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We previously developed and validated a risk prediction model for colorectal cancer in Japanese men using modifiable risk factors. To further improve risk prediction, we evaluated the degree of improvement obtained by adding a genetic risk score (GRS) using genome-wide association study (GWAS)-identified risk variants to our validated model. We examined the association between 36 risk variants identified by GWAS and colorectal cancer risk using a weighted Cox proportional hazards model in a nested case-control study within the Japan Public Health Center-based Prospective Study. GRS was constructed using six variants associated with risk in this study of the 36 tested. We assessed three models: a nongenetic model that included the same variables used in our previously validated model; a genetic model that used GRS; and an inclusive model, which included both. The c-statistic, integrated discrimination improvement (IDI), and net reclassification improvement (NRI) were calculated by the 5-fold cross-validation method. We estimated 10-year absolute risks for developing colorectal cancer. A statistically significant association was observed between the weighted GRS and colorectal cancer risk. The mean c-statistic for the inclusive model (0.66) was slightly greater than that for the nongenetic model (0.60). Similarly, the mean IDI and NRI showed improvement when comparing the nongenetic and inclusive models. These models for colorectal cancer were well calibrated. The addition of GRS using GWAS-identified risk variants to our validated model for Japanese men improved the prediction of colorectal cancer risk. Cancer Prev Res; 10(9); 535-41. ©2017 AACR .

Inclusion of a Genetic Risk Score into a Validated Risk Prediction Model for Colorectal Cancer in Japanese Men Improves Performance