Diagnostic accuracy of non-coding RNA for detecting endometriosis: A systematic review and meta-analysis.

OBJECTIVES

Endometriosis diagnosis currently relies on invasive laparoscopy, creating a need for non-invasive alternatives. This study evaluates microRNAs (miRNAs) as potential diagnostic biomarkers for endometriosis through systematic evidence synthesis and performance analysis.

METHODS

We systematically reviewed studies (1992-2025) from seven databases (Pub-Med/MEDLINE, Web of Science, Scopus, etc.) using endometriosis- and ncRNA-related keywords.

INCLUDED STUDIES: (1) used qRT-PCR for miRNA/lncRNA detection, (2) con-firmed endometriosis via laparoscopy, and (3) provided data to construct 2 × 2 contingency tables. All human biospecimens were eligible; no restrictions were applied to study design or language. Exclusions included non-RNA biomarkers or non-PCR methods. QUADAS-1 assessed methodological quality. To avoid multiplicity, diagnostic accuracy metrics (sensitivity, specificity) were calculated and synthesized separately for each biomarker. Evidence certainty was evaluated with GRADE.

RESULTS

Among 28 qualifying studies (most with QUADAS-1 scores ≥7), mir-8 showed optimal accuracy (sensitivity: 94.8 %, 95 % CI 58.0-99.6 %; specificity: 91.9 %, 95 % CI 71.7-98.1 %) with favorable likelihood ratios (PLR > 5, NLR < 0.2), albeit with significant het-erogeneity (I2 > 90 %). mir - 122 demonstrated more consistent performance with narrower confidence intervals.

CONCLUSIONS

While mir-8 exhibits superior diagnostic accuracy, mir - 122 expression must be validated in a patient cohort to underline its clinical utility. However, current evidence remains limited by low GRADE certainty. Our findings highlight two critical considerations for biomarker development: (1) the necessity of evaluating methodological quality and heterogeneity along-side traditional metrics, and (2) the distinct diagnostic profiles of individual miRNAs, which preclude combination approaches. These results emphasize the need for standardized, independent validation of candidate miRNAs before clinical implementation.