Introduction 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. Methods 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. Results 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. Conclusion 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.

中文翻译：

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尝试利用人工智能建立肝细胞癌的预后预测系统，以协助选择治疗方式。


简介 由于肝细胞癌 (HCC) 治疗的最新进展，确定初始或复发性 HCC 合适治疗的方法变得非常重要。本研究利用人工智能（AI）研究结果建立了一个系统，根据临床数据预测肝癌患者复发时的预后，作为选择治疗方式的参考。方法 作为训练队列，使用了 2000 年至 2021 年单个中心 1,985 名 HCC 患者在初次治疗和每次后续治疗复发时获得的 5,701 项观察结果。验证队列包括来自多个中心的患者在初始治疗时获得的 5,692 项观察结果。基于训练队列每次治疗时记录的 25 个临床因素构建了 AI 计算系统 (PRAID)，然后评估两个队列的 1 年和 3 年生存率的预测预后值。结果 排除缺乏日本肝癌研究组第 6 版（TNM-LCSGJ 6 版）白蛋白-胆红素（ALBI）分级或肿瘤淋巴结转移分期临床数据的患者后，ALBI-TNM-LCSGJ 6 版（ALBI- T) 和改良的 ALBI-T 评分证实两个队列中患者的预后相似。验证队列中 1 年和 3 年生存率预测的曲线下面积分别为 0.841（敏感性 0.933 [95% CI：0.925-0.940]，特异性 0.517 [95% CI：0.484-0.549]）和 0.796（敏感性分别为 0.806 [95% CI: 0.790-0.821]，特异性为 0.646 [95% CI: 0.624-0.668]）。结论 目前的 PRAID 系统可能会提供与短期和中期生存相关的有用的预后信息，以便为初始和复发性 HCC 病例制定最佳治疗方式的决策。