Waitlisting and liver transplantation for MetALD in the United States: An analysis of the UNOS national registry

Pedro Ochoa-Allemant; Marina Serper; Roy X Wang; Helen Tang; Bachir Ghandour; Sarem Khan; Nadim Mahmud

doi:10.1097/HEP.0000000000000914

Waitlisting and liver transplantation for MetALD in the United States: An analysis of the UNOS national registry

Hepatology. 2024 Apr 29. doi: 10.1097/HEP.0000000000000914. Online ahead of print.

Authors

Pedro Ochoa-Allemant¹, Marina Serper^{1

2

3}, Roy X Wang⁴, Helen Tang⁴, Bachir Ghandour⁴, Sarem Khan⁴, Nadim Mahmud^{1

2

3

5}

Affiliations

¹ Division of Gastroenterology and Hepatology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
² Leonard Davis Institute of Health Economics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, PA.
³ Gastroenterology Section, Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA.
⁴ Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
⁵ Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA.

PMID: 38683569
DOI: 10.1097/HEP.0000000000000914

Abstract

Background and aims: The new steatotic liver disease (SLD) nomenclature introduced metabolic and alcohol-associated liver disease (MetALD), describing the intersection of metabolic dysfunction-associated steatotic liver disease (MASLD) and alcohol-associated liver disease (ALD). Waitlisting and liver transplantation for MetALD are not well-defined. We aimed to develop and validate an algorithm for identifying SLD phenotypes and assess trends in waitlisting and transplant outcomes.

Methods: We conducted a retrospective cohort study using the United Network for Organ Sharing registry, supplemented with detailed single-center data. We developed five candidate algorithms for SLD classification and calculated their diagnostic performance. Trends in waitlist registrations and transplants were estimated, and competing risk analyses and Cox regression models were conducted to assess waitlist removal and post-transplant outcomes among SLD phenotypes.

Results: The best-performing algorithm demonstrated substantial agreement (weighted kappa, 0.62) for SLD phenotypes, with acceptable sensitivity (73%) for MetALD. Between 2002-2022, waitlist registrations and transplants for MetALD increased 2.9-fold and 3.3-fold. Since 2013, there was a significant increase in the absolute number of waitlist registrations (122 per year; 95% CI, 111-133) and transplants (107 per year; 95% CI, 94-120) for MetALD. Patients with MetALD experienced higher waitlist removal (aSHR, 1.10; 95% CI, 1.03-1.17), all-cause mortality (aHR, 1.13; 95%, 1.03-1.23), and graft failure (aHR, 1.12; 95% CI, 1.03-1.21) than those with ALD.

Conclusions: We developed and validated an algorithm for identifying SLD phenotypes in UNOS. MetALD is the third leading etiology among those waitlisted and transplanted, exhibiting worse pre- and post-transplantation outcomes compared to ALD. Identifying and addressing factors determining poor outcomes is crucial in this patient population.