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Metagenomic next generation sequencing for the diagnosis of tuberculosis meningitis: A systematic review and meta-analysis

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  • Guocan Yu
  • Wuchen Zhao
  • Yanqin Shen
  • Pengfei Zhu
  • Hong Zheng

Abstract

Background: Tuberculous meningitis (TBM) is a severe form of extrapulmonary tuberculosis and its early diagnosis is very difficult leading to present with severe disability or die. The current study aimed to assess the accuracy of metagenomic next generation sequencing (mNGS) for TBM, and to identify a new test for the early diagnosis of TBM. Methods: We searched for articles published in Embase, PubMed, Cochrane Library, China National Knowledge Infrastructure, and Wanfang Data up to June 30, 2020 for studies that assessed the efficacy of mNGS for the diagnosis of TBM. Then, the accuracy between mNGS and a composite reference standard (CRS) in these articles was compared using the meta-analysis approach. Results: Four independent studies with 342 samples comparing mNGS and a CRS were included in this study. The sensitivity of mNGS for TBM diagnosis ranged from 27% to 84%. The combined sensitivity of mNGS was 61%, and the I2 value was 92%. Moreover, the specificity of mNGS for TBM diagnosis ranged from 96% to 100%. The combined specificity of mNGS was 98%, and the I2 value was 74%. The heterogeneity between studies in terms of sensitivity and specificity was significant. The area under the curve (AUC) of the summary receiver operating characteristic curve (SROC) of mNGS for TBM was 0.98. Conclusions: The sensitivity of mNGS for TBM diagnosis was moderate. Furthermore, the specificity was extremely high, and the AUC of the SROC indicated a very good diagnostic efficacy. mNGS could be used as an early diagnostic method for TBM, however, the results should be treated with caution for the heterogeneity between studies was extremely significant. Systematic review registration: INPLASY202070100.

Suggested Citation

  • Guocan Yu & Wuchen Zhao & Yanqin Shen & Pengfei Zhu & Hong Zheng, 2020. "Metagenomic next generation sequencing for the diagnosis of tuberculosis meningitis: A systematic review and meta-analysis," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-12, December.
    • Handle: RePEc:plo:pone00:0243161
    DOI: 10.1371/journal.pone.0243161
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    References listed on IDEAS

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    1. Ben Dwamena, 2007. "Meta-analytical Integration of Diagnostic Accuracy Studies in Stata," North American Stata Users' Group Meetings 2007 4, Stata Users Group, revised 05 Sep 2007.
    2. David Moher & Alessandro Liberati & Jennifer Tetzlaff & Douglas G Altman & The PRISMA Group, 2009. "Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement," PLOS Medicine, Public Library of Science, vol. 6(7), pages 1-6, July.
    3. Ben Dwamena, 2007. "MIDAS: Stata module for meta-analytical integration of diagnostic test accuracy studies," Statistical Software Components S456880, Boston College Department of Economics, revised 05 Feb 2009.
    4. Guocan Yu & Yanqin Shen & Fangming Zhong & Bo Ye & Jun Yang & Gang Chen, 2018. "Diagnostic accuracy of the loop-mediated isothermal amplification assay for extrapulmonary tuberculosis: A meta-analysis," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-15, June.
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    1. Guocan Yu & Wenfeng Yu & Xudong Xu & Bo Ye & Liwei Yao, 2021. "Neoadjuvant immunotherapy for resectable esophageal cancer: A protocol of meta-analysis," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-7, June.
    2. Guocan Yu & Yanqin Shen & Bo Ye & Yan Shi, 2021. "Diagnostic accuracy of Mycobacterium tuberculosis cell-free DNA for tuberculosis: A systematic review and meta-analysis," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-16, June.
    3. P. S. Ramachandran & A. Ramesh & F. V. Creswell & A. Wapniarski & R. Narendra & C. M. Quinn & E. B. Tran & M. K. Rutakingirwa & A. S. Bangdiwala & E. Kagimu & K. T. Kandole & K. C. Zorn & L. Tugume & , 2022. "Integrating central nervous system metagenomics and host response for diagnosis of tuberculosis meningitis and its mimics," Nature Communications, Nature, vol. 13(1), pages 1-12, December.

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