Abstract：
OBJECTIVE: Brain tumors (BT) are among the most prevalent cancers in recent years. Various studies have examined the diagnostic role of microRNAs in different diseases; however, their diagnostic role in BT has not been comprehensively investigated. This meta-analysis was performed to assess microRNAs in the blood of patients with BTs accurately.
METHODS: Twenty-six eligible studies were included for analysis. The pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), area under curve (AUC), Q*index, summary receiver-operating characteristic (SROC) were assessed using the Meta-Disc V.1.4 and Comprehensive Meta-Analysis V.3.3 software.
RESULTS: The diagnostic accuracy of microRNA was high in identifying BT based on the pooled sensitivity 0.82 (95%CI: 0.816-0.84), specificity 0.82 (95%CI: 0.817-0.84), PLR 5.101 (95%CI: 3.99-6.51), NLR 0.187 (95%CI: 0.149-0.236), DOR 34.07 (95%CI: 22.56-51.43) as well as AUC (0.92), and Q*-index (0.86). Subgroup analyses were performed for sample types (serum/plasma), reference genes (RNU6, miR-39, and miR-24), and region to determine the diagnostic power of microRNAs in the diagnosis of BT using pooled sensitivity, specificity, PLR, NLR, AUC, and DOR.
CONCLUSIONS: This meta-analysis suggested that circulating microRNAs might be potential markers for noninvasive early detection of BT.
METHODS: Twenty-six eligible studies were included for analysis. The pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), area under curve (AUC), Q*index, summary receiver-operating characteristic (SROC) were assessed using the Meta-Disc V.1.4 and Comprehensive Meta-Analysis V.3.3 software.
RESULTS: The diagnostic accuracy of microRNA was high in identifying BT based on the pooled sensitivity 0.82 (95%CI: 0.816-0.84), specificity 0.82 (95%CI: 0.817-0.84), PLR 5.101 (95%CI: 3.99-6.51), NLR 0.187 (95%CI: 0.149-0.236), DOR 34.07 (95%CI: 22.56-51.43) as well as AUC (0.92), and Q*-index (0.86). Subgroup analyses were performed for sample types (serum/plasma), reference genes (RNU6, miR-39, and miR-24), and region to determine the diagnostic power of microRNAs in the diagnosis of BT using pooled sensitivity, specificity, PLR, NLR, AUC, and DOR.
CONCLUSIONS: This meta-analysis suggested that circulating microRNAs might be potential markers for noninvasive early detection of BT.
摘要：
目的：脑肿瘤（BT）是近年来最常见的癌症之一。各种研究已经检查了microRNA在不同疾病中的诊断作用;然而，它们在BT中的诊断作用尚未得到全面调查。进行此荟萃分析以准确评估BT患者血液中的microRNA。
方法：纳入26个符合条件的研究进行分析。汇集的敏感性，特异性，正似然比(PLR)，负似然比(NLR)，诊断优势比(DOR)，曲线下面积（AUC），Q*指数，使用Meta-DiscV.1.4和综合Meta-AnalysisV.3.3软件评估受试者工作特征摘要(SROC)。
结果：根据合并敏感性0.82（95CI：0.816-0.84），microRNA的诊断准确性高，特异性0.82（95CI：0.817-0.84），PLR5.101(95CI:3.99-6.51),NLR0.187（95CI：0.149-0.236），DOR34.07（95CI：22.56-51.43）以及AUC（0.92），和Q*指数（0.86）。对样本类型（血清/血浆）进行亚组分析，参考基因（RNU6、miR-39和miR-24），和区域来确定microRNAs在BT诊断中的诊断能力，特异性，PLR,NLR,AUC,和DOR。
结论：这项荟萃分析提示循环microRNAs可能是BT早期无创检测的潜在标志物。
方法：纳入26个符合条件的研究进行分析。汇集的敏感性，特异性，正似然比(PLR)，负似然比(NLR)，诊断优势比(DOR)，曲线下面积（AUC），Q*指数，使用Meta-DiscV.1.4和综合Meta-AnalysisV.3.3软件评估受试者工作特征摘要(SROC)。
结果：根据合并敏感性0.82（95CI：0.816-0.84），microRNA的诊断准确性高，特异性0.82（95CI：0.817-0.84），PLR5.101(95CI:3.99-6.51),NLR0.187（95CI：0.149-0.236），DOR34.07（95CI：22.56-51.43）以及AUC（0.92），和Q*指数（0.86）。对样本类型（血清/血浆）进行亚组分析，参考基因（RNU6、miR-39和miR-24），和区域来确定microRNAs在BT诊断中的诊断能力，特异性，PLR,NLR,AUC,和DOR。
结论：这项荟萃分析提示循环microRNAs可能是BT早期无创检测的潜在标志物。
