The Accuracy of Clinical TB Diagnoses among HIV positive and negative individuals in Zambia: Alternative Diagnoses, Treatment Outcomes, and Decision-Making Factors
Abstract
Despite increasing access to rapid, accurate tuberculosis (TB) diagnostics, 37% (2.5 million) of global TB notifications in 2022 were clinically diagnosed (i.e., lacking bacteriological confirmation). A key challenge in accurately diagnosing TB without bacteriological confirmation is that the clinical and radiological presentation of TB often mimics other conditions. Mounting evidence suggests that a considerable number of clinically diagnosed TB cases represent misdiagnoses, contributing to mortality rates that are 2-5 times higher than in bacteriologically confirmed TB patients. A better understanding of misdiagnoses can improve patient diagnosis and outcomes. Through targeted training and strong mentorship in clinical epidemiology and qualitative/mixed methods research, I will rigorously evaluate the accuracy of clinical TB diagnoses in Zambia, with a focus on characterizing alternative diagnoses, treatment outcomes, and the decision-making factors influencing clinicians. In Aim 1, I will analyze a well-characterized dataset comprising 295 patients initially assigned a clinical TB diagnosis to determine the proportion of persons with clinically diagnosed TB in Zambia that are unlikely to be true cases of TB, stratified by HIV status. In Aim 2, I will undertake a retrospective cohort analysis to compare treatment outcomes in likely TB vs. unlikely TB cases against that of bacteriologically confirmed cases and assess whether this differs by HIV status. In Aim 3, I will conduct in-depth interviews (n=12-20 total) with clinicians at primary, secondary and tertiary public health centers (n=4 total) to describe the factors that influence clinicians to make a clinical TB diagnosis. My career goal is to be an independent physician-scientist who applies clinical epidemiology to improve TB clinical care and programming in SSA. The findings generated from this CFAR award will inform a K43 proposal to develop, implement, and evaluate a toolkit aiding clinicians in minimizing misdiagnoses in Zambia, while improving TB detection and outcomes.