HBeAg阴性慢性乙型肝炎病毒感染者发生肝硬化风险模型的建立

Establishment of risk stratification model for developing cirrhosis in patients with HBeAg-negative chronic hepatitis B virus infection

目的探讨乙型肝炎e抗原(HBeAg)阴性慢性乙型肝炎病毒(HBV)感染者发生肝硬化的独立影响因素,建立列线图模型并检验其诊断效能。方法回顾性分析2011—2021年就诊于中国医科大学附属第一医院596例HBeAg阴性慢性HBV感染者和677例乙型肝炎相关肝硬化患者的临床常用实验室数据,按7∶3比例随机分为建模组(892例)和验证组(381例),采用多重共线性检验和多因素Logistic回归分析肝硬化的独立影响因素,建立列线图模型并通过受试者工作特征(ROC)曲线、校准曲线、临床决策曲线及临床影响曲线对模型进行验证。结果多因素Logistic回归分析显示乙型肝炎核心抗体(OR=1.492,95%CI 1.316~1.706)、γ-谷氨酰转移酶(OR=1.015,95%CI 1.010~1.022)、血小板计数(OR=0.986,95%CI 0.982~0.988)和白蛋白(OR=0.853,95%CI 0.824~0.882)是乙型肝炎相关肝硬化发生的独立影响因素(P<0.05),基于此4项指标构建列线图风险模型。ROC曲线显示模型的AUC为0.933(95%CI 0.916~0.950),验证组AUC为0.931(95%CI 0.905~0.956)。校准曲线显示模型一致性较好,决策曲线分析和临床影响曲线显示模型净收益率较高,临床应用性能较好。结论乙型肝炎核心抗体、γ-谷氨酰转移酶、血小板计数和白蛋白是HBeAg阴性慢性HBV感染者发生肝硬化的独立影响因素,基于此建立的列线图具有良好的区分度、校准度和应用性能,能够为肝硬化发病风险的预测提供帮助。

Objective To explore the independent predictive factors of cirrhosis in patients with hepatitis B e antigen(HBeAg)-negative chronic hepatitis B virus(HBV)infection,and establish a nomogram model based on clinical laboratory data and analyze the predictive value of this model.Methods The laboratory data of 596 patients with HBeAg-negative chronic HBV infection and 677 patients with hepatitis B cirrhosis,who were hospitalized in the First Hospital of China Medical University from 2011 to 2021,were retrospectively analyzed.Patients were randomly divided into training group(n=892)and validation group(n=381)at the ratio of 7∶3.The independent predictive factors of cirrhosis were analyzed by univariate logistic regression,multiple collinearity test and multivariate logistic regression.The nomogram model was established and the prediction value of this model was evaluated.Results According to multivariate logistic regression analysis,hepatitis B core antibody(OR=1.492,95%CI 1.316-1.706),glutamine transpeptidase(OR=1.015,95%CI 1.010-1.022),platelet(OR=0.986,95%CI 0.982-0.988)and albumin(OR=0.853,95%CI 0.824-0.882)were independent predictors of cirrhosis(P<0.05),and the nomogram was established based on the four indicators.Receiver operating characteristic curves showed that area under the curve of the nomogram was 0.933(95%CI 0.916-0.950),and that of the validation group was 0.931(95%CI 0.905-0.956).The calibration curves indicated the nomogram model was highly consistent with the actual outcome.Decision curves and clinical impact curves confirmed that the model had high net benefit and good clinical application performance.Conclusions Hepatitis B core antibody,glutamine transpeptidase,platelet and albumin are independent predictors of cirrhosis among patients with HBeAg-negative chronic HBV infection.The newly developed nomogram model based on these factors could be used to predict cirrhosis risk in these patients.