Work

Causal inference methodologies to assess the effect of missed clinic visits on treatment success rate among people with tuberculosis in rural Uganda

Year: 2025

Type: article

Abstract: BACKGROUND: Although randomized controlled trials are the gold standard design for cause-effect analysis, high costs and challenges around practicability, feasibility, and ethics may limit their use. In such situations, causal inference methods can improve the rigor of cause-effect analysis using observational data but such methods have infrequently been applied in tuberculosis (TB) research. We conducted a parallel comparison across three causal inference methods in order to assess the causal association between missed clinic visit/s and treatment success among people with drug-susceptible bacteriologically confirmed pulmonary TB. METHODS: We used causal inference methods to analyze cross-sectional data of adults with drug-susceptible bacteriologically confirmed pulmonary TB at clinics in rural eastern Uganda. We compared effect estimates from three causal inference methods, namely instrumental variable analysis, propensity-score analysis (adjustment, matching, weighting, and stratification), and double-robust estimation for cause-effect analysis. The exposure was missing a TB clinic visit/s and the outcome was treatment success defined as cure or treatment completion, both measured on a binary scale. Covariates were selected based on the literature, and their social and biological relevance to the outcome. We report the odds ratio and 95% confidence interval from each causal analysis. RESULTS: Of 762 participants (mean age of 39.3 ± 15.8 years) included, 186 (24.4%) had missed a clinic visit/s while 687 (90.2%) were successfully treated for TB. Missed clinic visit/s lowered treatment success across all analyses with instrumental variable analysis (OR 0.41, 95% CI 0.20-0.82), propensity-score analysis (adjustment [OR 0.49, 95% CI 0.30-0.82], matching [OR 0.43, 95% CI 0.21-0.91)], weighting [OR 0.52, 95% CI 0.30-0.91], and stratification [OR 0.34, 95% CI 0.19-0.62]), and double-robust estimation (OR 0.49, 95% CI 0.28-0.85). CONCLUSIONS: Missed clinic visit/s reduced the likelihood of TB treatment success rate across all causal inference methods, supporting a causal relationship. Studies are needed to examine interventions that enhance retention in TB treatment.

Source: BMC Medical Research Methodology

DOI: 10.1186/s12874-025-02553-x

Authors: Jonathan Izudi, Adithya Cattamanchi, Francis Bajunirwe

Institutions: Mbarara University of Science and Technology, San Francisco General Hospital, University of California, San Francisco, University of California, Irvine

Language: English

Topic: Advanced Causal Inference Techniques

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,090