Accuracy of frozen section diagnosis of borderline ovarian tumors

ObjectiveTo determine the correlation between the diagnosis of borderline ovarian tumors (BOTs) by frozen section and permanent histology analyses.MethodsThree hundred fifty-four pathology reports with diagnoses of BOTs by frozen section or permanent histology analysis at a single institution between 1995 and 2010 were evaluated with a review of the literature. Frozen section and permanent histology analyses were compared. Multivariate regression analysis was used to assess the influence of clinicopathological parameters on the likelihood of underdiagnosis.ResultsThe overall accuracy, i.e., agreement between frozen section and permanent histology diagnoses, was observed in 228 of 354 (64.4%) cases, yielding a sensitivity of 72.6%, a positive predictive value of 85.1%, underdiagnosis in 108 cases (30.5%), and overdiagnosis in 18 cases (5.1%). Based on multivariate analysis, mucinous histology (OR, 1.48; P = 0.022) was the only significant predictor for underdiagnosis by frozen section. A comprehensive search of the literature identified 46 studies investigating the accuracy of frozen section analysis of BOTs. The data of 7 of 46 studies that met the criteria for inclusion and the data of the current study were pooled. The overall accuracy was 67.1% (741/1104), yielding a sensitivity of 82.1%, a positive predictive value of 78.7%, underdiagnosis in 222 cases (20.1%), and overdiagnosis in 141 cases (12.8%).ConclusionsFrozen section analysis of BOTs has low accuracy, sensitivity, and positive predictive value, and underdiagnosis and overdiagnosis are frequent. Therefore, surgical decision-making for BOTs based on frozen section diagnosis should be done carefully, especially in tumors with mucinous histology.

Research highlights
► Accuracy of frozen section diagnosis of borderline ovarian tumors (BOTs): low.
► Underdiagnosis and overdiagnosis of BOTs: frequent.
► Surgical decision-making for BOTs on frozen section diagnosis: be careful.