The health and economic benefits of tests that predict future progression to Tuberculosis disease

Nicolas A. Menzies, Sourya Shrestha, Andrea Parriott, Suzanne M. Marks, Andrew N. Hill, David W. Dowdy, Priya B. Shete, Ted Cohen, Joshua A. Salomon

Research output: Contribution to journalArticlepeer-review


Background: Effective targeting of latent tuberculosis infection (LTBI) treatment requires identifying those most likely to progress to tuberculosis (TB). We estimated the potential health and economic benefits of diagnostics with improved discrimination for LTBI that will progress to TB. Methods: A base case scenario represented current LTBI testing and treatment services in the United States in 2020, with diagnosis via. interferon-gamma release assay (IGRA). Alternative scenarios represented tests with higher positive predictive value (PPV) for future TB but similar price to IGRA, and scenarios that additionally assumed higher treatment initiation and completion. We predicted outcomes using multiple transmission-dynamic models calibrated to different geographic areas and estimated costs from a societal perspective. Results: In 2020, 2.1% (range across model results: 1.1%-3.4%) of individuals with LTBI were predicted to develop TB in their remaining lifetime. For IGRA, we estimated the PPV for future TB as 1.3% (0.6%-1.8%). Relative to IGRA, we estimated a test with 10% PPV would reduce treatment volume by 87% (82%-94%), reduce incremental costs by 30% (15%-52%), and increase quality-adjusted life years by 3% (2%-6%). Cost reductions and health improvements were substantially larger for scenarios in which higher PPV for future TB was associated with greater initiation and completion of treatment. Conclusions: We estimated that tests with better predictive performance would substantially reduce the number of individuals treated to prevent TB but would have a modest impact on incremental costs and health impact of TB prevention services, unless accompanied by greater treatment acceptance and completion.

Original languageEnglish (US)
Pages (from-to)75-83
Number of pages9
Issue number1
StatePublished - Jan 1 2022


  • Latent TB infection
  • Mathematical modeling
  • Tuberculosis
  • United States

ASJC Scopus subject areas

  • Epidemiology


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