Forecasting Lung Transplant Benefit: A Dynamic Risk Modeling Approach

预测肺移植效益：动态风险建模方法

• 批准号: 10407519
• 负责人: JARROD DALTON
• 金额: $ 74.97万
• 依托单位: CLEVELAND CLINIC LERNER COM-CWRU
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-06-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10407519
• 关键词: Address; Caring; Chronic Obstructive Pulmonary Disease; Clinical; Decision Making; Development; Diagnosis; Disease; Disease model; Effectiveness; Ethics; Ethnic Origin; Failure; Foundations; Goals; Health; Health Care Costs; Health Personnel; Healthcare; Hospital Charges; Hour; Individual; Leadership; Length of Stay; Life; Lung; Lung Transplantation; Lung diseases; Measures; Medical; Medicare; Methodology; Methods; Modeling; Modernization; Mortality Decline; Organ; Patients; Policies; Population; Race; Research; Resources; Risk; Risk Assessment; Savings; Societies; Socioeconomic Status; System; Time; Transplant Recipients; Transplantation; United States; Update; Waiting Lists; Work; base; cystic fibrosis patients; design; disorder risk; dynamic system; end stage liver disease; functional outcomes; health care service utilization; hospital readmission; improved; indexing; individual patient; mortality; mortality risk; organ allocation; patient population; policy implication; post-transplant; survival outcome; time use; trend

Project Summary Increasing clinical demand for lung transplants has exacerbated the problem of rationing this limited yet life- saving societal resource. The Lung Allocation Score (LAS) system was developed to improve overall survival by identifying patients who would likely benefit the most from transplant. Despite this effort, there have been increasing rates of waiting list mortality, declines in long-term survival after transplant and dramatic increases in healthcare costs and utilization among transplant patients. Our project focuses on improving the LAS system by: 1) designing better methodologies to more accurately identify the progression of illness in a patient who is awaiting transplant, 2) predicting ideal timing of transplant to maximize the number of years gained from a transplant, and 3) evaluating different allocation strategies and their impact on individual and population level survival. We will achieve this by carrying out the following aims: Aim 1: Update the lung allocation score (LAS) underlying risk models to better accommodate subpopulation-level differences over time among lung transplant candidates. Aim 2: Develop and validate a forecasting model for lung transplant candidates’ dynamic health state and likelihood of transplantation over time using a systems-based microsimulation modeling approach. Aim 3: Evaluate the impact of lung allocation strategies that optimize patient- and population-level functional and survival outcomes. The results of this work will provide the foundation for improving lung allocation in the United States. We will optimize timing of lung transplantation to maximize transplant benefit at the individual patient and population levels. The methods identified in this project can be utilized in other scenarios where limited life saving resources must be rationed.

项目概要 临床对肺移植的需求不断增加，加剧了这种有限但生命有限的配给问题。 节约社会资源。肺分配评分 (LAS) 系统的开发是为了提高总体生存率 通过识别可能从移植中受益最大的患者。尽管做出了这些努力，但还是有 等待名单死亡率增加，移植后长期生存率下降并急剧增加 移植患者的医疗费用和利用率。 我们的项目重点是通过以下方式改进 LAS 系统：1）设计更好的方法以更准确地 确定等待移植的患者的病情进展，2) 预测理想的移植时机 最大限度地提高移植获得的年数，以及 3) 评估不同的分配策略和 它们对个人和群体生存的影响。我们将通过实现以下目标来实现这一目标： 目标 1：更新肺分配评分 (LAS) 基础风险模型以更好地适应 肺移植候选者之间随时间的亚群体水平差异。 目标 2：开发并验证肺移植候选者动态健康状况和健康状况的预测模型 使用基于系统的微观模拟建模方法随时间推移进行移植的可能性。 目标 3：评估优化患者和人群水平功能的肺分配策略的影响 和生存结果。 这项工作的结果将为改善美国的肺分配奠定基础。我们将 优化肺移植的时机，以最大限度地提高个体患者和人群的移植效益 水平。本项目中确定的方法可用于挽救生命有限的其他情况 资源必须实行配给。