The value of miRNAs as a biomarker for the diagnosis of gestational diabetes mellitus: a meta-analysis

Abstract

Objectives: The present meta-analysis evaluated the value of miRNAs in the diagnosis of gestational diabetes mellitus (GDM). Material and methods: Eligible studies were gathered from MEDLINE, EMBASE, PubMed, Chinese National Knowledge Infrastructure (CNKI), WanFang, and CQVIP information databases. Combined sensitivity, specificity, and summary receiver operating characteristic (SROC) curves of enrolled studies were analyzed using STATA 12.0. Diagnostic accuracy was examined by diagnostic likelihood ratio (DLR), diagnostic score, and diagnostic odds ratio (DOR). Publication bias was calculated using Deeks’ funnel plot. Results: 18 articles (29 studies) were included in this meta-analysis. The pooled sensitivity of overall miRNAs was 0.83 (95% CI = 0.77–0.88), and the specificity was 0.79 (95% CI = 0.72–0.84). The area under SROC curve (AUC) was 0.88 (95% CI = 0.85–0.90). The positive DLR was 3.94 (95% CI = 2.98–5.21), and the negative DLR was 0.22 (95% CI = 0.16–0.30). The diagnostic score was 2.91 (95% CI = 2.44–3.37), and the DOR was 18.27 (95% CI = 11.44–29.17). These results suggest that miRNAs have high diagnostic accuracy for GDM. High heterogeneity may be caused by study design, gestational age, and cutoff value. Subgroup analysis indicates that sensitivity and specificity are higher in case-control studies than in cohort studies. Specificity differs significantly in the cutoff value subgroup. Conclusions: Overall, miRNAs showed high accuracy in diagnosing of metabolic changes in GDM patients. High heterogeneity may be caused by study design, sampling gestational age, and cutoff value.