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 PREMM_1,2,6 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 PREMM_1,2,6. 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 PREMM_1,2,6 model in the identification of carriers of LS, including those with weaker phenotypes and individuals unaffected by cancer.

	Year	Citations

About