宏基因组二代测序技术检测脑脊液在结核性脑膜炎诊断中的应用价值的Meta分析

doi:10.3969/j.issn.1000-6621.2021.10.016

摘要/Abstract

摘要：

目的评价宏基因组二代测序技术检测脑脊液在结核性脑膜炎诊断中的应用价值。方法通过计算机检索PubMed、Embase、Cochrane Library、中国知网、万方、维普等数据库。中文检索词:宏基因组二代测序、二代测序、结核、结核性脑膜炎;英文检索词:metagenomic next-generation sequencing、mNGS、next-generation sequencing、tuberculosis、tuberculous meningitis、tuberculosis meningitis。收集从建库至2021年4月30日发表的宏基因组二代测序技术应用于脑脊液检测诊断结核性脑膜炎的相关文献,由2名研究者独立进行文献检索、筛选、数据提取,质量评价。以MetaDisc 1.4 软件进行Meta分析。结果检索出628篇文献,依据纳入和排除标准最终纳入7篇文献,包含477例患者,其中结核性脑膜炎患者231例。Meta分析结果显示,宏基因组二代测序技术检测脑脊液诊断结核性脑膜炎的汇总敏感度为62.0%(95%CI: 55.0%~68.0%)、汇总特异度为97.0%(95%CI: 94.0%~99.0%)、汇总阳性似然比为10.57(95%CI:4.84~23.11)、汇总阴性似然比为0.41(95%CI:0.27~0.60)、汇总诊断OR值为21.39(95%CI:10.18~44.95)、汇总受试者工作特征曲线下面积为0.956。结论宏基因组应用于脑脊液检测对结核性脑膜炎具有较高的诊断价值,可作为快速诊断结核性脑膜炎的有效方法。

关键词: 宏基因组二代测序, 结核, 脑膜, 诊断, Meta分析

Abstract:

Objective To evaluate the diagnostic value of metagenomic next-generation sequencing (mNGS) on cerebrospinal fluid for detecting tuberculous meningitis (TBM). Methods Literature on diagnosing TBM by mNGS assay on cerebrospinal fluid were collected by searching PubMed, Embase, Cochrane Library, CNKI, WanFang and VIP databases, enrolling literature recorded from database establishment to April 30, 2021.Both Chinese and English key words were “metagenomic next-generation sequencing”“mNGS”“next-generation sequencing”“tuberculosis”“tuberculosis meningitis” and “tuberculous meningitis”. Then two reviewers independently screened the literature according to the inclusion and exclusion criteria, extracted data and assessed the quality of included studies. MetaDisc 1.4 were used to conduct meta-analysis. Results Six hundred and twenty-eight articles were retrieved, and 7 articles were finally included according to the inclusion and exclusion criteria, involving 477 cases among whom 231 cases were diagnosed as TBM patients. Meta analysis showed that the pooled sensitivity and specificity of mNGS on cerebrospinal fluid in the diagnosis of TBM were 62.0% (95.0%CI: 55.0%-68.0%) and 97.0% (95.0%CI: 94.0%-99.0%), while the pooled positive likelihood ratio, negative likelihood ratio and diagnostic odds ratio were 10.57 (95%CI:4.84-23.11), 0.41 (95%CI:0.27-0.60), 21.39 (95%CI:10.18-44.95) respectively. The pooled area under the curve of receiver operating characteristic was 0.956. Conclusion mNGS on cerebrospinal fluid plays a valuable role in the diagnosis of TBM and can be used as an effective method for rapid diagnosis.

Key words: Metagenomic next-generation sequencing, Tuberculosis, meningeal, Diagnosis, Meta-analysis

陈文, 姚利, 陈康, 戴希勇. 宏基因组二代测序技术检测脑脊液在结核性脑膜炎诊断中的应用价值的Meta分析[J]. 中国防痨杂志, 2021, 43(10): 1066-1072. doi: 10.3969/j.issn.1000-6621.2021.10.016

CHEN Wen, YAO Li, CHEN Kang, DAI Xi-yong. Meta-analysis on the diagnostic value of metagenomic next-generation sequencing on cerebrospinal fluid for detecting tuberculous meningitis[J]. Chinese Journal of Antituberculosis, 2021, 43(10): 1066-1072. doi: 10.3969/j.issn.1000-6621.2021.10.016

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参考文献 21

[1]	Thwaites GE, van Toorn R, Schoeman J. Tuberculous meningitis: more questions, still too few answers. Lancet Neurol, 2013, 12(10): 999-1010. doi: 10.1016/S1474-4422(13)70168-6. doi: 10.1016/S1474-4422(13)70168-6 pmid: 23972913
[2]	Marais S, Thwaites G, Schoeman JF, et al. Tuberculous meningitis: a uniform case definition for use in clinical research. Lancet Infect Dis, 2010, 10(11): 803-812. doi: 10.1016/S1473-3099(10)70138-9. doi: 10.1016/S1473-3099(10)70138-9 URL
[3]	Mai NT, Thwaites GE. Recent advances in the diagnosis and management of tuberculous meningitis. Curr Opin Infect Dis, 2017, 30(1): 123-128. doi: 10.1097/QCO.0000000000000331. doi: 10.1097/QCO.0000000000000331 URL
[4]	Venkatesan A, Tunkel AR, Bloch KC, et al. Case definitions, diagnostic algorithms, and priorities in encephalitis: consensus statement of the international encephalitis consortium. Clin Infect Dis, 2013, 57(8): 1114-1128. doi: 10.1093/cid/cit458. doi: 10.1093/cid/cit458 pmid: 23861361
[5]	Colman RE, Anderson J, Lemmer D, et al. Rapid Drug Susceptibility Testing of Drug-Resistant Mycobacterium tuberculosis Isolates Directly from Clinical Samples by Use of Amplicon Sequencing: a Proof-of-Concept Study. J Clin Microbiol, 2016, 54(8): 2058-2067. doi: 10.1128/JCM.00535-16. doi: 10.1128/JCM.00535-16 URL
[6]	Salzberg SL, Breitwieser FP, Kumar A, et al. Next-generation sequencing in neuropathologic diagnosis of infections of the nervous system. Neurol Neuroimmunol Neuroinflamm, 2016, 3(4): e251. doi: 10.1212/NXI.0000000000000251. doi: 10.1212/NXI.0000000000000251 URL
[7]	Whiting P, Rutjes AW, Reitsma JB, et al. The development of QUADAS: a tool for the quality assessment of studies of diagnostic accuracy included in systematic reviews. BMC Med Res Methodol, 2003, 3: 25. doi: 10.1186/1471-2288-3-25. doi: 10.1186/1471-2288-3-25 pmid: 14606960
[8]	Zhou X, Wu H, Ruan Q, et al. Clinical Evaluation of Diagnosis Efficacy of Active Mycobacterium tuberculosis Complex Infection via Metagenomic Next-Generation Sequencing of Direct Clinical Samples. Front Cell Infect Microbiol, 2019, 9: 351. doi: 10.3389/fcimb.2019.00351. doi: 10.3389/fcimb.2019.00351 URL
[9]	Wang S, Chen Y, Wang D, et al. The Feasibility of Metagenomic Next-Generation Sequencing to Identify Pathogens Causing Tuberculous Meningitis in Cerebrospinal Fluid. Front Microbiol, 2019, 10: 1993. doi: 10.3389/fmicb.2019.01993. doi: 10.3389/fmicb.2019.01993 URL
[10]	Xing XW, Zhang JT, Ma YB, et al. Metagenomic Next-Generation Sequencing for Diagnosis of Infectious Encephalitis and Meningitis: A Large, Prospective Case Series of 213 Patients. Front Cell Infect Microbiol, 2020, 10: 88. doi: 10.3389/fcimb.2020.00088. doi: 10.3389/fcimb.2020.00088 URL
[11]	Yan L, Sun W, Lu Z, et al. Metagenomic Next-Generation Sequencing (mNGS) in cerebrospinal fluid for rapid diagnosis of Tuberculosis meningitis in HIV-negative population. Int J Infect Dis, 2020, 96: 270-275. doi: 10.1016/j.ijid.2020.04.048. doi: 10.1016/j.ijid.2020.04.048 URL
[12]	Yu G, Wang X, Zhu P, et al. Comparison of the efficacy of metagenomic next-generation sequencing and Xpert MTB/RIF in the diagnosis of tuberculous meningitis. J Microbiol Methods, 2021, 180: 106124. doi: 10.1016/j.mimet.2020.106124. doi: 10.1016/j.mimet.2020.106124 URL
[13]	Sun W, Lu Z, Yan L. Clinical efficacy of metagenomic next-generation sequencing for rapid detection of Mycobacterium tuberculosis in smear-negative extrapulmonary specimens in a high tuberculosis burden area. Int J Infect Dis, 2021, 103: 91-96. doi: 10.1016/j.ijid.2020.11.165. doi: 10.1016/j.ijid.2020.11.165 URL
[14]	Lin A, Cheng B, Han X, et al. Value of next-generation sequencing in early diagnosis of patients with tuberculous meningitis. J Neurol Sci, 2021, 422: 117310. doi: 10.1016/j.jns.2021.117310. doi: 10.1016/j.jns.2021.117310 URL
[15]	Chaidir L, Annisa J, Dian S, et al. Microbiological diagnosis of adult tuberculous meningitis in a ten-year cohort in Indonesia. Diagn Microbiol Infect Dis, 2018, 91(1): 42-46. doi: 10.1016/j.diagmicrobio.2018.01.004. doi: 10.1016/j.diagmicrobio.2018.01.004 URL
[16]	Donovan J, Thu D, Phu NH, et al. Xpert MTB/RIF Ultra versus Xpert MTB/RIF for the diagnosis of tuberculous meningitis: a prospective, randomised, diagnostic accuracy study. Lancet Infect Dis, 2020, 20(3): 299-307. doi: 10.1016/S1473-3099(19)30649-8. doi: S1473-3099(19)30649-8 pmid: 31924551
[17]	Wang J, Han Y, Feng J. Metagenomic next-generation sequencing for mixed pulmonary infection diagnosis. BMC Pulm Med, 2019, 19(1): 252. doi: 10.1186/s12890-019-1022-4. doi: 10.1186/s12890-019-1022-4 URL
[18]	Wilson MR, Naccache SN, Samayoa E, et al. Actionable diagnosis of neuroleptospirosis by next-generation sequencing. N Engl J Med, 2014, 370(25): 2408-2417. doi: 10.1056/NEJMoa1401268. doi: 10.1056/NEJMoa1401268 URL
[19]	Guan H, Shen A, Lv X, et al. Detection of virus in CSF from the cases with meningoencephalitis by next-generation sequencing. J Neurovirol, 2016, 22(2): 240-245. doi: 10.1007/s13365-015-0390-7. doi: 10.1007/s13365-015-0390-7 URL
[20]	Miao Q, Ma Y, Wang Q, et al. Microbiological Diagnostic Performance of Metagenomic Next-generation Sequencing When Applied to Clinical Practice. Clin Infect Dis, 2018, 67 suppl_2:S231-S240. doi: 10.1093/cid/ciy693. doi: 10.1093/cid/ciy693 URL
[21]	黄麦玲, 孙晴, 王桂荣, 等. Xpert MTB/RIF Ultra检测脑脊液对结核性脑膜炎的诊断价值. 中国防痨杂志, 2021, 43(7): 670-676. doi: 10.3969/j.issn.2095-3755.2019.01.011. doi: 10.3969/j.issn.2095-3755.2019.01.011

研究类型	纳入研究数	汇总敏感度(95%CI)	汇总特异度(95%CI)	汇总诊断比值比(95%CI)	AUC
前瞻性	3	41.0%(31.0%~52.0%)	97.0%(93.0%~99.0%)	16.54(7.03~38.92)	0.998
回顾性	4	76.0%(68.0%~83.0%)	100.0%(88.0%~100.0%)	35.52(7.70~163.85)	0.945