Improving MELD for use in acute liver failure
Authors: Mark J.W. McPhail
Journal: Journal of Hepatology (2010)

Cytokeratin 18-based modification of the MELD score improves prediction of spontaneous survival after acute liver injuryJournal of HepatologyVol. 53Issue 4PreviewPredicting the probability of patients with acute liver failure (ALF) to recover spontaneously is of major clinical importance. As apoptotic and necrotic cell death are crucial in the pathogenesis of ALF, we determined whether selected cell-death markers predict outcome of patients with ALF and/or discriminate between etiologies. Full-Text PDF Reply to the Letter to the Editor 'Improving MELD for use in acute liver failure'Journal of HepatologyVol. 54Issue 6PreviewThis is a reply to the Letter to the Editor by Dr. McPhail: Full-Text PDF Open Access Bechmann et al. [[1]Bechmann L.P. et al.Cytokeratin 18-based modification of the MELD score improves prediction of spontaneous survival after acute liver injury.J Hepatol. 2010; 53: 639-647Abstract Full Text Full Text PDF PubMed Scopus (133) Google Scholar] presented an interesting modification to the Model for End-Stage Liver Disease (MELD) score using M-65, a marker of hepatic necrosis, as a substitute for bilirubin in the MELD equation which they subsequently applied to a series of patients with acute liver failure (ALF). The statistical justification and reporting of the subsequent results is useful to discuss. MELD is constructed (Eq. (1)) from serum creatinine, bilirubin, and internationalized normalized ratio (INR), and is a highly successful risk stratification marker for death in patients with cirrhosis. While it is used for prognostication in ALF in the USA, there is considerable doubt as to its applicability in this setting partly because of the lack of utility of bilirubin as an early marker of disease severity in ALF. MELD was constructed [[2]Malinchoc M. et al.A model to predict poor survival in patients undergoing transjugular intrahepatic portosystemic shunts.Hepatology. 2000; 31: 864-871Crossref PubMed Scopus (2167) Google Scholar] from a Cox-proportional regression analysis of 231 patients with cirrhosis at the time of transjugular intrahepatic portosystemic shunt (TIPSS), where the quantitative predictors were logarithmically transformed to reduce the effect of influential outliers. The coefficients seen in the MELD equation are the regression coefficients derived from the computation using these transformed predictors.[MELD score]=9.57Ln(Creatinine)+3.78Ln(Bilirubin)+11.2Ln(INR)+6.43(1) Creatinine – mg/L, Bilirubin – mg/dL, INR – unitless. Bechmann et al.'s implantation of M-65 into MELD in this ALF cohort is concerning for a number of reasons. Their analysis is based on outcome alone and not the length of survival and therefore uses logistic regression (via Receiver Operating Characteristic (ROC) curves) not proportional hazards. In any multivariate analysis, the independence of predictors must be assessed and M-65, while having a clear univariate correlation with outcome, was not tested against INR and creatinine in a logistic or proportional hazards multivariate model. Furthermore, the effect of INR and creatinine on survival in ALF is likely to be different from cirrhosis; in fact, de novo regression modeling may give different regression coefficients that lead to a more useful MELD improvement rather than the assumption that the regression coefficients from patients with a different disease in a different country are immediately transferable. Improvements in modeling when assessed by ROC curve analysis can be assessed quantitatively as was lacking in the Bechman et al. analysis. ROC curve comparisons via the Delong method [[3]DeLong E.R. DeLong D.M. Clarke-Pearson D.L. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach.Biometrics. 1988; 44: 837-845Crossref PubMed Scopus (14634) Google Scholar] are non-parametric, well validated, and produce a p value for the comparison. While sensitivity and specificity improvements were discussed (again without quantitative comparators) and ROC curves were produced, there was no head to head graphical or quantitative ROC curve comparison between MELD and its modification or comparison among new multivariate models. These would have strengthened the analysis. Statistical models are not necessarily interchangeable between diseases or populations, and repeat modeling is necessary to provide evidence of validity of the model. Statistical assessment of improvements of multivariate models is available and should be reported to allow the quantitation of the significance of any improvement. Mark McPhail is supported by the Wellcome Trust, UK. Mark McPhail declared that he does not have anything to disclose regarding conflict of interest with respect to this letter.