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.

Public Health Relevance

Donor lungs for transplantation are limited. The current Lung Allocation Score (LAS) system for rationing donor lungs poorly identifies who is likely to benefit from transplant and has resulted in overall poor survival and increasing use of healthcare resources. This research will contribute to the development of a more accurate way of determining which patients are most likely to benefit from a lung transplant, which will be of benefit to individual patients and society in general.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
1R01HL153175-01
Application #
10028953
Study Section
Health Services Organization and Delivery Study Section (HSOD)
Program Officer
Craig, Matt
Project Start
2020-06-01
Project End
2024-05-31
Budget Start
2020-06-01
Budget End
2021-05-31
Support Year
1
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Cleveland Clinic Lerner
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
135781701
City
Cleveland
State
OH
Country
United States
Zip Code
44195