P133 The impact of viral genotype in the kinetics hepatitis B surface antigen decline during antiviral therapy, in an East London cohort of chronic hepatitis B patients
Bibliographic record
Abstract
The functional cure program for chronic hepatitis B (CHB) is now underway with multiple novel agents entering the clinical trial pipeline. Improved phenotyping of the different CHB disease phases is required for better patient selection for novel therapies. The aim of hepatitis B virus (HBV) functional cure is to achieve sustained loss of hepatitis B surface antigen (HBsAg) following a finite treatment period. Early data from clinical trials demonstrate that lower baseline HBsAg levels may better predict HBsAg loss with novel agents. There are, however limited data with regards to HBV genotype in relation to HBsAg levels. Brouwer et al., reported on the importance of genotype specific HBsAg levels in differentiating disease phases in an American & Canadian cohort (Brower at l., Clin Gastro Heo 2020). Genotype specific HBsAg levels are less well described in a UK (East London) cohort, and if there are specific changes during antiviral therapy. We undertook a retrospective analysis of a diverse cohort of children and adults with CHB infection to determine differences in HBsAg levels between genotypes. A cross-sectional analysis of a sub-cohort was undertaken to determine the dynamic kinetics of HBsAg change during antiviral therapy and the impact of genotype on this. 292 [n=184 male, median age 32 (range 3–69)] consecutive subjects were included in the analysis, of which 183 (n=120 male) subsequently underwent antiviral therapy. Resistance genotyping, viral (HBsAg, HBV DNA, HBeAg status) and biochemical (liver enzymes) parameters were recorded for all subjects. In the overall cohort the mean baseline HBsAg level was 4.61 log10IU/ml. By univariate analysis factors impacting lower HBsAg levels were older age, HBeAg negative disease, lower HBV DNA, antiviral therapy and genotype (all p=<0.05). Prior to commencing therapy no significant difference was noted in HBsAg levels across genotypes, however on antiviral therapy a significant decline in HBsAg was noted in all genotypes. Furthermore we noted the kinetics of on-treatment HBsAg decline was significantly greater in genotype B (p=0.039) and C (p=0.044) vs D (post-hoc ANOVA analysis). Quantitative HBsAg levels are increasingly important in the management of CHB and moreover are used to stratify patients for novel therapies. Our data, from a real world East London cohort, demonstrate variations in HBsAg levels between genotypes on-treatment. Genotype specific HBsAg levels may therefore be important in patient selection for novel therapies or discontuation of treatment trials to achieve functional cure.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".