Inclusion of a Genetic Risk Score into a Validated Risk Prediction Model for Colorectal Cancer in Japanese Men Improves Performance.
Inclusion of a Genetic Risk Score into a Validated Risk Prediction Model for Colorectal Cancer in Japanese Men Improves Performance.
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DOI：
10.1158/1940-6207.capr-17-0141
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发表时间：
2017-09
期刊：
影响因子：
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通讯作者：
Japan Public Health Center-based Prospective Study (JPHC Study) Group
中科院分区：
文献类型：
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作者：
Iwasaki M;Tanaka-Mizuno S;Kuchiba A;Yamaji T;Sawada N;Goto A;Shimazu T;Sasazuki S;Wang H;Marchand LL;Tsugane S;Japan Public Health Center-based Prospective Study (JPHC Study) Group
我们之前开发并验证了一个使用可改变风险因素的日本男性结直肠癌风险预测模型。为了进一步改善风险预测，我们通过使用全基因组关联研究（GWAS）识别的风险变异，在我们验证的模型中添加遗传风险评分（GRS）来评估改善程度。我们在日本公共卫生中心前瞻性研究的一项巢式病例对照研究中，使用加权Cox比例风险模型检查了GWAS确定的36种风险变异与结直肠癌风险之间的关系。在本研究中，36个测试变量中有6个与风险相关的变量构建了GRS。我们评估了三个模型：一个非遗传模型，其中包括我们之前验证的模型中使用的相同变量；采用GRS的遗传模型；还有一个包容性的模型，两者都包括在内。采用5重交叉验证法计算c统计量、综合判别改善（IDI）和净重分类改善（NRI）。我们估计了10年患结直肠癌的绝对风险。在加权GRS和结直肠癌风险之间观察到有统计学意义的关联。包含模型的平均c统计量（0.66）略大于非遗传模型的平均c统计量（0.60）。同样，在比较非遗传模型和包容性模型时，平均IDI和NRI也有所改善。这些结直肠癌的模型经过了很好的校准。将使用gwas识别的风险变异的GRS添加到我们对日本男性的验证模型中，提高了对结直肠癌风险的预测。
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.