Gamma Interferon Release Assays for Detection of Mycobacterium tuberculosis Infection

Author:

Pai Madhukar1,Denkinger Claudia M.12,Kik Sandra V.1,Rangaka Molebogeng X.3,Zwerling Alice4,Oxlade Olivia5,Metcalfe John Z.6,Cattamanchi Adithya6,Dowdy David W.4,Dheda Keertan7,Banaei Niaz8

Affiliation:

1. McGill International TB Centre and Department of Epidemiology & Biostatistics, McGill University, Montreal, Canada

2. Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA

3. Institute of Infectious Diseases and Molecular Medicine and Centre for Infectious Diseases and Epidemiology Research, University of Cape Town, Cape Town, South Africa

4. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA

5. Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA

6. Division of Pulmonary and Critical Care Medicine, San Francisco General Hospital, University of California, San Francisco, San Francisco, California, USA

7. Department of Medicine and UCT Lung Institute, University of Cape Town, Cape Town, South Africa

8. Department of Pathology and Medicine, Stanford University School of Medicine, Palo Alto, California, USA

Abstract

SUMMARY Identification and treatment of latent tuberculosis infection (LTBI) can substantially reduce the risk of developing active disease. However, there is no diagnostic gold standard for LTBI. Two tests are available for identification of LTBI: the tuberculin skin test (TST) and the gamma interferon (IFN-γ) release assay (IGRA). Evidence suggests that both TST and IGRA are acceptable but imperfect tests. They represent indirect markers of Mycobacterium tuberculosis exposure and indicate a cellular immune response to M. tuberculosis . Neither test can accurately differentiate between LTBI and active TB, distinguish reactivation from reinfection, or resolve the various stages within the spectrum of M. tuberculosis infection. Both TST and IGRA have reduced sensitivity in immunocompromised patients and have low predictive value for progression to active TB. To maximize the positive predictive value of existing tests, LTBI screening should be reserved for those who are at sufficiently high risk of progressing to disease. Such high-risk individuals may be identifiable by using multivariable risk prediction models that incorporate test results with risk factors and using serial testing to resolve underlying phenotypes. In the longer term, basic research is necessary to identify highly predictive biomarkers.

Publisher

American Society for Microbiology

Subject

Infectious Diseases,Microbiology (medical),Public Health, Environmental and Occupational Health,General Immunology and Microbiology,Epidemiology

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