Spectrum of latent tuberculosis — existing tests cannot resolve the underlying phenotypes

Pai, Madhukar

doi:10.1038/nrmicro2236-c1

Cited by 74 publications

(65 citation statements)

References 15 publications

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“…The primary goal of IGRAs is to identify those who will benefit from LTBI therapy. Unfortunately, IGRAs (and TST) are limited in this regard, for reasons including the low absolute risk of progression to disease, inability to distinguish reactivation from reinfection, reduced accuracy in immunocompromised patients, and inability to discriminate the various stages within the spectrum of LTBI (2,88). To maximize the positive predictive value of existing LTBI tests, LTBI screening should be reserved only for those who are at sufficiently high risk of progressing to disease.…”

Section: Discussionmentioning

confidence: 99%

“…1) (2). Among the stages shown in the figure, both TST and IGRAs are likely to be positive in all stages, with the possible exception of the innate immune response stage (i.e., exposed to TB but negative on both tests) (3,88).…”

Section: Predictive Value For Progression To Tb Diseasementioning

confidence: 99%

“…For all these reasons, both TST and IGRAs are generally unable to select out the phenotypes that are most likely to benefit from LTBI treatment (88,130). This is underscored by the observed low rates of progression to disease even in IGRA-and TST-positive individuals (106).…”

Section: Predictive Value For Progression To Tb Diseasementioning

confidence: 99%

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Gamma Interferon Release Assays for Detection of Mycobacterium tuberculosis Infection

et al. 2014

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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.

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Section: Discussionmentioning

confidence: 99%

Section: Predictive Value For Progression To Tb Diseasementioning

confidence: 99%

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Gamma Interferon Release Assays for Detection of Mycobacterium tuberculosis Infection

et al. 2014

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“…For example, none of the tests for active TB is sufficiently accurate, timely, and appropriate for low-income and low-technology settings, where most TB cases are found (reviewed in references 44, 87, 88, 91, 143, 144, 145, and 162). The recently developed gamma interferon (IFN-␥) release assays (IGRAs) diagnose latent M. tuberculosis infection (LTBI) more accurately than the century-old tuberculin skin test (reviewed in references 36, 77, 109, and 110), but they fail to facilitate decisions concerning targeted LTBI treatment (97,107,108). Indeed, it is recognized that the millennium development goals set by the United Nations in the fight against TB, i.e., cutting in half the global prevalence and death rate by 2015 (42), cannot be reached without the development of new diagnostic tools (http://www.stoptb.org/globalplan).…”

Section: Introductionmentioning

confidence: 99%

Immunodiagnosis of Tuberculosis: a Dynamic View of Biomarker Discovery

Kunnath-Velayudhan¹,

Gennaro²

2011

Clin Microbiol Rev

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SUMMARY Infection with Mycobacterium tuberculosis causes a variety of clinical conditions ranging from life-long asymptomatic infection to overt disease with increasingly severe tissue damage and a heavy bacillary burden. Immune biomarkers should follow the evolution of infection and disease because the host immune response is at the core of protection against disease and tissue damage in M. tuberculosis infection. Moreover, levels of immune markers are often affected by the antigen load. We review how the clinical spectrum of M. tuberculosis infection correlates with the evolution of granulomatous lesions and how granuloma structural changes are reflected in the peripheral circulation. We also discuss how antigen-specific, peripheral immune responses change during infection and how these changes are associated with the physiology of the tubercle bacillus. We propose that a dynamic approach to immune biomarker research should overcome the challenges of identifying those asymptomatic and symptomatic stages of infection that require antituberculosis treatment. Implementation of such a view requires longitudinal studies and a systems immunology approach leading to multianalyte assays.

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“…Current diagnostic tests do not discriminate between LTBI and active TB, and treatment for LTBI requires prolonged administration of antibiotics (4). An improved understanding of the host and pathogen mechanisms underlying LTBI may yield novel assays which can identify persons at increased risk for progression to active disease (5), as well as new drugs to shorten the duration of LTBI treatment (6).…”

mentioning

confidence: 99%

Latent Tuberculosis Infection: Myths, Models, and Molecular Mechanisms

Dutta

Karakousis

2014

Microbiol Mol Biol Rev

189

166

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SUMMARY The aim of this review is to present the current state of knowledge on human latent tuberculosis infection (LTBI) based on clinical studies and observations, as well as experimental in vitro and animal models. Several key terms are defined, including “latency,” “persistence,” “dormancy,” and “antibiotic tolerance.” Dogmas prevalent in the field are critically examined based on available clinical and experimental data, including the long-held beliefs that infection is either latent or active, that LTBI represents a small population of nonreplicating, “dormant” bacilli, and that caseous granulomas are the haven for LTBI. The role of host factors, such as CD4 + and CD8 + T cells, T regulatory cells, tumor necrosis factor alpha (TNF-α), and gamma interferon (IFN-γ), in controlling TB infection is discussed. We also highlight microbial regulatory and metabolic pathways implicated in bacillary growth restriction and antibiotic tolerance under various physiologically relevant conditions. Finally, we pose several clinically important questions, which remain unanswered and will serve to stimulate future research on LTBI.

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Spectrum of latent tuberculosis — existing tests cannot resolve the underlying phenotypes

Cited by 74 publications

References 15 publications

Gamma Interferon Release Assays for Detection of Mycobacterium tuberculosis Infection

Gamma Interferon Release Assays for Detection of Mycobacterium tuberculosis Infection

Immunodiagnosis of Tuberculosis: a Dynamic View of Biomarker Discovery

Latent Tuberculosis Infection: Myths, Models, and Molecular Mechanisms

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