新型生物标志物在慢性乙型肝炎自然进程中的预测意义

摘要/Abstract

摘要： 目的通过观察慢性乙型肝炎(CHB)患者中乙型肝炎病毒(HBV)RNA、DNA、乙型肝炎核心相关抗原(HBcrAg)及其他标志物的水平,寻找预测HBV不同阶段的新型生物标志物。方法纳入2018年1月1日至2021年1月1日在河北北方学院附属第一医院就诊且未接受任何治疗的CHB患者185例。按HBV感染阶段将其分为免疫耐受(IT)组45例、免疫清除(IC)组44例、HBeAg阴性非活动/静止携带(ENQ)组48例和HBeAg阴性肝炎(ENH)组48例。采用不同方法检测血清HBV RNA、HBcrAg、HBV DNA和丙氨酸氨基转移酶(ALT)等指标的水平,并采用不同统计软件建立预测CHB分期的模型及验证。结果根据HBV感染阶段标准,IT和IC组的HBV DNA、HBV RNA、HBcrAg、HBsAg水平显著高于ENQ和ENH组(P均<0.001);而IC和ENH组的ALT、天冬氨酸氨基转移酶(AST)、谷氨酰基转移酶(GGT)、受控衰减参数(CAP)和肝脏硬度值(LSM)高于IT和ENQ期(P均<0.05)。除IT和IC组两两比较外,感染各期的HBV RNA浓度差异显著,特别是HBV RNA>6 lg copies/mL在IT组和IC组中的占比分别为93.34%和81.82%(P均<0.05)。四个阶段的HBcrAg浓度分布与HBV RNA相似。相关性分析显示,在HBeAg阳性患者中,HBV RNA、HBcrAg、HBV DNA浓度之间呈正相关性(P均<0.001);在HBeAg阴性患者中,HBV RNA分别与HBV DNA(r=0.43)、HBcrAg(r=0.72)之间呈正相关(P均<0.001),HBV DNA与HBcrAg呈正相关(r=0.40,P<0.001)。在HBV RNA和HBcrAg基础上,HBeAg阳性和阴性者在ALT分层中比较,差异具有统计学意义(P均<0.01)。本研究将基线资料按照7∶3的比例分为训练组(129例)和验证组(56例),C5.0模型预测重要性结果显示,HBV RNA和ALT是重要的预测因子,准确率为93.15%。关联规则结果显示,ALT>38.15、HBcrAg>7.18、HBV RNA>4.34的预测强度最优,关联强度最好。内外部验证结果显示,实际观测值与模型预测值拟合良好,模型临床净收益较优;训练组和验证组的AUC分别为0.97(95%CI:0.94~1.00)和0.96(95%CI:0.91~1.00),表明训练模型预测良好。结论血清HBV RNA和HBcrAg联合ALT可能有助于监测CHB的进展。

关键词: 慢性乙型肝炎, 乙型肝炎病毒RNA, 乙型肝炎核心相关抗原, 乙型肝炎e抗原

Abstract: Objective To investigate the novel biomarkers for predicting the natural course of chronic hepatitis B (CHB) by observing the levels of hepatitis B virus (HBV) RNA, DNA, hepatitis B core-associated antigen (HBcrAg) and other markers in patients with HBV infection. Methods A total of 185 CHB patients who were treatment-naive were enrolled at the First Affiliated Hospital of Hebei North University from Jan 1, 2018 to Jan 1, 2021. The patients were divided into an immune tolerance (IT) group (n=45), an immune clearance (IC) group (n=44), a negative inactive/quiescent carrier (ENQ) group (n=48) and an HBeAg negative hepatitis (ENH) group (n=48) according to the staging criteria of HBV infection. The levels of serum HBV RNA, HBV DNA, HBcrAg and alanine aminotransferase (ALT) were detected by different methods, and the model for predicting CHB staging were established and verified via different statistical software. Results Based on the staging criteria of HBV infection, the levels of HBV DNA, HBV RNA, HBcrAg, HBsAg in IT and IC groups were significantly higher than those in ENQ and ENH groups (all P<0.001); similarily, the concentrations of alanine transaminase (ALT), aspartate transaminase (AST), glutamyl transferase (GGT), controlled attenuation parameter (CAP) and liver stiffness measurements (LSM) in IC and ENH groups were higher than those in IT and ENQ groups (all P<0.05). The HBV RNA concentrations of each stage of infection was significantly different except for IT group when compared with IC group. The proportion of HBV RNA>6 lg copies/mL in the IT group and IC group was 93.34% and 81.82%, respectively (all P<0.05). The concentration distribution of HBcrAg in the four stages was similar to those of HBV RNA. Correlation analysis showed that HBV RNA, HBcrAg, HBV DNA concentrations were positively correlated with each other in HBeAg-positive patients (all P<0.001). In the HBeAg-negative patients, HBV RNA was positively related to HBV DNA (r=0.43) and HBcrAg (r=0.72) (all P<0.001), HBV DNA was positively associated with HBcrAg (r=0.40, P<0.001). On the basis of HBV RNA and HBcrAg, HBeAg-positive and negative patients were compared after ALT stratification, with statistically significant difference (all P<0.01). In this study, baseline data were divided into a training (n=129) and a validation (n=56) group with a ratio of 7:3. The results of C5.0 model for the significance of prediction showed that HBV RNA and ALT were important predictors, with an accuracy of 93.15%. The results of association rules showed that the predictive and association effects of ALT > 38.15, HBcrAg > 7.18, HBV RNA > 4.34 were the best. The results of internal and external validations showed that the actual observed values fit well with the predicted values by this model, and the clinical net benefit of the model was better. The area under curve (AUC) of the training group and validation group were 0.97 (95%CI: 0.94~1.00) and 0.96 (95%CI: 0.91~1.00), respectively, indicating that the training model predicted well. Conclusion Serum HBV RNA and HBcrAg combined with ALT may be helpful in monitoring the progression of CHB.

Key words: Chronic hepatitis B, Hepatitis B virus RNA, Hepatitis B core-associated antigen, Hepatitis B e antigen

王宇娇, 陈勇, 田龙. 新型生物标志物在慢性乙型肝炎自然进程中的预测意义[J]. 肝脏, 2025, 30(12): 1620-1627.

WANG Yu-jiao, CHEN Yong, TIAN Long. The significance of novel biomarkers in predicting the natural course of chronic hepatitis B[J]. Chinese Hepatolgy, 2025, 30(12): 1620-1627.

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