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Bacterial Factors That Predict Relapse after Tuberculosis Therapy.

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The New England Journal of Medicine
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Higher minimum inhibitory concentrations (MICs) of isoniazid and rifampin in Mycobacterium tuberculosis pretreatment isolates predict a greater risk of tuberculosis relapse. This finding aids in identifying patients at higher risk for treatment failure.

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Area of Science:

  • Microbiology
  • Infectious Diseases
  • Pharmacology

Background:

  • Tuberculosis (TB) relapse occurs in approximately 5% of patients after 6 months of first-line therapy and 20% after short-course therapy.
  • Investigating pretreatment Mycobacterium tuberculosis (M. tuberculosis) isolates may reveal correlations between drug susceptibility and relapse risk.

Purpose of the Study:

  • To determine if minimum inhibitory concentrations (MICs) of isoniazid and rifampin below standard resistance breakpoints correlate with the risk of TB relapse.
  • To develop predictive models for TB relapse based on drug susceptibility testing.

Main Methods:

  • Analyzed M. tuberculosis isolates from patients in the Tuberculosis Trials Consortium Study 22 (development cohort) and DMID 01-009 study (validation cohort).
  • Determined MIC values for isoniazid and rifampin below standard resistance breakpoints.
  • Developed and validated predictive relapse models using MIC values, clinical, radiologic, and laboratory data.

Main Results:

  • Higher mean MICs of isoniazid (1.17-fold) and rifampin (1.53-fold) were observed in the relapse group compared to the cure group (P=0.02 and P<0.001, respectively).
  • MIC values were significantly associated with relapse in multivariable analyses.
  • Predictive models incorporating MIC values demonstrated high accuracy, with Area Under the Curve (AUC) values ranging from 0.779 to 0.964 across cohorts.

Conclusions:

  • Pretreatment M. tuberculosis isolates with higher MICs of isoniazid or rifampin below resistance breakpoints are associated with an increased risk of TB relapse.
  • Drug susceptibility testing of pretreatment isolates can aid in predicting TB treatment outcomes.