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An Automated Culture System for Use in Preclinical Testing of Host-Directed Therapies for Tuberculosis
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Interferon release does not add discriminatory value to smear-negative HIV-tuberculosis algorithms.

M X Rangaka1, H P Gideon, K A Wilkinson

  • 1Centre for Infectious Disease and Epidemiology Research School of Health Sciences, University of Cape Town, Observatory, 7925, Cape Town, South Africa. mxrangaka@yahoo.co.uk

The European Respiratory Journal
|July 2, 2011
PubMed
Summary

Interferon-gamma release assays (IGRAs) like QuantiFERON-TB Gold in-tube (QFT-GIT) do not improve tuberculosis screening in HIV patients. Current clinical algorithms are more effective for diagnosing active TB before preventive therapy.

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Area of Science:

  • Infectious Diseases
  • Clinical Diagnostics
  • Public Health

Background:

  • Clinical algorithms for tuberculosis (TB) screening in HIV-infected individuals before isoniazid preventive therapy (IPT) have limited accuracy.
  • Interferon-gamma release assays (IGRAs) show moderate accuracy for active TB but their added clinical value in pre-IPT assessment is unclear.

Purpose of the Study:

  • To evaluate if IGRAs, specifically QuantiFERON-TB Gold in-tube (QFT-GIT), improve the diagnostic discrimination of active TB when used as adjunct tests in HIV-infected individuals prior to IPT.
  • To assess the performance of QFT-GIT and Tuberculin Skin Test (TST) within a multivariable clinical prediction model.

Main Methods:

  • A study involving 779 sputum smear-negative, HIV-infected individuals screened for TB before IPT, established on or commencing antiretroviral therapy (ART).
  • Stepwise multivariable logistic regression was used to develop clinical prediction models for TB diagnosis.
  • Discriminatory ability was assessed using receiver operator characteristic area under the curve (AUC).

Main Results:

  • The prevalence of smear-negative TB by culture was 6.4%.
  • QFT-GIT and TST alone had comparable performance; negative tests yielded a 3-4% post-test probability of disease.
  • QFT-GIT did not significantly improve the discriminatory ability of the clinical algorithm (AUC 72% to 74%, p=0.33).
  • TST marginally improved the clinical model's discriminatory ability (AUC to 77%, p=0.04).

Conclusions:

  • QFT-GIT does not enhance the diagnostic performance of existing clinical algorithms for screening HIV-infected individuals for TB before preventive therapy.
  • The evaluation of new TB diagnostics should incorporate multivariable approaches beyond simple test accuracy to determine clinical relevance.