摘要
目的建立基于血清标志物联合检测的肝细胞癌(HCC)患病风险预测模型C-GALADⅡ,并对其预测价值进行分析。方法回顾性分析了8家医院及体检机构2018年4月至2020年10月收集的229例肝癌患者、2317例慢性肝病患者和982名健康人的临床资料,包括年龄、性别和血清检测信息等。队列按照6∶4分层随机抽样划分为训练集和测试集,在训练集上通过Logistic逐步向后回归建立预测模型,并在测试集上对模型效果进行验证。另收集了首都医科大学附属北京佑安医院的2021年3—7月临床数据,包括84例肝癌患者和204例慢性肝病用于模型的外部独立验证。采用受试者工作特征(ROC)的曲线下面积(AUC)、敏感度和特异度评估模型的效能。结果通过Logistic逐步向后回归,年龄、性别、甲胎蛋白(AFP)、甲胎蛋白异质体比率(AFP-L3%)、异常凝血酶原、血小板和总胆红素作为肝癌患病风险的预测指标进入模型,在测试集上验证模型所得ROC曲线下面积(AUC)为0.954,敏感度为88.04%,特异度为94.85%,在外部独立验证集的AUC为0.943,敏感度为89.29%,特异度为90.2%,性能优于其他已发表模型。结论C-GALADⅡ模型能够准确预测个体罹患肝癌的风险,为肝癌的血清学诊断提供参考依据。
Objective To establish a model C-GALAD for detecting hepatocellular carcinoma(HCC)from the chronic liver disease and healthy people based on the serum markers.Methods A clinical cohort including 229 hepatocellular carcinoma patients,2317 patients with chronic liver disease and 982 healthy people,was retrospectively collected from eight hospitals or physical examination institutions from April 2018 to October 2020.The data were divided into a training set and a testing set by stratified sampling with a 6∶4 ratio.A predictive model was established on the training set using a logistic backward regression method and validated on the testing set.In addition,clinical data from March to July 2021 in Beijing You′an Hospital affiliated to Capital Medical University,including 84 patients with liver cancer and 204 patients with chronic liver disease collected were used for external independent validation of the model.The receiver operating characteristic curve(ROC)area under curve(AUC),the sensitivity and the specificity were used to evaluate the effectiveness of the model.Results Through the logistic backward regression method,the seven signatures including age,gender,alpha-fetoprotein(AFP),alpha-fetoprotein alloplasm-3 ratio(AFP-L3%),des-gamma-carboxyprothrombin(DCP),platelet(PLT)and total bilirubin(TBIL)were selected as risk factors in the detection model.The area under the ROC curve(AUC)of the model on the testing set was 0.954,with an 88.04%sensitivity and a 94.85%specificity,and the AUC of model on the external independent validation set was 0.943,with an 89.29%sensitivity and a 90.2%specificity,which were better than other published models.Conclusion The C-GALADⅡmodel can accurately predict the risk of hepatocellular carcinoma occurrence,and thus provide a trustworthy diagnosis method of hepatocellular carcinoma.
作者
李鸿江
刘绍辉
易永祥
杜利军
刘相辰
宋虹
梁丽华
王炜
夏国栋
贾天野
刘爱霞
李艳召
许立达
李伯安
Li Hongjiang;Liu Shaohui;Yi Yongxiang;Du Lijun;Liu Xiangchen;Song Hong;Liang Lihua;Wang Wei;Xia Guodong;Jia Tianye;Liu Aixia;Li Yanzhao;Xu Lida;Li Boan(College of Life Science and Technology,Beijing University of Chemical Technology,Beijing 100029,China;Health Management Center,Xiangya Hospital,Central South University,Changsha 410008,China;Department of Laboratory Medicine,the Second Hospital of Nanjing,Nanjing 210003,China;Department of Laboratory Medicine,Huadu District People′s Hospital,Southern Medical University,Guangzhou 510800,China;Health Management Center,Shenzhen Hospital of Southern Medical University,Shenzhen 518000,China;Health Management Center,Liaoning Electric Power Central Hospital,Shenyang 110847,China;Health Management Center,Zhuzhou Central Hospital,Zhuzhou 412000,China;Health Management Center,the Affiliated Hospital of Southwest Medical University,Luzhou 646000,China;Department of Laboratory Medicine,the Fifth Medical Center of Chinese PLA General Hospital,Beijing 100039,China;Beijing Hotgen Biotech Co.,Ltd.,Beijing 102600,China)
出处
《中华检验医学杂志》
CAS
CSCD
北大核心
2022年第11期1170-1176,共7页
Chinese Journal of Laboratory Medicine
基金
国家科技重大专项(2017ZX10302201)。
关键词
癌
肝细胞
血液
诊断
Carcinoma
Hepatocellular
Blood
Diagnosis
