Prospective Study
Copyright ©The Author(s) 2015. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. May 14, 2015; 21(18): 5668-5676
Published online May 14, 2015. doi: 10.3748/wjg.v21.i18.5668
Models for predicting hepatitis B e antigen seroconversion in response to interferon-α in chronic hepatitis B patients
Chang-Tai Wang, Ya-Fei Zhang, Bing-Hu Sun, Yu Dai, Hui-Lan Zhu, Yuan-Hong Xu, Meng-Ji Lu, Dong-Liang Yang, Xu Li, Zhen-Hua Zhang
Chang-Tai Wang, Ya-Fei Zhang, Bing-Hu Sun, Yu Dai, Hui-Lan Zhu, Xu Li, Zhen-Hua Zhang, Department of Infectious Diseases, the First Affiliated Hospital, Anhui Medical University, Hefei 230022, Anhui Province, China
Yuan-Hong Xu, Department of Clinical Laboratory, the First Affiliated Hospital, Anhui Medical University, Hefei 230022, Anhui Province, China
Meng-Ji Lu, Institute of Virology, University Hospital of Essen, University of Duisburg-Essen, 45122 Essen, Germany
Dong-Liang Yang, Department of Infectious Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei Province, China
Author contributions: Zhang ZH conceived the idea and carried out the literature search and final editing; Wang CT, Zhang YF, Sun BH, Dai Y, Zhu HL and Xu YH performed the experiments; Wang CT and Zhang ZH analyzed the data and wrote the paper; Li X and Zhang ZH contributed reagents, materials, and analysis tools; Yang DL and Lu MJ provided technical assistance and helpful discussion.
Supported by Specialized Research Fund for the Doctoral Program of Higher Education of China, No. 20093420120005; and National Science Foundation of China, No. 30771907.
Ethics approval: The study was reviewed and approved by the ethics committee of Anhui Medical University.
Clinical trial registration: Not clinical trial.
Informed consent: All study participants, or their legal guardian, provided informed written consent prior to study enrollment.
Conflict-of-interest: We all have no conflicts of interest.
Data sharing: No additional data are available.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (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: http://creativecommons.org/licenses/by-nc/4.0/
Correspondence to: Zhen-Hua Zhang, MD, PhD, Department of Infectious Diseases, the First Affiliated Hospital, Anhui Medical University, 218 Jixi Road, Hefei 230022, Anhui Province, China. zzh1974cn@163.com
Telephone: +86-551-62922912 Fax: +86-551-62922912
Received: October 28, 2014
Peer-review started: October 29, 2014
First decision: November 26, 2014
Revised: December 17, 2014
Accepted: January 30, 2015
Article in press: January 30, 2015
Published online: May 14, 2015
Processing time: 201 Days and 21 Hours
Abstract

AIM: To develop models to predict hepatitis B e antigen (HBeAg) seroconversion in response to interferon (IFN)-α treatment in chronic hepatitis B patients.

METHODS: We enrolled 147 treatment-naïve HBeAg-positive chronic hepatitis B patients in China and analyzed variables after initiating IFN-α1b treatment. Patients were tested for serum alanine aminotransferase (ALT), hepatitis B virus-DNA, hepatitis B surface antigen (HBsAg), antibody to hepatitis B surface antigen, HBeAg, antibody to hepatitis B e antigen (anti-HBe), and antibody to hepatitis B core antigen (anti-HBc) at baseline and 12 wk, 24 wk, and 52 wk after initiating treatment. We performed univariate analysis to identify response predictors among the variables. Multivariate models to predict treatment response were constructed at baseline, 12 wk, and 24 wk.

RESULTS: At baseline, the 3 factors correlating most with HBeAg seroconversion were serum ALT level > 4 × the upper limit of normal (ULN), HBeAg ≤ 500 S/CO, and anti-HBc > 11.4 S/CO. At 12 wk, the 3 factors most associated with HBeAg seroconversion were HBeAg level ≤ 250 S/CO, decline in HBeAg > 1 log10 S/CO, and anti-HBc > 11.8 S/CO. At 24 wk, the 3 factors most associated with HBeAg seroconversion were HBeAg level ≤ 5 S/CO, anti-HBc > 11.4 S/CO, and decline in HBeAg > 2 log10 S/CO. Each variable was assigned a score of 1, a score of 0 was given if patients did not have any of the 3 variables. The 3 factors most strongly correlating with HBeAg seroconversion at each time point were used to build models to predict the outcome after IFN-α treatment. When the score was 3, the response rates at the 3 time points were 57.7%, 83.3%, and 84.0%, respectively. When the score was 0, the response rates were 2.9%, 0.0%, and 2.1%, respectively.

CONCLUSION: Models with good negative and positive predictive values were developed to calculate the probability of response to IFN-α therapy.

Keywords: Chronic hepatitis B, Interferon, Hepatitis B e antigen, Treatment, Model

Core tip: The response to interferon (IFN)-α therapy in chronic hepatitis B (CHB) patients varies significantly among individuals. This study of 147 patients evaluated multiple serological variables in hepatitis B e antigen (HBeAg)-positive CHB patients treated with IFN-α1b at baseline, 12 wk, and 24 wk, and then developed predictive models for HBeAg seroconversion at each of the 3 time points. The results suggest that models with good negative and positive predictive values were developed to calculate the probability of response to IFN-α therapy.