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

项目总结 三阴性乳腺癌(TNBC)是乳腺癌的一种侵袭性亚型。 治疗选择多，存活率低。大约12%到17%的患有乳腺癌的女性 被诊断出患有TNBC。患有TNBC的妇女预后相对较差，无法治疗 有针对性的治疗。然而，TNBC的风险在所有种族-族裔群体中并不是一致的 美国人口。对流行病学危险因素和TNBC发病率的回顾显示洞察力有限 风险的变化或降低风险，但母乳喂养史及以上者除外 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 当前的TNBC风险分类范例，以充分利用纵向信息，在 添加基准信息，其中风险预测/分层可以更新为新的 收集的观察结果反映了这名妇女最新的健康和行为相关状态。 具体地说，我们的目标是通过提出以下建议来调查5年和10年的TNBC风险预测性能 新的统计方法，充分利用基于个性化乳房X光检查的风险因素 重复的乳房X光照片。拟议的研究利用了华盛顿大学的TNBC队列和 丰富的数字化乳房X光检查，充分研究了BC的危险因素，10年的随访和病理 已确认的事件TNBC。所有建议的统计方法将由R代码补充，我们 将公之于众。

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.