| 摘要: |
| 目的 建立并验证基于up-to-seven（Up7）标准肝细胞癌（HCC）肝移植术后患者的长期生存Cox回归预测模型，以辅助制定临床决策。方法 回顾性分析251例符合Up7标准的HCC肝移植术后患者的临床和随访资料。采用逐步回归向前法进行多因素Cox回归分析，获得HCC肝移植术后患者长期生存的独立预测因素，并建立长期生存Cox回归预测模型。使用R 3.4.3软件获得预测模型评分，采用生存决策树方式确定模型的截断值。绘制预测模型在其他肝移植标准[上海复旦标准、加利福尼亚大学旧金山分校（UCSF）标准、意大利米兰（Milan）标准]下HCC肝移植术后患者的Kaplan-Meier生存曲线，并采用log-rank检验分析组间差异。采用受试者工作特征（ROC）曲线检验预测模型的预测效能。结果 多因素Cox回归分析显示，甲胎蛋白（AFP）、总胆红素（T-Bil）、微血管侵犯（MVI）、肿瘤最大径（Diameter）是HCC肝移植术后患者长期生存的独立预测因素，据此建立的长期生存Cox回归预测模型命名为ATMD（AFP，T-Bil，MVI，Diameter）模型：h（t，x）=h0（t）exp[0.284×肿瘤最大径（cm）+0.773×MVI（是=1；否=0）+0.404×lg AFP（ng/mL）+0.003×T-Bil（μmol/L）]，根据判别生存树设定ATMD模型截断值为1.44，评分>1.44为高危组，≤1.44为低危组。符合Up7标准的高危组和低危组患者分别为87例和164例，符合上海复旦标准的分别为33例和144例，符合UCSF标准的分别为29例和134例，符合Milan标准的分别为29例和131例。Kaplan-Meier生存曲线分析显示，在Up7标准、上海复旦标准、UCSF标准和Milan标准下ATMD模型高危组和低危组患者累积生存率差异均有统计学意义（P<0.001，P=0.008，P<0.001，P=0.001），ATMD模型预测的HCC肝移植术后3年生存的ROC曲线下面积分别是76.63%、75.87%、73.32%和69.41%。结论 ATMD模型对于符合Up7标准、上海复旦标准、UCSF标准和Milan标准的HCC肝移植术后生存情况有良好的预测能力，对符合以上标准的HCC肝移植患者的术前决策和术后风险评估有重要意义。 |
| 关键词: ATMD模型 肝肿瘤 肝细胞癌 肝移植 长期生存 预后 |
| DOI：10.16781/j.0258-879x.2018.07.0745 |
| 投稿时间：2018-01-21修订日期：2018-04-24 |
| 基金项目:国家自然科学基金（81671576），上海市卫生和计划生育委员会项目（201640274）. |
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| Modeling and validation of a survival prediction model for hepatocellular carcinoma patients after liver transplantation based on up-to-seven criteria |
| DONG Jun-feng,TENG Fei,LI Pei-lei,SUN Ke-yan,FU Hong,GUO Wen-yuan,DING Guo-shan* |
(Department of Organ Transplantation, Changzheng Hospital, Navy Medical University(Second Military Medical University), Shanghai 200003, China
*Corresponding author) |
| Abstract: |
| Objective To establish a long-term survival prediction model for hepatocellular carcinoma (HCC) patients after liver transplantation based on up-to-seven (Up7) criteria, and to validate the prediction model in different liver transplantation criteria, so as to assist clinical decision-making for the treatment of HCC. Methods We retrospectively analyzed the clinical and follow-up data of 251 HCC patients who underwent liver transplantation with Up7 criteria. Stepwise regression method was used to conduct multivariate Cox regression analysis to obtain the independent predictors of long-term survival after HCC liver transplantation, and to establish the survival Cox regression prediction model. R 3.4.3 software was used to score the prediction model, and the decision tree technique was used to determine the cut-off value. The Kaplan-Meier survival curve of the HCC patients after liver transplantation was drawn to validate the prediction model in different criteria (Shanghai Fudan criteria, University of California, San Francisco[UCSF] criteria and Italy Milan criteria), and the difference between groups was analyzed by log-rank test. The receiver operating characteristic (ROC) curve was used to test the predictive effectiveness of the model. Results Multivariate Cox regression analysis suggested that α-fetoprotein (AFP), total bilirubin (T-Bil), microvascular invasion (MVI) and tumor maximal diameter (Diameter) were the independent predictors of long-term survival of HCC liver transplant recipients after liver transplantion. We built the ATMD (AFP, T-Bil, MVI, Diameter) model using these factors:h (t, x)=h0 (t) exp (0.284×Diameter[cm]+0.773×MVI[yes=1; no=0]+0.404×lg AFP[ng/mL]+0.003×T-Bil[μmol/L]). The cut-off value of ATMD model was 1.44. The scores being more than 1.44 were defined as the high-risk group, and scores being 1.44 or less were defined as the low-risk group. The cases in the high-risk and low-risk groups who met the Up7 criteria, Shanghai Fudan criteria, UCSF criteria and Italy Milan criteria had 87 and 164, 33 and 144, 29 and 134, and 29 and 131, respectively. Kaplan-Meier survival analysis showed that the cumulative survival rates of the liver transplantation recipients with Up7 criteria, Shanghai Fudan criteria, UCSF criteria or Milan criteria were significantly different between the high- and low-risk groups (P<0.001, P=0.008, P<0.001, P=0.001). The areas under the ROC curve of the three-year survival of the liver transplantation recipients predicted by ATMD model were 76.63%, 75.87%, 73.32% and 69.41%, respectively. Conclusion The ATMD model has a good survival prediction ability for the HCC patients meeting Up7 criteria, Shanghai Fudan criteria, UCSF criteria or Milan criteria. It is of great significance for preoperative decision-making and postoperative risk assessment of HCC liver transplantation recipients meeting the above criteria. |
| Key words: ATMD model liver neoplasms hepatocellular carcinoma liver transplantation long-term survival prognosis |
