宏基因组下一代测序在诊断感染性疾病中的诊断准确性：一项荟萃分析。
Diagnostic accuracy of metagenomic next-generation sequencing in diagnosing infectious diseases: a meta-analysis.
机构信息
Department of Intensive Care Unit, the First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
Department of Clinical Pharmacy, Zhejiang Provincial Key Laboratory for Drug Evaluation and Clinical Research, the First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
出版信息
Sci Rep. 2022 Dec 5;12(1):21032. doi: 10.1038/s41598-022-25314-y.
Many common pathogens are difficult or impossible to detect using conventional microbiological tests. However, the rapid and untargeted nature of metagenomic next-generation sequencing (mNGS) appears to be a promising alternative. To perform a systematic review and meta-analysis of evidence regarding the diagnostic accuracy of mNGS in patients with infectious diseases. An electronic literature search of Embase, PubMed and Scopus databases was performed. Quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Summary receiver operating characteristics (sROC) and the area under the curve (AUC) were calculated; A random-effects model was used in cases of heterogeneity. A total of 20 papers were eligible for inclusion and synthesis. The sensitivity and specificity of diagnostic mNGS were 75% and 68%, respectively. The AUC from the SROC was 85%, corresponding to excellent performance. mNGS demonstrated satisfactory diagnostic performance for infections and yielded an overall detection rate superior to conventional methods.
许多常见病原体很难或不可能通过常规微生物检测来检测。然而，宏基因组下一代测序（mNGS）的快速和非靶向性质似乎是一种很有前途的替代方法。为了对 mNGS 在感染性疾病患者中的诊断准确性进行系统评价和荟萃分析。对 Embase、PubMed 和 Scopus 数据库进行了电子文献检索。使用诊断准确性研究的质量评估-2 工具评估质量。计算汇总受试者工作特征（sROC）和曲线下面积（AUC）；在存在异质性的情况下使用随机效应模型。共有 20 篇论文符合纳入和综合标准。诊断性 mNGS 的灵敏度和特异性分别为 75%和 68%。来自 SROC 的 AUC 为 85%，表明性能优异。mNGS 对感染的诊断性能令人满意，总体检测率优于传统方法。
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