Mechanisms Underlying SES Disparities in Breast Cancer Mortality

描述(申请人提供)：乳腺癌患者的社会经济差异(SES)在1980年的“S”和1990年的S期间出现，并持续到2000年的“S”初期。现有的文献和/或我们的初步数据证明，在筛查和后续乳房摄影的使用、保乳手术和放射治疗的使用、替代辅助内分泌治疗(芳香酶抑制剂和他莫昔芬)的选择和使用方面，社会经济学方面的差异提供了证据，并且一旦启动，可能还会坚持内分泌治疗。也有证据表明，乳腺癌患者在使用低容量医院时可能存在SES差异，这与较差的存活率有关。目前尚不清楚的是，这些过程因素在多大程度上相互关联，导致观察到的生存差异，以及在旨在减少这些差异的计划中，哪些公共政策或卫生保健提供干预值得最大程度地关注。在这项应用中，我们建议经验性地展示这些因素中的每一个对观察到的乳腺癌女性SES死亡率差异的影响程度。具体地说，我们的目标是：(1)利用当代乳腺癌老年妇女队列，记录乳腺癌护理模式中的SES差异，以及3年和5年死亡率；(2)分解导致SES乳腺癌死亡率差异的因素，最显著的是(I)筛查，(Ii)疾病程度；(Iii)初步治疗；(Iv)辅助和后续护理；以及(V)卫生系统 结构和政策因素；以及(3)模拟替代公共政策对癌症死亡率的影响及其对SES差异的影响。这些目标将会实现 通过分析2005-2007年SEER-Medicare-Part D部分数据并跟踪到2012年。我们建议首先使用分类和回归树(CART)方法，确定在术后60个月治疗连续过程中定义的乳腺癌护理模式。然后，我们将使用基于Oaxaca-Blinder回归的分解方法，根据构成这些护理模式的每个结构和过程措施的贡献来分配观察到的SES死亡率差异，量化每个措施可解释的部分，以及仍未解释的差异。最后，我们将使用这些分析产生的参数估计来模拟当前正在考虑的替代方案(例如，增加D部分保费和自付费用、消除覆盖差距)在抵消或加剧乳腺癌治疗和结果方面的差异方面的预期效果。这项拟议的研究不仅将提供机械性信息，以集中努力纠正SES在乳腺癌死亡率方面的差距，还将提供一个创新的政策模拟，为确定如何最好地分配公共医疗和处方药保险计划的资源以获得最大价值的努力提供信息。

DESCRIPTION (provided by applicant): Socioeconomic (SES) disparities in survival from breast cancer developed during the 1980's and 1990's, and have persisted into the early 2000's. The existing literature and/or our preliminary data provide evidence of process disparities among SES groups in the use of screening and follow-up mammography, the use of breast conserving surgery with radiotherapy, the choice and use of alternative adjuvant endocrine therapy (aromatase inhibitors vs. tamoxifen) and possibly persistence with endocrine therapy once initiated. There is also evidence that SES disparities may exist among breast cancer patients in the use of low-volume hospitals, which are associated with worse survival. What is unclear is the extent to which these process factors inter-relate to lead to the observed survival disparities, and which public policy or health care delivery interventions deserve greatest attention in a program designed to reduce these disparities. In this application, we propose to show empirically the extent to which each of these factors contribute to the observed SES disparities in mortality among women with breast cancer. Specifically, our aims are to: (1) To document SES disparities in patterns of breast cancer care, and in 3- and 5-year mortality using a contemporary cohort of elderly women with incident breast cancer; (2) To decompose the factors underlying SES disparities in breast cancer mortality, most notably, (i) screening, (ii) extent of disease; (iii) initial treatment; (iv) adjuvant and follow-up care; and (v) health system structural and policy factors; and (3) To simulate the effect of alternative public policies on cancer mortality and their implications for SES disparities therein. These aims will be carried out by analyzing data from the 2005-2007 SEER-Medicare-Part D data and followed until 2012. We propose to first identify patterns of breast cancer care, defined over the 60-month post-surgery treatment continuum, using the Classification and Regression Tree (CART) methodology. We will then apportion the observed SES disparities in mortality according to the contribution of each structural and process measures comprising these patterns of care, using the Oaxaca-Blinder regression-based decomposition approach, quantifying the portion explained by each, and the differences that remain unexplained. Finally, we will use parameter estimates generated by these analyses to simulate the anticipated effect of alternative proposals currently under consideration (e.g., increasing Part D premiums and co-pays, eliminating the coverage gap) in offsetting or exacerbating disparities in breast cancer treatments and outcomes. The proposed study will not only provide mechanistic information to focus efforts to remediate SES disparities in breast cancer mortality, but will also provide an innovative policy simulation that will inform efforts to determine how best to allocate the resources of public medical and prescription drug insurance programs in order to obtain the greatest value.