Reliability of Frozen Section Biopsy in Detecting Endometrial Pathologies: A Systematic Review of Sensitivity and...

Endometrial pathologies, ranging from benign hyperplasia to carcinoma, present significant diagnostic challenges in gynecologic practice. Frozen section (FS) biopsy, a rapid intraoperative histopathological evaluation method, is widely used for surgical decision-making, but its diagnostic reliability remains debated. This systematic review evaluates the sensitivity, specificity, and overall accuracy of FS biopsy in detecting endometrial pathologies compared with final histopathology. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, we conducted a comprehensive search of PubMed, Scopus, Web of Science, and Embase up to July 2025. Fifteen studies meeting predefined eligibility criteria (e.g., comparative design, sufficient diagnostic data) were included. Risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. Data on sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and concordance rates were extracted and synthesized narratively due to methodological heterogeneity. Among the 15 studies, FS biopsy exhibited high specificity and variable sensitivity. Concordance with final histopathology was strong for invasive carcinomas but poor for complex atypical hyperplasia (CAH). Reported accuracy ranged from 43.47% to 97%, with higher reliability for high-grade tumors and myometrial invasion. Limitations included sampling errors and pathologist-dependent variability. FS biopsy is highly specific for detecting endometrial malignancies and valuable for intraoperative guidance, particularly when gross lesions are present. However, its limited sensitivity for CAH and early-stage cancers necessitates caution. Integration with preoperative imaging and standardized protocols may optimize its use. Final paraffin-embedded histopathology remains the gold standard for definitive diagnosis.