Abstract
<b><i>Introduction:</i></b> Because of recent developments in treatments for hepatocellular carcinoma (HCC), methods for determining suitable therapy for initial or recurrent HCC have become important. This study used artificial intelligence (AI) findings to establish a system for predicting prognosis of HCC patients at time of reoccurrence based on clinical data as a reference for selection of treatment modalities. <b><i>Methods:</i></b> As a training cohort, 5,701 observations obtained at the initial and each subsequent treatment for recurrence from 1,985 HCC patients at a single center from 2000 to 2021 were used. The validation cohort included 5,692 observations from patients at multiple centers obtained at the time of the initial treatment. An AI calculating system (PRAID) was constructed based on 25 clinical factors noted at each treatment from the training cohort, and then predictive prognostic values for 1- and 3-year survival in both cohorts were evaluated. <b><i>Results:</i></b> After exclusion of patients lacking clinical data regarding albumin-bilirubin (ALBI) grade or tumor-node-metastasis stage of the Liver Cancer Study Group of Japan, 6th edition (TNM-LCSGJ 6th), ALBI-TNM-LCSGJ 6th (ALBI-T) and modified ALBI-T scores confirmed that prognosis for patients in both cohorts was similar. The area under the curve for prediction of both 1- and 3-year survival in the validation cohort was 0.841 (sensitivity 0.933 [95% CI: 0.925–0.940], specificity 0.517 [95% CI: 0.484–0.549]) and 0.796 (sensitivity 0.806 [95% CI: 0.790–0.821], specificity 0.646 [95% CI: 0.624–0.668]), respectively. <b><i>Conclusion:</i></b> The present PRAID system might provide useful prognostic information related to short and medium survival for decision-making regarding the best therapeutic modality for both initial and recurrent HCC cases.