Department of Hepatology Division 2, Beijing Ditan Hospital, Capital Medical University, Beijing, China.
Infectious Disease Department, Xuanwu Hospital, Capital Medical University, Beijing, China.
Front Immunol. 2023 Jan 19;13:1119124. doi: 10.3389/fimmu.2022.1119124. eCollection 2022.
Precise assessment of liver inflammation in untreated hepatitis B e antigen (HBeAg)-positive patients with chronic hepatitis B virus (HBV) infection can determine when to initiate antiviral therapy. The aim of this study was to develop and validate a nomogram model for the prediction of non-minimal liver inflammation based on liver pathological injuries combined with age and alanine aminotransferase (ALT), aspartate aminotransferase (AST), hepatitis B surface antigen (HBsAg), HBeAg, and HBV DNA quantification.
We retrospectively included 735 HBeAg-positive chronic hepatitis B (CHB) patients with ALT < 80 U/L as the primary cohort and prospectively enrolled 196 patients as the validation cohort. Multivariate logistic regression analysis identified independent impact factors. A nomogram to predict significant liver inflammation was developed and validated.
Multivariate logistic regression analysis showed that HBeAg, AST, and age were independent risk factors for predicting non-minimal liver inflammation in untreated CHB patients. The final formula for predicting non-minimal liver inflammation was Logit() = -1.99 - 0.68 × LogHBeAg + 0.04 × Age + 0.06 × AST. A nomogram for the prediction of non-minimal liver inflammation was established based on the results from the multivariate analysis. The predicted probability of the model being consistent with the actual probability was validated by the calibration curves, showing the best agreement in both the primary and validation cohorts. The C-index was 0.767 (95%CI = 0.734-0.802) in the primary cohort and 0.749 (95%CI = 0.681-0.817) in the prospective validation cohort.
The nomogram based on HBeAg, AST, and age might help predict non-minimal liver inflammation in HBeAg-positive CHB patients with ALT < 80 U/L, which is practical and easy to use for clinicians.
准确评估未经治疗的乙型肝炎 e 抗原（HBeAg）阳性慢性乙型肝炎病毒（HBV）感染患者的肝脏炎症，可以确定何时开始抗病毒治疗。本研究旨在建立并验证一种基于肝病理损伤联合年龄、丙氨酸氨基转移酶（ALT）、天门冬氨酸氨基转移酶（AST）、乙肝表面抗原（HBsAg）、HBeAg 和 HBV DNA 定量的预测非最小肝脏炎症的列线图模型。
我们回顾性纳入了 735 名 ALT<80 U/L 的 HBeAg 阳性慢性乙型肝炎（CHB）患者作为主要队列，并前瞻性纳入了 196 名患者作为验证队列。多变量 logistic 回归分析确定了独立的影响因素。建立并验证了预测显著肝脏炎症的列线图。
多变量 logistic 回归分析显示，HBeAg、AST 和年龄是预测未经治疗的 CHB 患者非最小肝脏炎症的独立危险因素。预测非最小肝脏炎症的最终公式为 Logit()=-1.99-0.68×LogHBeAg+0.04×年龄+0.06×AST。根据多变量分析结果建立了预测非最小肝脏炎症的列线图。校准曲线验证了模型预测概率与实际概率的一致性，在主要和验证队列中均显示出最佳的一致性。在主要队列中的 C 指数为 0.767（95%CI=0.734-0.802），在前瞻性验证队列中的 C 指数为 0.749（95%CI=0.681-0.817）。
基于 HBeAg、AST 和年龄的列线图有助于预测 ALT<80 U/L 的 HBeAg 阳性 CHB 患者的非最小肝脏炎症，对于临床医生来说具有实用性和易用性。
