Effects of disability on the diagnosis of breast cancer

残疾对乳腺癌诊断的影响

• 批准号: 7127692
• 负责人: Mabel E Caban
• 金额: $ 12.82万
• 依托单位: UNIVERSITY OF TEXAS MED BR GALVESTON
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-30 至 2010-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7127692
• 关键词: African American; Hispanic Americans; Medicare /Medicaid; age difference; behavioral /social science research tag; breast neoplasm /cancer diagnosis; breast neoplasms; caucasian American; clinical research; computer assisted diagnosis; diagnosis quality /standard; female; functional ability; health care model; health disparity; health services research tag; human data; human old age (65+); mammography; method development; neoplasm /cancer classification /staging; person with disability; racial /ethnic difference; socioeconomics; statistics /biometry; women' s health

DESCRIPTION (provided by applicant): Candidate: Mabel Caban, M.D., is an assistant professor in the Department of Orthopedics and Rehabilitation who will serve as principal investigator of this project. As a research fellow at Baylor College of Medicine in 1999, she initiated studies on disparities in the breast cancer treatment of female patients with disabilities. Dr. Caban seeks to study disability using Medicare beneficiary claims. Career Goals: (1) Develop skills as an independent investigator on health services and outcome research; (2) Develop expertise using SEER Medicare linked database to examine the effect of disability on the diagnosis of breast cancer in older women; (3) Develop public speaking skills and improve scientific communication; and (4) Submit an R01 grant to continue the study of disability and health outcomes. Research Plan: The purpose of the study is to determine the association between disability and tumor size/stage of breast cancer diagnosis. The specific aims of the research are to: (1) Define and validate an algorithm using Medicare claims that identifies women with disabilities (functional limitations). (2) Using the disability algorithm from Aim 1, determine the effect of disability on: (a) The use of screening mammography using SEER Medicare linked database. (b) Tumor size and stage at diagnosis of breast cancer using the SEER Medicare linked database. (c) Tumor size and stage at diagnosis for different subpopulations defined by age at diagnosis, race/ethnicity, and socio-economic status using the SEER Medicare linked database. (3) Build two multivariable models (to predict size and stage) to determine the effect of disability on tumor size and stage adjusting for other relevant confounders using the SEER Medicare database. I will apply the algorithm from Aim 1. Method: The disability algorithm will be developed using Medicare Current Beneficiary Survey. The algorithm will then be applied using SEER Medicare linked database to study all breast cancer cases in women aged 69 and older who are in the SEER registries from 1995 through 1999 to determine the effect of disability on use of mammography and on tumor stage/size. First, the analysis will be unadjusted, then stratified by subgroups (age, race, stage), and then adjusted by relevant confounders in a multivariate model.

描述（由申请人提供）： 候选人：Mabel Caban，医学博士，是骨科和康复系的助理教授，将担任该项目的首席研究员。 1999 年，作为贝勒医学院的研究员，她发起了关于残疾女性乳腺癌治疗差异的研究。卡班博士试图利用医疗保险受益人索赔来研究残疾。职业目标： (1) 培养作为卫生服务和结果研究独立调查员的技能； (2) 利用 SEER Medicare 链接数据库开发专业知识，以检查残疾对老年妇女乳腺癌诊断的影响； (3) 培养公开演讲技巧并提高科学沟通能力； (4) 提交 R01 拨款以继续研究残疾和健康结果。研究计划：该研究的目的是确定残疾与乳腺癌诊断的肿瘤大小/分期之间的关联。 研究的具体目标是： (1) 使用医疗保险索赔定义并验证一种算法，该算法可识别残疾妇女（功能限制）。 (2) 使用目标 1 中的残疾算法，确定残疾对以下方面的影响： (a) 使用 SEER Medicare 链接数据库进行乳房 X 线摄影筛查。 (b) 使用 SEER Medicare 链接数据库诊断乳腺癌时的肿瘤大小和分期。 (c) 使用 SEER Medicare 链接数据库，根据诊断年龄、种族/族裔和社会经济地位定义不同亚群的肿瘤大小和诊断阶段。 (3) 建立两个多变量模型（用于预测大小和分期），以确定残疾对肿瘤大小和分期的影响，使用 SEER Medicare 数据库调整其他相关混杂因素。我将应用目标 1 中的算法。 方法：残疾算法将使用医疗保险当前受益人调查来开发。然后，该算法将使用 SEER Medicare 链接数据库来研究 1995 年至 1999 年 SEER 登记处 69 岁及以上女性的所有乳腺癌病例，以确定残疾对乳房 X 光检查的使用和肿瘤分期/大小的影响。首先，分析将不进行调整，然后按子组（年龄、种族、阶段）分层，然后根据多元模型中的相关混杂因素进行调整。