A Quantitative Benefit-Risk Analysis of Isoniazid for Treatment of Latent Tuberculosis Infection Using Incremental Benefit Framework

Jan 1, 2013, 00:00 AM
10.1016/j.jval.2012.09.006
https://www.valueinhealthjournal.com/article/S1098-3015(12)04131-9/fulltext
Section Title : Economic Evaluation
Section Order : 21
First Page : 66

Background

We undertook a quantitative benefit-risk analysis of a targeted isoniazid (INH) therapy for latent tuberculosis (TB) infection for different groups of contacts of active TB cases.

Methods

We developed a decision-analytic model to compare the treatment of latent TB infection in subgroups of contacts to no treatment over a 6-year time horizon in a Canadian setting. Contacts were stratified into 32 groups on the basis of five binary variables: type of contact (close or casual), tuberculin skin test (TST) results (positive or negative at 5 mm cutoff), Bacillus Calmette-Guérin vaccination status, place of birth (foreign- or Canadian-born), and age group (cutoff 35 years). Risk of TB reactivation was calculated for each subgroup from a longitudinal registry of contacts, adjusted for several potential confounders and comorbid conditions. We calculated the quality-adjusted life-years gained because of delayed or prevention of active TB via treatment of latent TB infection versus quality-adjusted life-years lost because of the adverse events to INH.

Results

A targeted policy based on adopting INH therapy only in subgroups with positive expected incremental net health benefit resulted in a different treatment decision than the current guidelines in five subgroups comprising 3.9% of the contacts. Namely, the targeted policy comprised no INH therapy in casual contacts with a positive vaccination history even with a positive TST result and INH therapy in foreign-born close contacts younger than 35 years even with a negative TST result.

Conclusions

From a benefit-risk viewpoint, INH treatment of contacts should be tailored on the basis of risk assessment algorithms that consider a range of factors at the time of screening.

https://www.valueinhealthjournal.com/action/showCitFormats?pii=S1098-3015(12)04131-9&doi=10.1016/j.jval.2012.09.006
HEOR Topics :
  • Infectious Disease
  • Methodological & Statistical Research
  • Modeling and simulation
  • Respiratory-Related Disorders
  • Specific Diseases & Conditions
Tags :
  • benefit-risk analysis
  • decision uncertainty
  • quality-adjusted life-years
  • tuberculosis
Regions :
  • North America