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Identifying predictors of racial disparity in treatment and mortality among patients diagnosed with breast cancer in South Carolina and geospatial investigation of breast cancer patient navigation

Identifying predictors of racial disparity in treatment and mortality among patients diagnosed with breast cancer in South Carolina and geospatial investigation of breast cancer patient navigation
确定南卡罗来纳州乳腺癌患者治疗和死亡率种族差异的预测因素以及乳腺癌患者导航的地理空间调查
批准号:
9567963
负责人:
Oluwole Adeyemi Babatunde
金额:
$3.97万
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-09-20 至 2019-06-30

项目摘要

项目成果

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中文摘要
翻译
治疗开始的延迟导致黑人妇女死亡率较高,尽管其发病率较低。 乳腺癌(BrCa)在黑人与白色妇女之间的比较。生存研究表明, 与BrCa病例中较不利的生存期有关。辅助激素的使用 治疗(AHT)已被证明可以改善激素受体 全球BrCa阳性(HR+)患者,因为它降低了BrCa死亡率和复发率。的优点 尽管有AHT,但10 - 30%符合条件的BrCa患者从未开始AHT治疗, AHT从未完成治疗,导致复发和死亡率增加。这种缺乏初始吸收 与白人相比,黑人对AHT的依从性更差。有效缩小性别差距 少数民族的治疗延误和死亡率将需要确定机制, 特别是哪些差异发生,研究邻里水平的因素,已被证明会影响 黑人妇女接受BrCa治疗的几率。对于这项申请,我建议评估种族 利用来自所有研究的数据,在南卡罗来纳州(SC), 来自SC中央癌症登记处的8年以上女性BrCa病例与行政医疗相关 以及公共保险和私人保险BrCa患者的药房索赔数据。我将评估 1)地理因素,2)种族差异,3)地理信息系统之间的复杂相互作用 (GIS)映射,4)生存方法和5)多水平模型,以确定治疗延迟的预测因子, 可以干预的死亡率。地理信息系统方法尚未用于具体确定个人- 和邻里水平的特点,可能有助于在黑人中的BrCa死亡率的背景下, 多层次生存建模;这有可能允许应用循证方法 减少不平等。该项目有3个目标:1)评估治疗延迟的种族差异, 在诊断为乳腺癌的患者中使用AHT(博士前和完成); 2)识别 南卡罗来纳州黑人妇女健康地区乳腺癌相关生存率差异的预测因素 利用多层次生存模型和GIS方法(博士预科,尚未完成); 3) 评估社区水平因素是否会改变患者导航对初始推荐摄入量的影响 乳腺癌护理和少数民族人群中诊断解决的时间(博士后方向)。的 F99阶段的奖学金将提供必要的培训和指导,以促进我的知识 和技能1)差异,2)生存,3)多层次,4)地理信息系统,和5)地理空间分析。K00阶段将 让我接触1)干预性分析,如癌症患者导航,2)随机对照试验 以及3)在此期间提高我的学术生产力和专业发展,包括 准备和提交赠款和出版物。
英文摘要
Delay in treatment initiation contributes to higher mortality among Black women despite lower incidence of breast cancer (BrCa) among Black compared to White women. Survival studies show that a delay of two months has been linked with a less favorable survival among BrCa cases. The use of Adjuvant Hormonal Therapy (AHT) has been shown to improve both short- and long-term survival among Hormone Receptor Positive (HR+) BrCa patients worldwide as it reduces BrCa mortality and reoccurrence. The advantages of AHT notwithstanding, 10-30% of eligible BrCa patients never start treatment with AHT and many who start AHT never complete the treatment leading to reoccurrence and increased mortality. This lack of initial uptake and adherence to AHT is worse among Blacks compared to Whites. Effective reduction of disparities in treatment delays and mortality among racial minorities will require the identification of the mechanisms by which disparities occur particularly, studying neighborhood-level factors that have been shown to affect the odds of receipt of BrCa treatments among Black women. For this application, I propose to assess racial disparities in BrCa treatment and mortality in South Carolina (SC) utilizing data that was derived from all female BrCa cases over eight years from the SC Central Cancer Registry linked with administrative medical and pharmacy claims data for both publicly insured and privately insured BrCa patients. I will assess the complex interplay between 1) geographic factors, 2) racial disparities 3) Geographical Information System (GIS) mapping, 4) survival methods and 5) multi-level models to identify predictors of treatment delays and mortality that can be intervened upon. GIS methods have not been utilized to specifically identify individual- and neighborhood-level characteristics that may contribute to BrCa mortality among blacks within the context of multilevel survival modelling; this has the potential to allow for the application of evidence-based approaches to reduce disparities. This project has 3 aims: 1) to assess racial disparities in treatment delays and the utilization of AHT among patients diagnosed with breast cancer (Pre-Doctoral and completed); 2) to identify predictors of dissimilarity in breast cancer related survival by health regions among Black women in SC utilizing multilevel survival models and GIS methodologies (Pre-Doctoral and yet to be completed); 3) to assess if neighborhood-level factors modify the effect of patient navigation on uptake of initial recommended breast cancer care and time to diagnostic resolution among minority populations (Post-Doctoral direction). The F99 phase of this fellowship award will provide the necessary training and mentoring to further my knowledge and skill in 1) disparities, 2) survival, 3) multi-level, 4) GIS, and 5) geospatial analyses. The K00 phase will expose me to 1) interventional analyses such as cancer patient navigation, 2) Randomized Controlled Trials and 3) enhance my scholarly productivity and professional development during this fellowship, including preparation and submission of grants and publications.
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