MELD 3.0: The Model for End-Stage Liver Disease Updated for the Modern Era.

The Model for End-Stage Liver Disease (MELD) has been established as a reliable indicator of short-term survival in patients with end-stage liver disease. The current version (MELDNa), consisting of the international normalized ratio and serum bilirubin, creatinine, and sodium, has been used to determine organ allocation priorities for liver transplantation in the United States. The objective was to optimize MELD further by taking into account additional variables and updating coefficients with contemporary data. All candidates registered on the liver transplant wait list in the US national registry from January 2016 through December 2018 were included. Uni- and multivariable Cox models were developed to predict survival up to 90 days after wait list registration. Model fit was tested using the concordance statistic (C-statistic) and reclassification, and the Liver Simulated Allocation Model was used to estimate the impact of replacing MELDNa with the new model. The final multivariable model was characterized by (1) additional variables of female sex and serum albumin, (2) interactions between bilirubin and sodium and between albumin and creatinine, and (3) an upper bound for creatinine at 3.0 mg/dL. The final model (MELD 3.0) had better discrimination than MELDNa (C-statistic, 0.869 vs 0.862; P < .01). Importantly, MELD 3.0 correctly reclassified a net of 8.8% of decedents to a higher MELD tier, affording them a meaningfully higher chance of transplantation, particularly in women. In the Liver Simulated Allocation Model analysis, MELD 3.0 resulted in fewer wait list deaths compared to MELDNa (7788 vs 7850; P = .02). MELD 3.0 affords more accurate mortality prediction in general than MELDNa and addresses determinants of wait list outcomes, including the sex disparity.

Kim WR ，Mannalithara A ，Heimbach JK ，Kamath PS ，Asrani SK ，Biggins SW ，Wood NL ，Gentry SE ，Kwong AJ ... -  《-》

A revised model for end-stage liver disease optimizes prediction of mortality among patients awaiting liver transplantation.

The Model for End Stage Liver Disease (MELD) was originally developed based on data from patients who underwent the transjugular intrahepatic portosystemic shunt procedure. An updated MELD based on data from patients awaiting liver transplantation should improve mortality prediction and allocation efficiency. Wait-list data from adult primary liver transplantation candidates from the Organ Procurement and Transplantation Network were divided into a model derivation set (2005-2006; n=14,214) and validation set (2007-2008; n=13,945). Cox regression analysis was used to derive and validate an optimized model that updated coefficients and upper and lower bounds for MELD components and included serum levels of sodium. Main outcomes measure was ability to predict 90-day mortality of patients on the liver transplantation wait list. Optimized MELD score updated coefficients and implemented new upper and lower bounds for creatinine (0.8 and 3.0 mg/dL, respectively) and international normalized ratio (1 and 3, respectively). Serum sodium concentrations significantly predicted mortality, even after adjusting for the updated MELD model. The final model, based on updated fit of the 4 variables (ie, bilirubin, creatinine, international normalized ratio, and sodium) had a modest yet statistically significant gain in discrimination (concordance: 0.878 vs 0.865; P<.01) in the validation dataset. Utilization of the new score could affect up to 12% of patients (based on changed score for 459 of 3981 transplants in the validation set). Modification of MELD score to update coefficients, change upper and lower bounds, and incorporate serum sodium levels improved wait-list mortality prediction and should increase efficiency of allocation of donated livers.

Leise MD ，Kim WR ，Kremers WK ，Larson JJ ，Benson JT ，Therneau TM ... -  《-》

Defining a Liver Transplant Benefit Threshold for the Model for End-Stage Liver Disease-Sodium Score.

Beal EW ，Akateh C ，Tumin D ，Bagante F ，Black SM ，Washburn K ，Azouley D ，Pawlik TM ... -  《-》

Validation of the five-variable Model for End-stage Liver Disease (5vMELD) for prediction of mortality on the liver transplant waiting list.

Modifications to the Model for End-Stage Liver Disease (MELD) have been proposed to improve prioritization of liver transplant (LT) candidates. Using a U.S. database, we derived a revised MELD including sodium and albumin [5-variable MELD (5vMELD)] that improved prediction of waiting list mortality. Our objectives were to confirm the association between hypoalbuminaemia and mortality and to externally validate 5vMELD in Canadian LT candidates. Among adults registered on the LT waiting list at the University of Alberta (01/2000-10/2009), Cox regression determined the association between albumin and 1-year waiting list mortality. The discrimination of MELD, MELDNa and 5vMELD for predicting 1-year mortality were compared using c-statistics. Among 677 patients, 17% died and 51% underwent LT within 1 year of listing. Median serum albumin was 3.1 g/dl (IQR 2.6-3.6) and 70% of patients were hypoalbuminaemic (albumin <3.5 g/dl). One-year mortality in patients with normal serum albumin and hypoalbuminaemia were 14% and 29% respectively (P = 0.004). For patients with serum albumin between 2.0 and 4.0 g/dl, an approximately linear, inverse relationship was observed between albumin and 1-year mortality [adjusted hazard ratio (HR) 1.45; 95% CI 1.03-2.03; P = 0.03]. For this outcome, the c-statistic of 5vMELD (0.778) was superior to those of MELD (0.754) and MELDNa (0.765) (both P ≤ 0.05). Hypoalbuminaemia is an independent predictor of mortality on the LT waiting list. Compared with MELD and MELDNa, 5vMELD improves prediction of mortality suggesting that modification of these scores to include serum albumin should be considered as a means of prioritizing LT candidates.

Myers RP ，Tandon P ，Ney M ，Meeberg G ，Faris P ，Shaheen AA ，Aspinall AI ，Burak KW ... -  《-》

Proposing a Sex-Adjusted Sodium-Adjusted MELD Score for Liver Transplant Allocation.

Sealock JM ，Ziogas IA ，Zhao Z ，Ye F ，Alexopoulos SP ，Matsuoka L ，Chen G ，Davis LK ... -  《-》