The study was approved by the Institutional Review Board of Mayo Foundation and the Ethics Committee of the Korean National Cancer Center. The HCC lesions were characterized by cross-sectional radiographic characteristics, which included (1) the number of tumor nodules, (2) the diameter of the largest nodule, (3) vascular invasion (enhancing vascular tumor thrombi), and (4) extrahepatic metastasis. Based on these radiographic information and laboratory data at entry into the study, individual patients were staged according to the BCLC, the CLIP score, and the JIS score. The original MELD score (before

modification for the purpose of organ allocation) was calculated as published.18 For survival analysis, patients were followed from the first visit date for HCC assessment B-Raf cancer forward until July 22, 2010 and September 1, 2004 in the derivation and validation cohorts, respectively. To ascertain complete capture of all decedents, a proprietary information source (Accurint) was used to supplement information in the medical records in the derivation cohort and the National Cancer Registry data in the validation

cohort. Death from any causes was considered an event in this analysis. In the base-case analysis, liver transplantation was not considered an event, whereas a subsequent sensitivity analysis was conducted censoring liver transplantation. Patient survival probability was estimated using the Kaplan-Meier buy Depsipeptide method. The main tool for survival analysis was the proportional hazards model. Based on variables with univariate significance (P < 0.10) and clinical relevance, multivariate models were created. The output of the model was expressed as coefficients, which were used to compute hazard ratios. In addition, the coefficients were used to calculate

a risk score, which, in turn, was used to predict survival. In the derivation cohort, cross-validation was used to examine the reproducibility of the survival model. The data were 上海皓元医药股份有限公司 randomly divided into four equal subsets and the coefficients were recalculated after removing one subset of the data at a time. The concordance (c)-statistic was computed using the new coefficients in the remainder of the data. The c-statistic from each of the four subsets was compared to one another. In testing the accuracy of the model prediction in the validation cohort, patients were divided into three groups at the 25th and 75th percentiles of the risk score. The observed survival in the validation cohort was compared with survival estimated by the survival model. The goodness-of-fit of the models was assessed using the c-statistics.