Detecting racial disparities in cancer survival by integrating multiple high-dimensional observational studies

通过整合多个高维观察研究来检测癌症生存的种族差异

• 批准号: 10699968
• 负责人: Subharup Guha
• 金额: $ 32.55万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-07 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10699968
• 关键词: Accounting; African American population; Asian population; Bayesian Modeling; Biological Factors; Boston; Cancer Patient; Cations; Caucasians; Cause of Death; Censuses; Cessation of life; Clinical; Compensation; Complex; Computer software; Country; DNA; DNA Sequence Alteration; Dana-Farber Cancer Institute; Data Set; Databases; Detection; Diagnosis; Disparity; Equilibrium; Equity; Ethnic Origin; Fostering; General Hospitals; Genetic; Goals; Health; Health Disparities Research; Inequity; International; Knowledge; Leukocytes; Lung; Malignant Neoplasms; Malignant neoplasm of lung; Massachusetts; Mayo Clinic Cancer Center; Methods; Mutation; Observational Study; Oncogenic; Outcome; Pathology; Patients; Population; Population Characteristics; Procedures; Process; Property; Race; Research; Research Design; Research Personnel; Sample Size; Serum; Smoking; Stage at Diagnosis; Structural Racism; Target Populations; Tumor Tissue; Uncertainty; United States National Institutes of Health; Weight; cancer health disparity; cancer survival; cohort; data structure; density; design; dietary; ethnic disparity; flexibility; health care availability; high dimensionality; improved; innovation; interest; minority patient; multiple omics; mutational status; novel; open source; racial disparity; racial minority; racial minority population; racial population; screening; social; social determinants; social disparities

PROJECT SUMMARY/ABSTRACT Despite overall improvements, ethnic or racial disparities continue to increase, suggesting deficiencies in research designs for understanding disparities. For example, compared to the 2017 US Census, most observational cancer studies were found to over represent Caucasians and underrepresent African Americans and Asians. How to utilize these studies to detect and understand racial disparities remains challenging. This proposal is motivated by the Boston Lung Cancer Survival Cohort (BLCSC), one of the largest lung cancer cohorts globally, which consists of lung cancer cases registered since 1992 at the Dana-Farber Cancer Institute (DFCI) and the Massachusetts General Hospital (MGH), and has expanded to the MD Anderson Cancer Center (MDACC) and Mayo Clinic. This rich database provides a unique opportunity for studying racial disparities in cancer outcomes as well as presents a challenge with unbalanced covariates across racial groups. We also have access to the International Lung and Cancer Consortium (ILCCO), an international cohort established in 2004 with a data structure similar to BLCSC. Leveraging these cancer cohorts, we develop methods with a common goal of effectively identifying racial disparities in cancer outcomes by integrating high dimensional observational studies with multiple racial groups. Rich datasets like BLCSC and ILLCO are ideal for integrative, unconfounded detection of racial disparities in cancer outcomes, and for generating statistical findings generalizable to a realistic and inclusive larger population.

项目总结/摘要 尽管总体上有所改善，但民族或种族差异继续增加，这表明 研究设计在理解差异方面的缺陷。例如，与 2017年美国人口普查发现，大多数观察性癌症研究过度代表高加索人 而非裔美国人和亚洲人的代表性不足。如何利用这些研究来检测和 理解种族差异仍然是一个挑战。 这一提议是由波士顿肺癌生存队列（BLCSC）提出的，BLCSC是世界上最大的肺癌生存队列之一。 全球最大的肺癌队列，包括自1992年以来登记的肺癌病例 丹娜-法伯癌症研究所（DFCI）和马萨诸塞州总医院（MGH），以及 已扩展到MD安德森癌症中心（MDACC）和马约诊所。这个丰富的数据库 为研究癌症结果中的种族差异提供了一个独特的机会， 提出了一个挑战，即各种族之间的协变量不平衡。我们还可以访问 国际肺癌联盟（ILCCO），一个成立于1999年的国际队列， 2004年，数据结构类似于BLCSC。 利用这些癌症队列，我们开发了一个共同目标的方法， 通过整合高维度的观察结果，确定癌症结局中的种族差异 多个种族群体的研究。BLCSC和ILLCO等丰富的数据集是集成、 癌症结局中种族差异的无混淆检测，并用于生成统计数据 调查结果可推广到现实和包容性更大的人群。