BMJ Global Health (Jan 2023)

Prevalence and predictive factors of tuberculosis treatment interruption in the Asia region: a systematic review and meta-analysis

  • Ian CK Wong,
  • Ai Ling Oh,
  • Mohd Makmor-Bakry,
  • Farida Islahudin

DOI
https://doi.org/10.1136/bmjgh-2022-010592
Journal volume & issue
Vol. 8, no. 1

Abstract

Read online

Introduction Tuberculosis (TB) treatment interruption remains a critical challenge leading to poor treatment outcomes. Two-thirds of global new TB cases are mostly contributed by Asian countries, prompting systematic analysis of predictors for treatment interruption due to the variable findings.Methods Articles published from 2012 to 2021 were searched through seven databases. Studies that established the relationship for risk factors of TB treatment interruption among adult Asian were included. Relevant articles were screened, extracted and appraised using Joanna Briggs Institute’s checklists for cohort, case–control and cross-sectional study designs by three reviewers. Meta-analysis was performed using the random effect model in Review Manager software. The pooled prevalence and predictors of treatment interruption were expressed in ORs with 95% CIs; heterogeneity was assessed using the I2 statistic. The publication bias was visually inspected using the funnel plot.Results Fifty eligible studies (658 304 participants) from 17 Asian countries were included. The overall pooled prevalence of treatment interruption was 17% (95% CI 16% to 18%), the highest in Southern Asia (22% (95% CI 16% to 29%)), followed by Eastern Asia (18% (95% CI 16% to 20%)) and South East Asia (16% (95% CI 4% to 28%)). Seven predictors were identified to increase the risk of treatment interruption, namely, male gender (OR 1.38 (95% CI 1.26 to 1.51)), employment (OR 1.43 (95% CI 1.11 to 1.84)), alcohol intake (OR 2.24 (95% CI 1.58 to 3.18)), smoking (OR 2.74 (95% CI 1.98 to 3.78)), HIV-positive (OR 1.50 (95% CI 1.15 to 1.96)), adverse drug reactions (OR 2.01 (95% CI 1.20 to 3.34)) and previously treated cases (OR 1.77 (95% CI 1.39 to 2.26)). All predictors demonstrated substantial heterogeneity except employment and HIV status with no publication bias.Conclusion The identification of predictors for TB treatment interruption enables strategised planning and collective intervention to be targeted at the high-risk groups to strengthen TB care and control in the Asia region.