Literature DB >> 25430663

Predicting Hepatitis B Virus (HBV) Surface Antigen Seroclearance in HBV e Antigen-Negative Patients With Chronic Hepatitis B: External Validation of a Scoring System.

Jessica Liu1, Tai-Chung Tseng2, Hwai-I Yang3, Mei-Hsuan Lee4, Richard Batrla-Utermann5, Chin-Lan Jen1, Sheng-Nan Lu6, Li-Yu Wang7, San-Lin You1, Pei-Jer Chen8, Chien-Jen Chen9, Jia-Horng Kao10.   

Abstract

BACKGROUND: Hepatitis B virus (HBV) surface antigen (HBsAg) seroclearance is the ultimate serological end point in chronic hepatitis B. This study aimed to develop and validate a prediction score for spontaneous HBsAg seroclearance in HBV e antigen (HBeAg)-negative patients with chronic hepatitis B due to HBV genotype B or C.
METHODS: The development cohort included 2491 untreated participants from the community-based REVEAL-HBV study, who were HBeAg negative, anti-hepatitis C virus negative, and cirrhosis free. The independent validation cohort consisted of 1934 hospital-based individuals from the National Taiwan University Hospital. Clinical markers included in the model were age and serum HBV DNA and HBsAg levels. Cox proportional hazards regression models were used to create the prediction model.
RESULTS: A prediction score ranging from 0 to 27 was developed. Predicted probabilities of 5- and 10-year HBsAg seroclearance ranged from 0.95% to 30.49% and from 2.58% to 62.52%, respectively. When applied to the independent validation cohort, the areas under the receiver operating characteristic curves for the 5- and 10-year prediction of HBsAg seroclearance in the validation cohort were 0.82 (95% confidence interval [CI], .76-.88) and 0.74 (95% CI, .70-.78). Model fit was still adequate, according to Hosmer-Lemeshow goodness of fit tests.
CONCLUSIONS: A clinically applicable prediction score for HBsAg seroclearance was developed and externally validated. This model can assist clinicians in further stratifying risk groups.
© The Author 2014. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  epidemiology; prediction model; viral hepatitis

Mesh:

Substances:

Year:  2014        PMID: 25430663     DOI: 10.1093/infdis/jiu659

Source DB:  PubMed          Journal:  J Infect Dis        ISSN: 0022-1899            Impact factor:   5.226


  6 in total

1.  HBsAg loss in chronic hepatitis B: pointers to the benefits of curative therapy.

Authors:  Geoffrey Dusheiko; Bo Wang; Ivana Carey
Journal:  Hepatol Int       Date:  2016-05-31       Impact factor: 6.047

2.  Hepatitis B Surface Antigen Loss and Hepatocellular Carcinoma Development in Patients With Dual Hepatitis B and C Infection.

Authors:  Wan-Ting Yang; Li-Wei Wu; Tai-Chung Tseng; Chi-Ling Chen; Hung-Chih Yang; Tung-Hung Su; Chia-Chi Wang; Stephanie Fang-Tzu Kuo; Chen-Hua Liu; Pei-Jer Chen; Ding-Shinn Chen; Chun-Jen Liu; Jia-Horng Kao
Journal:  Medicine (Baltimore)       Date:  2016-03       Impact factor: 1.889

3.  Switching to PegIFNα-2b leads to HBsAg loss in patients with low HBsAg levels and HBV DNA suppressed by NAs.

Authors:  Jing Huang; Ka Zhang; Wenli Chen; Jinyao Liao; Xiaodan Luo; Ren Chen
Journal:  Sci Rep       Date:  2017-10-17       Impact factor: 4.379

Review 4.  Treatment for Viral Hepatitis as Secondary Prevention for Hepatocellular Carcinoma.

Authors:  Saleh A Alqahtani; Massimo Colombo
Journal:  Cells       Date:  2021-11-09       Impact factor: 6.600

5.  The association between sPD-1 levels versus liver biochemistry and viral markers in chronic hepatitis B patients: a comparative study of different sPD-1 assays.

Authors:  Wen-Juei Jeng; Chien-Hung Chen; Yi-Wen Wang; Mei-Hung Pan; Chia-Wei Lin; Chun-Yen Lin; Hwai-I Yang
Journal:  Virol J       Date:  2022-03-31       Impact factor: 4.099

6.  Use of a Deep Learning Approach for the Sensitive Prediction of Hepatitis B Surface Antigen Levels in Inactive Carrier Patients.

Authors:  Hiroteru Kamimura; Hirofumi Nonaka; Masaya Mori; Taichi Kobayashi; Toru Setsu; Kenya Kamimura; Atsunori Tsuchiya; Shuji Terai
Journal:  J Clin Med       Date:  2022-01-13       Impact factor: 4.241

  6 in total

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