Lung Cancer Incidence Trends in South Africa from 2011 to 2022 and Investigation of Non- Small Cell Lung Cancer Biomarkers Using Rule-Based Natural Language Processing

Abstract

Background: Lung cancer is the leading cancer in men and second in women worldwide. Biomarkers play a critical role in lung cancer diagnosis, prognosis, and treatment, guiding therapeutic decisions and enabling personalised medicine. This study aimed to evaluate lung cancer trends from 2011 to 2022 using data from the pathology-based National Cancer Registry of South Africa (NCR-SA). Additionally, the study employed rule-based Natural Language Processing (NLP) techniques to automate the extraction of biomarkers from pathology reports and analysed their prevalence rates. Methods: We conducted a cross-sectional study; using pathologically confirmed lung cancer data from NCR- SA. Using the Segi world standard population and mid-year population estimates from Statistics South Africa (StatsSA), we calculated the Age-Standardised Incidence Rates (ASIR). We computed annual percentage change (APC) and 95% confidence intervals (CI) to analyse lung cancer trends using Joinpoint regression. Rule-based Natural Language Processing (NLP) was used to extract biomarkers from pathology reports of Non-Small Cell Lung Cancer (NSCLC) cases. The algorithm’s performance was evaluated using precision, recall, and F1 score on manually annotated pathology reports. The prevalence of these biomarkers was analysed. Results: Lung cancer remains a major health concern in South Africa (SA), with 54,405 cases diagnosed between 2011 and 2022, comprising 46,661 NSCLC cases (85.8%) and 4,607 SCLC cases (8.5%). Males accounted for 61.7% of cases. White patients (48.0%) had the highest proportion, followed by Black (28.0%), Coloureds (18.0%), and Indian/Asian (4.0%) patients. Private hospitals diagnosed 64.0% of cases. Lung cancer incidence increased by 2.1%, with notable declines in 2017–2020, followed by a rise in 2020–2022. Among 46,160 NSCLC cases, adenocarcinoma (58.4%) was the most common, followed by squamous cell carcinoma (23.6%), unclassified NSCLC (12.5%), and large cell carcinoma (5.5%). Biomarker extraction showed high precision, with 22 biomarkers identified, including 14 diagnostics and 8 predictive biomarkers. Diagnostic biomarkers appeared in 92.2% of reports, while predictive biomarkers were reported in only 7.8%, reflecting gaps in molecular testing. TTF1 (28.0%), CK7 (22.0%), and Napsin A (11.4%) were the most tested diagnostic biomarkers. Predictive biomarkers, including PD-L1 (1.8%) and EGFR (1.1%), had lower testing rates, particularly in public hospitals, where EGFR and PD-L1 testing were nearly absent compared to private hospitals. v Conclusion: Lung cancer incidence in SA declined from 2015 to 2020, possibly due to smoking regulations. However, racial disparities persist, with Whites having the highest lung cancer incidence. These disparities likely reflect differences in diagnostic access, varying smoking prevalence rates among racial groups, and socioeconomic differences in the populations that use private healthcare. Diagnostic biomarkers are widely used in clinical practice, whereas predictive biomarkers have lower positivity rates, indicating limited availability. Expanding biomarker testing is essential for early detection, treatment optimisation, and broader adoption of personalised immunotherapy in SA.