实用器官移植电子杂志 ›› 2019, Vol. 7 ›› Issue (1): 35-39.DOI: 10.3969/j.issn.2095-5332.2019.01.010

• 论著 • 上一篇    下一篇

基于纤维蛋白原浓度的肝癌肝移植复发预测模型

曾凯宁,汪国营,杨卿,姚嘉,李洋,张剑文,张英才,李华,易述红,汪根树,张剑,杨扬,陈规划
  

  1. 广东省器官移植研究中心,中山大学器官移植研究所,中山大学附属第 三医院肝脏移植中心,广东 广州 510630
  • 出版日期:2019-01-20 发布日期:2021-06-23
  • 基金资助:

    国家“十三五”科技重大专项(2017ZX10203205-006-001);

    广东省科技计划项目(2014B020228003); 

    广东省自然科学基金(2015A030312013);

    广州市科技计划项目(2014Y2-00200,2014Y2-00544,201508020262);

    广东 省医学科学技术研究基金项目(A2017370)

A scoring model for prediction of hepatocellular carcinoma recurrence after liver transplantation based on fibrinogen concentration

Zeng Kaining, Wang Guoying, Yang Qing, Yao Jia, Li Yang, Zhang Jianwen, Zhang Yingcai, Li Hua, Yi Shuhong, Wang Genshu, Zhang Jian, Yang Yang, Chen Guihua. 
  

  1. Organ Transplantation Research Center of Guangdong Province ;Organ Transplantation Institute, Sun Yat-sen University, Department of Liver Transplantation ; the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630,Guangdong, China
  • Online:2019-01-20 Published:2021-06-23

摘要:

目的 探讨肝癌肝移植术后复发的危险因素,建立多因素的肝癌肝移植复发预测模型,为评 估肝癌肝移植患者预后和筛选合适的肝癌肝移植患者提供依据。方法 回顾性分析中山大学附属第三医院 173 例行肝移植术的肝细胞癌患者的临床资料及随访资料,通过单因素分析和多因素 Cox 回归分析筛选肝癌肝移植术后复发的独立危险因素,将筛选出的危险因素通过 Logistic 回归建立回归模型。结果 经单因素分析和多因素Cox回归分析,发现术前纤维蛋白原浓度、血管受侵、肿瘤总体积> 115 cm3 以及甲胎蛋白(alpha fetoprotein,AFP)> 400 ng/ml 是肝癌肝移植术后复发的独立危险因素。通过Logistic回归建立复发预测模型:Y = -3.047+0.699× 纤维蛋白原 +1.568× 肿瘤总体积> 115 cm3 (0 =否,1 =是)+0.317× 血管受侵(0 =无,1 =有) +1.6×AFP > 400 ng/ml(0 =否,1 =是)。研究建立的模型对肝癌肝移植术后复发的预测有较高的敏感度(86.6%)、特异性(65.8%),受试者工作特征(receiver operating characteristic,ROC)曲线下面积为 0.800,高于米兰标准(0.687)、杭州标准(0.703)。符合 Y ≤ -0.79 的患者 5 年无复发生存率(recurrence free survival,RFS)显著高于 Y > -0.79 的患者(92.3% 比 34.1%,P < 0.001)。符合米兰标准、杭州标准的患者中,Y ≤ -0.79 和 Y > -0.79 的患者 5 年 RFS 仍存在显著差异(94.9% 比 40.9%,P < 0.001 ;93.6% 比 45.7%,P < 0.001)。结论 术前纤维蛋白原、血管受侵、肿瘤总体积> 115 cm3 以及 AFP > 400 ng/ml是肝癌肝移植术后复发的独立危险因素。研究建立的基于纤维蛋白原浓度的预测模型对肝癌肝移植术后复发的预测有较高的敏感度及特异性,能够将可能受益的患者筛选出来。

关键词: 肝癌 , 肝移植 , 复发 , 预测模型

Abstract:

Objective To analyse the risk factors of hepatocellular carcinoma(HCC)recurrence after liver transplantation and to build a logistic regression model to predict HCC recurrence which helps patient's selection. Methods A total number of 173 patients diagnosed with HCC and received liver transplantation were enrolled in the research. Univariate and multivariate Cox analysis were used to explore the risk factors of HCC recurrence after liver transplantation, logistic regression was used to build a scoring model. Results Univariate andmultivariate Cox regression analysis showed that plasma fibrinogen concentration, macrovascular invasion, total tumorvolume > 115 cm3 and alpha fetoprotein(AFP)> 400 ng/ml were independent risk factors of HCC recurrence afterliver transplantation. The logistic regression model was, Y = logit(P)= -3.047 + 0.699 × fibrinogen concentration + 1.568× TTV > 115 cm3 (0 = no,1 = yes) + 0.317×macrovascular invasion (0 = no,1 = yes) + 1.6× AFP > 400 ng/ml(0 = no,1 = yes). The sensitivity and specificity in predicting HCC recurrence were 86.6% and 65.8%. The area under receiver operating characteristic (ROC) curve was 0.800, compared with 0.687 of Milan criteria and 0.703 of Hangzhou criteria. The 5-year RFS of patients with model score Y ≤ -0.79 was significantly higher thanpatients with Y > -0.79(92.3% vs. 34.1%,P < 0.001). Within patients who meet Milan and Hangzhou criteria,the 5-year RFS of patients with Y ≤ -0.79 was also significantly higher than patients with Y > -0.79(94.9% vs. 40.9%,P < 0.001;93.6% vs. 45.7%,P < 0.001,respectively). ConclusionPlasma fibrinogen concentration,macrovascular invasion, total tumor volume > 115 cm3 and AFP> 400ng/ml were independent risk factors of HCC recurrence after liver transplantation. The logistic regression models we built was sensitive and specific in predicting HCC recurrence after liver transplantation.

Key words: Hepatocellular carcinoma, Liver transplantation, Recurrence, Model