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Meta-Analysis
. 2017 Feb;23(2):61-68.
doi: 10.1016/j.cmi.2016.09.008. Epub 2016 Sep 22.

Whole genome sequencing of Mycobacterium tuberculosis for detection of drug resistance: a systematic review

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Free article
Meta-Analysis

Whole genome sequencing of Mycobacterium tuberculosis for detection of drug resistance: a systematic review

D Papaventsis et al. Clin Microbiol Infect. 2017 Feb.
Free article

Abstract

Objectives: We conducted a systematic review to determine the diagnostic accuracy of whole genome sequencing (WGS) of Mycobacterium tuberculosis for the detection of resistance to first- and second-line anti-tuberculosis (TB) drugs.

Methods: The study was conducted according to the criteria of the Preferred Reporting Items for Systematic Reviews group. A total of 20 publications were included. The sensitivity, specificity, positive-predictive value and negative-predictive value of WGS using phenotypic drug susceptibility testing methods as a reference standard were determined.

Results: Anti-TB agents tested included all first-line drugs, a variety of reserve drugs, as well as new drugs. Polymorphisms in a total of 53 genes were tested for associations with drug resistance. Pooled sensitivity and specificity values for detection of resistance to selected first-line drugs were 0.98 (95% CI 0.93-0.98) and 0.98 (95% CI 0.98-1.00) for rifampicin and 0.97 (95% CI 0.94-0.99) and 0.93 (95% CI 0.91-0.96) for isoniazid, respectively. Due to high heterogeneity in study designs, lack of data, knowledge of resistance mechanisms and clarity on exclusion of phylogenetic markers, there was a significant variation in analytical performance of WGS for the remaining first-line, reserved drugs and new drugs.

Conclusions: Whole genome sequencing could be considered a promising alternative to existing phenotypic and molecular drug susceptibility testing methods for rifampicin and isoniazid pending standardization of analytical pipelines. To ensure clinical relevance of WGS for detection of M. tuberculosis complex drug resistance, future studies should include information on clinical outcomes.

Keywords: Drug resistance; Genetic polymorphisms; Laboratory diagnostics; Performance characteristics; Tuberculosis; Whole genome sequencing.

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