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Purpose Current Lynch syndrome (LS) prediction models quantify the risk to an individual of carrying a pathogenic germline mutation in three mismatch repair (MMR) genes: MLH1, MSH2, and MSH6. We developed a new prediction model, PREMM5, that incorporates the genes PMS2 and EPCAM to provide comprehensive LS risk assessment. Patients and Methods PREMM5 was developed to predict the likelihood of a mutation in any of the LS genes by using polytomous logistic regression analysis of clinical and germline data from 18,734 individuals who were tested for all five genes. Predictors of mutation status included sex, age at genetic testing, and proband and family cancer histories. Discrimination was evaluated by the area under the receiver operating characteristic curve (AUC), and clinical impact was determined by decision curve analysis; comparisons were made to the existing PREMM1,2,6 model. External validation of PREMM5 was performed in a clinic-based cohort of 1,058 patients with colorectal cancer. Results Pathogenic mutations were detected in 1,000 (5%) of 18,734 patients in the development cohort; mutations included MLH1 (n = 306), MSH2 (n = 354), MSH6 (n = 177), PMS2 (n = 141), and EPCAM (n = 22). PREMM5 distinguished carriers from noncarriers with an AUC of 0.81 (95% CI, 0.79 to 0.82), and performance was similar in the validation cohort (AUC, 0.83; 95% CI, 0.75 to 0.92). Prediction was more difficult for PMS2 mutations (AUC, 0.64; 95% CI, 0.60 to 0.68) than for other genes. Performance characteristics of PREMM5 exceeded those of PREMM1,2,6. Decision curve analysis supported germline LS testing for PREMM5 scores ≥ 2.5%. Conclusion PREMM5 provides comprehensive risk estimation of all five LS genes and supports LS genetic testing for individuals with scores ≥ 2.5%. At this threshold, PREMM5 provides performance that is superior to the existing PREMM1,2,6 model in the identification of carriers of LS, including those with weaker phenotypes and individuals unaffected by cancer.

Purpose Prostate cancer has been described as a component tumor of Lynch syndrome (LS), with tumors obtained from mutation carriers demonstrating the DNA mismatch repair deficiency phenotype. Previous studies quantifying prostate cancer risk in LS have provided conflicting results. Methods We examined cancer histories of probands and their first- through fourth-degree relatives for 198 independent mutation-positive LS families enrolled in two US familial cancer registries. Modified segregation analysis was used to calculate age-specific cumulative risk or penetrance estimates, with accompanying Wald-type CIs. Cumulative lifetime risks and hazard ratio (HR) estimates for prostate cancer were calculated and compared with those of the general population. Results Ninety-seven cases of prostate cancer were observed in 4,127 men. Median age at prostate cancer diagnosis was 65 years (range, 38 to 89 years), with 11.53% of affected individuals diagnosed before age 50 years. The cumulative risk of prostate cancer at ages 60 and 80 years was 6.30% (95% CI, 2.47 to 9.96) and 30.0% (95% CI, 16.54 to 41.30), as compared with the population risk of 2.59% and 17.84%, respectively. The overall prostate cancer HR among carriers was 1.99 (95% CI, 1.31 to 3.03). Conclusion The cumulative lifetime risk of prostate cancer in individuals with LS is two-fold higher than in the general population and is slightly higher in carriers diagnosed before age 60 years (HR, 2.48; 95% CI, 1.34 to 4.59). These estimates are clinically valuable to quantify risk for both patients and providers.

1517Background: LS is the one of the most common inherited causes of cancer and predisposes to a wide variety of cancers. UTCs (kidney, renal pelvis, ureter, and bladder cancer) are collectively th...

1521Background: Identifying LS in pts without a prior history of an associated cancer (unaffected pts) relies exclusively on family history analysis and is thus inherently different from LS evaluat...

5024 Background: Lynch syndrome (LS), a heritable condition due to a mismatch repair (MMR) gene mutation, accounts for nearly 2% of all endometrial cancer (EC) cases. Prediction models for LS have been developed but have not been evaluated among EC cases. Methods: PREMM1,2,6, MMRpredict and MMRpro risk scores were calculated for 563 population-based, unselected EC cases and 129 clinic-based, high-risk EC cases who underwent genetic evaluation for LS. Discriminative ability of each model was assessed using the area under the receiver operating curve (AUC). Sensitivity and specificity were calculated at 5% cut-off for PREMM1,2,6 and MMRpro, and at 0.5% cut- off for MMRpredict (EC replaced a proximal colorectal cancer (CRC) diagnosis). Results: Pathogenic MMR gene mutations were detected in 14 population-based and 80 clinic-based subjects. PREMM1,2,6, MMRpredict and MMRpro were able to distinguish mutation carriers from non-carriers with AUC of 0.77, 0.79 and 0.75, respectively, for the unselected cohort and...