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Clinical Impact of a Modified Lung Allocation Score That Mitigates Selection Bias

E. M. Schnellinger1, E. Cantu2, D. E. Schaubel1, S. E. Kimmel3, A. J. Stephens-Shields1

1University of Pennsylvania, Philadelphia, PA, 2Hospital of the University of Pennsylvania, Philadelphia, PA, 3University of Florida, Gainesville, FL

Meeting: 2022 American Transplant Congress

Abstract number: 1479

Keywords: Lung transplantation, Organ Selection/Allocation, Prediction models, Survival

Topic: Clinical Science » Lung » 64 - Lung: All Topics

Session Information

Session Name: Lung Transplantation

Session Type: Poster Abstract

Date: Monday, June 6, 2022

Session Time: 7:00pm-8:00pm

 Presentation Time: 7:00pm-8:00pm

Location: Hynes Halls C & D

*Purpose: The U.S. lung allocation system uses the Lung Allocation Score (LAS) to prioritize lung transplant candidates. Selection bias, induced by dependent censoring of waitlisted candidates and prediction of post-transplant survival among surviving, transplanted patients only, is only partially addressed in the LAS. Recently published work using a modified LAS (mLAS) designed to mitigate selection bias demonstrated improved performance compared to the current LAS. We sought to define the clinical impact of implementing this mLAS.

*Methods: Analyses used data from lung transplant candidates registered on the waitlist between 2016-2017. Modified and existing LAS scores were computed for each registrant at each observed organ offer date; individuals were ranked accordingly. Logistic regression and generalized linear mixed models were used to examine demographic and clinical characteristics associated with higher priority under the modified versus existing LAS, and determine whether differences in rank were explained more by changes in predicted pre- or post-transplant survival. Simulations examined how one-year waitlist, post-transplant, and overall survival might change under the mLAS.

*Results: Diagnosis group, six-minute walk distance, continuous mechanical ventilation, and functional status demonstrated the highest impact on differential allocation (Figure). Changes in predicted pre-transplant survival explained a greater proportion of variability in differences in rank than changes in predicted post-transplant survival, suggesting that selection bias has a larger impact on the estimate of waitlist urgency than on the estimate of post-transplant survival. In simulations, waitlist survival improved under the mLAS, with a median difference of 1.28% (interquartile range [IQR]: 0.52%-2.43%). Post-transplant and overall survival remained comparable across models. The majority (84.4%) of individuals received hypothetical transplant under both LAS models. Among the subset of individuals (15.6%) to whom organs were differentially allocated under the mLAS, the median difference in waitlist survival was 6.89% (IQR: 2.46%-11.5%).

*Conclusions: Implementing a modified LAS that mitigates selection bias into clinical practice can lead to important differences in allocation and possibly modest improvement in waitlist survival.

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To cite this abstract in AMA style:

Schnellinger EM, Cantu E, Schaubel DE, Kimmel SE, Stephens-Shields AJ. Clinical Impact of a Modified Lung Allocation Score That Mitigates Selection Bias [abstract]. Am J Transplant. 2022; 22 (suppl 3). https://atcmeetingabstracts.com/abstract/clinical-impact-of-a-modified-lung-allocation-score-that-mitigates-selection-bias/. Accessed May 18, 2025.

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