A quantitative benefit-risk analysis of isoniazid for treatment of latent tuberculosis infection using incremental benefit framework.

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A quantitative benefit-risk analysis of isoniazid for treatment of latent tuberculosis infection using incremental benefit framework.

Value Health. 2013 Jan-Feb;16(1):66-75

Authors: Sadatsafavi M, Marra C, Marra F, Moran O, FitzGerald JM, Lynd L

Abstract
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.

PMID: 23337217 [PubMed - indexed for MEDLINE]

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