AUTHOR=Zhang Lu , Bi Xiaoyue , Chen Xiaoxue , Zhang Luxue , Xiong Qiqiu , Cao Weihua , Lin Yanjie , Yang Liu , Jiang Tingting , Deng Wen , Wang Shiyu , Wu Shuling , Liu Ruyu , Gao Yuanjiao , Shen Ge , Chang Min , Hao Hongxiao , Xu Mengjiao , Hu Leiping , Lu Yao , Li Minghui , Xie Yao 

TITLE=A nomogram based on HBeAg, AST, and age to predict non-minimal liver inflammation in CHB patients with ALT <80 U/L

JOURNAL=Frontiers in Immunology

VOLUME=13

YEAR=2023

URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2022.1119124

DOI=10.3389/fimmu.2022.1119124

ISSN=1664-3224

ABSTRACT=<sec><title>Objective</title><p>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.</p></sec><sec><title>Methods</title><p>We retrospectively included 735 HBeAg-positive chronic hepatitis B (CHB) patients with ALT &lt; 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.</p></sec><sec><title>Results</title><p>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(<italic>P</italic>) = −1.99 − 0.68 × Log<sub>10</sub>HBeAg + 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.</p></sec><sec><title>Conclusions</title><p>The nomogram based on HBeAg, AST, and age might help predict non-minimal liver inflammation in HBeAg-positive CHB patients with ALT &lt; 80 U/L, which is practical and easy to use for clinicians.</p></sec>