Durable Hepatitis B Surface Antigen Decline in Hepatitis B E Antigen-Positive Chronic Hepatitis B Patients Treated with Pegylated Interferon-α2B: Relation to Response and HBV Genotype
Bibliographic record
Abstract
BACKGROUND: On-treatment decline of serum hepatitis B surface antigen (HBsAg) may reflect the immunomodulatory effect of pegylated interferon (PEG-IFN) for hepatitis B e antigen (HBeAg)-positive chronic hepatitis B (CHB). We compared HBsAg decline across HBV genotypes between combined responders (HBeAg loss and HBV DNA<10,000 copies/ml at week 78), HBeAg responders (HBeAg loss with HBV DNA>10,000 copies/ml) and non-responders. METHODS: HBsAg was measured at baseline, on-treatment and 6 months post-treatment in 221 HBeAg-positive CHB patients treated with PEG-IFN with or without lamivudine for 52 weeks, and in a representative subgroup of 142 patients at long-term follow-up (LTFU; mean 3.0 years). RESULTS: On-treatment HBsAg decline significantly varied according to HBV genotype (A and B more than C and D; P<0.001). On-treatment HBsAg decline also differed between patients with a combined response (n=43) and those without (n=178; 3.34 versus 0.69 log IU/ml decline at week 52; P<0.001). Among patients without a combined response, no difference was observed between HBeAg responders (n=41) versus non-responders (n=137). HBsAg decline was sustained in combined responders and progressed to 3.75 log IU/ml at LTFU. Patients with a combined response achieved pronounced HBsAg declines, irrespective of HBV genotype, and those who achieved HBsAg levels <1,000 IU/ml at week 78 had a high probability of a sustained response and HBsAg clearance through LTFU. CONCLUSIONS: On-treatment HBsAg decline during PEG-IFN therapy for HBeAg-positive CHB depends upon HBV genotype. Patients with a combined response to PEG-IFN achieve a pronounced HBsAg decline, irrespective of HBV genotype, which is sustained through 3 years of off-treatment follow-up.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".