domingo, 30 de julio de 2017

Inclusion of a genetic risk score into a validated risk prediction model for colorectal cancer in Japanese men improves performance. - PubMed - NCBI

2017 Jul 20. pii: canprevres.0141.2017. doi: 10.1158/1940-6207.CAPR-17-0141. [Epub ahead of print]

Inclusion of a genetic risk score into a validated risk prediction model for colorectal cancer in Japanese men improves performance.

Iwasaki M1, Tanaka-Mizuno S2, Kuchiba A3, Yamaji T4, Sawada N4, Goto A4, Shimazu T4, Sasazuki S4, Wang H5, Le Marchand L5, Tsugane S4.

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Abstract

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 hazard model in a nested case-control study within the Japan Public Health Center-based Prospective Study. GRS was constructed using 6 variants associated with risk in this study out of the 36 tested. We assessed three models: a non-genetic model which included the same variables used in our previously validated model; a genetic model which 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 non-genetic model (0.60). Similarly, the mean IDI and NRI showed improvement when comparing the non-genetic 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.