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

乳腺癌进展和保健方面的差距趋势 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 人口因癌症事件和结果而遭受痛苦。有 旨在改善健康结果并减少 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，确定导致 健康差距的开始和变化，并量化已识别风险的影响 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适度分析方法 采用最近开发的数据挖掘和机器学习技术， 一般调解分析。使用这些方法，研究人员将能够 区分并推断风险因素对观察到的健康状况的影响 个人和环境层面的差异。此外，我们将能够 确定健康差距随着时间的推移和新政策的实施而发生的变化。 一个R包将被开发用于实施所提出的新方法。 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癌型诊断， 关于风险因素影响的推论，这些因素有助于改变种族差距， 时间; 2）调查个人因素和社会/身体因素的交互作用 环境对解释路易斯安那州乳腺癌结果的种族差异的影响。

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.