Tumor burden with AFP improves survival prediction for TACE-treated patients with HCC: An international observational study☆

Background & Aims: Current prognostic models for patients with hepatocellular carcinoma (HCC) undergoing transarterial chemoembolization (TACE) are not extensively validated and widely accepted. We aimed to develop and validate a continuous model incorporating tumor burden and biology for individual survival prediction and risk stratification. Methods: Overall, 4,377 treatment-naive candidates for whom TACE was recommended, from 39 centers in five countries, were enrolled and divided into training, internal validation, and two external validation datasets. The novel model was developed using a Cox multivariable regression analysis and compared with our original 6-and-12 model (the largest tumor size [ts, centimetres] + tumor number [tn]) and other available models in terms of predictive accuracy. Results: <0.001) from low-risk to high-risk strata, respectively. These findings were confirmed in validation and subgroup analyses. Conclusions: The 6-and-12 model 2.0 significantly improved individual outcome predictions and better stratified the candidates recommended for TACE; thus, this model could be used in both clinical practice and trial design. Impact and implications: In this international multicentre study, we developed and internally and externally validated a novel outcome prediction model for candidates with HCC who would be ideal for TACE. The model, called the 6-and-12 model 2.0, was based on 4,377 patients from 39 centers in five countries. The model offers individualized outcome prediction, outperforming the original 6-and-12 model score and other existing metrics across all datasets and subsets. Based on different levels of alpha-fetoprotein (AFP) and corresponding cut-offs of tumor burden, patients could be stratified into three risk strata with significantly different survival prognoses, which could provide a referential framework to control study heterogeneity and define the target population in future trial designs.