Intraoperative frozen section risk assessment accurately tailors the surgical staging in patients affected by early-stage endometrial cancer: the application of 2 different risk algorithms.

OBJECTIVE: The aim of this study was to investigate the frozen section (FS) accuracy in tailoring the surgical staging of patients affected by endometrial cancer, using 2 different risk classifications. METHODS/MATERIALS: A retrospective analysis of 331 women affected by type I endometrial cancer and submitted to FS assessment at the time of surgery. Pathologic features were examined on the frozen and permanent sections according to both the GOG33 and the Mayo Clinic algorithms. We compared the 2 models through the determination of Landis and Koch kappa statistics, concordance rate, sensitivity, specificity, positive predictive value, and negative predictive value for each risk algorithm, to assess whether there are differences in FS accuracy depending on the model used. RESULTS: The observed agreement between the frozen and permanent sections was respectively good (k = 0.790) for the GOG33 and optimal (k = 0.810) for the Mayo classification. Applying the GOG33 algorithm, 20 patients (6.7%) were moved to an upper risk status, and 20 (6.7%) were moved to a lower risk status on the permanent section; the concordance rate was 86.5%. With the Mayo Clinic algorithm, discordant cases between frozen and permanent sections were 19 (7.6%), and the risk of lymphatic spread was underestimated only in 1 case (0.4%); the concordance rate was 92.4%. The sensitivity, specificity, positive predictive value, and negative predictive value for the GOG33 were 92%, 94%, 92%, and 93%, whereas with the Mayo algorithm, these were 98%, 91%, 77%, and 99%, respectively. CONCLUSIONS: According to higher correlation rate and observed agreement (92.4% vs 86.5% and k = 0.810 vs 0.790, respectively), the Mayo Clinic algorithm minimizes the number of patients undertreated at the time of surgery than the GOG33 classification and can be adopted as an FS algorithm to tailor the surgical treatment of early-stage endometrial cancer even in different centers.

Frozen section pathology at time of hysterectomy accurately predicts endometrial cancer in patients with preoperative diagnosis of atypical endometrial hyperplasia.

OBJECTIVES: A significant number of women diagnosed with atypical endometrial hyperplasia (AEH) on endometrial biopsy will be diagnosed with endometrial cancer (EC) on the hysterectomy specimen at permanent section. Surgical treatment for AEH and EC differ substantially. We have assessed the concordance in EC between frozen and permanent sections on patients undergoing hysterectomy for AEH. MATERIALS AND METHODS: A retrospective review of 66 frozen sections on patients undergoing hysterectomy for AEH was performed. Frozen and permanent section diagnoses were categorized as negative or positive for malignancy. Permanent section carcinomas were classified as low or high risk based on their histopathology, myometrial invasion and differentiation. Correlation between frozen and permanent section and sensitivity, specificity, PPV, NPV and accuracy of frozen section in predicting EC in permanent section were calculated. Likelihood of diagnosing EC on frozen section was compared based on risk stratification at permanent section. RESULTS: Frozen and permanent sections revealed malignancy in 43.9% and 56% of the patients respectively. 94.1% of high risk carcinomas were identified as EC at frozen section as compared to 55% of low risk EC. Concordance was good (κ=0.75). Sensitivity, specificity, NPV, PPV and accuracy in predicting EC at frozen section were 73%, 93.1%, 73% and 93.1% respectively. Carcinomas were detected at frozen section significantly more often if they were at high risk. CONCLUSIONS: The substantial agreement between frozen and permanent sections allows minimizing under- and overtreatment of women undergoing hysterectomy for AEH. High risk EC are efficiently identified in frozen section.