Evaluating the diagnostic accuracy of microRNA-494 as a biomarker in cancers: A systematic review and meta-analysis

Abstract

MicroRNA-494 (miR-494) has emerged as a potential diagnostic biomarker for cancer detection, but conflicting reports have led to uncertainty regarding its clinical utility. This study aims to address these discrepancies by conducting a comprehensive meta-analysis of miR-494 diagnostic performance across various cancer types. A comprehensive literature search was performed across multiple databases, including PubMed, Web of Science, Wanfang databases, and CNKI (China National Knowledge Infrastructure), with a cutoff date of April 23, 2024. Eligible studies were identified using predefined inclusion criteria and various search strategies to ensure a thorough coverage of the available evidence. To evaluate the diagnostic performance of miR-494 in cancer detection, relevant measures such as sensitivity, specificity, and other diagnostic accuracy indicators were extracted from the included studies. These data were synthesized using bivariate meta-analysis models to generate pooled estimates of miR-494 diagnostic performance. All statistical analyses were conducted using the STATA 16.0 software. This meta-analysis pooled data from 8 studies, comprising a total of 647 cancer cases and 407 healthy controls. The aggregated diagnostic performance of miR-494 was as follows: a sensitivity of 0.67 (95% confidence interval [CI], 0.52–0.80), a specificity of 0.85 (95% CI, 0.77–0.91), and an area under the curve of 0.86 (95% CI, 0.82–0.88), indicating good overall diagnostic accuracy. The diagnostic odds ratio (DOR) was 12.11 (95% CI, 7–21), suggesting that miR-494 has strong discriminatory power in distinguishing cancer patients from healthy individuals. The positive likelihood ratio of 4.62 (95% CI, 3.1–6.8) and negative likelihood ratio of 0.38 (95% CI, 0.26–0.56) further support the diagnostic utility of miR-494. Deeks’ funnel plot asymmetry test was employed to assess potential publication bias, yielding a P value of 0.50, which suggests the absence of significant bias in the included studies. The meta-analysis results suggest that miR-494 exhibits promising diagnostic performance in detecting cancer, with moderate accuracy. The pooled sensitivity, specificity, and high area under the receiver operating characteristic curve highlight its potential as a cancer biomarker, indicating its utility in early detection and accurate diagnosis.