The PREMM(1,2,6) model predicts risk of MLH1, MSH2, and MSH6 germline mutations based on cancer history.

摘要

BACKGROUND & AIMS: We developed and validated a model to estimate the risks of mutations in the mismatch repair (MMR) genes MLH1, MSH2, and MSH6 based on personal and family history of cancer. METHODS: Data were analyzed from 4539 probands tested for mutations in MLH1, MSH2, and MSH6. A multivariable polytomous logistic regression model (PREMM(1,2,6)) was developed to predict the overall risk of MMR gene mutations and the risk of mutation in each of the 3 genes. The discriminative ability of the model was validated in 1827 population-based colorectal cancer (CRC) cases. RESULTS: Twelve percent of the original cohort carried pathogenic mutations (204 in MLH1, 250 in MSH2, and 71 in MSH6). The PREMM(1,2,6) model incorporated the following factors from the probands and first- and second-degree relatives (odds ratio; 95% confidence intervals [CIs]): male sex (1.9; 1.5-2.4), a CRC (4.3; 3.3-5.6), multiple CRCs (13.7; 8.5-22), endometrial cancer (6.1; 4.6-8.2), and extracolonic cancers (3.3; 2.4-4.6). The areas under the receiver operating characteristic curves were 0.86 (95% CI, 0.82-0.91) for MLH1 mutation carriers, 0.87 (95% CI, 0.83-0.92) for MSH2, and 0.81 (95% CI, 0.69-0.93) for MSH6; in validation, they were 0.88 for the overall cohort (95% CI, 0.86-0.90) and the population-based cases (95% CI, 0.83-0.92). CONCLUSIONS: We developed the PREMM(1,2,6) model, which incorporates information on cancer history from probands and their relatives to estimate an individual's risk of mutations in the MMR genes MLH1, MSH2, and MSH6. This Web-based decision making tool can be used to assess risk of hereditary CRC and guide clinical management.