Using prognostic and predictive clinical features to make personalised survival prediction in advanced hepatocellular carcinoma patients undergoing sorafenib treatment

Abstract

BACKGROUND: Sorafenib is the current standard of care for patients with advanced hepatocellular carcinoma (aHCC) and has been shown to improve survival by about 3 months compared to placebo. However, survival varies widely from under three months to over two years. The aim of this study was to build a statistical model that allows personalised survival prediction following sorafenib treatment. METHODS: We had access to 1130 patients undergoing sorafenib treatment for aHCC as part of the control arm for two phase III randomised clinical trials (RCTs). A multivariable model was built that predicts survival based on baseline clinical features. The statistical approach permits both group-level risk stratification and individual-level survival prediction at any given time point. The model was calibrated, and its discrimination assessed through Harrell's c-index and Royston-Sauerbrei's R 2 D. RESULTS: The variables influencing overall survival were vascular invasion, age, ECOG score, AFP, albumin, creatinine, AST, extrahepatic spread and aetiology. The model-predicted survival very similar to that observed. The Harrell's c-indices for training and validation sets were 0.72 and 0.70, respectively indicating good prediction. CONCLUSIONS: Our model ('PROSASH') predicts patient survival using baseline clinical features. However, it will require further validation in a routine clinical practice setting.

Current strategies for the treatment of intermediate and advanced hepatocellular carcinoma

“…The variables influencing overall survival in the PROSASH score were vascular invasion, age, ECOG score, AFP, albumin, creatinine, AST, extrahepatic spread and aetiology. Corresponding data can be entered into an online tool that calculates the respective survival percentage at 6, 12, 24 and 36 months (https://jscalc.io/calc/oGSDLHDsDg9g2XBF) [27].…”

The role of PNI to predict survival in advanced hepatocellular carcinoma treated with Sorafenib

“…PNI index is composed of only two parameters. This simplification of the index makes it more available and simpler for daily clinical practice respect others index evaluated by our and others groups [5,8,[35][36][37][38].…”

“…Interestingly, the PNI has demonstrated to correlate with survival outcomes of patients with several gastrointestinal cancers [33,34], including HCC [35][36][37] but not in advanced stage. [38].…”

Sorafenib for Patients with Hepatocellular Carcinoma and Child-Pugh B Liver Cirrhosis: Lessons Learned from a Terminated Study

“…Interestingly, one patient with a partial response to sorafenib had an OS of 26 months, showing that longer survival is possible in patients with Child-Pugh B and underscoring limitations of Child-Pugh as a prognostic tool when considering sorafenib. Novel algorithms, such as the recently proposed "Prediction of Survival in Advanced Sorafenib-treated HCC" (PROSASH) score have refined survival prediction based on prognostic and predictive clinical features [27,28]. This approach offers an individualized survival prediction with a higher accuracy than the Child-Pugh score and BCLC-algorithm [29].…”