Performance of the model for end-stage liver disease score for mortality prediction and the potential role of etiology


      • Discrimination of MELD is widely reported as fair to good, although its calibration is still unclear.
      • In 2 cirrhosis cohorts we found barely acceptable c-statistics, which were significantly worse in patients with non-viral etiology.
      • Calibration was largely unsatisfactory with the Mayo and UNOS MELD versions.
      • Validated recalibrations of MELD-Mayo and UNOS versions are presented which allow reliable predictions for clinical practice.
      • Age, albumin and ascites as the indication for TIPS are candidate variables for an update to the MELD-TIPS score.

      Background & Aims

      Although the discriminative ability of the model for end-stage liver disease (MELD) score is generally considered acceptable, its calibration is still unclear. In a validation study, we assessed the discriminative performance and calibration of 3 versions of the model: original MELD-TIPS, used to predict survival after transjugular intrahepatic portosystemic shunt (TIPS); classic MELD-Mayo; and MELD-UNOS, used by the United Network for Organ Sharing (UNOS). We also explored recalibrating and updating the model.


      In total, 776 patients who underwent elective TIPS (TIPS cohort) and 445 unselected patients (non-TIPS cohort) were included. Three, 6 and 12-month mortality predictions were calculated by the 3 MELD versions: discrimination was assessed by c-statistics and calibration by comparing deciles of predicted and observed risks. Cox and Fine and Grey models were used for recalibration and prognostic analyses.


      In the TIPS/non-TIPS cohorts, the etiology of liver disease was viral in 402/188, alcoholic in 185/130, and non-alcoholic steatohepatitis in 65/33; mean follow-up±SD was 25±9/19±21 months; and the number of deaths at 3-6-12 months was 57-102-142/31-47-99, respectively. C-statistics ranged from 0.66 to 0.72 in TIPS and 0.66 to 0.76 in non-TIPS cohorts across prediction times and scores. A post hoc analysis revealed worse c-statistics in non-viral cirrhosis with more pronounced and significant worsening in the non-TIPS cohort. Calibration was acceptable with MELD-TIPS but largely unsatisfactory with MELD-Mayo and -UNOS whose performance improved much after recalibration. A prognostic analysis showed that age, albumin, and TIPS indication might be used to update the MELD.


      In this validation study, the performance of the MELD score was largely unsatisfactory, particularly in non-viral cirrhosis. MELD recalibration and candidate variables for an update to the MELD score are proposed.

      Lay summary

      While the discriminative performance of the model for end-stage liver disease (MELD) score is credited to be fair to good, its calibration, the correspondence of observed to predicted mortality, is still unsettled. We found that application of 3 different versions of the MELD in 2 independent cirrhosis cohorts yielded largely imprecise mortality predictions particularly in non-viral cirrhosis. Thus, we propose a recalibration and suggest candidate variables for an update to the model.

      Graphical abstract


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        • Malinchoc M.
        • Kamath P.S.
        • Gordon F.D.
        • Peine C.J.
        • Rank J.
        • ter Borg P.C.
        A model to predict poor survival in patients undergoing transjugular intrahepatic portosystemic shunts.
        Hepatology. 2000; 31: 864-871
        • Kamath P.S.
        • Wiesner R.H.
        • Malinchoc M.
        • Kremers W.
        • Therneau T.M.
        • Kosberg C.L.
        • et al.
        A model to predict survival in patients with end-stage liver disease.
        Hepatology. 2001; 33: 464-470
        • Freeman R.B.
        • Wiesner R.H.
        • Harper A.
        • McDiarmid S.V.
        • Lake J.
        • Edwards E.
        The new liver allocation system: moving towards evidence based transplantation policy.
        Liver Transplant. 2002; 8: 851-858
      1. OPTN policy 9. Page 167. Accessed on October 22nd 2020.

      2. (accessed on june the 12th 2020).

      3. (accessed on june the 12th 2020).

      4. on june the 12th 2020).

        • Kamath P.S.
        • Kim W.R.
        The model for end-stage liver disease (MELD).
        Hepatology. 2007; 45: 797-805
        • Cholangitas E.
        • Marelli L.
        • Shusang V.
        • Senzolo M.
        • Rolles K.
        • Patch D.
        • et al.
        A systematic review of the performance of the Model for End-Stage Liver Disease (MELD) in the setting of liver transplantation.
        Liv Transpl. 2006; 12: 1049-1061
        • Freeman Jr., R.B.
        • Gish G.R.
        • Harper A.
        • Davis G.L.
        • Vierling J.
        • Lieblein L.
        • et al.
        Model for end-stage liver disease (MELD) exception guidelines: results and recommendations from the MELD exception study group and conference (MESSAGE) for the approval of patients who need liver transplantation with diseases not considered by the standard MELD formula.
        Liver Transplant. 2006; 12: S128-S136
        • Luca A.
        • Angermayr B.
        • Bertolini G.
        • Koenig F.
        • Vizzini G.
        • Ploner M.
        • et al.
        An integrated MELD model including serum sodium and age improves the prediction of early mortality in patients with cirrhosis.
        Liver Transpl. 2007; 13: 1174-1180
        • Pugh R.N.
        • Murray-Lyon I.M.
        • Dawson J.L.
        • Pietroni M.C.
        • Williams R.
        Transection of the esophagus for bleeding oesophageal varices.
        Br J Surg. 1973; 60: 646-649
        • World Medical Association
        World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects.
        JAMA. 2013; 310: 2191-2194
        • Pintile M.
        Competing risks. A practical perspective.
        John Wiley & Sons, Chichester2006
        • Cox D.R.
        Regression models and life-Tables (with discussion).
        J R Statist Soc B. 1972; 34: 187-220
        • Austin P.
        • Fine J.P.
        Practical recommendations for reporting Fine-Gray model analyses for competing risk data.
        Stat Med. 2017; 36 (4991-4400)
        • Debray T.P.
        • Vergouwe Y.
        • Koffijberg H.
        • Nieboer D.
        • Steyerberg E.W.
        • Moons K.G.
        A new framework to enhance the interpretation of external validation studies of clinical prediction models.
        J Clin Epidemiol. 2015; 68: 279-289
        • Steyerberger E.W.
        Clinical prediction models. A practical approach to development, validation and updating.
        2nd ed. © Springer Nature Switzerland AG, 2019
        • Hanley J.A.
        • McNeil B.J.
        The meaning and use of the area under a receiver operating characteristic (ROC) curve.
        Radiology. 1982; 143: 29-36
        • Hosmer D.W.
        • Hosmer T.
        • Le Cessie S.
        • Lemeshow S.
        A comparison of goodness-of-fit tests for the logistic regression model.
        Stat Med. 1997; 16: 965-980
        • Fine J.P.
        • Gray R.J.
        A proportional hazards model for the subdistribution of competing risk.
        J Am Stat Ass. 1999; 94: 496-509
        • Finkenstedt A.
        • Dorn L.
        • Edlinger M.
        • Prokop W.
        • Risch L.
        • Griesmacher A.
        • et al.
        Cystatin C is a strong predictor of survival in patients with cirrhosis: is a cystatin C-based MELD better?.
        Liver Int. 2012 Sep; 32: 1211-1216
        • Vilar Gomez E.
        • Bertot L.C.
        • Oramas B.G.
        • Soler E.A.
        • Navarro R.L.
        • Elias J.D.
        • et al.
        Application of a biochemical and clinical model to predict individual survival in patients with end-stage liver disease.
        World J Gastroenterol. 2009 Jun 14; 15: 2768-2777
        • Renfrew P.D.
        • Quan H.
        • Doig C.J.
        • Dixon E.
        • Molinari M.
        The Model for End-stage Liver Disease accurately predicts 90-day liver transplant wait-list mortality in Atlantic Canada.
        Can J Gastroenterol. 2011 Jul; 25: 359-364
        • Bettinger D.
        • Sturm L.
        • Plaff L.
        • Hahn F.
        • Kloekner R.
        • Volkwein L.
        • et al.
        Refining prediction of survival after TIPS with the novel Freiburg index of post-TTIPS survival.
        J Hepatol. 2021; 74: 1362-1372