A major goal of tuberculosis (TB) epidemiological studies is to obtain results that can be generalized to the larger population with TB. The ability to extrapolate findings on the determinants of TB treatment outcomes is also important. We compared baseline clinical and demographic characteristics and determinants of anti-TB treatment outcomes between persons enrolled in the Regional Prospective Observational Research in Tuberculosis (RePORT)-Brazil cohort between June 2015 and June 2019, and the registry of TB cases reported to the Brazilian National TB Program (Information System for Notifiable Diseases [SINAN]) during the same time period. Multivariable regression models adjusted for the study site were performed using second-generation p-values, a novel statistical approach. Associations with unfavorable treatment outcomes were tested for both RePORT-Brazil and SINAN cohorts. A total of 1,060 culture-confirmed TB patients were enrolled in RePORT-Brazil and 455,873 TB cases were reported to SINAN. Second-generation p-value analyses revealed that the cohorts were strikingly similar with regard to sex, age, use of antiretroviral therapy and positive initial smear sputum microscopy. However, diabetes, HIV infection, and smoking were more frequently documented in RePORT-Brazil. Illicit drug use, the presence of diabetes, and history of prior TB were associated with unfavorable TB treatment outcomes; illicit drug use was associated with such outcomes in both cohorts. There were important similarities in demographic characteristics and determinants of clinical outcomes between the RePORT-Brazil cohort and the Brazilian National registry of TB cases.

Measurement errors are present in many data collection procedures and can harm analyses by biasing estimates. To correct for measurement error, researchers often validate a subsample of records and then incorporate the information learned from this validation sample into estimation. In practice, the validation sample is often selected using simple random sampling (SRS). However, SRS leads to inefficient estimates because it ignores information on the error-prone variables, which can be highly correlated to the unknown truth. Applying and extending ideas from the two-phase sampling literature, we propose optimal and nearly optimal designs for selecting the validation sample in the classical measurement-error framework. We target designs to improve the efficiency of model-based and design-based estimators, and show how the resulting designs compare to each other. Our results suggest that sampling schemes that extract more information from the error-prone data are substantially more efficient than SRS, for both design- and model-based estimators. The optimal procedure, however, depends on the analysis method, and can differ substantially. This is supported by theory and simulations. We illustrate the various designs using data from an HIV cohort study.

Background: Genetic polymorphisms have been associated with risk of antituberculosis treatment toxicity. We characterized associations with adverse events and treatment failure/recurrence among adults treated for tuberculosis in Brazil. Methods: Participants were followed in Regional Prospective Observational Research in Tuberculosis (RePORT)-Brazil. We included persons with culture-confirmed drug-susceptible pulmonary tuberculosis who started treatment between 2015 and 2019, and who were eligible for pharmacogenetics. Treatment included 2 months of isoniazid, rifampin or rifabutin, pyrazinamide, and ethambutol, then 4 months of isoniazid and rifampin or rifabutin, with 24-month follow-up. Analyses included 43 polymorphisms in 20 genes related to antituberculosis drug hepatotoxicity or pharmacokinetics. Whole exome sequencing was done in a case-control toxicity subset. Results: Among 903 participants in multivariable genetic association analyses, NAT2 slow acetylator status was associated with increased risk of treatment-related grade 2 or greater adverse events, including hepatotoxicity. Treatment failure/recurrence was more likely among NAT2 rapid acetylators, but not statistically significant at the 5% level. A GSTM1 polymorphism (rs412543) was associated with increased risk of treatment-related adverse events, including hepatotoxicity. SLCO1B1 polymorphisms were associated with increased risk of treatment-related hepatoxicity and treatment failure/recurrence. Polymorphisms in NR1/2 were associated with decreased risk of adverse events and increased risk of failure/recurrence. In whole exome sequencing, hepatotoxicity was associated with a polymorphism in VTI1A, and the genes METTL17 and PRSS57, but none achieved genome-wide significance. Conclusion: In a clinical cohort representing three regions of Brazil, NAT2 acetylator status was associated with risk for treatment-related adverse events. Additional significant polymorphisms merit investigation in larger study populations, particularly regarding risk of treatment failure/recurrence.

Diagnosis of M. tuberculosis (Mtb) infection in close contacts is critical for TB control. Smoking is a risk factor for Mtb infection and TB disease but its effect on longitudinal interferon-gamma release assay (IGRA) results remains unknown. We conducted a multi-site prospective study in Brazil between 2015-2019, among close contacts of adults with culture-confirmed pulmonary TB. IGRA was performed at baseline, month 6 if negative at baseline, and month 24-30 after enrollment. IGRA results were categorized as IGRA-positive (maintained from baseline to last visit), IGRA-conversion (from negative to positive at any time), IGRA-reversion (from positive to negative at any time), and IGRA-negative (maintained from baseline to last visit). Associations between IGRA results and smoking status at baseline (current/former vs never) in contacts were evaluated using propensity score-adjusted logistic regression models. Estimated propensity score was used as a covariate in models, which regressed the outcome (IGRA-positive, IGRA-conversion, IGRA-reversion) on smoking status. Of 430 close contacts, 89 (21%) were IGRA-positive, 30 (7%) were converters, 30 (7%) were reverters and 22 were indeterminate. Smoking frequency was 26 (29%) among IGRA-positive contacts, 7 (23%) in converters, and 3 (10%) in reverters. Smoking in contacts was associated with lower odds of IGRA-reversion (adjusted odds ratio = 0.16; 95% confidence interval = [0.03-0.70]). We did not detect associations between smoking and IGRA-positive or IGRA-conversion. Our findings highlight the importance of smoking on longitudinal IGRA results. This has implications for clinical care and clinical trials in which IGRA status is monitored or used as an outcome.