Comparison of MELD, MELD-Na, and MELD 3.0 scoring systems for transplant prioritization in the Turkish population: A

Kenan Moral1, Murat Harputluoğlu2, Gülşah Fidan Özkumur3

  • 1Department of Gastroenterology and Hepatology, Gazi University, Ankara, Turkey.

Insights

MELD 3.0 and MELD-Na scores accurately predict short-term mortality in Turkish liver transplant candidates, outperforming the standard MELD score. However, MELD 3.0 requires further refinement for improved clinical utility.

Area of Science:

  • Hepatology
  • Transplantation Medicine
  • Medical Statistics

Background:

  • The Model for End-Stage Liver Disease Sodium (MELD-Na) score is crucial for predicting mortality in liver transplant candidates.
  • MELD 3.0 is a proposed advancement to improve mortality risk estimation.
  • Evaluating MELD 3.0's accuracy in diverse populations is essential for clinical adoption.

Purpose of the Study:

  • To assess the predictive accuracy of MELD 3.0 for short-term mortality in Turkish liver transplant candidates.
  • To compare the performance of MELD 3.0 against MELD and MELD-Na scores.
  • To identify optimal cutoff values and evaluate transplant-free survival.

Main Methods:

  • A nationwide, multicenter study included 1,689 liver transplant candidates.
  • Discriminative abilities were assessed using the area under the receiver operating characteristic curve (AUROC).
  • Transplant-free survival was analyzed using Kaplan-Meier and log-rank tests.

Main Results:

  • MELD 3.0 demonstrated the highest AUROC (0.753) for 3-month mortality, followed by MELD-Na (0.747) and MELD (0.725).
  • MELD-Na and MELD 3.0 significantly outperformed MELD (p<0.001) but were comparable to each other (p=0.17).
  • Optimal cutoff values were identified as 18 for MELD and 21 for MELD-Na and MELD 3.0.

Conclusions:

  • MELD 3.0 and MELD-Na show comparable and superior performance to MELD in predicting 3-month mortality for Turkish liver transplant candidates.
  • While MELD 3.0 shows promise, further refinements are necessary to enhance its clinical utility.
  • The study highlights the importance of population-specific validation for mortality prediction models.