An ALBI- and Ascites-Based Model to Predict Survival for BCLC Stage B Hepatocellular Carcinoma

We aimed to develop a predictive model constituted with the ALBI grade, the ascites, and tumor burden related parameters in patients with BCLC stage B HCC.

Patients diagnosed as the BCLC stage B HCC were collected from a retrospective database. Construction and validation of the predictive model were performed based on multivariate Cox regression analysis. Predictive accuracy, discrimination (c-index), and fitness performance (calibration curve) of the model were compared with the other eight models. The decision curve analysis (DCA) was used to evaluate the clinical utility.

A total of 1773 patients diagnosed as BCLC stage B HCC between 2007 and 2016 were included in the present study. The ALBI-AS grade, the AFP level, and the 8-and-14 grade were used for the development of a prognostic prediction model after multivariate analysis. The area under the receiver operator characteristic curve (AUROC) for overall survival at 1, 2, and 3 years predicted by the present model were 0.73, 0.69, and 0.67 in the training cohort. The concordance index (c-index) and the Aiken information criterion (AIC) were 0.68 and 6216.3, respectively. In the internal and external validation cohorts, the present model still revealed excellent predictive accuracy, discrimination, and fitness performance. Then the ALBI-AS based model was evaluated to be superior to other prognostic models with the highest AUROC, c-index, and lowest AIC values. Moreover, DCA also demonstrated that the present model was clinically beneficial.

The ALBI-AS grade is a novel predictor of survival for patients with BCLC stage B HCC.