A Model to Predict Survival in Patients With End–Stage Liver Disease
Top Cited Papers
- 1 February 2001
- journal article
- review article
- Published by Wolters Kluwer Health in Hepatology
- Vol. 33 (2), 464-470
- https://doi.org/10.1053/jhep.2001.22172
Abstract
A recent mandate emphasizes severity of liver disease to determine priorities in allocating organs for liver transplantation and necessitates a disease severity index based on generalizable, verifiable, and easily obtained variables. The aim of the study was to examine the generalizability of a model previously created to estimate survival of patients undergoing the transjugular intrahepatic portosystemic shunt (TIPS) procedure in patient groups with a broader range of disease severity and etiology. The Model for End–Stage Liver Disease (MELD) consists of serum bilirubin and creatinine levels, International Normalized Ratio (INR) for prothrombin time, and etiology of liver disease. The model's validity was tested in 4 independent data sets, including (1) patients hospitalized for hepatic decompensation (referred to as “hospitalized” patients), (2) ambulatory patients with noncholestatic cirrhosis, (3) patients with primary biliary cirrhosis (PBC), and (4) unselected patients from the 1980s with cirrhosis (referred to as “historical” patients). In these patients, the model's ability to classify patients according to their risk of death was examined using the concordance (c)–statistic. The MELD scale performed well in predicting death within 3 months with a c–statistic of (1) 0.87 for hospitalized patients, (2) 0.80 for noncholestatic ambulatory patients, (3) 0.87 for PBC patients, and (4) 0.78 for historical cirrhotic patients. Individual complications of portal hypertension had minimal impact on the model's prediction (range of improvement in c–statistic: <.01 for spontaneous bacterial peritonitis and variceal hemorrhage to ascites: 0.01–0.03). The MELD scale is a reliable measure of mortality risk in patients with end–stage liver disease and suitable for use as a disease severity index to determine organ allocation priorities.Keywords
This publication has 42 references indexed in Scilit:
- MicroRNA expression profiles predictive of human renal allograft statusProceedings of the National Academy of Sciences, 2009
- MiRTif: a support vector machine-based microRNA target interaction filterBMC Bioinformatics, 2008
- The database of experimentally supported targets: a functional update of TarBaseNucleic Acids Research, 2008
- MeCP2-dependent repression of an imprinted miR-184 released by depolarizationHuman Molecular Genetics, 2008
- NCBI GEO: mining tens of millions of expression profiles--database and tools updateNucleic Acids Research, 2006
- Gene expression analyses reveal molecular relationships among 20 regions of the human CNSneurogenetics, 2006
- Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profilesProceedings of the National Academy of Sciences, 2005
- Combinatorial microRNA target predictionsNature Genetics, 2005
- Conserved Seed Pairing, Often Flanked by Adenosines, Indicates that Thousands of Human Genes are MicroRNA TargetsCell, 2005
- Gene Expression Omnibus: NCBI gene expression and hybridization array data repositoryNucleic Acids Research, 2002