Identifying optimal candidates for post-TIPS patients with HCC undergoing TACE: a multicenter observational study

Abstract

Objective: To develop a prognostic model for post-transjugular intrahepatic portosystemic shunt (TIPS) patients with hepatocellular carcinoma (HCC) beyond the Milan criteria treated by transarterial chemoembolization (TACE). Design: Between January 2013 and January 2020, 512 patients with HCC beyond the Milan criteria who underwent TACE after TIPS were retrospectively recruited from 15 tertiary centers. Patients were randomly sorted into a training set (n = 382) and a validation set (n = 130). Medical data and overall survival were assessed. A prediction model was developed using multivariate Cox regression analyses. Predictive performance and discrimination were evaluated and compared with other prognostic models. Results: Vascular invasion, log10(AFP), 1/creatinine, extrahepatic spread, and log10(ALT) were the most significant prognostic factors of survival. These five parameters were included in a new VACEA score. This score was able to stratify patients in the training set into four distinct risk grades whose median overall survival were 25.2, 15.1, 8.9, and 6.2 months, respectively. The 6-month, 1-year, 2-year, and 3-year AUROC values and C-index of the VACEA model were 0.819, 0.806, 0.779, 0.825, and 0.735, respectively, and higher than those of other seven currently available models in both the training and validation sets, as well as in different subgroups. Conclusion: The VACEA score could stratify post-TIPS patients with HCC beyond the Milan criteria treated by TACE and help to identify candidates who benefit from this treatment. Key Points: • Vascular invasion, AFP, creatinine, extrahepatic spread, and ALT were independent significant prognostic factors of survival for HCC patients who underwent TACE after TIPS. • Our new model, named VACEA score, can accurately predict prognosis at the individual level and stratify patients into four distinct risk grades. • The VACEA model showed better prognostic discrimination and calibration than other current TACE-/TIPS-specific models [Figure not available: see fulltext.].