Sex-based survival disparities persist in liver transplantation: MELD 3.0 fails to improve survival for waitlisted women.

BACKGROUND & AIMS: As a response to the well-documented disadvantages within the current allocation system, MELD 3.0 emerged on July 15, 2023, to more accurately characterize end-stage liver disease severity across the sexes. While simulation modeling predicted fewer waitlist deaths compared to MELD-Na, there is a lack of empirical data evaluating the efficacy of MELD 3.0 since its implementation. This study aims to conduct a waitlist patient survival study to explore sex- and age-based survival disparities in women and quantify empirical survival differences among waitlisted liver transplant candidates before and after the implementation of MELD 3.0.

METHODS

A retrospective, cross-sectional patient risk analysis of the Scientific Registry of Transplant Recipients (SRTR) database of liver transplant candidates listed from January 1, 2017, to September 3, 2024.

SETTING

The United States.

PARTICIPANTS

Adult liver transplant candidates on the waitlist (N = 95, 211). Exclusion criteria included a history of prior transplant and the need for multi-organ transplant.

EXPOSURES: All-cause patient waitlist mortality.

MAIN OUTCOMES AND MEASURES: The primary outcome was the persistence of the waitlist survival gap between the sexes before and after the implementation of MELD 3.0. Secondary outcomes included risk-adjusted survival disparities in association with age.

RESULTS

Across the two MELD eras, waitlisted females experienced a 16.28% mean increase in the relative 180-day median hazard ratio as compared to males. Patients 65 years and older had a 350% mean increase in their 180-day mortality hazard ratio as compared to patients 18 to 35 years of age. Patients 65 years of age and older with MELD scores greater than 34 experienced a 180-day median survival probability of 65%.

CONCLUSIONS AND RELEVANCE: Despite the implementation of MELD 3.0, the waitlist survival gap disadvantaging women persists. The relationships between waitlist survival and patient age and sex are complex and time-dependent. As such, time-dependent survival models along with the addition of patient age and other characteristics could significantly improve patient survival diagnostics and help close the waitlist survival gap between the sexes.