Department of Medicine, Division of Digestive Health and Liver Diseases, University of Miami Miller School of Medicine, Miami, Florida, USA.
Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, Florida, USA.
Hepatol Commun. 2024 Nov 4;8(11). doi: 10.1097/HC9.0000000000000581. eCollection 2024 Nov 1.
Prognosticating survival among patients with HCC and cirrhosis must account for both the tumor burden/stage, as well as the severity of the underlying liver disease. Although there are many staging systems used to guide therapy, they have not been widely adopted to predict patient-level survival after the diagnosis of HCC. We sought to develop a score to predict long-term survival among patients with early- to intermediate-stage HCC using purely objective criteria.
Retrospective cohort study among patients with HCC confined to the liver, without major medical comorbidities within the Veterans Health Administration from 2014 to 2023. Tumor data were manually abstracted and combined with clinical and laboratory data to predict 5-year survival from HCC diagnosis using accelerated failure time models. The data were randomly split using a 75:25 ratio for training and validation. Model discrimination and calibration were assessed and compared to other HCC staging systems.
The cohort included 1325 patients with confirmed HCC. A risk score using baseline clinical, laboratory, and HCC-related survival had excellent discrimination (integrated AUC: 0.71 in the validation set) and calibration (based on calibration plots and Brier scores). Models had superior performance to the BCLC and ALBI scores and similar performance to the combined BCLC-ALBI score.
We developed a risk score using purely objective data to accurately predict long-term survival for patients with HCC. This score, if validated, can be used to prognosticate survival for patients with HCC, and, in the setting of liver transplantation, can be incorporated to consider the net survival benefit of liver transplantation versus other curative options.
预测 HCC 和肝硬化患者的生存情况必须考虑肿瘤负担/分期，以及潜在肝脏疾病的严重程度。虽然有许多分期系统用于指导治疗，但它们尚未广泛用于预测 HCC 诊断后患者的生存情况。我们旨在开发一种评分系统，使用纯粹的客观标准来预测早期至中期 HCC 患者的长期生存情况。
这是一项回顾性队列研究，纳入了 2014 年至 2023 年期间在退伍军人健康管理局内患有局限于肝脏的 HCC 且无重大合并症的患者。通过加速失效时间模型，使用手动提取的肿瘤数据并结合临床和实验室数据来预测 HCC 诊断后 5 年的生存情况。数据随机分为 75:25 的训练和验证比例。评估和比较了模型的区分度和校准度，并与其他 HCC 分期系统进行比较。
该队列纳入了 1325 例确诊 HCC 的患者。使用基线临床、实验室和 HCC 相关生存的风险评分具有出色的区分度（验证集中的综合 AUC：0.71）和校准度（基于校准图和 Brier 评分）。这些模型的性能优于 BCLC 和 ALBI 评分，与联合 BCLC-ALBI 评分的性能相当。
我们使用纯粹的客观数据开发了一种风险评分系统，可准确预测 HCC 患者的长期生存情况。如果经过验证，该评分可用于预测 HCC 患者的生存情况，并且在肝移植的背景下，可以纳入考虑肝移植与其他根治性选择相比的净生存获益。
