Observational studyClinical infectious diseases : an official publication of the Infectious Diseases Society of America2026
Characterizing Treatment Adherence Trajectories in the endTB Multisite Cohort of Drug-Resistant Tuberculosis Patients: An Application of Group-Based Trajectory Modeling.
Observational study in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Tuberculosis Disease Severity Assessment Using Clinical Variables and Radiology Enabled by Artificial Intelligence.The Journal of infectious diseases · 2026Article
- A Retrospective Analysis Examining the Impact of Educational Attainment and Social Determinants of Health on Rifampicin-Resistant Tuberculosis Treatment Outcomes.Open forum infectious diseases · 2026Article
- Non-Adherence to Anti-Tuberculosis Treatment and Its Determinants Among Tuberculosis Patients in Tanzania.Journal of community health · 2026Article
- Treatment Adherence With an Oral 9-Month Regimen for Rifampicin-Resistant Tuberculosis in South Africa.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2026Observational
- Measurement of Tuberculosis treatment adherence: A methodological scoping review of observational studies.PLOS global public health · 2026Article
- Effect of smoking on drug-resistant tuberculosis treatment outcomes and potential mechanistic pathways: a multicountry cohort study.BMJ open respiratory research · 2025Observational
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Authors and funding
22 authors.
Funding
Abstract
backgroundIn tuberculosis (TB) care, adherence is often assessed using a simple 80% threshold, which may overlook meaningful patterns. We analyzed adherence trajectories among individuals treated for rifampicin- or multidrug-resistant TB (RR/MDR-TB) in the endTB observational study to identify more informative patterns.
methodsWe applied a joint latent class mixed model to classify adherence trajectories and assess their relationship with treatment outcomes. Model performance was compared to common classification methods (eg 80% adherence threshold) using Kendall's τb and area under the receiver operating curve for predicting unsuccessful outcomes.
resultsAmong 1787 individuals, we identified 4 adherence patterns: "consistently high" (72.5%), "high to low" (14.3%), "low to high" (7.3%), and "consistently low" (5.9%). Compared to the "consistently high" group, those in "high to low" (hazard ratio [HR] = 23.2; 95% confidence interval [CI]: 15.7-24.3) and "consistently low" (HR = 43.2; 95% CI: 26.2-71.5) groups had significantly higher risk of unsuccessful outcomes, while the "low to high" group did not (HR = 0.7; 95% CI: .1-3.8). Our trajectory model more accurately predicted outcomes than common classification methods (P < .01).
conclusionsGroup-based trajectory modeling provides more nuanced insights into adherence patterns than conventional classification methods. Our findings demonstrate that patients with RR/MDR-TB who exhibited initial poor adherence followed by subsequent improvement achieved clinical outcomes comparable to those with consistently high adherence throughout treatment. This finding challenges the prevailing assumption that sustained high adherence is necessary for treatment success, suggesting that adherence patterns, rather than overall adherence rates, may be more predictive of clinical outcomes in the management of RR/MDR-TB.
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