Bedaquiline Adherence Predicts Retention-in-Care in Patients With Drug-Resistant Tuberculosis and HIV

Abstract RATIONALE: While non-adherence to medication is a well-known challenge in multidrug-resistant tuberculosis (MDR-TB) treatment, the link between adherence and loss to retention in care remains underexplored in high-burden settings. Adherence has been difficult to study due to the lack of real-time monitoring tools. With the adoption of bedaquiline (BDQ)-based all-oral regimens, research is crucial to identifying populations at higher risk of treatment interruption. We hypothesized that adherence measured using mHealth will predict retention in care, and pill-to-pill BDQ adherence will be independently associated with retention in care. METHODS: People with MDR-TB and HIV on ART starting BDQ-based regimens were prospectively enrolled from 2016 to 2020 in South Africa. BDQ adherence was measured using electronic dose monitoring (Wisepill RT2000) for 6 months, and participants were followed monthly until treatment completion (up to 24 months). Adherence was estimated based on recorded versus expected pill box openings and 6-month cumulative adherence was classified as low (<90%) or high (≥90%). Stratified Kaplan-Meier analysis was performed with differences assessed using log-rank p test. Logistic regression identified the effect of adherence on end-of-treatment retention, with the model's strength of association calculated using ROC analysis. Cox proportional hazards were utilized to predict the risk of non-retention, with adherence as a covariate among other confounders gathered from prior literature. RESULTS: Patients with high BDQ adherence had significantly better retention in care (89%) compared to those with lower adherence (66%) (p < 0.0001) at the end of treatment. Although adherence was assessed over the first six months, the gap in retention continued to widen. Logistic regression suggested that higher cumulative adherence strongly predicted end-of-treatment retention, with an odds ratio of 1.05 (95% CI 1.038-1.083) per percentile increase in adherence and an AUC of 0.759, indicating good model accuracy. Key confounders, including DOT presence, severe adverse effects, age, gender, and socioeconomic factors, were also identified. After adjustment, both higher adherence and older age significantly reduced loss to retention in care (p = 0.018 and p = 0.006, respectively). CONCLUSIONS: Our findings underscore the pivotal role of adherence in MDR-TB treatment. High BDQ adherence not only serves as a strong predictor of MDR-TB treatment outcome but also identifies individuals at risk for loss of retention in care. Early identification of adherence challenges can help direct interventions to support adherence and may reduce risks of treatment failure, drug resistance, and mortality associated with MDR-TB.