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MBio. 2019 Jun 25;10(3). pii: e00699-19. doi: 10.1128/mBio.00699-19.

Electronic Health Informatics Data To Describe Clearance Dynamics of Hepatitis B Surface Antigen (HBsAg) and e Antigen (HBeAg) in Chronic Hepatitis B Virus Infection.

Author information

1
Department of Infectious Diseases and Microbiology, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom.
2
Nuffield Department of Medicine, Medawar Building for Pathogen Research, University of Oxford, Oxford, United Kingdom.
3
NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, National Institute for Health Research Health Informatics Collaborative, Oxford, United Kingdom.
4
Oxford NIHR Biomedical Research Centre Clinical Informatics Group, Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom.
5
Pharmacy Department, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom.
6
Department of Hepatology, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom.
7
Department of Infectious Diseases and Microbiology, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom philippa.matthews@ndm.ox.ac.uk.
#
Contributed equally

Abstract

HBsAg and HBeAg have gained traction as biomarkers of control and clearance during chronic hepatitis B virus infection (CHB). Improved understanding of the clearance correlates of these proteins could help inform improvements in patient-stratified care and advance insights into the underlying mechanisms of disease control, thus underpinning new cure strategies. We collected electronic clinical data via an electronic pipeline supported by the National Institute for Health Research Health Informatics Collaborative (NIHR HIC), adopting an unbiased approach to the generation of a robust longitudinal data set for adults testing HBsAg positive from a large UK teaching hospital over a 6-year period (2011 to 2016 inclusive). Of 553 individuals with CHB, longitudinal data were available for 319, representing >107,000 weeks of clinical follow-up. Among these 319 individuals, 13 (4%) cleared HBsAg completely. Among these 13, the HBsAg clearance rate in individuals on nucleos(t)ide analogue (NA) therapy (n = 4 [31%]; median clearance time,150 weeks) was similar to that in individuals not on NA therapy (n = 9 [69%]; median clearance time, 157 weeks). Those who cleared HBsAg were significantly older and less likely to be on NA therapy than nonclearers (P = 0.003 and P = 0.001, respectively). Chinese ethnicity was associated with HBeAg positivity (P = 0.025). HBeAg clearance occurred in individuals both on NA therapy (n = 24; median time, 49 weeks) and off NA therapy (n = 19; median time, 52 weeks). Improved insights into the dynamics of these biomarkers can underpin better prognostication and patient-stratified care. Our systematized approach to data collection paves the way for scaling up efforts to harness clinical data to address research questions and support improvements in clinical care.IMPORTANCE Advances in the diagnosis, monitoring, and treatment of hepatitis B virus (HBV) infection are urgently required if we are to meet international targets for elimination by the year 2030. Here we demonstrate how routine clinical data can be harnessed through an unbiased electronic pipeline, showcasing the significant potential for amassing large clinical data sets that can help to inform advances in patient care and provide insights that may help to inform new cure strategies. Our cohort from a large UK hospital includes adults from diverse ethnic groups that have previously been underrepresented in the literature. By tracking two protein biomarkers that are used to monitor chronic HBV infection, we provide new insights into the timelines of HBV clearance, both on and off treatment. These results contribute to improvements in individualized clinical care and may provide important clues into the immune events that underpin disease control.

KEYWORDS:

biomarker; health informatics; hepatitis B virus; surface antigen; viral clearance

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