AUTHOR=Gong Xue , He Yunru , Zhou Kaiyu , Hua Yimin , Li Yifei TITLE=Efficacy of Xpert in tuberculosis diagnosis based on various specimens: a systematic review and meta-analysis JOURNAL=Frontiers in Cellular and Infection Microbiology VOLUME=13 YEAR=2023 URL=https://www.frontiersin.org/journals/cellular-and-infection-microbiology/articles/10.3389/fcimb.2023.1149741 DOI=10.3389/fcimb.2023.1149741 ISSN=2235-2988 ABSTRACT=Objective

The GeneXpert MTB/RIF assay (Xpert) is a diagnostic tool that has been shown to significantly improve the accuracy of tuberculosis (TB) detection in clinical settings, with advanced sensitivity and specificity. Early detection of TB can be challenging, but Xpert has improved the efficacy of the diagnostic process. Nevertheless, the accuracy of Xpert varies according to different diagnostic specimens and TB infection sites. Therefore, the selection of adequate specimens is critical when using Xpert to identify suspected TB. As such, we have conducted a meta-analysis to evaluate the effectiveness of Xpert for diagnosis of different TB types using several specimens.

Methods

We conducted a comprehensive search of several electronic databases, including PubMed, Embase, the Cochrane Central Register of Controlled Trials, and the World Health Organization clinical trials registry center, covering studies published from Jan 2008 to July 2022. Data were extracted using an adapted version of the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modeling Studies. Where appropriate, meta-analysis was performed using random-effects models. The risk of bias and level of evidence was assessed using the Quality in Prognosis Studies tool and a modified version of the Grading of Recommendations Assessment, Development, and Evaluation. RStudio was utilized to analyze the results, employing the meta4diag, robvis, and metafor packages.

Results

After excluding duplicates, a total of 2163 studies were identified, and ultimately, 144 studies from 107 articles were included in the meta-analysis based on predetermined inclusion and exclusion criteria. Sensitivity, specificity and diagnostic accuracy were estimated for various specimens and TB types. In the case of pulmonary TB, Xpert using sputum (0.95 95%CI 0.91–0.98) and gastric juice (0.94 95%CI 0.84–0.99) demonstrated similarly high sensitivity, surpassing other specimen types. Additionally, Xpert exhibited high specificity for detecting TB across all specimen types. For bone and joint TB, Xpert, based on both biopsy and joint fluid specimens, demonstrated high accuracy in TB detection. Furthermore, Xpert effectively detected unclassified extrapulmonary TB and tuberculosis lymphadenitis. However, the Xpert accuracy was not satisfactory to distinguish TB meningitis, tuberculous pleuritis and unclassified TB.

Conclusions

Xpert has exhibited satisfactory diagnostic accuracy for most TB infections, but the efficacy of detection may vary depending on the specimens analyzed. Therefore, selecting appropriate specimens for Xpert analysis is essential, as using inadequate specimens can reduce the ability to distinguish TB.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=370111, identifier CRD42022370111.