Background:Hepatocellular carcinoma (HCC) patients have a poor prognosis after radio-frequency ablation (RFA), and investigating the risk factors affecting RFA and establishing predictive models are important for improving the prognosis of HCC patients.Methods:Patients with HCC undergoing RFA in Shenzhen People’s Hospital between January 2011 and December 2021 were included in this study. Using the screened independent influences on recurrence and survival, predictive models were constructed and validated, and the predictive models were then used to classify patients into different risk categories and assess the prognosis of different categories.Results:Cox regression model indicated that cirrhosis (hazard ratio [HR] = 1.65), alpha-fetoprotein (AFP) ⩾400 ng/mL (HR = 2.03), tumor number (multiple) (HR = 2.11), tumor diameter ⩾20 mm (HR = 2.30), and platelets (PLT) ⩾ 244 (109/L) (HR = 2.37) were independent influences for recurrence of patients after RFA. On the contrary, AFP ⩾400 ng/mL (HR = 2.48), tumor number (multiple) (HR = 2.52), tumor diameter ⩾20 mm (HR = 2.25), PLT ⩾244 (109/L) (HR = 2.36), and hemoglobin (HGB) ⩾120 (g/L) (HR = 0.34) were regarded as independent influences for survival. The concordance index (C-index) of the nomograms for predicting disease-free survival (DFS) and overall survival (OS) was 0.727 (95% confidence interval [CI] = 0.770-0.684) and 0.770 (95% CI = 0.821-7.190), respectively. The prognostic performance of the nomograms was significantly better than other staging systems by analysis of the time-dependent C-index and decision curves. Each patient was scored using nomograms and influencing factors, and patients were categorized into low-, intermediate-, and high-risk groups based on their scores. In the Kaplan-Meier survival curve, DFS and OS were significantly better in the low-risk group than in the intermediate- and high-risk groups.Conclusions:The 2 prediction models created in this work can effectively predict the recurrence and survival rates of HCC patients following RFA.

中文翻译：

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预测接受射频消融的肝细胞癌患者复发和生存的风险模型

背景：肝细胞癌（HCC）患者射频消融（RFA）后预后较差，研究影响RFA的危险因素并建立预测模型对于改善HCC患者的预后具有重要意义。本研究纳入2011年1月至2021年12月期间深圳市人民医院。利用筛选出的对复发和生存的独立影响因素，构建预测模型并进行验证，然后利用预测模型将患者分为不同风险类别并评估不同类别的预后。结果：Cox回归模型表明肝硬化（风险比） [HR] = 1.65)、甲胎蛋白 (AFP) ⩾400 ng/mL (HR = 2.03)、肿瘤数量（多个）(HR = 2.11)、肿瘤直径 ⩾20 mm (HR = 2.30) 和血小板 (PLT) ) ⩾ 244 (109/L) (HR = 2.37) 是 RFA 后患者复发的独立影响因素。相反，AFP⩾400ng/mL（HR=2.48），肿瘤数量（多个）（HR=2.52），肿瘤直径⩾20mm（HR=2.25），PLT⩾244（109/L) (HR = 2.36) 和血红蛋白 (HGB) ⩾120 (g/L) (HR = 0.34) 被视为生存的独立影响因素。用于预测无病生存 (DFS) 和总生存 (OS) 的列线图的一致性指数 (C 指数) 为 0.727（95% 置信区间 [CI] = 0.770-0.684）和 0.770（95% CI = 0.821- 7.190），分别。通过对时间依赖性 C 指数和决策曲线的分析，列线图的预后性能明显优于其他分期系统。使用列线图和影响因素对每位患者进行评分，并根据评分将患者分为低、中、高风险组。在Kaplan-Meier生存曲线中，低危组的DFS和OS均显着优于中危组和高危组。结论：本工作创建的2个预测模型可以有效预测肿瘤的复发率和生存率。 RFA 后的 HCC 患者。