Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2012 Mar;54(6):784-91.
doi: 10.1093/cid/cir951. Epub 2012 Jan 19.

Risk of progression to active tuberculosis following reinfection with Mycobacterium tuberculosis

Affiliations
Review

Risk of progression to active tuberculosis following reinfection with Mycobacterium tuberculosis

Jason R Andrews et al. Clin Infect Dis. 2012 Mar.

Abstract

Background: The risk of progression to active tuberculosis is greatest in the several years following initial infection. The extent to which latent tuberculosis infection reduces the risk of progressive disease following reexposure and reinfection is not known. Indirect estimates from population models have been highly variable.

Methods: We reviewed prospective cohort studies of persons exposed to individuals with infectious tuberculosis that were published prior to the widespread treatment of latent tuberculosis to estimate the incidence of tuberculosis among individuals with latent tuberculosis infection (LTBI group) and without latent tuberculosis (uninfected; UI group). We calculated the incidence rate ratio (IRR) of tuberculosis disease following infection between these 2 groups. We then adjusted incidence for expected reactivation, proportion of each group that was infected, and median time of observation following infection during the study.

Results: We identified 18 publications reporting tuberculosis incidence among 23 paired cohorts of individuals with and without latent infection (total N = 19 886). The weighted mean adjusted incidence rate of tuberculosis in the LTBI and UI groups attributable to reinfection was 13.5 per 1000 person-years (95% confidence interval [CI]: 5.0-26.2 per 1000 person-years) and that attributable to primary infection was 60.1 per 1000 person-years (95% CI: 38.6-87.4 per 1000 person-years). The adjusted IRR for tuberculosis in the LTBI group compared with the UI group was 0.21 (95% CI: .14-.30).

Conclusions: Individuals with latent tuberculosis had 79% lower risk of progressive tuberculosis after reinfection than uninfected individuals. The risk reduction estimated in this study is greater than most previous estimates made through population models.

PubMed Disclaimer

Figures

Figure 1.
Figure 1.
Selection of studies for analysis. ARI, annual risk of infection.
Figure 2.
Figure 2.
Incidence rate ratio of tuberculosis in the latent tuberculosis infection group compared with uninfected group by study, with weighted result in random effects model.
Figure 3.
Figure 3.
Incidence rate ratio estimate and proportion of cases attributable to reinfection in the latent tuberculosis infection group according to reactivation rate used in the model (dotted line denotes base case).

Comment in

  • Reinfection redux.
    Vernon AA, Villarino ME. Vernon AA, et al. Clin Infect Dis. 2012 Mar;54(6):792-3. doi: 10.1093/cid/cir947. Epub 2012 Jan 19. Clin Infect Dis. 2012. PMID: 22267720 No abstract available.

References

    1. Connor C. Tuberculosis among medical students. The Diplomate. 1940;12:241–6.
    1. Horsburgh CR. Priorities for the treatment of latent tuberculosis infection in the United States. N Engl J Med. 2004;350:2060–7. - PubMed
    1. Stead WW. Pathogenesis of a first episode of chronic pulmonary tuberculosis in man: recrudescence of residuals of the primary infection or exogenous reinfection? Am Rev Respir Dis. 1967;95:729–45. - PubMed
    1. Chiang C-Y, Riley LW. Exogenous reinfection in tuberculosis. Lancet Infect Dis. 2005;5:629–36. - PubMed
    1. Colijn C, Cohen T, Murray M. Mathematical models of tuberculosis: accomplishments and future challenges. International Symposium on Mathematical and Computational Biology. BIOMAT 2006: International Symposium on Mathematical and Computational Biology. Singapore, World Scientific. 2006