Abstract

BackgroundDespite the existence of numerous studies investigating the diagnostic potential of blood microRNAs for colorectal cancer, the microRNAs under consideration vary widely, and comparative analysis of their diagnostic value is lacking. Consequently, this systematic review aims to identify the most effective microRNA blood tumor markers to enhance clinical decision-making in colorectal cancer screening.MethodA comprehensive search of databases, including PubMed, Embase, Web of Science, Scopus, and Cochrane, was conducted to identify case‒control or cohort studies that examined the diagnostic value of peripheral blood microRNAs in colorectal cancer. Studies were included if they provided sensitivity and specificity data, were published in English and were available between January 1, 2000, and February 10, 2023. The Critical Appraisal Skills Programme (CASP) checklist was employed for quality assessment. A Bayesian network meta-analysis was performed to estimate combined risk ratios (RRs) and 95% confidence intervals (CIs), with results presented via rankograms. This study is registered with the International Platform of Registered Systematic Review and Meta-analysis Protocols (INPLASY), 202,380,092.ResultsFrom an initial pool of 2254 records, 79 met the inclusion criteria, encompassing a total of 90 microRNAs. The seven most frequently studied microRNAs (43 records) were selected for inclusion, all of which demonstrated moderate to high quality. miR-23, miR-92, and miR-21 exhibited the highest sensitivity and accuracy, outperforming traditional tumor markers CA19-9 and CEA in terms of RR values and 95% CI for both sensitivity and accuracy. With the exception of miR-17, no significant difference was observed between each microRNA and CA19-9 and CEA in terms of specificity.ConclusionsAmong the most extensively researched blood microRNAs, miR-23, miR-92, and miR-21 demonstrated superior diagnostic value for colorectal cancer due to their exceptional sensitivity and accuracy. This systematic review and network meta-analysis may serve as a valuable reference for the clinical selection of microRNAs as tumor biomarkers.

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