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Qiu J, Zhang S, Feng Y, Su X, Cai J, Chen S, Liu J, Huang S, Huang H, Zhu S, Wen H, Li J, Yan H, Diao Z, Liang X, Zeng F. Efficacy and safety of hepatitis B vaccine: an umbrella review of meta-analyses. Expert Rev Vaccines 2024; 23:69-81. [PMID: 38055218 DOI: 10.1080/14760584.2023.2289566] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 11/27/2023] [Indexed: 12/07/2023]
Abstract
BACKGROUND There is a lack of synthesis of literature to determine hepatitis B vaccine (HepB) strategies for hepatitis B virus (HBV) supported by quality evidence. We aimed to explore the efficacy and safety of HepB strategies among people with different characteristics. RESEARCH DESIGN AND METHODS PubMed, Cochrane Library, Embase, and Web of Science were searched for meta-analyses comparing the efficacy and safety of HepB up to July 2023. RESULTS Twenty-one meta-analyses comparing 83 associations were included, with 16 high quality, 4 moderate, and 1 low quality assessed by AMSTAR 2. Highly suggestive evidence supports HepB booster and HepB with 1018 adjuvant (HBsAg-1018) for improved seroprotection, and targeted and universal HepB vaccination reduced HBV infection Suggestive evidence indicated that targeted vaccination decreased the rate of hepatitis B surface antibody positivity and booster doses increased seroprotection in people aged 10-20. Weak evidence suggests potential local/systemic reaction risk with nucleotide analogs or HBsAg-1018. Convincing evidence shows HLA-DPB1*04:01 and DPB1*04:02 increased, while DPB1*05:01 decreased, hepatitis B antibody response. Obesity may reduce HepB seroprotection, as highly suggested. CONCLUSION Targeted vaccination could effectively reduce HBV infection, and adjuvant and booster vaccinations enhance seroprotection without significant reaction. Factors such as obesity and genetic polymorphisms may affect the efficacy.
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Affiliation(s)
- Jiamin Qiu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, PR China
| | - Shiwen Zhang
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, PR China
| | - Yonghui Feng
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, PR China
| | - Xin Su
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, PR China
| | - Jun Cai
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, PR China
| | - Shiyun Chen
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, PR China
| | - Jiazi Liu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, PR China
| | - Shiqi Huang
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, PR China
| | - Haokun Huang
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, PR China
| | - Sui Zhu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, PR China
| | - Huiyan Wen
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, PR China
| | - Jiaxin Li
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, PR China
| | - Haoyu Yan
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, PR China
| | - Zhiquan Diao
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, PR China
| | - Xiaofeng Liang
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, PR China
- Jinan University-BioKangtai Vaccine Institute, Jinan University, Shenzhen, China
| | - Fangfang Zeng
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, PR China
- Jinan University-BioKangtai Vaccine Institute, Jinan University, Shenzhen, China
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Hu H, Shen Y, Hu M, Zheng Y, Xu K, Li L. Incidence and Influencing Factors of New Hepatitis B Infections and Spontaneous Clearance: A Large-Scale, Community-Based Study in China. Front Med (Lausanne) 2021; 8:717667. [PMID: 34869415 PMCID: PMC8637118 DOI: 10.3389/fmed.2021.717667] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Accepted: 08/23/2021] [Indexed: 01/05/2023] Open
Abstract
Background: Hepatitis B surface antigen (HBsAg) is widely used in hepatitis B screening, and HBsAg seroclearance indicates hepatitis B eradication. Few studies have explored the incidence of and determinants for spontaneous seroclearance using a long-term follow-up cohort study. Our research aimed to examine the incidence of and influencing factors for hepatitis B virus infection and spontaneous clearance of HBsAg from a large-scale cohort in China. Methods: A total of 151,926 resident individuals in Tongxiang underwent HBsAg screening at least thrice in a 7-year period. Serum samples collected at baseline and follow-up examinations were tested for HBsAg. Cox proportional hazard models were used to analyze determinants of HBsAg seroclearance and persistent HBsAg presence. Results: Among the 151,926 participants, new hepatitis B infections occurred in 4,497 participants, yielding an incidence rate of 571.38 per 100,000 person-years. The incidence rate for males was higher than that for females. In the multivariate Cox regression analysis, female gender, alcohol drinking history, hepatitis family history and middle-age group were predictors for persistent positive HBsAg status. Conclusions: The incidence rate of new hepatitis B infections was 571.38 per 100,000 person-years. Male and aged people in this community cohort have a higher infection rate. Alcohol drinking and hepatitis family history were risk factor leading to chronic infection. Female and middle-aged people were prone to persistent positive HBsAg status.
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Affiliation(s)
- Haiyang Hu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, School of Medicine, The First Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Yangfan Shen
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, School of Medicine, The First Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Ming Hu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, School of Medicine, The First Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Yang Zheng
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, School of Medicine, The First Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Kaijin Xu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, School of Medicine, The First Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Lanjuan Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, School of Medicine, The First Affiliated Hospital, Zhejiang University, Hangzhou, China
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Dimitrov Y, Ducher M, Kribs M, Laurent G, Richter S, Fauvel JP. Variables linked to hepatitis B vaccination success in non-dialyzed chronic kidney disease patients: Use of a bayesian model. Nephrol Ther 2019; 15:215-219. [PMID: 31129001 DOI: 10.1016/j.nephro.2019.02.010] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2018] [Revised: 02/01/2019] [Accepted: 02/03/2019] [Indexed: 02/07/2023]
Abstract
BACKGROUND Hepatitis B vaccination is recommended for chronic kidney disease (CKD) patients before starting dialysis. We performed an analyis aimed to describe the clinical and biological parameters related to the success of vaccination in CKD patients before starting dialysis. METHODS We extracted data of 170 non-dialyzed patients who were offered hepatitis B vaccination from a register. They received a first vaccination of 40μg followed by boosters after one, two and six months. Patients were considered protected if their hepatitis B antibody level was >10IU/L, three months apart. A logistic regression and a Bayesian model were used to describe the relationships between variables and the success of vaccination. RESULTS Vaccination protected 50.6% of the patients. Model adjustment to the data was higher using the Bayesian model compared to the logistic regression (with area under the ROC curve of 0.955±0.007 vs 0.775±0.066 respectively). The Bayesian model's robustness studied using a 10 fold cross validation showed a percentage of misclassified subjects of 12.4±1.8%, a sensitivity of 87.7±0.3%, a specificity of 87.5±0.3%, a positive predictive value of 87.8±0.3% and negative predictive value of 87.4±0.2%. As classified by the Bayesian model, the variables most related to successful vaccination were, in descending order: age, eGFR, protidemia, albuminemia, cause of renal failure, gender, previous vaccination and weight. CONCLUSION The Bayesian network confirmed that both kidney function and nutritional status of patients are important factors to explain the success of vaccination against hepatitis B in CKD patients before dialysis. For research purposes, before an external validation, the network can be used online at www.hed.cc/?s=Bhepatitis&n=ReseauhepatiteBsup10.neta.
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Affiliation(s)
- Yves Dimitrov
- Nephrology Department, centre hospitalier de Haguenau, 64, avenue du professeur Leriche, 67500 Haguenau, France.
| | - Michel Ducher
- Pharmacy Department, hospices civils de Lyon, université Claude-Bernard Lyon 1, 69000 Lyon, France
| | - Marc Kribs
- Nephrology Department, centre hospitalier de Haguenau, 64, avenue du professeur Leriche, 67500 Haguenau, France
| | - Guillaume Laurent
- Nephrology Department, centre hospitalier de Haguenau, 64, avenue du professeur Leriche, 67500 Haguenau, France
| | | | - Jean-Pierre Fauvel
- Hospices civils de Lyon, université Claude-Bernard Lyon 1, 69000 Lyon, France
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