Lynch Syndrome Patients with Limited Family History Identified in a Laboratory Setting: A Descriptive Study

TLDR

The study developed and validated the PREMM(1,2,6) model to estimate individual risk of pathogenic mutations in the MMR genes MLH1, MSH2, and MSH6 using personal and family cancer history. The model was built with a multivariable polytomous logistic regression (PREMM(1,2,6)) trained on 4,539 probands, incorporating factors such as sex, colorectal and endometrial cancers, and extracolonic cancers from probands and relatives. Validation in 1,827 colorectal cancer cases showed the model achieved AUCs of 0.86–0.88 for overall mutation risk, with 12 % of the original cohort carrying pathogenic MMR mutations, and the tool is available online for clinical use.

Abstract

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.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.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).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.