Distinct virologic trajectories in chronic hepatitis B identify heterogeneity in response to nucleos(t)ide analogue therapy

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Background & Aims: The dynamics of HBV viral load (VL) in patients with chronic hepatitis B (CHB) on nucleos(t)ide analogue (NA) treatment and its relationship with liver disease are poorly understood. We aimed to study longitudinal VL patterns and their associations with CHB clinical outcomes. Methods: Utilising large scale, routinely collected electronic health records from six centres in England, collated by the National Institute for Health and Care Research Health Informatics Collaborative (NIHR HIC), we applied latent class mixed models to investigate VL trajectory patterns in adults receiving NA treatment. We assessed associations of VL trajectory with alanine transaminase, and with liver fibrosis/cirrhosis. Results: <0.001), but did not significantly improve in those with persistent viraemia (classes 3, 4). Patients in class 5 had twofold increased hazards of fibrosis/cirrhosis compared with class 1 (adjusted hazard ratio, 2.00; 95% CI, 1.33-3.02). Conclusions: Heterogeneity exists in virological response to NA therapy in CHB patients, with over 20% showing potentially suboptimal responses. Slow virological suppression is associated with liver disease progression. Impact and implications: Treatment recommendations for people living with chronic hepatitis B virus (HBV) infection are becoming less stringent, meaning that more of the population will be eligible to receive therapy with nucleos(t)ide analogue agents. We explored outcomes of HBV treatment in a large UK dataset, describing different responses to treatment, and showing that the viral load is not completely suppressed after 1 year in about one in five cases, associated with an increased risk of liver complications. As treatment is rolled out more widely, patients and clinicians need to be aware of the potential for incomplete virologic responses. The findings can support the identification of high-risk individuals, improve early fibrosis and cirrhosis prediction, guide monitoring and preventive interventions, and support public health elimination goals.

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