Clinical and epidemiological characteristics associated with unfavorable tuberculosis treatment outcomes in TB-HIV co-infected patients in Brazil: a hierarchical polytomous analysis

Abstract

Background: TB patients co-infected with HIV have worse treatment outcomes than non-coinfected patients. How clinical characteristics of TB and socioeconomic characteristics influence these outcomes is poorly understood. Here, we use polytomous regression analysis to identify clinical and epidemiological characteristics associated with unfavorable treatment outcomes among TB-HIV co-infected patients in Brazil.

Methods: TB-HIV cases reported in the Brazilian information system (SINAN) between January 1, 2001 and December 31, 2011 were identified and categorized by TB treatment outcome (cure, default, death, and development of MDR TB). We modeled treatment outcome as a function of clinical characteristics of TB and patient socioeconomic characteristics by polytomous regression analysis. For each treatment outcome, we used cure as the reference outcome.

Results: Between 2001 and 2011, 990,017 cases of TB were reported in SINAN, of which 93,147 (9.4%) were HIV co-infected. Patients aged 15-19 (OR=2.86; 95% CI: 2.09-3.91) and 20-39 years old (OR=2.30; 95% CI: 1.81-2.92) were more likely to default on TB treatment than those aged 0-14 years old. In contrast, patients aged ≥60 years were more likely to die from TB (OR=2.22; 95% CI: 1.43-3.44) or other causes (OR=2.86; 95% CI: 2.14-3.83). Black patients were more likely to default on TB treatment (OR=1.33; 95% CI: 1.22-1.44) and die from TB (OR=1.50; 95% CI: 1.29-1.74). Finally, alcoholism was associated with all unfavorable outcomes: default (OR=1.94; 95% CI: 1.73-2.17), death due to TB (OR=1.46; 95% CI: 1.25-1.71), death due to other causes (OR=1.38; 95% CI: 1.21-1.57) and MDR-TB (OR=2.29; 95% CI: 1.46-3.58).

Conclusions: Socio-economic vulnerability has a significant effect on treatment outcomes among TB-HIV co-infected patients in Brazil. Enhancing social support, incorporation of alcohol abuse screening and counseling into current TB surveillance programs and targeting interventions to specific age groups are interventions that could improve treatment outcomes.

Keywords: Coinfection; HIV; Logistic regression; Tuberculosis.

Fig. 1

Study flow diagram for selection of patients included in our study.