Systematic differences in TB treatment outcomes across Brazil by patient- and area-related factors: an analysis of national disease registry data.

BACKGROUND: Many individuals initiating tuberculosis (TB) treatment do not successfully complete the regimen. Understanding variation in treatment outcomes could reveal opportunities to improve the effectiveness of TB treatment services. METHODS: We extracted data on treatment outcomes and patient covariates from Brazil's National Disease Notification Information System, for new TB patients diagnosed during 2015-2018. We analysed whether or not patients experienced an unsuccessful treatment outcome (any death on treatment, loss to follow-up or treatment failure). We constructed a statistical model (logistic regression with regularised two-way interactions) to predict treatment outcomes as a function of socio-demographic factors, co-prevalent health conditions, health behaviours, membership of vulnerable populations and form of TB disease. We used this model to decompose state- and municipality-level variation in treatment outcomes into differences attributable to patient-level and area-level factors. RESULTS: Treatment outcomes data for 259 449 individuals were used for the analysis. Across Brazilian states, variation in unsuccessful treatment due to patient-level factors was substantially less than variation due to area-level factors, with the difference between best and worst performing states (lowest and highest fraction with unsuccessful treatment, respectively) equal to 7.1 and 13.3 percentage points for patient-level and area-level factors. Similar results were estimated at the municipality level, with 9.3 percentage points separating best and worst performing municipalities according to patient-level factors, and 20.5 percentage points separating best and worst performing municipalities to area-level factors. Results were similar when we analysed loss to follow-up as an outcome. CONCLUSIONS: Our analysis revealed substantial variation in TB treatment outcomes across states and municipalities, with only a minority attributable to patient-level factors. Area-level variation likely reflects consequences of differences in health system organisation or socio-environmental factors not reflected in patient-level data. Further research on these factors is needed to identify effective approaches to TB care, reduce geographic disparities and improve treatment outcome.