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中华肝脏外科手术学电子杂志 ›› 2022, Vol. 11 ›› Issue (06) : 615 -618. doi: 10.3877/cma.j.issn.2095-3232.2022.06.016

临床研究

血清学多参数Logistic回归模型对肝细胞癌的诊断价值
陈家豪1, 邝小红2, 廖媛1, 刘志欢1, 陈忠城1, 周文营1,()   
  1. 1. 510630 广州,中山大学附属第三医院检验科
    2. 510630 广州,中山大学附属第三医院超声科
  • 收稿日期:2022-08-05 出版日期:2022-12-10
  • 通信作者: 周文营
  • 基金资助:
    国家自然科学基金(81802403)

Diagnostic value of serological parameters-based Logistic regression model for hepatocellular carcinoma

Jiahao Chen1, Xiaohong Kuang2, Yuan Liao1, Zhihuan Liu1, Zhongcheng Chen1, Wenying Zhou1,()   

  1. 1. Clinical Laboratory, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China
    2. Department of Ultrasound, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China
  • Received:2022-08-05 Published:2022-12-10
  • Corresponding author: Wenying Zhou
引用本文:

陈家豪, 邝小红, 廖媛, 刘志欢, 陈忠城, 周文营. 血清学多参数Logistic回归模型对肝细胞癌的诊断价值[J/OL]. 中华肝脏外科手术学电子杂志, 2022, 11(06): 615-618.

Jiahao Chen, Xiaohong Kuang, Yuan Liao, Zhihuan Liu, Zhongcheng Chen, Wenying Zhou. Diagnostic value of serological parameters-based Logistic regression model for hepatocellular carcinoma[J/OL]. Chinese Journal of Hepatic Surgery(Electronic Edition), 2022, 11(06): 615-618.

目的

基于血清学参数构建肝细胞癌(肝癌)诊断的Logistic回归模型,并探讨其应用价值。

方法

本研究对象为2017年1月至2019年12月首次在中山大学附属第三医院就诊的473例肝病患者,其中肝癌231例,乙肝肝硬化113例,慢性乙型病毒性肝炎患者129例。选取同期111例健康体检者作为正常对照组。所有研究对象均签署知情同意书,符合医学伦理学规定。采用Logistic回归分析构建肝癌诊断模型,绘制ROC曲线对模型的效能进行分析。

结果

多因素Logistic回归分析显示,年龄、性别、AST、总胆汁酸(TBA)、AFP与肝癌发生明显相关(HR=1.07,0.14,0.99,0.99,1.01;P<0.05)。Logistic回归模型公式:Logit(P)=-1.004+0.065×年龄-1.971×性别(男性=1,女性=2)+0.006×AFP-0.014×AST-0.008×TBA。基于年龄、性别、AST、TBA、AFP的多参数Logistic回归模型ROC曲线的曲线下面积(AUC)、敏感度及阴性预测值最高,分别为0.878、0.719、0.820。该模型诊断肝癌的AUC明显大于AFP单独诊断的0.762(Z=5.363,P<0.05)。

结论

基于年龄、性别、AST、TBA、AFP的多参数Logistic回归模型有助于提高肝癌的诊断效能。

Objective

To establish a Logistic regression model based on serological parameters for the diagnosis of hepatocellular carcinoma (HCC) and to evaluate its application value.

Methods

A total of 473 patients with liver diseases who were admitted to the Third Affiliated Hospital of Sun Yat-sen University for the first time from January 2017 to December 2019 were recruited, including 231 cases of HCC, 113 cases of hepatitis B cirrhosis and 129 chronic hepatitis B. 111 healthy subjects in the same period were assigned into the control group. The informed consents of all patients were obtained and the local ethical committee approval was received. The diagnostic model for HCC was established by Logistic regression analysis. The efficiency of this model was evaluated by the receiver operating characteristic (ROC) curve.

Results

Multivariate Logistic regression analysis showed that age, sex, AST, total bile acid (TBA) and AFP were significantly correlated with the incidence of HCC (HR=1.07, 0.14, 0.99, 0.99, 1.01; P<0.05). The formula of Logistic regression model: Logit(P)=-1.004+0.065×age-1.971×sex (male=1, female=2)+0.006×AFP-0.014×AST-0.008×TBA. The area under the ROC curve (AUC), sensitivity and negative predictive value of ROC curve of multivariate Logistic regression model based on age, sex, AST, TBA and AFP were the highest up to 0.878, 0.719 and 0.820, respectively. The AUC of this model in diagnosing HCC was significantly higher than 0.762 of the AFP-based model (Z=5.363, P<0.05).

Conclusions

Multivariate Logistic regression model based on age, sex, AST, TBA and AFP contributes to enhancing the diagnostic efficiency of HCC.

表1 肝癌组、肝硬化组、慢乙肝组及正常对照组基本临床特征
表2 肝癌发生影响因素的Logistic回归分析
图1 AFP与不同Logistic回归模型诊断肝癌的ROC曲线注:TBA为总胆汁酸
表3 AFP单指标与不同Logistic回归模型对肝癌诊断价值的比较
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