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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)
Patients with nonalcoholic fatty liver disease (NAFLD) and advanced liver fibrosis are at the highest risk for progressing to end-stage liver disease. We constructed and validated a scoring system consisting of routinely measured and readily available clinical and laboratory data to separate NAFLD patients with and without advanced fibrosis. A total of 733 patients with NAFLD confirmed by liver biopsy were divided into 2 groups to construct (n ؍ 480) and validate (n ؍ 253) a scoring system. Routine demographic, clinical, and laboratory variables were analyzed by multivariate modeling to predict presence or absence of advanced fibrosis. Age, hyperglycemia, body mass index, platelet count, albumin, and AST/ALT ratio were independent indicators of advanced liver fibrosis. A scoring system with these 6 variables had an area under the receiver operating characteristic curve of 0.88 and 0.82 in the estimation and validation groups, respectively. By applying the low cutoff score (؊1.455), advanced fibrosis could be excluded with high accuracy (negative predictive value of 93% and 88% in the estimation and validation groups, respectively). By applying the high cutoff score (0.676), the presence of advanced fibrosis could be diagnosed with high accuracy (positive predictive value of 90% and 82% in the estimation and validation groups, respectively). By applying this model, a liver biopsy would have been avoided in 549 (75%) of the 733 patients, with correct prediction in 496 (90%). Conclusion: a simple scoring system accurately separates patients with NAFLD with and without advanced fibrosis, rendering liver biopsy for identification of advanced fibrosis unnecessary in a substantial proportion of patients. (HEPATOLOGY 2007;45:846-854.)
JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org.. Biometrika Trust is collaborating with JSTOR to digitize, preserve and extend access to Biometrika. SUMMARY Nonproportional hazards can often be expressed by extending the Cox model to include time varying coefficients; e.g., for a single covariate, the hazard function for subject i is modelled as exp { fl(t)Zi(t)}. A common example is a treatment effect that decreases withtime. We show that the function /3(t) can be directly visualized by smoothing an appropriate residual plot. Also, many tests of proportional hazards, including those of Cox are related to time-weighted score tests of the proportional hazards hypothesis, and can be visualized as a weighted least-squares line fitted to the residual plot.
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