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已发表论文
基于聚乙二醇干扰素治疗后乙肝表面抗原血清清除的预测模型的开发与验证：一项多中心研究
Authors Liu HH , Jiang XM, Cui C , Zhao J, Xu J, Wang SK, Hu LH, Yin YP, Wang X, Yu LJ, Xu C, Zhao ZH, Xing YQ , Liu Y, Wang K, Gao S
Received 9 June 2025
Accepted for publication 28 October 2025
Published 7 November 2025 Volume 2025:19 Pages 9973—9982
DOI https://doi.org/10.2147/DDDT.S545700
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Muzammal Hussain
Hui-Hui Liu,1 Xue-Mei Jiang,2 Chao Cui,3 Jing Zhao,4 Juan Xu,5 Si-Kui Wang,6 Lei-Hua Hu,7 Yan-Ping Yin,8 Xiao Wang,9 Li-Jun Yu,10 Cheng Xu,11 Zheng-Hua Zhao,12 Yan-Qing Xing,13 Yue Liu,3 Kai Wang,1 Shuai Gao1
1Department of Hepatology, Qilu Hospital of Shandong University, Jinan, Shandong, People’s Republic of China; 2Department of Hepatology, Shandong Public Health Clinical Center, Jinan, Shandong, People’s Republic of China; 3Department of Infectious Disease, Qilu Hospital of Shandong University Dezhou Hospital, Dezhou, Shandong, People’s Republic of China; 4Department of Infectious Disease, Weifang People’s Hospital, Shandong Second Medical University, Weifang, Shandong, People’s Republic of China; 5Department of Infectious Disease, Shengli Oilfield Central Hospital, Dongying, Shandong, People’s Republic of China; 6Department of Infectious Disease, Liaocheng People’s Hospital, Liaocheng, Shandong, People’s Republic of China; 7Department of Internal Medicine, Jinmen Lake Street Community Health Service Center, Tianjin, People’s Republic of China; 8Department of Gastroenterology, Yantai City Yantai Mountain Hospital, Yantai, Shandong, People’s Republic of China; 9Liver Disease Center, Digestive Diseases Hospital of Shandong First Medical University, Jining, Shandong, People’s Republic of China; 10Department of Epidemiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong, People’s Republic of China; 11Department of Infectious Disease, Linyi People’s Hospital, Linyi, Shandong, People’s Republic of China; 12Department of Infectious Disease, Taian City Central Hospital, Taian, Shandong, People’s Republic of China; 13Department of Infectious Disease, Zibo Central Hospital, Zibo, Shandong, People’s Republic of China
Correspondence: Shuai Gao, Department of Hepatology, Qilu Hospital of Shandong University, No. 107, Wenhuaxi Road, Jinan, Shandong, 250012, People’s Republic of China, Tel +86-531-82169596, Fax +86-531-86927544, Email qilugaoshuai@sdu.edu.cn
Purpose: Early prediction of HBsAg seroclearance prior to the application of Peg-IFN-based therapy has important clinical implications. This study aims to construct a predictive model with baseline parameters for HBsAg seroclearance after Peg-IFN-based therapy in virally suppressed patients with HBeAg-negative chronic hepatitis B (CHB).
Patients and Methods: From January 1, 2018 to May 1, 2023, we retrospectively enrolled 377 nucleos(t)ide analogue-suppressed patients with HBeAg-negative CHB who received a 48-week Peg-IFN-based therapy from 10 centers in China. A multivariate cox regression model was developed for predicting HBsAg seroclearance in a development cohort with 229 patients recruited from 5 centers, then validated in an independent validation cohort with 148 patients recruited from another 5 centers. This study is registered with ClinicalTrials.gov, number NCT06196632.
Results: In the development and validation cohort, 17.9% (41/229) and 20.27% (30/148) of patients achieved HBsAg seroclearance, respectively. The best performing model was constructed by age (HR 0.962, 95% CI 0.928– 0.997), baseline HBsAg (HR 0.998, 95% CI 0.997– 0.999) and alanine aminotransferase (HR 1.008, 95% CI 1.003– 1.012). It showed good predictive performance in predicting HBsAg seroclearance in both the development [area under the receiver operating characteristic curve (AUC) 0.842] and validation cohort (AUC 0.852). Using cut-off points of − 2.7 and − 1.3, it can identify HBeAg-negative CHB patients with high, intermediate and low incidence rate of HBsAg seroclearance.
Conclusion: A model was constructed with baseline parameters for predicting HBsAg seroclearance after Peg-IFN-based therapy in virally suppressed patients with HBeAg-negative CHB. It showed good predictive value and can provide guidance for the clinical application of Peg-IFN-based therapy.
Keywords: chronic hepatitis B, pegylated interferon alfa, HBsAg seroclearance, multicentre study, predictive model
1Department of Hepatology, Qilu Hospital of Shandong University, Jinan, Shandong, People’s Republic of China; 2Department of Hepatology, Shandong Public Health Clinical Center, Jinan, Shandong, People’s Republic of China; 3Department of Infectious Disease, Qilu Hospital of Shandong University Dezhou Hospital, Dezhou, Shandong, People’s Republic of China; 4Department of Infectious Disease, Weifang People’s Hospital, Shandong Second Medical University, Weifang, Shandong, People’s Republic of China; 5Department of Infectious Disease, Shengli Oilfield Central Hospital, Dongying, Shandong, People’s Republic of China; 6Department of Infectious Disease, Liaocheng People’s Hospital, Liaocheng, Shandong, People’s Republic of China; 7Department of Internal Medicine, Jinmen Lake Street Community Health Service Center, Tianjin, People’s Republic of China; 8Department of Gastroenterology, Yantai City Yantai Mountain Hospital, Yantai, Shandong, People’s Republic of China; 9Liver Disease Center, Digestive Diseases Hospital of Shandong First Medical University, Jining, Shandong, People’s Republic of China; 10Department of Epidemiology, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Jinan, Shandong, People’s Republic of China; 11Department of Infectious Disease, Linyi People’s Hospital, Linyi, Shandong, People’s Republic of China; 12Department of Infectious Disease, Taian City Central Hospital, Taian, Shandong, People’s Republic of China; 13Department of Infectious Disease, Zibo Central Hospital, Zibo, Shandong, People’s Republic of China
Correspondence: Shuai Gao, Department of Hepatology, Qilu Hospital of Shandong University, No. 107, Wenhuaxi Road, Jinan, Shandong, 250012, People’s Republic of China, Tel +86-531-82169596, Fax +86-531-86927544, Email qilugaoshuai@sdu.edu.cn
Purpose: Early prediction of HBsAg seroclearance prior to the application of Peg-IFN-based therapy has important clinical implications. This study aims to construct a predictive model with baseline parameters for HBsAg seroclearance after Peg-IFN-based therapy in virally suppressed patients with HBeAg-negative chronic hepatitis B (CHB).
Patients and Methods: From January 1, 2018 to May 1, 2023, we retrospectively enrolled 377 nucleos(t)ide analogue-suppressed patients with HBeAg-negative CHB who received a 48-week Peg-IFN-based therapy from 10 centers in China. A multivariate cox regression model was developed for predicting HBsAg seroclearance in a development cohort with 229 patients recruited from 5 centers, then validated in an independent validation cohort with 148 patients recruited from another 5 centers. This study is registered with ClinicalTrials.gov, number NCT06196632.
Results: In the development and validation cohort, 17.9% (41/229) and 20.27% (30/148) of patients achieved HBsAg seroclearance, respectively. The best performing model was constructed by age (HR 0.962, 95% CI 0.928– 0.997), baseline HBsAg (HR 0.998, 95% CI 0.997– 0.999) and alanine aminotransferase (HR 1.008, 95% CI 1.003– 1.012). It showed good predictive performance in predicting HBsAg seroclearance in both the development [area under the receiver operating characteristic curve (AUC) 0.842] and validation cohort (AUC 0.852). Using cut-off points of − 2.7 and − 1.3, it can identify HBeAg-negative CHB patients with high, intermediate and low incidence rate of HBsAg seroclearance.
Conclusion: A model was constructed with baseline parameters for predicting HBsAg seroclearance after Peg-IFN-based therapy in virally suppressed patients with HBeAg-negative CHB. It showed good predictive value and can provide guidance for the clinical application of Peg-IFN-based therapy.
Keywords: chronic hepatitis B, pegylated interferon alfa, HBsAg seroclearance, multicentre study, predictive model