How Endpoint Definitions Shape Epidemiologic Inference on Tuberculosis Treatment Outcomes: A Secondary Analysis from Lima, Peru
Year: 2026
Type: article
Abstract: BACKGROUND/OBJECTIVES: Tuberculosis treatment outcomes are often dichotomized into heterogeneous composites that may obscure outcome-specific associations. We compared baseline characteristics across mutually exclusive out-comes-loss to follow-up (LTFU), death, and not evaluated/transferred versus documented cure-and examined the composite endpoints secondarily in a prospective cohort of adults with smear-positive pulmonary tuberculosis treated in Lima, Peru, in 2010-2011. METHODS: The complete-case cohort included 1233 participants. The primary analysis used ridge-penalized multinomial logistic regression (lambda = 0.16); a mean bias-reduced multinomial model assessed sparse-data sensitivity. RESULTS: Overall, 1016 participants were cured, 127 experienced LTFU, 30 died, and 60 were not evaluated/transferred. Drug use was associated primarily with LTFU (aOR 4.15; 95% CI 2.55-6.75), whereas HIV-positive status showed the largest, although imprecisely estimated, association with death (aOR 32.12; 95% CI 8.95-115.33; six deaths among 22 HIV-positive participants). The bias-reduced estimate was similar (aOR 35.56; 95% CI 9.80-129.08). Multidrug-resistant tuberculosis was associated with several non-cure categories; its association with the combined not evaluated/transferred category was largely driven by participants still in treatment at database closure. Composite endpoints changed the magnitude and interpretation of several associations and did not eliminate sparse outcome-exposure cells. CONCLUSIONS: Endpoint definitions therefore materially shaped epidemiologic inference. Dis-aggregated outcomes should be reported alongside composite indicators, and findings from this historical cohort should not be interpreted as contemporary risk estimates for Lima.
Source: Infectious Disease Reports
DOI: 10.3390/idr18050108
Institution: National University Toribio Rodríguez de Mendoza
Language: English
Subfield: Infectious Diseases
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,172
OpenAlex ID: W7214572573