Development and Validation of the PREMM5 Model for Comprehensive Risk Assessment of Lynch Syndrome
| Autor: | Ewout W. Steyerberg, Matthew B. Yurgelun, Hajime Uno, Jeffrey A. Meyerhardt, Fay Kastrinos, Robert J. Mayer, Matthew H. Kulke, Ashley McFarland, Deborah Schrag, Carmelita Alvero, Chinedu Ukaegbu, Charles S. Fuchs, Sapna Syngal, Kimmie Ng |
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| Přispěvatelé: | Public Health |
| Rok vydání: | 2017 |
| Předmět: |
Male
Proband Cancer Research Bioinformatics Logistic regression Risk Assessment Cohort Studies 03 medical and health sciences 0302 clinical medicine Germline mutation Predictive Value of Tests PMS2 medicine Humans Genetic Predisposition to Disease Germ-Line Mutation Mismatch Repair Endonuclease PMS2 Genetic testing Models Genetic Receiver operating characteristic medicine.diagnostic_test business.industry Reproducibility of Results ORIGINAL REPORTS Middle Aged Epithelial Cell Adhesion Molecule medicine.disease Colorectal Neoplasms Hereditary Nonpolyposis Lynch syndrome DNA-Binding Proteins Logistic Models MutS Homolog 2 Protein ROC Curve Oncology 030220 oncology & carcinogenesis Mutation (genetic algorithm) Female 030211 gastroenterology & hepatology MutL Protein Homolog 1 business |
| Zdroj: | Journal of Clinical Oncology, 35(19), 2165-+. American Society of Clinical Oncology |
| ISSN: | 1527-7755 0732-183X |
| DOI: | 10.1200/jco.2016.69.6120 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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