Studying Socioeconomic Disparities in Cancer Survival with Tapered Matching

通过锥形匹配研究癌症生存的社会经济差异

• 批准号: 8772925
• 负责人: JEFFREY H SILBER
• 金额: $ 43.27万
• 依托单位: CHILDREN'S HOSP OF PHILADELPHIA
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-07-03 至 2017-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8772925
• 关键词: Accounting; Asians; Breast Cancer Treatment; Cancer Patient; Characteristics; Chronic Disease; Colon Carcinoma; Data; Databases; Diagnosis; Education; Elderly; Eligibility Determination; Future; Goals; Hispanics; Income; Low income; Malignant Neoplasms; Medicare; Methodology; Methods; Minority; Minority Groups; Modeling; Neighborhoods; Not Hispanic or Latino; Observational Study; Patients; Population; Population Characteristics; Poverty; Race; Research; Research Design; Series; Socioeconomic Status; Study models; System; Testing; Time; Treatment Factor; Treatment outcome; Update; Widespread Disease; Work; aged; design; improved; low socioeconomic status; malignant breast neoplasm; public health relevance; socioeconomics

DESCRIPTION (provided by applicant): There has been extensive research examining the influence of race and socioeconomic status (SES) on disparities in cancer survival. The problem with most studies that model this question is that (1) race and SES are closely entwined, so coefficients on race and income are difficult to interpret; (2) model coefficients on covariates ar dominated by the majority population; and (3) the determinants of disparities are not transparent using standard regression models since formal testing of race coefficient differences across models lacks clear interpretation when models are composed of different covariates. Recently we introduced the concept of Tapered Multivariate Matching (TMM) and applied this methodology to the study of racial disparities in breast cancer treatment and survival. By using a focal group (the minority population) and a series of "tapered" matches to the focal group, forcing the majority population to more closely resemble the minority population in sequential matches, the method allows one to (1) observe and formally compare majority to minority patient covariates, treatments, and outcomes inside and across each match and (2) observe and formally compare the changing majority population characteristics across each match, thereby uncovering potential causes for observed disparities. In the present study we propose to reorient and update the TMM study design specifically to examine SES across and within racial strata. The overall goal of the study is to better understand why breast and colon cancer patients with lower SES in the Medicare system have worse survival and to suggest potential remedies to improve these disparities. This is a retrospective observational study that utilizes secondary data in the SEER-Medicare database for over 250,000 elderly breast and colon cancer patients diagnosed between 1991 and 2009. The study has three aims. AIM 1: To determine the overall SES-associated disparity in presentation and treatment factors and survival between patients defined as having lower income and education through a number of alternative definitions of SES using patient level information (Medicare Dual Eligibility) and neighborhood level information on income, education, and poverty (from the patient's neighborhood level data), accounting for race. AIM 2: To determine whether disparities in presentation factors, treatment, and survival have changed over time (over the last two decades). AIM 3: To understand why survival disparities exist through use of Tapered Multivariate Matching. This study builds on our previous work but requires a modified matching design and completely new matches. Results from this study should aid in understanding why disparities in cancer survival persist by race and SES and should help in reducing such disparities in the future.

描述（由申请人提供）：有广泛的研究考察了种族和社会经济地位（SES）对癌症生存差异的影响。大多数对这个问题进行建模的研究的问题在于：(1)种族和社会经济地位紧密相连，因此种族和收入的系数很难解释；(2)协变量的模型系数受多数群体支配；(3)差异的决定因素使用标准回归模型是不透明的，因为当模型由不同的协变量组成时，对模型之间种族系数差异的正式检验缺乏明确的解释。最近，我们引入了锥形多变量匹配（TMM）的概念，并将该方法应用于乳腺癌治疗和生存中的种族差异研究。通过使用焦点群体（少数群体）和与焦点群体的一系列“锥形”匹配，迫使多数群体在顺序匹配中更接近少数群体，该方法允许人们(1)观察并正式比较每个匹配内部和跨匹配的多数和少数患者协变量、治疗和结果；(2)观察并正式比较每个匹配中不断变化的多数群体特征。从而揭示观察到的差异的潜在原因。在本研究中，我们建议重新定位和更新TMM研究设计，专门研究跨种族和种族内部的SES。该研究的总体目标是更好地理解为什么在医疗保险体系中社会经济地位较低的乳腺癌和结肠癌患者生存率较差，并提出改善这些差异的潜在补救措施。这是一项回顾性观察性研究，利用SEER-Medicare数据库中的次要数据，研究了1991年至2009年间诊断出的250,000多名老年乳腺癌和结肠癌患者。这项研究有三个目的。目的1：通过使用患者水平信息（联邦医疗保险双重资格）和社区水平收入、教育和贫困信息（来自患者的社区水平数据），考虑种族因素，通过一些替代的SES定义，确定被定义为收入和教育程度较低的患者在表现和治疗因素以及生存方面的总体SES相关差异。目的2：确定表现因素、治疗和生存的差异是否随时间（过去二十年）而改变。目的3：通过使用锥形多变量匹配来理解生存差异存在的原因。这项研究建立在我们以前的工作基础上，但需要修改匹配设计和全新的匹配。这项研究的结果应该有助于理解为什么种族和社会经济地位对癌症生存的差异持续存在，并且应该有助于在未来减少这种差异。