Nomogram and Artificial Neural Network for Prognostic Performance on the Albumin-Bilirubin Grade for Hepatocellular Carcinoma Undergoing Transarterial Chemoembolization

Abstract

PurposeTo construct the albumin-bilirubin (ALBI) grade and the Child-Turcotte-Pugh (CTP) score based on nomograms, as well as to develop an artificial neural network (ANN) to compare the prognostic performance of the 2 scores for hepatocellular carcinoma (HCC) that has undergone transarterial chemoembolization. Materials and MethodsThis multicentric retrospective study included patients with HCC who underwent transarterial chemoembolization monotherapy as an initial treatment at 4 institutions between January 2008 and December 2016. In the training cohort, significant risk factors associated with overall survival (OS) were identified by univariate and multivariate analyses. The prognostic nomograms and ANN were established and then validated in 2 validation cohorts. ResultsA total of 838 patients (548, 115, and 175 in the training cohort and validation cohorts 1 and 2, respectively) were included. The median OS was 10.4, 15.7, and 9.2 months in the training cohort and validation cohorts 1 and 2, respectively. In the training cohort, both ALBI grade and CTP score were identified as significant risk factors. The ALBI grade and CTP score based on nomograms were established separately and showed similar prognostic performance when assessed externally in validation cohorts (C-index in validation cohort 1: 0.823 vs 0.802, P = .417; in validation cohort 2: 0.716 vs 0.729, P = .793). ANN showed that ALBI grade had higher importance on survival prediction than CTP score. ConclusionsALBI grade performs at least no worse than CTP score regarding survival prediction for HCC receiving transarterial chemoembolization. Considering the easy application, ALBI grade has the potential to be regarded as an alternative to CTP score.