Department of Surgery, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH.
Department of Surgery, University of Verona, Verona, Italy.
Ann Surg. 2024 Mar 1;279(3):471-478. doi: 10.1097/SLA.0000000000006056. Epub 2023 Jul 31.
We sought to develop and validate a preoperative model to predict survival after recurrence (SAR) in hepatocellular carcinoma (HCC).
Although HCC is characterized by recurrence as high as 60%, models to predict outcomes after recurrence remain relatively unexplored.
Patients who developed recurrent HCC between 2000 and 2020 were identified from an international multi-institutional database. Clinicopathologic data on primary disease and laboratory and radiologic imaging data on recurrent disease were collected. Multivariable Cox regression analysis and internal bootstrap validation (5000 repetitions) were used to develop and validate the SARScore. Optimal Survival Tree analysis was used to characterize SAR among patients treated with various treatment modalities.
Among 497 patients who developed recurrent HCC, median SAR was 41.2 months (95% CI 38.1-52.0). The presence of cirrhosis, number of primary tumors, primary macrovascular invasion, primary R1 resection margin, AFP>400 ng/mL on the diagnosis of recurrent disease, radiologic extrahepatic recurrence, radiologic size and number of recurrent lesions, radiologic recurrent bilobar disease, and early recurrence (≤24 months) were included in the model. The SARScore successfully stratified 1-, 3- and 5-year SAR and demonstrated strong discriminatory ability (3-year AUC: 0.75, 95% CI 0.70-0.79). While a subset of patients benefitted from resection/ablation, Optimal Survival Tree analysis revealed that patients with high SARScore disease had the worst outcomes (5-year AUC; training: 0.79 vs. testing: 0.71). The SARScore model was made available online for ease of use and clinical applicability ( https://yutaka-endo.shinyapps.io/SARScore/ ).
The SARScore demonstrated strong discriminatory ability and may be a clinically useful tool to help stratify risk and guide treatment for patients with recurrent HCC.
我们旨在开发和验证一种预测肝细胞癌（HCC）复发后生存（SAR）的术前模型。
尽管 HCC 的复发率高达 60%，但预测复发后结局的模型仍相对较少。
从一个国际多机构数据库中确定了在 2000 年至 2020 年间发生复发性 HCC 的患者。收集了原发性疾病的临床病理数据以及复发性疾病的实验室和放射影像学数据。采用多变量 Cox 回归分析和内部自举验证（5000 次重复）来开发和验证 SARScore。最优生存树分析用于描述接受各种治疗方式的患者的 SAR 特征。
在 497 例发生复发性 HCC 的患者中，SAR 的中位时间为 41.2 个月（95%CI 38.1-52.0）。存在肝硬化、肿瘤数量、原发性大血管侵犯、原发性 R1 切除边缘、复发性疾病诊断时 AFP>400ng/ml、影像学肝外复发、影像学肿瘤大小和数量、影像学复发性双侧疾病和早期复发（≤24 个月）被纳入模型。SARScore 成功地对 1、3 和 5 年 SAR 进行了分层，且具有很强的区分能力（3 年 AUC：0.75，95%CI 0.70-0.79）。虽然一部分患者受益于切除/消融治疗，但最优生存树分析显示，SARScore 高的患者结局最差（5 年 AUC；训练：0.79 vs. 测试：0.71）。SARScore 模型已在网上提供，以方便使用和临床适用性（https://yutaka-endo.shinyapps.io/SARScore/）。
SARScore 具有很强的区分能力，可能是一种有用的临床工具，有助于对复发性 HCC 患者进行风险分层并指导治疗。
