Dynamic prediction incorporating time-varying covariates for the onset of breast cancer

项目摘要 三阴性乳腺癌（TNBC）是一种侵袭性乳腺癌亚型，具有有限的免疫反应性。 治疗选择和生存率低。大约12%至17%的乳腺癌患者 诊断为TNBC。患有TNBC的妇女的结果相对较差，无法治疗 有针对性的治疗然而，TNBC的风险在所有种族-族裔群体中并不一致。 美国人口。流行病学风险因素和TNBC发病率的审查显示， 风险或风险降低的变化，但母乳喂养史除外， 蔬菜和谷物的摄入量。我们的目标是带来个性化的动态预测，以提高 目前的TNBC风险分类模式，以充分利用纵向信息， 除基线信息外，风险预测/分层可更新为新的 收集观察结果，以反映妇女的最新健康和行为相关状况。 具体而言，我们的目标是调查5年和10年TNBC风险预测性能， 新型统计方法充分利用基于乳房X光检查的个性化风险因素， 重复的乳房X光照片。拟议的研究利用了WashU TNBC队列， 丰富的数字乳腺X线照片，充分研究了BC风险因素，10年随访和病理学 TNBC确认的事件。所有提出的统计方法都将由R代码补充， 将公开提供。

PROJECT SUMMARY Triple negative breast cancer (TNBC) is an aggressive subtype of breast cancer with limited treatment options and poor survival. Approximately 12% to 17% of women with breast cancer are diagnosed with TNBC. Women with TNBC have relatively poor outcomes and cannot be treated with targeted therapies. However, the risk of TNBC is not uniform across all race-ethnic groups of the US population. Review of epidemiologic risk factors and TNBC incidence shows limited insight to variation in risk or risk reduction with the exception of history of breast feeding and higher vegetable and grain intake. We aim to bring personalized dynamic prediction to improve the current TNBC risk classification paradigm to make full use of the longitudinal information, in addition to the baseline information, where risk prediction/stratification can be updated as new observations are gathered to reflect the woman’s latest health- and behavioral-related status. Specifically, we aim to investigate 5- and 10-year TNBC risk prediction performance by proposing novel statistical methods that fully utilize the personalized mammogram-based risk factors from repeated mammogram images. The proposed study capitalizes on the WashU TNBC cohort with rich digital mammograms with well-studied BC risk factors, 10 years of follow-up and pathology confirmed incident TNBC. All proposed statistical methods will be supplemented by R code that we will make publicly available.