荟萃分析
肺癌
医学
细胞外小泡
肿瘤科
内科学
小RNA
阶段(地层学)
曲线下面积
诊断优势比
癌症
优势比
生物
基因
古生物学
生物化学
细胞生物学
作者
Hairong Huang,Jinyuan Zhu,Yong Lin,Zhexiao Zhang,Jie Liu,Chenfei Wang,Hongfu Wu,Tangbin Zou
标识
DOI:10.1080/14737159.2021.1935883
摘要
Background: This meta-analysis aimed to evaluate the diagnostic accuracy of extracellular vesicles (EV) miRNAs for non-small cell lung cancer (NSCLC).Methods: All eligible studies were searched in an online database. Stata 15.0, Meta-disc 14.0 and Review Manager 5.2 software packages were used to perform all statistical analysis.Results: The analysis included 16 articles and 70 studies. Pooled sensitivity (SEN) and specificity (SPE), positive predictive value and negative predictive value were 0.77 (95% CI: 0.72-0.80), 0.83 (95% CI: 0.78-0.86), 0.88 (95% CI: 0.86-0.90) and 0.63 (95% CI: 0.58-0.68), respectively. The overall diagnostic odds ratio (DOR) was 16 (95% CI: 11-21) and the area under the curve (AUC) was 0.86 (95% CI: 0.83-0.89). 3 EV miRNAs could identify metastatic NSCLC from healthy, and 10 distinguish early-stage NSCLC. The respective targets of EV miR-21, miR-210, and miR-1290 could activate PI3K/AKT-related pathway.Conclusion: EV miRNAs had high diagnostic accuracy (AUC = 0.86) for NSCLC, especially metastatic NSCLC (AUC = 0.90), and early-stage NSCLC (AUC = 0.88). Besides, multitudinous EV miRNAs combined showed higher diagnostic value than alone. EV miR-21, miR-210, and miR-1290 might be associated with PI3K/AKT-related pathway and the valuable diagnostic biomarkers for NSCLC.
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