TB Research

Isoniazid (INH) mono-resistance and tuberculosis (TB) treatment success: analysis of European surveillance data, 2002 to 2014

Basel Karo, Anke Kohlenberg, Vahur Hollo, Raquel Duarte, Lena Fiebig, Sarah Jackson, Cathriona Kearns, Csaba Ködmön, et al. (13 authors)

Eurosurveillance · 2019-03

Abstract

INTRODUCTION: Isoniazid (INH) is an essential drug for tuberculosis (TB) treatment. Resistance to INH may increase the likelihood of negative treatment outcome. AIM: We aimed to determine the impact of INH mono-resistance on TB treatment outcome in the European Union/European Economic Area and to identify risk factors for unsuccessful outcome in cases with INH mono-resistant TB. METHODS: In this observational study, we retrospectively analysed TB cases that were diagnosed in 2002-14 and included in the European Surveillance System (TESSy). Multilevel logistic regression models were applied to identify risk factors and correct for clustering of cases within countries. RESULTS: A total of 187,370 susceptible and 7,578 INH mono-resistant TB cases from 24 countries were included in the outcome analysis. Treatment was successful in 74.0% of INH mono-resistant and 77.4% of susceptible TB cases. In the final model, treatment success was lower among INH mono-resistant cases (Odds ratio (OR): 0.7; 95% confidence interval (CI): 0.6-0.9; adjusted absolute difference in treatment success: 5.3%). Among INH mono-resistant TB cases, unsuccessful treatment outcome was associated with age above median (OR: 1.3; 95% CI: 1.2-1.5), male sex (OR: 1.3; 95% CI: 1.1-1.4), positive smear microscopy (OR: 1.3; 95% CI: 1.1-1.4), positive HIV status (OR: 3.3; 95% CI: 1.6-6.5) and a prior TB history (OR: 1.8; 95% CI: 1.5-2.2). CONCLUSIONS: This study provides evidence for an association between INH mono-resistance and a lower likelihood of TB treatment success. Increased attention should be paid to timely detection and management of INH mono-resistant TB.

MeSH terms

  • Medicine
  • Isoniazid
  • Odds ratio
  • Tuberculosis
  • Internal medicine
  • Confidence interval
  • Logistic regression
  • Drug resistance