Wang Yongjing, Sun Dianshui, Wang Juandong, Dou Aixia, Zheng Chengyun
Department of Hematology, The Second Hospital of Shandong University Jinan 250033, Shandong, P. R. China.
Cancer Center, The Second Hospital of Shandong University Jinan 250033, Shandong, P. R. China.
Int J Clin Exp Med. 2015 Aug 15;8(8):14479-89. eCollection 2015.
MicroRNAs (miRNAs) have attracted many attentions in lymphoma diagnostic research. The inconsistence of diagnostic performance in these existed literatures leading us to conduct this meta-analysis. In order to have a scientific and reliable study, all related articles were screened from Medline, Embase, CNKI and other databases. The sensitivity and specificity of each involved research were used to plot the summary receiver operator characteristic (SROC) curve and calculate the area under the curve (AUC). The QUADAS-2 tool was applied to estimate the quality of included studies. In addition, Deeks' funnel plot asymmetry test was performed to estimate publication bias. Overall, 14 studies from 6 articles were included to evaluate the whole test performance. The overall pooled results were as follows: sensitivity was 0.91 (95% CI: 0.83-0.95), specificity was 0.84 (95% CI: 0.75-0.90), the AUC was 0.93 (95% CI: 0.91-0.95), positive likelihood ratio-PLR was 5.5 (95% CI: 3.5-8.8), negative likelihood ratio-NLR was 0.11 (95% CI: 0.06-0.21), and diagnostic odds ratio-DOR was 50 (95% CI: 19-128). In summary, results from meta-analysis showed that miRNAs analysis might significantly increase the diagnostic accuracy of lymphoma. Further massive prospective studies still needed to validate our conclusion before clinical application.
微小RNA(miRNA)在淋巴瘤诊断研究中已引起广泛关注。现有文献中诊断性能的不一致促使我们进行这项荟萃分析。为了进行科学可靠的研究,我们从Medline、Embase、中国知网和其他数据库中筛选了所有相关文章。使用每项纳入研究的敏感性和特异性绘制汇总受试者工作特征(SROC)曲线,并计算曲线下面积(AUC)。应用QUADAS - 2工具评估纳入研究的质量。此外,进行Deeks漏斗图不对称性检验以评估发表偏倚。总体而言,纳入了6篇文章中的14项研究来评估整体测试性能。总体合并结果如下:敏感性为0.91(95%置信区间:0.83 - 0.95),特异性为0.84(95%置信区间:0.75 - 0.90),AUC为0.93(95%置信区间:0.91 - 0.95),阳性似然比(PLR)为5.5(95%置信区间:3.5 - 8.8),阴性似然比(NLR)为0.11(95%置信区间:0.06 - 0.21),诊断比值比(DOR)为50(95%置信区间:19 - 128)。总之,荟萃分析结果表明,miRNA分析可能会显著提高淋巴瘤的诊断准确性。在临床应用之前,仍需要进一步的大规模前瞻性研究来验证我们的结论。