Cui Jianxiong
Department of Oncology, Sichuan Provincial Crops Hospital of Chinese People's Armed Police Forces Leshan 614000, Sichuan, China.
Int J Clin Exp Med. 2015 Feb 15;8(2):1703-14. eCollection 2015.
Cancer is a main public health problem all over the world with its high morbidity and mortality. MicroRNA-16 (miRNA-16, miR-16) family members have been considered as potential biomarkers in cancer diagnosis in several previous studies, but their results were inconsistent.
The present meta-analysis was conducted to assess the diagnostic efficacy of miR-16 family for cancer systematically.
Multiple search strategies and random-effects model were used. Pooled sensitivity, specificity and other parameters were calculated. Totally, 1,259 cancer patients and 855 controls from 16 articles were enrolled in this meta-analysis.
The pooled results for sensitivity, specificity, positive likelihood ratios (PLR), negative likelihood ratios (NLR), diagnostic odds ratio (DOR) and the area under the curve (AUC) were 0.80 (95% CI: 0.73-0.85), 0.77 (95% CI: 0.70-0.84), 3.5 (95% CI: 2.5-5.0), 0.26 (95% CI: 0.19-0.36), 14 (95% CI: 8-25) and 0.86 (95% CI: 0.82-0.88), respectively. Our subgroup analyses indicated miR-16 family assay was more appropriate in Asian populations.
Our findings demonstrated that miR-16 family members have a relatively high value as promising biomarkers in diagnosing cancers. Nevertheless, the clinical application of miR-16 family profiling for cancers diagnosis still needs further large-scale studies and additional improvements of substantiation.
癌症是全球主要的公共卫生问题,发病率和死亡率都很高。在先前的几项研究中,MicroRNA-16(miRNA-16,miR-16)家族成员被认为是癌症诊断中的潜在生物标志物,但其结果并不一致。
本荟萃分析旨在系统评估miR-16家族对癌症的诊断效能。
采用多种检索策略和随机效应模型。计算合并敏感度、特异度及其他参数。本荟萃分析共纳入16篇文章中的1259例癌症患者和855例对照。
合并后的敏感度、特异度、阳性似然比(PLR)、阴性似然比(NLR)、诊断比值比(DOR)和曲线下面积(AUC)分别为0.80(95%CI:0.73-0.85)、0.77(95%CI:0.70-0.84)、3.5(95%CI:2.5-5.0)、0.26(95%CI:0.19-0.36)、14(95%CI:8-25)和0.86(95%CI:0.82-0.88)。我们的亚组分析表明,miR-16家族检测在亚洲人群中更适用。
我们的研究结果表明,miR-16家族成员作为有前景的生物标志物在癌症诊断中具有较高价值。然而,miR-16家族谱在癌症诊断中的临床应用仍需要进一步的大规模研究和更多的确证改进。