http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0010 http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0011 http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0012 https://data.worldbank.org/indicator/NY.GDP.PCAP.KD http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0014 http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0016 http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0017 http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0018 http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0019 http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0020 http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0021 http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0022 http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0023 http://apps.who.int/iris/bitstream/handle/10665/44165/9789241547833_eng.pdf;jsessionid=55726609AC458C2C4F3A654E152746E2?sequence=1 http://www.r-inla.org/ http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0026 http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0027 http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0028 http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0029 http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0030 http://erj.ersjournals.com/content/26/3/503.abstract http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0032 http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0033 http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0034 http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0035 http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0036 http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0037 http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0038 http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0039 http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0040 http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0041 http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0042 http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0043 http://refhub.elsevier.com/S2772-7076(22)00156-4/sbref0044 Evaluating determinants of treatment outcomes among tuberculosis patients in the mining district of Butha Buthe, Lesotho Background Methods Study design Study setting Population of study Data collection Treatment outcomes Statistical analysis Results Sociodemographic characteristics Treatment outcomes Association between demographic characteristics and treatment outcomes Determinants of unfavourable TB treatment outcomes Survival probability of outcome death between phases of treatment Discussion Conclusion and recommendations Declarations Acknowledgements References