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命手术，但仍存在严重的 局限性，因为移植后的中位生存期仅为5.5年，仅为移植后存活期的一半。 其他类型的器官移植不幸的是，这种低生存率是由于肺的加速恶化， 功能在移植后的几年里，移植中心的做法不能完全解释，捐赠者 因素，或接受者因素。令人不安的是，还有不同的生存地理变化高达39% 根据美国的地区，我们假设，地方，定义为社会和环境的位置 对一个人有意义，影响接受者的健康，在一个机械的假设中，这些基于地点的因素 对肺造成亚临床微损伤，在移植后数年内加速肺功能丧失。 对于基于地点的因素如何加剧地理上的差异， 肺移植受者的存活率很低。在缺乏这些知识的情况下，很难准确地评估风险。 对接受者进行分层，并制定患者和政策层面的干预措施。为了弥补这一差距，我们利用 地理信息科学，被定义为测量，绘制地图和建模的框架。 目标1的范围是通过对多中心队列进行地理编码以识别个体， 受援国一级的普查区。这使得能够链接到具有广泛社会关系的高粒度联邦数据集 和环境健康措施，然后应用多层次模型和建立的空间 聚类检测方法这是重要的，因为这些结果将使我们能够摆脱现有的 通过早期筛查肺功能恶化或定制的“一刀切”临床方法 免疫抑制药物，以防止高危患者的肺功能丧失。目标2的范围是 通过绘制美国各地的差异并提高已建立的临床诊断的准确性， 预测模型我们将把单一的国家移植登记处与高度重视的联邦数据合并 衡量社会和环境健康因素，并测试是否将基于地点的因素纳入 新的多水平模型和已建立的临床考克斯模型的性能。新的地图和更准确 模型将是确定和减少地域差异以及改善 通过有针对性的资源分配。我们的长期目标是改善次优肺移植 生存，并确保无论在何处都能实现这一改进。这个项目是有影响力的，因为我们是 第一次在肺移植中超越我们医院的墙壁，创造前所未有的全面数据 可转化为患者和政策层面的干预措施。本提案是对《最终规则》的回应 美国卫生与公众服务部规定，患者的地理位置应具有最低限度的 在移植结果中的作用，移植领域的任务几乎没有取得进展， 过去二十年来，在很大程度上是由于我们的建议旨在填补知识空白。