Conclusion
breast cancer
REGRESSION, BREAST CANCER
In summary, we have found genetic and lifestyle risk predictors for breast cancer with moderate discrimination, which might provide reference for breast cancer screening in southeast China. Further population‐based studies are needed to validate the model for future applications in personalized breast cancer screening programs.Among all factors considered, the best model was achieved when polygenetic risk score, lifestyle, and reproductive factors were considered jointly in the logistic regression model (AUC = 0.73; 95% CI: 0.70–0.77). The performance of the models established in this study is better than that using scores calculated from CKB, Gail and Tyrer–Cuzick models. However, there is no significant difference between the machine learning models and logistic model.
Shuqing Zou, Yuxiang Lin and Xingxing Yu these authors contributed equally to this work and share first authorship.