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血液中microRNA-21对肺癌诊断价值的Meta分析 被引量:5

A Meta-analysis about the diagnosis value of microRNA-21 on lung cancer in patient serum
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摘要 目的通过Meta分析已报道文献中的微小RNA-21(microRNA-21,miR-21)对肺癌的诊断价值,探讨血液中的miR-21对肺癌的诊断价值。方法检索中国知网、维普、万方、PubMed和Embsase等数据库,按照已定的纳入和排出标准筛选文献。采用Quadas量表评估纳入文献质量。通过Stata12和Meta-Disc软件合并纳入文献的诊断值并检测评估异质性和发表偏倚。结果共检出994篇相关文献,通过筛选,7篇文献(含1 088例样本)纳入本次Meta分析。通过合并文献得出,miR-21对肺癌的诊断灵敏度、特异度、阳性似然比、和阴性似然分别为0.68(95%CI:0.55-0.79),0.82(95%CI:0.76-0.86),3.70(95%CI:2.60-5.25)和0.39(95%CI:0.27-0.58);综合诊断指标综合曲线下面积(SROC)和诊断比值比(DOR)分别为0.84(95%CI:0.80-0.87)和9.90(95%CI:4.75-20.63)。结论目前研究证据表明,miR-21对肺癌具有较好诊断价值,可作为肺癌诊断的潜在指标。 Objective To explore the clinical diagnostic value of microRNA-21 in lung cancer through a Meta-analysis. Methods China National Knowledge Infrastructure (CNKI) ,Technology of Chongqing (VIP) ,Wan Fang, PubMed and Embase databases were searched to identify studies in English and Chinese that assessed the diagnostic value of serum miR-21 for lung cancer. Two independent investigators identified and extracted the study characteristics from all articles according to defined inclusion and exclusion criteria. Quality assessment of diagnostic accuracy studies (QUADAS) was used to score the quality of the eligible studies. Stata12 and Meta-DiSc software were used to test the heterogeneity and to perform the Meta-analysis. Results Our search returned 994 articles ,of which seven fulfilled the inclusion criteria,accounting for 588 patients and 500 controls. Using random-effect model analysis,the summary assessments revealed that the mean sensitivity was 0.68 (95 % CI: 0. 55 to 0.79) and specificity was 0.82 (95%CI:0.76 to 0.86). The area under the receiver operating characteristic curve was 0.84 (95 %CI:0.80 to 0.87). Conclusion The current evidence suggests that serum miR-21 have moderate sensitivity and specificity for lung cancer diagnostic,and can be a potential diagnostic marker for lung cancer.
作者 陈劼
出处 《重庆医学》 CAS 北大核心 2015年第17期2389-2391,共3页 Chongqing medicine
关键词 微RNA-21 肺肿瘤 诊断 鉴别 META分析 microRNA-21 lung neoplasms diagnosis,differential Metaanalysis
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