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. 2024 Jul 18;11(8):ofae416.
doi: 10.1093/ofid/ofae416. eCollection 2024 Aug.

Retreatment and Anti-tuberculosis Therapy Outcomes in Brazil Between 2015 and 2022: A Nationwide Study

Affiliations

Retreatment and Anti-tuberculosis Therapy Outcomes in Brazil Between 2015 and 2022: A Nationwide Study

Beatriz Barreto-Duarte et al. Open Forum Infect Dis. .

Abstract

Background: Adherence to anti-tuberculosis treatment (ATT) in Brazil remains a challenge in achieving the goals set by the World Health Organization (WHO). Patients who are lost to follow-up during treatment pose a significant public health problem. This study aimed to investigate the factors associated with unfavorable ATT outcomes among those undergoing retreatment in Brazil.

Methods: We conducted an observational study of patients aged ≥18 years with tuberculosis (TB) reported to the Brazilian National Notifiable Disease Information System between 2015 and 2022. Clinical and epidemiologic variables were compared between the study groups (new cases and retreatment). Regression models identified variables associated with unfavorable outcomes.

Results: Among 743 823 reported TB cases in the study period, 555 632 cases were eligible, consisting of 462 061 new cases and 93 571 undergoing retreatments (44 642 recurrent and 48 929 retreatments after loss to follow-up [RLTFU]). RLTFU (odds ratio [OR], 3.96 [95% confidence interval {CI}, 3.83-4.1]) was a significant risk factor for any type of unfavorable ATT. Furthermore, RLTFU (OR, 4.93 [95% CI, 4.76-5.11]) was the main risk factor for subsequent LTFU. For death, aside from advanced age, living with HIV (OR, 6.28 [95% CI, 6.03-6.54]) was the top risk factor.

Conclusions: Retreatment is a substantial risk factor for unfavorable ATT outcomes, especially after LTFU. The rates of treatment success in RLTFU are distant from the WHO End TB Strategy targets throughout Brazil. These findings underscore the need for targeted interventions to improve treatment adherence and outcomes in persons who experience RLTFU.

Keywords: epidemiology; loss to follow-up; retreatment; treatment outcome; tuberculosis.

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Conflict of interest statement

Potential conflicts of interest. All authors: No reported conflicts.

Figures

Figure 1.
Figure 1.
Flowchart of tuberculosis (TB) cases notified in Brazil between 2015 and 2021, stratified according to the history of prior TB and anti-TB therapy. Abbreviations: HCU, healthcare unit; RLTFU, retreatment after loss to follow-up; SINAN, Brazilian Tuberculosis Database System.
Figure 2.
Figure 2.
Distribution of tuberculosis (TB) treatment outcomes, stratified according to entry mode in the healthcare system. Sankey diagrams show frequencies of each TB treatment outcome in the Brazilian Tuberculosis Database System (SINAN) registry of TB cases identified between 2015 and 2022 among new cases (A), retreatment cases (B), TB cases reported among retreatment after loss to follow-up (C), and recurrent cases (a case with a previous history of TB cure) (D). Loss to follow-up: the patient has taken >30 consecutive days to return to a treatment unit after the expected return date; unfavorable outcome: TB treatment failure (positive sputum smear results remain until the end of treatment); death: the knowledge of a patient's death during treatment.
Figure 3.
Figure 3.
Results from the logistic regression model quantifying the associations between various risk factors for unfavorable treatment outcomes in the overall population of the study. We adjusted the model for social vulnerabilities: homelessness, pregnancy, immigration incarceration, and healthcare work. Each feature represents an independent association removing the effect of the other features in the model. Abbreviations: COVID-19, coronavirus disease 2019; DOT, directly observed treatment; HIV, human immunodeficiency virus; LB, lower boundary of the 95% confidence interval; OR, odds ratio; RLTFU, retreatment after loss to follow-up; UB, upper boundary of the 95% confidence interval.
Figure 4.
Figure 4.
Results from multinomial regression models to quantify the associations between risk factors for death and loss to follow-up in the overall study population. We adjusted the model for social vulnerabilities: homelessness, pregnancy, immigration incarceration, and healthcare work. Each feature represents an independent association removing the effect of the other features in the model. Abbreviations: COVID-19, coronavirus disease 2019; DOT, directly observed treatment; HIV, human immunodeficiency virus; LB, lower boundary of the 95% confidence interval; LTFU, loss to follow-up; OR, odds ratio; RLTFU, retreatment after loss to follow-up; UB, upper boundary of the 95% confidence interval.

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