A systematic review and meta-analysis of the diagnostic accuracy of metagenomic next-generation sequencing for diagnosing tuberculous meningitis

Front Immunol. 2023 Sep 26:14:1223675. doi: 10.3389/fimmu.2023.1223675. eCollection 2023.

Abstract

Objective: The utility of metagenomic next-generation sequencing (mNGS) in the diagnosis of tuberculous meningitis (TBM) remains uncertain. We performed a meta-analysis to comprehensively evaluate its diagnostic accuracy for the early diagnosis of TBM.

Methods: English (PubMed, Medline, Web of Science, Cochrane Library, and Embase) and Chinese (CNKI, Wanfang, and CBM) databases were searched for relevant studies assessing the diagnostic accuracy of mNGS for TBM. Review Manager was used to evaluate the quality of the included studies, and Stata was used to perform the statistical analysis.

Results: Of 495 relevant articles retrieved, eight studies involving 693 participants (348 with and 345 without TBM) met the inclusion criteria and were included in the meta-analysis. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and area under the summary receiver-operating characteristic curve of mNGS for diagnosing TBM were 62% (95% confidence interval [CI]: 0.46-0.76), 99% (95% CI: 0.94-1.00), 139.08 (95% CI: 8.54-2266), 0.38 (95% CI: 0.25-0.58), 364.89 (95% CI: 18.39-7239), and 0.97 (95% CI: 0.95-0.98), respectively.

Conclusions: mNGS showed good specificity but moderate sensitivity; therefore, a more sensitive test should be developed to assist in the diagnosis of TBM.

Keywords: cerebrospinal fluid; diagnosis; meta-analysis; metagenomic next-generation sequencing; tuberculous meningitis.

Publication types

  • Meta-Analysis
  • Systematic Review
  • Review
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Databases, Factual
  • High-Throughput Nucleotide Sequencing
  • Humans
  • ROC Curve
  • Sensitivity and Specificity
  • Tuberculosis, Meningeal* / diagnosis

Grants and funding

This work was supported by grant from Jiangxi Province Traditional Chinese medicine science and technology Project (no. 2023A0174).