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Published on: September 16, 2022
Development and Validation of the PREMM5 Model for Comprehensive Risk Assessment of Lynch Syndrome
Fay Kastrinos1, Hajime Uno1, Chinedu Ukaegbu1
1Fay Kastrinos and Ashley McFarland, Columbia University Medical Center, New York, NY; Hajime Uno, Chinedu Ukaegbu, Matthew B. Yurgelun, Matthew H. Kulke, Deborah Schrag, Jeffrey A. Meyerhardt, Charles S. Fuchs, Robert J. Mayer, Kimmie Ng, and Sapna Syngal, Dana-Farber Cancer Institute; Carmelita Alvero, Harvard T.H. Chan School of Public Health; Matthew B. Yurgelun, Matthew H. Kulke, Deborah Schrag, Jeffrey A. Meyerhardt, Charles S. Fuchs, Robert J. Mayer, Kimmie Ng, and Sapna Syngal, Harvard Medical School; Sapna Syngal, Brigham and Women's Hospital, Boston, MA; and Ewout W. Steyerberg, University Medical Center Rotterdam, Rotterdam, the Netherlands.
Abstract:
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.
Insights
The new PREMM5 model improves Lynch syndrome (LS) risk prediction by including PMS2 and EPCAM genes. It offers superior performance over existing models for identifying LS gene mutation carriers.
Area of Science:
- Genetics
- Oncology
- Bioinformatics
Background:
- Lynch syndrome (LS) prediction models currently assess risk for MLH1, MSH2, and MSH6 gene mutations.
- Comprehensive risk assessment requires incorporating PMS2 and EPCAM genes.
Purpose of the Study:
- To develop and validate PREMM5, a novel prediction model for Lynch syndrome risk.
- PREMM5 incorporates five mismatch repair (MMR) genes: MLH1, MSH2, MSH6, PMS2, and EPCAM.
Main Methods:
- Developed PREMM5 using polytomous logistic regression on clinical and germline data from 18,734 individuals.
- Utilized sex, age, and cancer history as predictors.
- Evaluated discrimination with AUC and clinical utility with decision curve analysis.
- Externally validated in a cohort of 1,058 colorectal cancer patients.
Main Results:
- PREMM5 identified pathogenic mutations in 5% of the development cohort (n=1,000).
- Achieved an AUC of 0.81 in the development cohort and 0.83 in the validation cohort.
- PREMM5 demonstrated superior performance compared to the PREMM1,2,6 model.
- Recommended germline LS testing for PREMM5 scores ≥ 2.5%.
Conclusions:
- PREMM5 provides comprehensive LS risk estimation across all five MMR genes.
- Supports germline LS genetic testing for individuals with PREMM5 scores ≥ 2.5%.
- PREMM5 enhances carrier identification, including those with milder phenotypes or unaffected by cancer.
