U.S. Department of Veterans Affairs
Date of this Version
2016
Document Type
Article
Citation
Clinical Infectious Diseases® 2016;62(9):1081–8
Abstract
Background. The Xpert MTB/RIF (Xpert) assay is a rapid nucleic acid amplification test widely used in settings of high tuberculosis prevalence to detect tuberculosis as well as rpoB mutations associated with rifampin resistance. Data are needed on the diagnostic performance of Xpert in lower-prevalence settings to inform appropriate use for both tuberculosis detection and the need for respiratory isolation.
Methods. Xpert was compared to 2 sputum samples, each evaluated with acid-fast bacilli (AFB) smear and mycobacterial culture using liquid and solid culture media, from participants with suspected pulmonary tuberculosis from the United States, Brazil, and South Africa.
Results. Of 992 participants enrolled with evaluable results, 22% had culture-confirmed tuberculosis. In 638 (64%) US participants, 1 Xpert result demonstrated sensitivity of 85.2% (96.7% in participants with AFB smear-positive [AFB+] sputum, 59.3% with AFB smear-negative [AFB–] sputum), specificity of 99.2%, negative predictive value (NPV) of 97.6%, and positive predictive value of 94.9%. Results did not differ between higher- and low-prevalence settings. A second Xpert assay increased overall sensitivity to 91.1% (100% if AFB+, 71.4% if AFB–), with specificity of 98.9%. In US participants, a single negative Xpert result predicted the absence of AFB+/culture-positive tuberculosis with an NPV of 99.7%; NPV of 2 Xpert assays was 100%, suggesting a role in removing patients from airborne infection isolation. Xpert detected tuberculosis DNA and mutations associated with rifampin resistance in 5 of 7 participants with rifampin-resistant, culture-positive tuberculosis. Specificity for rifampin resistance was 99.5% and NPV was 98.9%.
Conclusions. In the United States, Xpert testing performed comparably to 2 higher-tuberculosis-prevalence settings. These data support the use of Xpert in the initial evaluation of tuberculosis suspects and in algorithms assessing need for respiratory isolation.
Comments
© The Author 2016.
This document is a U.S. government work and is not subject to copyright in the United States.
DOI: 10.1093/cid/ciw035