Retrospective Study
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Hepatol. Mar 27, 2024; 16(3): 405-417
Published online Mar 27, 2024. doi: 10.4254/wjh.v16.i3.405
Prediction model for hepatitis B e antigen seroconversion in chronic hepatitis B with peginterferon-alfa treated based on a response-guided therapy strategy
Pei-Xin Zhang, Xiao-Wei Zheng, Ya-Fei Zhang, Jun Ye, Wei Li, Qian-Qian Tang, Jie Zhu, Gui-Zhou Zou, Zhen-Hua Zhang
Pei-Xin Zhang, Ya-Fei Zhang, Jun Ye, Qian-Qian Tang, Jie Zhu, Gui-Zhou Zou, Zhen-Hua Zhang, Department of Infectious Diseases, The Second Affiliated Hospital of Anhui Medical University, Hefei 230601, Anhui Province, China
Xiao-Wei Zheng, Department of Infectious Diseases, Anhui Provincial Hospital, Hefei 230000, Anhui Province, China
Wei Li, Department of Hepatology, The Second People’s Hospital of Fuyang City, Fuyang 236000, Anhui Province, China
Author contributions: Zhang PX and Zheng XW contributed to the data analysis and drafting of the manuscript; Zhang PX, Zheng XW, Zhang YF, Ye J, Li W, Tang QQ, and Zou GZ contributed to the data acquisition; Zhang YF, Zhu J, Zou GZ, and Zhang ZH contributed in the process assessment; Zhang ZH contributed in the study conception and design; and all authors have read and approved the final version of the manuscript.
Supported by the Anhui Provincial Natural Science Foundation, No. 2108085MH298; the Scientific Research Project of the Second Affiliated Hospital of Anhui Medical University, No. 2019GMFY02 and 2021lcxk027; and the Scientific Research Project of Colleges and Universities in Anhui Province, No. KJ2021A0323.
Institutional review board statement: All procedures performed in studies involving human participants were in accordance with the ethical standards of the Ethics Committee (Anhui Medical University No. 2012624) and with the 1975 Helsinki Declaration.
Informed consent statement: Written informed consent was obtained from all patients.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: The original anonymous dataset is available on request from the corresponding author at zzh1974cn@163.com.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Zhen-Hua Zhang, MD, Professor, Department of Infectious Diseases, The Second Affiliated Hospital of Anhui Medical University, No. 678 Furong Road, Hefei 230601, Anhui Province, China. zzh1974cn@163.com
Received: November 7, 2023
Peer-review started: November 7, 2023
First decision: December 6, 2023
Revised: December 27, 2023
Accepted: February 1, 2024
Article in press: February 1, 2024
Published online: March 27, 2024
Processing time: 140 Days and 23.8 Hours
ARTICLE HIGHLIGHTS
Research background

Hepatitis B virus (HBV) infection poses a major public health threat worldwide. Recently, many studies on the efficacy of peginterferon-alfa (PEG-IFNα) in treatment-experienced hepatitis B e antigen (HBeAg)-positive chronic hepatitis B (CHB) patients are scarce. Models for predicting HBeAg seroconversion in patients with HBeAg-positive CHB after nucleos(t)ide analog (NAs) treatment are necessary.

Research motivation

In clinical practice, many NAs-treated patients with HBeAg-positive CHB did not attain HBeAg seroconversion, and drug withdrawal is unsafe. Currently, IFN is appropriate for young patients with CHB who desire to end treatment permanently. It is necessary to explore accurate prediction models for the response to PEG-IFNα therapy and viable response-guided therapy (RGT) strategy in patients with HBeAg-positive CHB.

Research objectives

The key significance of this study is to establish a simple scoring model based on a RGT strategy for predicting HBeAg seroconversion and hepatitis B surface antigen (HBsAg) clearance for treatment-experienced patients with HBeAg-positive CHB.

Research methods

In this study, seventy-five treatment-experienced patients with HBeAg-positive CHB underwent a 52-wk PEG-IFNα treatment and a 24-wk follow-up. Logistic regression analysis was used to assess parameters at baseline, week 12, and week 24 to predict HBeAg seroconversion at 24 wk off-treatment. The two best predictors at each time point were applied to establish a prediction model for PEG-IFNα therapy efficacy. Parameters at each time point meeting the corresponding optimal cut-off thresholds were scored as 1 or 0.

Research results

We found that the two most meaningful predictors were HBsAg ≤ 1000 IU/mL and HBeAg ≤ 3 S/CO at baseline, HBsAg ≤ 600 IU/mL and HBeAg ≤ 3 S/CO at week 12, and HBsAg ≤ 300 IU/mL and HBeAg ≤ 2 S/CO at week 24. For a total score of 0 vs 2 at baseline, week 12, and week 24, the response rates were 23.8%, 15.2%, and 11.1% vs 81.8%, 80.0%, and 82.4%, respectively, and the HBsAg clearance rates were 2.4%, 3.0%, and 0.0%, vs 54.5%, 40.0%, and 41.2%, respectively.

Research conclusions

We successfully established a predictive model and diagnosis-treatment process based on the RGT strategy to predict HBeAg and HBsAg seroconversion to PEG-IFNα therapy in patients with HBeAg-positive CHB.

Research perspectives

The prediction models established for treatment-experienced patients with HBeAg-positive CHB are simplistic and practical, and the RGT strategy can help to optimize the use of PEG-IFNα. These results need to be further confirmed by multicenter, large-scale prospective studies.