The heterogeneity of intermediate-stage hepatocellular carcinoma (HCC) and the widespread use of transarterial chemoembolization (TACE) outside recommended guidelines have encouraged the development of scoring systems that predict patient survival. The aim of this study was to build and validate statistical models that offer individualized patient survival prediction using response to TACE as a variable. Clinically relevant baseline parameters were collected for 4,621 patients with HCC treated with TACE at 19 centers in 11 countries. In some of the centers, radiological response (as assessed by modified Response Evaluation Criteria in Solid Tumors [mRECIST]) was also accrued. The data set was divided into a training set, an internal validation set, and two external validation sets. A new pre-TACE model ("Pre-TACE-Predict") and a post-TACE model ("Post-TACE-Predict") that included response were built. The performance of the models in predicting overall survival (OS) was compared with existing ones. Median OS was 19.9 months. The factors influencing survival were tumor number and size, alpha-fetoprotein, albumin, bilirubin, vascular invasion, etiology, and response as assessed by mRECIST. The proposed models showed superior predictive accuracy compared to existing models (the HAP score and its various modifications) and allowed for patient stratification into four distinct risk categories whose median OS ranged from 7 months to more than 4 years. Conclusion: A TACE-specific and extensively validated model based on routinely available clinical features and response after first TACE permitted patient-level prognostication.
Prediction of Survival Among Patients Receiving Transarterial Chemoembolization for Hepatocellular Carcinoma: A Response-Based Approach
Pinato, David J;Pirisi, Mario;
2020-01-01
Abstract
The heterogeneity of intermediate-stage hepatocellular carcinoma (HCC) and the widespread use of transarterial chemoembolization (TACE) outside recommended guidelines have encouraged the development of scoring systems that predict patient survival. The aim of this study was to build and validate statistical models that offer individualized patient survival prediction using response to TACE as a variable. Clinically relevant baseline parameters were collected for 4,621 patients with HCC treated with TACE at 19 centers in 11 countries. In some of the centers, radiological response (as assessed by modified Response Evaluation Criteria in Solid Tumors [mRECIST]) was also accrued. The data set was divided into a training set, an internal validation set, and two external validation sets. A new pre-TACE model ("Pre-TACE-Predict") and a post-TACE model ("Post-TACE-Predict") that included response were built. The performance of the models in predicting overall survival (OS) was compared with existing ones. Median OS was 19.9 months. The factors influencing survival were tumor number and size, alpha-fetoprotein, albumin, bilirubin, vascular invasion, etiology, and response as assessed by mRECIST. The proposed models showed superior predictive accuracy compared to existing models (the HAP score and its various modifications) and allowed for patient stratification into four distinct risk categories whose median OS ranged from 7 months to more than 4 years. Conclusion: A TACE-specific and extensively validated model based on routinely available clinical features and response after first TACE permitted patient-level prognostication.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
