Performance of PREM1,2,6, MMRpredict, and MMRpro in detecting Lynch syndrome among endometrial cancer cases

Purpose: Lynch syndrome accounts for 2-5% of endometrial cancer cases. Lynch syndrome prediction models have not been evaluated among endometrial cancer cases. Methods: Area under the receiver operating curve (AUC), sensitivity and specificity of PREMM1,2,6, MMRpredict, and MMRpro scores were assessed among 563 population-based and 129 clinic-based endometrial cancer cases. Results: A total of 14 (3%) population-based and 80 (62%) clinic-based subjects had pathogenic mutations. PREMM1,2,6, MMRpredict, and MMRpro were able to distinguish mutation carriers from -noncarriers (AUC of 0.77, 0.76, and 0.77, respectively), among -population-based cases. All three models had lower discrimination for the clinic-based cohort, with AUCs of 0.67, 0.64, and 0.54, respectively. Using a 5% cutoff, sensitivity and specificity were as follows: PREMM1,2,6, 93% and 5% among populatio Conclusion: Currently available prediction models have limited clinical utility in determining which patients with endometrial cancer should undergo genetic testing for Lynch syndrome. Immunohistochemical analysis and microsatellite instability testing may be the best currently available tools to screen for Lynch syndrome in endometrial cancer patients