目的·基于术前CT影像联合临床指标构建预测模型，评估其在肝细胞癌（hepatocellular carcinoma，HCC）患者肝移植术后复发风险与生存状况预测中的应用价值，旨在识别超出米兰标准但肝移植术后仍可获得理想预后的患者，进而为优化肝移植受者的选择策略提供新的循证依据。方法·纳入2015年1月—2025年1月在上海交通大学医学院附属第一人民医院接受首次原位肝移植的HCC患者，收集其实验室检查报告、病理结果、CT影像等临床资料。随访时间定义为自肝移植手术日起，至患者死亡或研究截止日期（2025年1月31日）止。采用米兰标准评估纳入研究的患者，统计符合与超出米兰标准的患者的分布情况。通过单因素及多因素Cox分析，筛选影响HCC患者肝移植术后肿瘤复发和总体生存的独立危险因素，构建复发风险和生存预后的预测模型。依据多因素Cox回归结果中各变量的回归系数（β）进行等比例赋分。根据约登指数最大化原则确定风险评分的最佳截断值，将患者分为低危组和高危组，评估2组患者的无复发生存率及累积生存率差异。将模型风险评分与UCSF（University of California，San Francisco）标准交叉分层，分析不同分层组间无复发生存率与累积生存率的差异。结果·研究共纳入95例HCC患者，其中64例超出米兰标准，44例术后肿瘤复发。根据多因素Cox回归分析结果，选择术前甲胎蛋白（α-fetoprotein，AFP）>400 ng/mL、肿瘤数量>3个、肿瘤最大直径>3 cm、肝脾最大长径比（liver-to-spleen length ratio，LSLR）>1.43（均P<0.05），建立无复发预测模型；选择术前AFP>400 ng/mL、肿瘤数量>3个、肿瘤最大直径>3 cm、肝脾密度比（liver-spleen density ratio，LSR）>1.2（均P<0.05），建立生存预测模型。根据模型将患者分为低危组和高危组。无复发预测模型的低危组患者术后1年、3年、5年无复发生存率（86.2% vs 22.7%，78.0% vs 6.5%，78.0% vs 3.2%；χ²=63.642，P<0.001）和累积生存率（87.8% vs 74.2%，82.8% vs 51.2%，79.0% vs 25.6%；χ²=14.878，P<0.001）均显著高于高危组患者，生存预测模型的低危组患者术后1年、3年、5年无复发生存率（82.5% vs 19.8%，68.7% vs 4.9%，68.7% vs 4.9%；χ²=55.999，P<0.001）和累积生存率（90.8% vs 67.2%，83.9% vs 42.2%，80.4% vs 14.1%；χ²=27.590，P<0.001）亦显著高于高危组患者。在无复发预测模型和生存预测模型中，低危符合UCSF标准组与低危超出UCSF标准组患者的无复发生存率及累积生存率差异无统计学意义。结论·构建的复发与生存预测模型可有效评估HCC患者肝移植术后的复发风险与生存状况，可为筛选超出米兰标准且肝移植术后预后良好的患者提供新的依据，有利于优化肝移植受者选择策略。

Objective ·Based on preoperative CT imaging combined with clinical indicators, predictive models were constructed to evaluate its application value in the recurrence risk and survival status of patients with hepatocellular carcinoma (HCC) after liver transplantation. The aim was to identify patients who exceeded the Milan criteria but could still obtain an ideal prognosis after liver transplantation, and to provide a new evidence-based basis for optimizing the selection strategy of liver transplant recipients. Methods ·Patients with HCC who underwent first orthotopic liver transplantation at Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, from January 2015 to January 2025 were included. The clinical data, including laboratory examinations, pathological results, and CT imaging were collected. The follow-up period was defined as the time from the date of liver transplantation to patient death or the study endpoint (January 31, 2025). The patients included in the study were evaluated using the Milan criteria, and the distribution of patients who met and exceeded the Milan criteria was analyzed. Through univariate and multivariate Cox analyses, independent risk factors affecting tumor recurrence and overall survival after liver transplantation in patients with HCC were screened, and predictive models for recurrence risk and survival prognosis were constructed. According to the regression coefficient (β) of each variable in the multivariate Cox regression results, proportional scores were assigned. According to the principle of maximizing the Youden index, the optimal cut-off value of the risk score was determined. The patients were divided into low-risk and high-risk groups, and the differences in recurrence-free survival and cumulative survival between the two groups were evaluated. The model risk scores were cross-stratified with the UCSF (University of California, San Francisco) standard to analyze the differences between the recurrence-free survival and cumulative survival among different stratified groups. Results ·A total of 95 patients with HCC were included in the study, among whom 64 exceeded the Milan criteria and 44 had postoperative tumor recurrence. According to the results of multivariate Cox regression analysis, preoperative AFP>400 ng/mL, tumor number>3, maximum tumor diameter>3 cm, and liver-spleen maximum length ratio (LSLR)>1.43 were included to establish the recurrence-free prediction model (P<0.05). Additionally, preoperative AFP>400 ng/mL, tumor number>3, maximum tumor diameter>3 cm, and liver-to-spleen density ratio (LSR)>1.2 were included to establish the survival prediction model (P<0.05). According to the models, the patients were subsequently stratified into low-risk and high-risk groups. In the recurrence-free prediction model, the 1-year, 3-year, and 5-year recurrence-free survival rates (86.2% vs 22.7%, 78.0% vs 6.5%, 78.0% vs 3.2%; χ²=63.642, P<0.001) and cumulative survival rates (87.8% vs 74.2%, 82.8% vs 51.2%, 79.0% vs 25.6%; χ²=14.878, P<0.001) in the low-risk group were significantly higher than those in the high-risk group. In the survival prediction model, the 1-year, 3-year, and 5-year recurrence-free survival rates (82.5% vs 19.8%, 68.7% vs 4.9%, 68.7% vs 4.9%; χ²=55.999, P<0.001) and cumulative survival rates (90.8% vs 67.2%, 83.9% vs 42.2%, 80.4% vs 14.1%; χ²=27.590, P<0.001) in the low-risk group were also significantly higher than those in the high-risk group. In the recurrence-free prediction model and survival prediction model, there were no significant differences in the recurrence-free survival and cumulative survival between the low-risk group within the UCSF criteria and the low-risk group beyond the UCSF criteria. Conclusion ·The recurrence and survival prediction models constructed in this study can effectively evaluate the recurrence risk and survival status of HCC patients after liver transplantation, and can provide a new basis for screening patients who exceed the Milan criteria but still achieve favorable prognosis after liver transplantation, thereby contributing to the optimization of liver transplant recipient selection strategies.