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Dong W, Da Roza CC, Cheng D, Zhang D, Xiang Y, Seto WK, Wong WCW. Development and validation of HBV surveillance models using big data and machine learning. Ann Med 2024; 56:2314237. [PMID: 38340309 PMCID: PMC10860422 DOI: 10.1080/07853890.2024.2314237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 01/30/2024] [Indexed: 02/12/2024] Open
Abstract
BACKGROUND The construction of a robust healthcare information system is fundamental to enhancing countries' capabilities in the surveillance and control of hepatitis B virus (HBV). Making use of China's rapidly expanding primary healthcare system, this innovative approach using big data and machine learning (ML) could help towards the World Health Organization's (WHO) HBV infection elimination goals of reaching 90% diagnosis and treatment rates by 2030. We aimed to develop and validate HBV detection models using routine clinical data to improve the detection of HBV and support the development of effective interventions to mitigate the impact of this disease in China. METHODS Relevant data records extracted from the Family Medicine Clinic of the University of Hong Kong-Shenzhen Hospital's Hospital Information System were structuralized using state-of-the-art Natural Language Processing techniques. Several ML models have been used to develop HBV risk assessment models. The performance of the ML model was then interpreted using the Shapley value (SHAP) and validated using cohort data randomly divided at a ratio of 2:1 using a five-fold cross-validation framework. RESULTS The patterns of physical complaints of patients with and without HBV infection were identified by processing 158,988 clinic attendance records. After removing cases without any clinical parameters from the derivation sample (n = 105,992), 27,392 cases were analysed using six modelling methods. A simplified model for HBV using patients' physical complaints and parameters was developed with good discrimination (AUC = 0.78) and calibration (goodness of fit test p-value >0.05). CONCLUSIONS Suspected case detection models of HBV, showing potential for clinical deployment, have been developed to improve HBV surveillance in primary care setting in China. (Word count: 264).
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Affiliation(s)
- Weinan Dong
- Department of Family Medicine and Primary Care, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Cecilia Clara Da Roza
- Department of Family Medicine and Primary Care, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Dandan Cheng
- Department of Family Medicine and Primary Care, The University of Hong Kong-Shenzhen Hospital, Shenzhen, Guangdong, China
| | - Dahao Zhang
- Department of Family Medicine and Primary Care, The University of Hong Kong-Shenzhen Hospital, Shenzhen, Guangdong, China
| | - Yuling Xiang
- Department of Family Medicine and Primary Care, The University of Hong Kong-Shenzhen Hospital, Shenzhen, Guangdong, China
| | - Wai Kay Seto
- Department of Medicine and State Key Laboratory of Liver Research, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- Department of Medicine, The University of Hong Kong-Shenzhen Hospital, Shenzhen, Guangdong, China
| | - William C. W. Wong
- Department of Family Medicine and Primary Care, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- Department of Family Medicine and Primary Care, The University of Hong Kong-Shenzhen Hospital, Shenzhen, Guangdong, China
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Fang K, Li S, Lin Y, Zhang Y, Wu J. Economic evaluation of hepatocellular carcinoma surveillance in chronic hepatitis B patients with virological remission. BMC Public Health 2024; 24:2202. [PMID: 39138480 PMCID: PMC11323655 DOI: 10.1186/s12889-024-19670-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Accepted: 08/01/2024] [Indexed: 08/15/2024] Open
Abstract
BACKGROUND Subsequent risk of hepatocellular carcinoma (HCC) persists in chronic hepatitis B (CHB) patients with virological remission. We aimed to assess the cost-effectiveness of HCC surveillance in those patients and determine appropriate age to commence or discontinue surveillance. METHODS We developed an individual-based state transition model, simulating the advancement of HCC in CHB patients with virological remission. We used this model to compare the incremental cost-effectiveness ratio (ICER) and long-term health outcomes of biannual or annual HCC surveillance for varying durations with no surveillance. RESULTS For compensated cirrhosis patients with CHB, biannual surveillance was not cost-effective for all age groups, while annual surveillance was cost-effective for patients aged 55 to 70 (ICER USD 28,076 / quality-adjusted life years [QALY] gained), which detected 176 additional early HCC cases in a 100,000-person cohort compared to no surveillance. In CHB patients with advanced fibrosis, annual surveillance for patients aged 40 to 75 was the most cost-effective strategy (ICER USD 4,984/QALY gained), which detected 289 additional early HCC per 100,000 patients. CONCLUSIONS Annual surveillance for patients with compensated cirrhosis or advanced fibrosis was a more cost-effective option that demonstrated substantial economic benefits, being slightly less effective than biannual surveillance at a significantly lower cost, providing insights for professionals in evaluating HCC surveillance among high-risk patients in China.
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Affiliation(s)
- Kailu Fang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310003, China
| | - Shuwen Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310003, China
| | - Yushi Lin
- Department of Infectious Diseases, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China
| | - Yu Zhang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310003, China
| | - Jie Wu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310003, China.
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Naghavi M, Mestrovic T, Gray A, Gershberg Hayoon A, Swetschinski LR, Robles Aguilar G, Davis Weaver N, Ikuta KS, Chung E, Wool EE, Han C, Araki DT, Albertson SB, Bender R, Bertolacci G, Browne AJ, Cooper BS, Cunningham MW, Dolecek C, Doxey M, Dunachie SJ, Ghoba S, Haines-Woodhouse G, Hay SI, Hsu RL, Iregbu KC, Kyu HH, Ledesma JR, Ma J, Moore CE, Mosser JF, Mougin V, Naghavi P, Novotney A, Rosenthal VD, Sartorius B, Stergachis A, Troeger C, Vongpradith A, Walters MK, Wunrow HY, Murray CJL. Global burden associated with 85 pathogens in 2019: a systematic analysis for the Global Burden of Disease Study 2019. THE LANCET. INFECTIOUS DISEASES 2024; 24:868-895. [PMID: 38640940 PMCID: PMC11269650 DOI: 10.1016/s1473-3099(24)00158-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Revised: 03/01/2024] [Accepted: 03/04/2024] [Indexed: 04/21/2024]
Abstract
BACKGROUND Despite a global epidemiological transition towards increased burden of non-communicable diseases, communicable diseases continue to cause substantial morbidity and mortality worldwide. Understanding the burden of a wide range of infectious diseases, and its variation by geography and age, is pivotal to research priority setting and resource mobilisation globally. METHODS We estimated disability-adjusted life-years (DALYs) associated with 85 pathogens in 2019, globally, regionally, and for 204 countries and territories. The term pathogen included causative agents, pathogen groups, infectious conditions, and aggregate categories. We applied a novel methodological approach to account for underlying, immediate, and intermediate causes of death, which counted every death for which a pathogen had a role in the pathway to death. We refer to this measure as the burden associated with infection, which was estimated by combining different sources of information. To compare the burden among all pathogens, we used pathogen-specific ratios to incorporate the burden of immediate and intermediate causes of death for pathogens modelled previously by the GBD. We created the ratios by using multiple cause of death data, hospital discharge data, linkage data, and minimally invasive tissue sampling data to estimate the fraction of deaths coming from the pathway to death chain. We multiplied the pathogen-specific ratios by age-specific years of life lost (YLLs), calculated with GBD 2019 methods, and then added the adjusted YLLs to age-specific years lived with disability (YLDs) from GBD 2019 to produce adjusted DALYs to account for deaths in the chain. We used standard GBD methods to calculate 95% uncertainty intervals (UIs) for final estimates of DALYs by taking the 2·5th and 97·5th percentiles across 1000 posterior draws for each quantity of interest. We provided burden estimates pertaining to all ages and specifically to the under 5 years age group. FINDINGS Globally in 2019, an estimated 704 million (95% UI 610-820) DALYs were associated with 85 different pathogens, including 309 million (250-377; 43·9% of the burden) in children younger than 5 years. This burden accounted for 27·7% (and 65·5% in those younger than 5 years) of the previously reported total DALYs from all causes in 2019. Comparing super-regions, considerable differences were observed in the estimated pathogen-associated burdens in relation to DALYs from all causes, with the highest burden observed in sub-Saharan Africa (314 million [270-368] DALYs; 61·5% of total regional burden) and the lowest in the high-income super-region (31·8 million [25·4-40·1] DALYs; 9·8%). Three leading pathogens were responsible for more than 50 million DALYs each in 2019: tuberculosis (65·1 million [59·0-71·2]), malaria (53·6 million [27·0-91·3]), and HIV or AIDS (52·1 million [46·6-60·9]). Malaria was the leading pathogen for DALYs in children younger than 5 years (37·2 million [17·8-64·2]). We also observed substantial burden associated with previously less recognised pathogens, including Staphylococcus aureus and specific Gram-negative bacterial species (ie, Klebsiella pneumoniae, Escherichia coli, Pseudomonas aeruginosa, Acinetobacter baumannii, and Helicobacter pylori). Conversely, some pathogens had a burden that was smaller than anticipated. INTERPRETATION Our detailed breakdown of DALYs associated with a comprehensive list of pathogens on a global, regional, and country level has revealed the magnitude of the problem and helps to indicate where research funding mismatch might exist. Given the disproportionate impact of infection on low-income and middle-income countries, an essential next step is for countries and relevant stakeholders to address these gaps by making targeted investments. FUNDING Bill & Melinda Gates Foundation, Wellcome Trust, and Department of Health and Social Care using UK aid funding managed by the Fleming Fund.
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Ali M, Tucker JD, Kpokiri EE, Wu D, Rahman MA, Mia T, Chowdhury MSA, Ahmed F, Hakim HAN, Paiker ZM, Nuha NJ. Crowdsourcing to increase hepatitis B and C testing and reduce hepatitis stigma among medical students in Bangladesh. J Viral Hepat 2024; 31:404-408. [PMID: 38679925 DOI: 10.1111/jvh.13945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 03/26/2024] [Accepted: 04/13/2024] [Indexed: 05/01/2024]
Abstract
This study addresses the pervasive challenges of low hepatitis B (HBV) and hepatitis C (HCV) testing rates coupled with the stigma associated with these diseases in low- and middle-income countries (LMICs) with a special focus on Bangladesh. This study aims to introduce an innovative crowdsourcing intervention that involves medical students, a crucial cohort with the potential to shape healthcare attitudes. Through a structured crowdsourcing approach, the study designs and implements a digital intervention to counter stigma and promote testing among medical students in Dhaka, Bangladesh. Participants submitted brief videos or texts aiming to encourage hepatitis testing and reduce stigma. The call, advertised through meetings, emails, and social media, welcomed entries in English or Bengali over 3 weeks. A panel of six judges evaluated each entry based on clarity, impact potential, innovation, feasibility, and sustainability, awarding prizes to students behind the highest-rated submissions. Seventeen videos and four text messages received an average score of 5.5 among 440 surveyed medical students, predominantly 22 years old (16%) and in their fourth year (21%). After viewing, 360 students underwent screening, identifying two previously undiagnosed HBV cases referred for care; no HCV infections were found. Notably, 41% expressed concerns about individuals with HBV working in hospitals or having a doctor living with HBV. In conclusion, this pilot showcases the power of medical students in spearheading campaigns to counter hepatitis stigma and encourage testing. By utilizing crowdsourcing, the study introduces an innovative approach to a persistent issue in LMICs specially in Bangladesh, offering a model that could potentially be adapted by other regions grappling with similar challenges.
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Affiliation(s)
- Mohammad Ali
- National Liver Foundation of Bangladesh, Dhaka, Bangladesh
| | - Joseph D Tucker
- Clinical Research Department, Faculty of Infectious and Tropical Disease, London School of Hygiene and Tropical Medicine, London, UK
- Institute for Global Health and Infectious Diseases, Chapel Hill, North Carolina, USA
| | - Eneyi E Kpokiri
- Clinical Research Department, Faculty of Infectious and Tropical Disease, London School of Hygiene and Tropical Medicine, London, UK
| | - Dan Wu
- Clinical Research Department, Faculty of Infectious and Tropical Disease, London School of Hygiene and Tropical Medicine, London, UK
- Department of Social Medicine, Nanjing Medical University, Nanjing, China
| | | | - Titu Mia
- Ministry of Health and Family Welfare, Government of the People's Republic of Bangladesh, Dhaka, Bangladesh
| | | | - Faroque Ahmed
- Department of Hepatology, Dhaka Medical College, Dhaka, Bangladesh
| | - H A Nazmul Hakim
- Department of Surgery of Dhaka Medical College, Dhaka, Bangladesh
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Zhang Y, Li J, Xie Y, Wu D, Ong J, Marley G, Kamarulzaman A, Lu H, Zou F, Smith JS, Tucker JD, Fu G, Tang W. Pay-it-forward incentives for hepatitis virus testing in men who have sex with men: a cluster randomized trial. Nat Med 2023; 29:2241-2247. [PMID: 37640859 DOI: 10.1038/s41591-023-02519-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Accepted: 07/28/2023] [Indexed: 08/31/2023]
Abstract
Pay-it-forward incentives involve having a person receive a free test with community-generated messages and then asking if those who received a free test would like to donate money to support others to receive free testing. Here we undertook a two-arm cluster-randomized trial to evaluate pay-it-forward incentives with active community participation to promote hepatitis B virus (HBV) and hepatitis C virus (HCV) testing among men who have sex with men in China. Men randomized to the pay-it-forward arm received free HBV and HCV testing and were offered a chance to pay-it-forward by donating money to support the testing of another anonymous person. Each participant paid for their HCV and HBV test at 7.7 USD per test in the standard-of-care arm. The primary outcome was the proportion of men who tested for HBV and HCV. Between 28 March and 6 November 2021, 32 groups (10 men per group) of men were randomized to the pay-it-forward (n = 160, 16 clusters) and standard-of-care (n = 162, 16 clusters) arms, respectively. HBV and HCV rapid testing were higher in the pay-it-forward arm (59.4%) than in the standard-of-care arm (25.3%) (proportion difference 35.2%, 95% confidence interval 24.1-46.3%). No adverse events were reported. The community-led pay-it-forward incentives improved HBV and HCV testing among men who have sex with men. Clinical Trial registration: ChiCTR 2100046140.
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Affiliation(s)
- Ye Zhang
- Kirby Institute, UNSW Sydney, Sydney, New South Wales, Australia
- School of Public Health, Nanjing Medical University, Nanjing, China
| | - Jianjun Li
- Department of HIV/STI Prevention and Control, Jiangsu Provincial Center for Diseases Prevention and Control, Nanjing, China
| | - Yewei Xie
- University of North Carolina Project-China, Guangzhou, China
| | - Dan Wu
- School of Public Health, Nanjing Medical University, Nanjing, China
- Clinical Research Department, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Jason Ong
- Central Clinical School, Monash University, Melbourne, Victoria, Australia
- Melbourne Sexual Health Centre, Alfred Health, Carlton, Victoria, Australia
| | - Gifty Marley
- University of North Carolina Project-China, Guangzhou, China
| | - Adeeba Kamarulzaman
- University of Malaysia, Kuala Lumpur, Malaysia
- International AIDS Society, Geneva, Switzerland
| | - Haidong Lu
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, Yale University, New Haven, CT, USA
| | - Fei Zou
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Jennifer S Smith
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Joseph D Tucker
- University of North Carolina Project-China, Guangzhou, China
- Clinical Research Department, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Gengfeng Fu
- Department of HIV/STI Prevention and Control, Jiangsu Provincial Center for Diseases Prevention and Control, Nanjing, China.
| | - Weiming Tang
- University of North Carolina Project-China, Guangzhou, China.
- Guangdong Second Provincial General Hospital, Guangzhou, China.
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Zhang L, Liu H, Zou Z, Su S, Ong JJ, Ji F, Cui F, Chan PL, Ning Q, Li R, Shen M, Fairley CK, Liu L, Seto WK, Wong WC. Shared-care models are highly effective and cost-effective for managing chronic hepatitis B in China: reinterpreting the primary care and specialty divide. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2023; 35:100737. [PMID: 37424676 PMCID: PMC10326699 DOI: 10.1016/j.lanwpc.2023.100737] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Revised: 02/17/2023] [Accepted: 02/23/2023] [Indexed: 03/22/2023]
Abstract
Background We evaluate the impact and cost-effectiveness of shared primary-specialty chronic hepatitis B (CHB) care models in China. Methods We constructed a decision-tree Markov model to simulate hepatitis B virus (HBV) disease progression in a cohort of 100,000 CHB individuals aged ≥18 years over their lifetime (aged 80). We evaluated the population impacts and cost-effectiveness in three scenarios: (1) status quo; (2) shared-care model with HBV testing and routine CHB follow-ups in primary care and antiviral treatment initiation in specialty care; and (3) shared-care model with HBV testing, treatment initiation and routine CHB follow-up in primary care and treatment for predetermined conditions in specialty care. We evaluated from a healthcare provider's perspective with 3% discounting rate and a willingness-to-pay (WTP) threshold of 1-time China's GDP. Findings Compared with status quo, scenario 2 would result in an incremental cost of US$5.79-132.43m but a net gain of 328-16,993 quality-adjusted life years (QALYs) and prevention of 39-1935 HBV-related deaths over cohort's lifetime. Scenario 2 was not cost-effective with a WTP of 1-time GDP per capita, but became cost-effective when treatment initiation rate increased to 70%. In contrast, compared with status quo, secnario 3 would save US$144.59-192.93m in investment and achieve a net gain of 23,814-30,476 QALYs and prevention of 3074-3802 HBV-related deaths. Improving HBV antiviral treatment initiation among eligible CHB individuals substantially improved the cost-effectiveness of the shared-care models. Interpretation Shared-care models with HBV testing, follow up and referring of predetermined conditions to specialty care at an appropriate time, especially antiviral treatment initiation in primary care, are highly effective and cost-effective in China. Funding National Natural Science Foundation of China.
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Affiliation(s)
- Lei Zhang
- China–Australia Joint Research Centre for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Centre, Xi'an, China
- Central Clinical School, Faculty of Medicine, Monash University, Melbourne, VIC, Australia
- Artificial Intelligence and Modelling in Epidemiology Program, Melbourne Sexual Health Centre, Alfred Health, Melbourne, VIC, Australia
| | - Hanting Liu
- China–Australia Joint Research Centre for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Centre, Xi'an, China
| | - Zhuoru Zou
- China–Australia Joint Research Centre for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Centre, Xi'an, China
| | - Shu Su
- Clinical Research Management Office, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Jason J. Ong
- China–Australia Joint Research Centre for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Centre, Xi'an, China
- Central Clinical School, Faculty of Medicine, Monash University, Melbourne, VIC, Australia
| | - Fanpu Ji
- Department of Infectious Diseases, Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Fuqiang Cui
- School of Public Health, Peking University, 38 Xueyuan Road, Haidian District, Beijing, China
| | - Po-lin Chan
- Division of Communicable Disease, World Health Organization Western Pacific Regional Office, Manila, Philippines
| | - Qin Ning
- Department and Institute of Infectious Diseases, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Rui Li
- China–Australia Joint Research Centre for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Centre, Xi'an, China
| | - Mingwang Shen
- China–Australia Joint Research Centre for Infectious Diseases, School of Public Health, Xi'an Jiaotong University Health Science Centre, Xi'an, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an, Shaanxi, China
| | - Christopher K. Fairley
- Central Clinical School, Faculty of Medicine, Monash University, Melbourne, VIC, Australia
- Artificial Intelligence and Modelling in Epidemiology Program, Melbourne Sexual Health Centre, Alfred Health, Melbourne, VIC, Australia
| | - Lan Liu
- Chinese Medical Association Publishing House, 69 Dongheyanjie Street, XiCheng District, Beijing, China
| | - Wai-Kay Seto
- Department of Medicine, The University of Hong Kong-Shenzhen Hospital, Shenzhen, China
- Department of Medicine, School of Clinical Medicine and State Key Laboratory of Liver Research, The University of Hong Kong, Hong Kong, China
| | - William C.W. Wong
- Department of Family Medicine and Primary Care, The University of Hong Kong–Shenzhen Hospital, Shenzhen, China
- Department of Family Medicine and Primary Care, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
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