抗-HBs联合抗-HBe对HBsAg/HBeAg/抗-HBc阳性患者HBeAg血清学转换的预测价值  

Predictive value of anti-HBs+anti-HBe for seroconversion of HBeAg in patients with positive HBsAg/HBeAg/anti-HBc

作　　者：谭亚峰 孙凤兰 夏巍[1] 欧阳耀灵 李承彬[1] 陈珍霞 吴松[1] 余运运 江涛[1] TAN Yafeng;SUN Fenglan;XIA Wei;OUYANG Yaoling;LI Chengbin;CHEN Zhenxia;WU Song;YU Yunyun;JIANG Tao(Department of Clinical Laboratory,Jingzhou Hospital Affiliated to Yangtze University,Jingzhou,Hubei 434000,China;Department of Gynecology,Jingzhou Hospital Affiliated to Yangtze University,Jingzhou,Hubei 434000,China)

机构地区：[1]长江大学附属荆州医院医学检验部,湖北荆州434000 [2]长江大学附属荆州医院妇科,湖北荆州434000

出　　处：《临床肝胆病杂志》2023年第8期1832-1840,共9页Journal of Clinical Hepatology

基　　金：荆州市科技计划项目(2022HC68)。

摘　　要：目的建立HBsAg/HBeAg/抗-HBc阳性(以下简称“大三阳”)+抗-HBe阳性模式患者HBeAg血清学转换预测模型,并验证其预测价值。方法选取2018年4月1日—2022年8月1日于长江大学附属荆州医院行乙型肝炎血清标志物和HBV DNA定量检测的乙型肝炎患者6055例,根据不同乙型肝炎血清学指标模式分为5组:HBsAg阴性组、HBsAg/抗-HBe/抗-HBc阳性组、大三阳+抗-HBe阳性组、大三阳+抗-HBs阳性组和大三阳组。分析不同乙型肝炎血清学指标模式的特点及不同组别中HBeAg水平的差异。非正态分布的多组连续性变量组间比较采用Kruskal-Wallis H检验。计数资料组间比较采用χ^(2)检验。采用线性回归分析不同组别HBeAg水平差异。采用Logistic回归筛选独立影响因素,获得最优预测因子。通过受试者工作特征曲线(ROC曲线)验证预测效能。使用R Studio4.2.1建立预测模型并验证。结果与大三阳模式相比,大三阳+抗-HBe阳性、大三阳+抗-HBs阳性模式患者HBeAg水平均降低(P值均<0.01)。多因素Logistic回归分析显示,抗-HBe是HBeAg血清学转换的独立影响因素(P=0.014)。Lasso回归分析筛选结果显示,大三阳+抗-HBe阳性患者发生HBeAg血清学转换的最优预测因子为抗-HBe+抗-HBs。ROC曲线结果显示,抗-HBe+抗-HBs的AUC为0.733(95%CI:0.588~0.878,P=0.0048)。纳入抗-HBe+抗-HBs建立预测模型,其区分度(AUC=0.733)、准确度(C=0.733,B=0.20,P=0.946)、检测效能及稳定度(加强Bootstrap检验C=0.726)均表现良好。结论乙型肝炎患者体内抗-HBs或抗-HBe的出现均促进HBeAg水平下降,且抗-HBe促进HBeAg水平下降的能力强于抗-HBs。抗-HBe+抗-HBs可用于大三阳+抗-HBe阳性模式患者HBeAg血清学转换的预测。Objective To establish a predictive model for HBeAg seroconversion in patients with positive HBsAg/HBeAg/anti-HBc and anti-HBe,and to investigate the predictive value of this model.Methods A total of 6055 patients with hepatitis B who received the quantification of the serum markers for hepatitis B and HBV DNA in Jingzhou Hospital Affiliated to Yangtze University from April 1,2018 to August 1,2022 were enrolled,and according to the pattern of serological markers for hepatitis B,they were divided into negative HBsAg group,positive HBsAg/anti-HBe/anti-HBc group,positive HBsAg/HBeAg/anti-HBc+positive anti-HBe group,positive HBsAg/HBeAg/anti-HBc+positive anti-HBs group,and positive HBsAg/HBeAg/anti-HBc group.The characteristics of different patterns of serological markers were analyzed,and the level of HBeAg was compared between groups.The Kruskal-Wallis H test was used for comparison of non-normally distributed continuous variables between multiple groups;the chi-square test was used for comparison of categorical data between groups.The linear regression analysis was used to analyze the difference in HBeAg content between different groups;the logistic regression analysis was used to screen for independent influencing factors and obtain the optimal predictive factors.The receiver operating characteristic(ROC)curve analysis was used to validate the predictive performance of the model.R Studio4.2.1 was used to establish and validate the predictive model.Results Compared with the positive HBsAg/anti-HBe/anti-HBc group,the positive HBsAg/HBeAg/anti-HBc+positive anti-HBe group and the positive HBsAg/HBeAg/anti-HBc+positive anti-HBs group had a significant reduction in the level of HBeAg(both P<0.01).The multivariate logistic regression analysis showed that anti-HBe was an independent influencing factor for HBeAg seroconversion(P=0.014),and the Lasso regression analysis showed that anti-HBe+anti-HBs was the optimal predictive factor for HBeAg seroconversion in the patients with positive HBsAg/HBeAg/anti-HBc and positive an

关 键 词：乙型肝炎抗原 血清转换 预测 

分 类 号：R512.62[医药卫生—内科学]