Li Qingru, Tian Jing, Chen Cuiqing, Liu Hong, Li Binyi
Department of Nephrology, the Eighth Clinical Medical School of Guangzhou University of Chinese Medicine, Foshan, China.
Department of Nephrology, Foshan Hospital of Traditional Chinese Medicine, Foshan, China.
Front Oncol. 2024 Oct 28;14:1441429. doi: 10.3389/fonc.2024.1441429. eCollection 2024.
This meta-analysis aims to evaluate the potential of exosomal microRNAs(Exo-miRs) as diagnostic biomarkers for renal cell carcinoma(RCC).
Clinical studies reporting the use of Exo-miRs in the diagnosis of RCC were retrieved from PubMed, Web of Science, Cochrane Library, Embase, China National Knowledge Infrastructure (CNKI), Wanfang, VIP, and Chinese Biomedical Literature Database (SinoMed). After relevant data were screened and extracted, the quality of the included studies was assessed using the QUADAS-2 tool. The Meta-disc (version 1.4) software was used to analyze the heterogeneity of threshold/non-threshold effects in the included studies. The Stata MP (version 16.0) software was used to calculate sensitivity(Sen), specificity(Spe), positive likelihood ratio(+LR), negative likelihood ratio(-LR), area under the curve(AUC), diagnostic odds ratio(DOR), and publication bias.
A total of 11 studies were included in this meta-analysis. Spearman correlation coefficient was 0.319 ( = 0.075; >0.05), indicating no threshold effects. The pooled Sen, Spe, +LR, -LR, DOR, and AUC were 0.73 (95% , 0.68-0.78), 0.81 (95% , 0.76-0.85), 3.80 (95% , 3.02-4.77), 0.33 (95% , 0.28-0.40), 11.48 (95% , 8.27-15.95), and 0.84 (95% , 0.80-0.87), respectively. No publication bias was detected among the included studies.
The expression of Exo-miRs plays an important role in the diagnosis of RCC. However, owing to the limited number of included studies and heterogeneity among them, further clinical research is necessary to verify the findings of this meta-analysis.
https://www.crd.york.ac.uk/PROSPERO, identifier CRD42023445956.
本荟萃分析旨在评估外泌体微小RNA(Exo-miRs)作为肾细胞癌(RCC)诊断生物标志物的潜力。
从PubMed、Web of Science、Cochrane图书馆、Embase、中国知网(CNKI)、万方、维普和中国生物医学文献数据库(SinoMed)中检索报告使用Exo-miRs诊断RCC的临床研究。在筛选和提取相关数据后,使用QUADAS-2工具评估纳入研究的质量。Meta-disc(1.4版)软件用于分析纳入研究中阈值/非阈值效应的异质性。Stata MP(16.0版)软件用于计算敏感性(Sen)、特异性(Spe)、阳性似然比(+LR)、阴性似然比(-LR)、曲线下面积(AUC)、诊断比值比(DOR)和发表偏倚。
本荟萃分析共纳入11项研究。Spearman相关系数为0.319( = 0.075;>0.05),表明无阈值效应。合并的Sen、Spe、+LR、-LR、DOR和AUC分别为0.73(95% ,0.68 - 0.78)、0.81(95% ,0.76 - 0.85)、3.80(95% ,3.02 - 4.77)、0.33(95% ,0.28 - 0.40)、11.48(95% ,8.27 - 15.95)和0.84(95% ,0.80 - 0.87)。纳入研究中未检测到发表偏倚。
Exo-miRs的表达在RCC诊断中起重要作用。然而,由于纳入研究数量有限且存在异质性,需要进一步的临床研究来验证本荟萃分析的结果。