A place-based approach to geographic disparities in lung transplant

基于地点的肺移植地理差异方法

• 批准号: 10655779
• 负责人: Wayne M Tsuang
• 金额: $ 71.84万
• 依托单位: CLEVELAND CLINIC LERNER COM-CWRU
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2028-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10655779
• 关键词: Acceleration; Address; Adherence; Area; Bioethics; Biological Markers; Blood Tests; Cardiac; Censuses; Clinical; Clinical Data; County; Cox Models; Data; Data Set; Deterioration; Diabetes Mellitus; Disparity; Dose; Ensure; Environmental Health; Environmental Risk Factor; Exposure to; Geographic Locations; Geography; Goals; Graft Rejection; Health; Hospitals; Immunosuppression; Individual; Information Sciences; Injury; Institution; Intervention; Investigation; Knowledge; Life; Location; Lung; Lung Transplantation; Lung diseases; Maps; Measurement; Measures; Methods; Modeling; Operative Surgical Procedures; Organ Donor; Organ Transplantation; Outcome; Patient Care; Patients; Performance; Persons; Pharmaceutical Preparations; Policies; Population; Resource Allocation; Risk; Risk Factors; Role; Testing; Time; Translations; Transplant Recipients; Transplantation; United States; United States Dept. of Health and Human Services; Variant; asthmatic patient; clinical predictive model; cohort; community-level factor; comorbidity; cost efficient; data repository; detection method; early screening; experience; geographic disparity; health determinants; high risk; improved; improved outcome; innovation; loss of function; mortality risk; multilevel analysis; novel; patient stratification; pollutant; post-transplant; predictive modeling; prevent; primary outcome; pulmonary function; risk stratification; secondary outcome; social; social factors; social vulnerability; spatial epidemiology; success; survival disparity; survival prediction; transplant centers; transplant registry; transplantation medicine

PROJECT SUMMARY While lung transplant is a lifesaving surgery for patients with fatal lung diseases, there remains a critical limitation as median post-transplant survival is merely 5.5 years which is only half the survival experienced by other organ transplant types. Unfortunately, this low survival is from the accelerated deterioration in lung function in the years after transplant and cannot be fully explained by transplant center practices, donor factors, or recipient factors. Troublingly, there is also disparate survival by geography which varies up to 39% depending on the region of the U.S. We hypothesize that place, defined as a social and environmental location with meaning to a person, impacts recipient health and in a mechanistic hypothesis these place-based factors cause subclinical micro-injuries to the lungs which accelerate lung function loss in the years after transplant. There is a gap in knowledge on how place-based factors exacerbate both the geographically disparate and poor survival of lung transplant recipients. In the absence of this knowledge, it is difficult to precisely risk stratify recipients and develop patient and policy level interventions. To address this gap, we leverage the Geographic Information Sciences, defined as the framework to measure, map, and model the effects of place. The scope of Aim 1 is to inform clinical decisions by geocoding a multicenter cohort to identify individual recipient level census tracts. This enables linkage to highly granular federal datasets with a wide array of social and environmental health measures followed by the application of multilevel models and established spatial cluster detection methods. This is significant as these results would enable us to pivot away from an existing one-size-fits-all clinical approach by screening earlier for worsening lung function or tailoring immunosuppression medications to prevent lung function loss for at risk patients. The scope of Aim 2 is to inform policy through mapping disparities across the U.S. and improving the accuracy of established clinical prediction models. We will merge the singular national transplant registry with highly valued federal data measuring social and environmental health factors, and test the inclusion of place-based factors on the performance of novel multilevel models and established clinical cox models. New maps and more accurate models would be a significant advance towards identifying and reducing geographic disparities and improving outcomes through targeted resource allocation. Our long-term goal is to improve the suboptimal lung transplant survival and ensure this improvement is achieved regardless of place. This project is impactful as we are the first in lung transplant to look beyond the walls of our hospitals to create unprecedented comprehensive data translatable towards patient and policy level interventions. This proposal is responsive to the Final Rule mandate by the U.S. Department of Health and Human Services that patient geography should have a minimal role in transplant outcomes, a mandate the field of transplantation has made little progress towards over the past two decades due, in large part, to gaps in knowledge that our proposal aims to fill.

项目摘要 虽然肺移植是致命肺部疾病患者的救生手术，但仍然存在关键 限制作为中位移植后生存仅为5。5年，这只是一半的生存。 其他器官移植类型。不幸的是，这种低的生存率来自肺的加速恶化 移植后的几年功能，无法通过移植中心实践，捐助者充分说明 因素或受体因素。令人困扰的是，地理的生存也不同 根据美国的区域，我们假设该地方定义为社会和环境位置 对一个人的意义，影响接受者的健康和机械假设，这些基于地方的因素 在移植后的几年中导致肺部肺部功能损失。 关于基于地点因素如何加剧地理上不同和 肺移植受者的存活不良。在没有这些知识的情况下，很难精确冒险 对接收者进行分层并制定患者和政策水平干预措施。为了解决这个差距，我们利用 地理信息科学，定义为测量，映射和建模位置效果的框架。 AIM 1的范围是通过地理编码多中心队列来识别个体来告知临床决策 接受者水平人口普查区。这使与高度粒状联邦数据集的链接具有各种各样的社交 以及环境健康措施，然后采用多级模型和建立的空间 聚类检测方法。这很重要，因为这些结果将使我们能够从现有的 较早的肺功能或调整量的临床方法，临床临床方法。 免疫抑制药物可防止风险患者的肺部功能损失。目标2的范围是 通过在美国绘制差距并提高既定临床的准确性来告知政策 预测模型。我们将将单数的国家移植注册中心与非常有价值的联邦数据合并 衡量社会和环境健康因素，并测试将基于位置的因素包含在 新型多级模型和已建立的临床COX模型的性能。新地图和更准确的 模型将是识别和降低地理差异并改善地理差异的重大进步 通过目标资源分配结果。我们的长期目标是改善次优的肺移植 生存并确保无论位置如何实现这一改进。这个项目具有影响力，因为我们是 首先，在肺移植中，可以超越医院的墙壁，以创建前所未有的综合数据 可转换为患者和政策水平干预措施。该提议对最终规则有反应 美国卫生和公共服务部的任务，患者地理应该最少 在移植结果中的作用，移植领域的任务几乎没有取得进展 在很大程度上，过去的二十年是由于我们的提议旨在填补的知识差距。