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Is there an optimal staging system or liver reserve model that can predict outcome in hepatocellular carcinoma?

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Background Many staging systems and liver reserve models have been proposed to predict hepatocellular carcinoma (HCC) prognosis. However, there is no consensus as to which model provides the best prognostic… Click to show full abstract

Background Many staging systems and liver reserve models have been proposed to predict hepatocellular carcinoma (HCC) prognosis. However, there is no consensus as to which model provides the best prognostic value. We aimed to investigate the prognostic role of 8 noninvasive models including the albumin-bilirubin index (ALBI), AST to platelet ratio index (APRI), Barcelona Clinic Liver Cancer (BCLC), Cancer of the Liver Italian Program (CLIP) system, Child-Pugh (CP) class, Fibrosis-4 (FIB-4) score, model for end-stage liver disease (MELD) score, and platelet-albumin-bilirubin index (PALBI) in patients with HCC. Methods This is a retrospective study of 900 HCC patients. Patients who underwent transplantation were excluded. The Kaplan-Meier method was used to estimate the survival probabilities. Multivariate cox proportional hazard models were used to calculate the survival trend. P<0.05 was considered significant. The area under receiver operating characteristic curve (AUC) was calculated to test the discriminatory power over 1- and 3-year mortality and recurrence. Results For predicting 1- and 3-year mortality, the CLIP score provided the highest AUC value, followed by the BCLC stage and the PALBI grade. For predicting 3-year recurrence, the CLIP score demonstrated the highest discriminative power followed by the PALBI grade, ALBI grade and BCLC system. However, all included models were found to be poor predictors for recurrence. Conclusions The CLIP score is more accurate prognostic model to predict mortality and recurrence than the BCLC stage. Regarding the liver reserve models, the PALBI is the most accurate prognostic models among 6 models to predict mortality and recurrence.

Keywords: hepatocellular carcinoma; system; model predict; liver reserve; model

Journal Title: Journal of gastrointestinal oncology
Year Published: 2018

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