MicroRNAs as potential diagnostic biomarkers in renal cell carcinoma.

Abstract

Emerging evidence has suggested that microRNAs (miRNAs) may be promising novel biomarkers for the diagnosis of renal cell carcinoma (RCC). However, the results of current studies are still conflicting. Hence, we undertake the current meta-analysis to comprehensively assess the diagnostic potential of miRNAs in RCC. The bivariate meta-analysis model was employed to summarize the sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR). Summary receiver operating characteristic (SROC) curve and area under the curve (AUC) were used to evaluate the diagnostic accuracy. Subgroup analyses and meta-regression were used to explore the between-study heterogeneity. Deeks' funnel plot asymmetry test was used to test the potential of publication bias. All analyses were performed using STATA software (version 12.0). The pooled sensitivity and specificity of miRNAs for the diagnosis of RCC were 0.85 (95% confidence interval (CI), 0.77-0.90) and 0.84 (95% CI, 0.70-0.92). The value of AUC was 0.91 (95% CI, 0.88-0.93), suggesting that the diagnostic accuracy of miRNAs achieved a relatively high level. Furthermore, subgroup analyses showed that tissue-based miRNA assay is recommended to improve the diagnostic accuracy. In conclusion, the high degree of diagnostic accuracy suggests that miRNA in RCC patients may serve as next-generation biomarkers for detection of the disease. However, large-scale investigations and additional improvements are urgently needed to confirm our results and verify the feasibility of routine clinical utilization.