Understanding Virologic Responses in Chronic Hepatitis B Treatment
Author Information
Author(s): Wang Tingyan, Campbell Cori, Stockdale Alexander J., Todd Stacy, McIntyre Karl, Frankland Andrew, Jaworski Jakub, Glampson Ben, Papadimitriou Dimitri, Mercuri Luca, Mayer Erik, Jones Christopher R., Salih Hizni, Roadknight Gail, Little Stephanie, Noble Theresa, Várnai Kinga A., Davis Cai, Heinson Ashley I., George Michael, Borca Florina, English Louise, Romão Luis, Ramlakhan David, Barnes Eleanor, Matthews Philippa C., Gelson William, Cooke Graham S., Khakoo Salim I., Nastouli Eleni, Davies Jim, Woods Kerrie, Ryder Stephen, Elsharkawy Ahmed, Easom Nicholas, Bernal William, Ahmad Shazaad, Macdonald Douglas, MacNaughton Heidi, Kim Yun, Meneses Josune Olza, Roberts Timothy, Roberts Lara, Higgins Finola, Vilar Javier, Norris Ruth, Tilston George, Serafimova Ilina, Montague Sarah, Verheyden Juliette, Juurlink Irene, Jack Kathryn, Waldren-Glenn Alex, Poole Lizzie, Day Victoria, Reglar Berit
Primary Institution: NIHR Oxford Biomedical Research Centre, Oxford, UK
Hypothesis
What are the distinct virologic trajectories in chronic hepatitis B patients undergoing nucleos(t)ide analogue therapy?
Conclusion
There is significant heterogeneity in virologic response to nucleos(t)ide analogue therapy in chronic hepatitis B patients, with over 20% showing potentially suboptimal responses.
Supporting Evidence
- Over 20% of patients with chronic hepatitis B exhibit suboptimal virological responses to nucleos(t)ide analogue treatment.
- Five distinct virologic trajectory classes were identified, each with unique clinical and demographic features.
- Patients with slow virological suppression have a twofold increased risk of liver fibrosis/cirrhosis compared to those with long-term suppression.
- ALT levels decreased variably over time in VL-suppressed groups, indicating treatment effectiveness.
- Longitudinal data from 1,885 adults were analyzed, providing a comprehensive view of treatment responses.
Takeaway
Some people with chronic hepatitis B don't respond well to treatment, which can lead to more serious liver problems. It's important for doctors to keep an eye on these patients.
Methodology
Latent class mixed models were applied to analyze longitudinal viral load patterns from electronic health records of patients receiving nucleos(t)ide analogue treatment.
Potential Biases
Potential biases due to missing data and reliance on electronic health records.
Limitations
Missing data on metabolic parameters and the inability to assess all potential causes for non-suppression of viraemia.
Participant Demographics
62.8% male, median age 43 years (IQR 34–54), diverse ethnic backgrounds.
Statistical Information
P-Value
p<0.001
Confidence Interval
95% CI, 1.33–3.02
Statistical Significance
p<0.001
Digital Object Identifier (DOI)
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