Trends of disparities in breast cancer progression and health care considering multilevel risk factors

乳腺癌进展和医疗保健方面的差异趋势 考虑多层次风险因素 健康差距在美国广泛存在。非裔美国人和西班牙裔美国人 人们不成比例地遭受癌症事件和结果的影响。确实有 旨在改善健康结果和减少 差距。需要有助于监测健康趋势的研究方法 差异，评估干预措施的效率，确定有助于 健康差距的开始和变化，并量化已确定的风险的影响 各种因素。 在这项研究中，我们建议开发现代分析方法来解决这些问题 研究中的要求。我们提出了单层次和多层次的慢化分析方法 采用了最近开发的数据挖掘和机器学习技术的 一般调解分析。使用这些方法，研究人员将能够 危险因素对被观测健康影响的辨证推论 来自个人和环境两个层面的差异。此外，我们将能够 确定健康差距随时间和新政策使用情况的变化。 将为实施拟议的新方法开发一个R包。 我们将在以下方面演示该方法：1)使用 符合条件的乳腺癌患者的肿瘤分型诊断、鉴定和制作 对导致种族差距变化的危险因素的影响的推断 时间；以及2)调查个人因素和社会/物理因素的交互影响 关于解释路易斯安那州乳腺癌结果的种族差异的环境。

Trends of disparities in breast cancer progression and health care considering multilevel risk factors Health disparities widely exist in the United States. African Americans and Hispanic populations suffer disproportionally from cancer incidents and outcomes. There are treatments and policies designed trying to improve health outcomes and reduce disparities. Research methods are needed that help monitor the trend of health disparities, evaluate efficiencies of interventions, identify risk factors that contribute to the start and the change in health disparities, and quantify the effects of identified risk factors. In this study, we propose to develop modern analytical methods that address these requests in research. We propose single- and multi-level moderation analysis methods that adopt recently developed data mining and machine learning techniques in the general mediation analysis. Using these methods, researchers will be able to differentiate and make inferences on effects of risk factors on the observed health disparities from both individual and environmental levels. In addition, we will be able to identify changes of health disparities over time and over employment of new policies. An R package will be developed for the implementation of the proposed novel methods. We will demonstrate the method in 1) identifying the trend of racial disparity in using the Oncotype diagnosis among eligible breast cancer patients, and identifying and making inferences on effects of risk factors that contribute to the change of racial disparity over time; and 2) Investigating the interactive effects of individual factors and social/physical environments on explaining racial disparities in breast cancer outcomes in Louisiana.