# A place-based approach to geographic disparities in lung transplant

> **NIH NIH R01** · CLEVELAND CLINIC LERNER COM-CWRU · 2024 · $671,654

## Abstract

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...

## Key facts

- **NIH application ID:** 10892883
- **Project number:** 5R01HL164660-02
- **Recipient organization:** CLEVELAND CLINIC LERNER COM-CWRU
- **Principal Investigator:** Wayne M Tsuang
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $671,654
- **Award type:** 5
- **Project period:** 2023-08-01 → 2028-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10892883

## Citation

> US National Institutes of Health, RePORTER application 10892883, A place-based approach to geographic disparities in lung transplant (5R01HL164660-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10892883. Licensed CC0.

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