Investigating the utility of each MELD edition in predicting liver transplant outcomes.

BACKGROUND

The Model for End-Stage Liver Disease (MELD) has prioritized liver transplant candidates since 2002, with revisions yielding 2.0 (2016) and 3.0 (2022) models. Updates aimed to enhance transplant allocation equity, but each model's ability to predict post-transplant outcomes remains unclear.

METHODS

Utilizing the Organ Procurement Transplant Network database, binary logistic regression models evaluated associations between MELD cohorts and 10 post-transplant outcomes, adjusting for MELD score. MELD 1.0 served as the reference. Odds ratios (ORs), 95% confidence intervals (CIs), and p-values were reported for MELD 2.0 versus 1.0 and MELD 3.0 versus 1.0.

RESULTS

MELD 3.0 had the most significant association with graft failure due to infection (OR = 1.30, p = 0.023), recurrent disease (OR = 0.12, p < 0.001), hepatitis (OR = 0.03, p < 0.001), chronic rejection (OR = 0.67, p = 0.041), hepatic artery thrombosis (OR = 2.51, p < 0.001), primary non-function (OR = 3.93, p < 0.001), diffuse cholangitis (OR = 2.32, p < 0.001), and overall graft loss (OR = 6.34, p < 0.001). Compared to the MELD 1.0 cohort, transplant recipients in the MELD 2.0 cohort were most strongly associated with an increased risk for acute rejection (OR = 1.58, p < 0.001) and chronic rejection (OR = 1.28, p < 0.001). While MELD 2.0 was not the strongest, it still showed significant associations with graft failure due to infection (OR = 1.162, p = 0.017), recurrent disease (OR = 0.486, p < 0.001), hepatitis recurrence (OR = 0.061, p < 0.001), diffuse cholangitis (OR = 1.523, p < 0.001), hepatic artery thrombosis (OR = 2.050, p < 0.001), primary non-function (OR = 2.869, p < 0.001), and graft loss overall (OR = 3.272, p < 0.001) compared to the MELD 1.0 cohort.

CONCLUSION

The MELD 3.0 cohort demonstrated significant associations with both increased and decreased risks across multiple post-transplant outcomes. These results underscore the importance of monitoring how allocation policy changes may influence post-transplant outcomes at the population level.