基于血清异常凝血酶原、甲胎蛋白构建预测肝细胞癌发病的列线图模型及模型评估  

Construction and validation of a nomogram for predicting the incidence of hepatocellular carcinoma based on serum abnormal prothrombin and alpha-fetoprotein

作　　者：于龙 王向坤 张旭东[1] 刘中原 郭玉祥 王茂森 韩庆芳 李仁锋[1] Yu Long;Wang Xiangkun;Zhang Xudong;Liu Zhongyuan;Guo Yuxiang;Wang Maosen;Han Qingfang;Li Renfeng(Department of Hepatobiliary and Pancreatic Surgery,the First Affiliated Hospital of Zhengzhou University,Zhengzhou 450052,China)

机构地区：[1]郑州大学第一附属医院肝胆胰外科,郑州450052

出　　处：《中华肝胆外科杂志》2025年第1期1-5,共5页Chinese Journal of Hepatobiliary Surgery

基　　金：国家自然科学基金(82302961);河南省医学科技攻关计划项目(LHGJ20220706)。

摘　　要：目的构建基于血清异常凝血酶原、甲胎蛋白的预测肝细胞癌发病的列线图模型并评估其预测效果。方法回顾分析2021年1月至2023年12月于郑州大学第一附属医院接受治疗的351例肝病患者资料,其中男性285例,女性66例,年龄(52.9±11.9)岁。351例患者中包括肝细胞癌229例(65.2%)、肝硬化87例(24.8%)、慢性乙型病毒性肝炎35例(10.0%)。不放回抽样以7∶3的比例随机将351例患者分为训练集(n=245)和测试集(n=106),训练集用于构建列线图,测试集用于评估模型,同时比较两数据集性别、年龄、疾病类型等指标。基于训练集,单因素和多因素logistic回归分析肝细胞癌发病的影响因素,并依据多因素结果构建预测肝细胞癌发病的列线图。受试者工作特征(ROC)曲线、校准曲线评估列线图预测效果,决策曲线分析评估模型临床适用性。结果训练集和测试集患者年龄、性别、疾病类型等指标比较,差异均无统计学意义(均P>0.05)。单因素logistic回归分析,年龄、异常凝血酶原对数值(LnPIVKA-Ⅱ)、甲胎蛋白对数值(LnAFP)、有糖尿病史与肝细胞癌发病相关(均P<0.05)。多因素logistic回归分析,年龄大(OR=1.07,95%CI:1.03~1.12)、LnPIVKA-Ⅱ高(OR=2.97,95%CI:1.97~4.46)、LnAFP高(OR=1.43,95%CI:1.11~1.84)及有糖尿病史(OR=5.17,95%CI:1.02~26.17)是肝细胞癌发病的危险因素(均P<0.05)。基于上述变量构建预测肝细胞癌发病列线图模型,ROC曲线分析列线图预测肝细胞癌发病的曲线下面积在训练集为0.920(95%CI:0.886~0.953),在测试集为0.934(95%CI:0.891~0.977)。校准曲线与理想曲线贴合较好,预测情况与实际情况基本一致。决策曲线分析显示,在多数阈值下(0.1~1.0)模型净获益均大于0。结论基于年龄、LnPIVKA-Ⅱ、LnAFP和糖尿病史构建的列线图,可以有效预测肝细胞癌发病风险且具有临床适用性。ObjectiveTo construct a nomogram model for predicting the incidence of hepatocellular carcinoma based on serum abnormal prothrombin and alpha-fetoprotein and evaluate the predictive effect.MethodsRetrospective analysis of data from 351 patients with liver disease who received treatment at the First Affiliated Hospital of Zhengzhou University from January 2021 to December 2023,including 285 males and 66 females,aged(52.9±11.9)years.Among the 351 patients,there were 229 cases(65.2%)of hepatocellular carcinoma,87 cases(24.8%)of liver cirrhosis,and 35 cases(10.0%)of chronic hepatitis B.All patients were randomly divided into a training set(n=245)and a testing set(n=106)in a 7∶3 ratio without replacement sampling.The training set was used to construct the model,and the testing set was used to evaluate the model.At the same time,gender,age,disease type,and other indicators were compared between the two sets.The risk factors of hepatocellular carcinoma were analyzed by univariate and multivariate logistic regression based on the training set,and a nomogram was constructed to predict the incidence of hepatocellular carcinoma based on the multivariate results.Receiver operating characteristic(ROC)curve and calibration curve were used to evaluate the predictive performance of nomogram,and decision curve analysis was used to evaluate the clinical applicability of the model.ResultsThere was no statistically significant difference in age,gender,disease type,etc.between the training and testing sets of patients(all P>0.05).Univariate logistic regression analysis showed that age,abnormal prothrombin logarithm(LnPIVKA-Ⅱ),alpha-fetoprotein logarithm(LnAFP),and diabetes were associated with hepatocellular carcinoma(all P<0.05).Multivariate logistic regression analysis showed that older age(OR=1.07,95%CI:1.03-1.12),higher LnPIVKA-Ⅱ(OR=2.97,95%CI:1.97-4.46),higher LnAFP(OR=1.43,95%CI:1.11-1.84)and diabetes(OR=5.17,95%CI:1.02-26.17)were risk factors for hepatocellular carcinoma(all P<0.05).Based on the above variables,a nomogr

关 键 词：癌 肝细胞 甲胎蛋白类 列线图 异常凝血酶原 

分 类 号：R73[医药卫生—肿瘤]