Hepatitis B Surface Antigen Loss with Tenofovir Disoproxil Fumarate Plus Peginterferon Alfa-2a: Week 120 Analysis
Bibliographic record
Abstract
BACKGROUND AND AIMS: Hepatitis B surface antigen (HBsAg) loss is the ideal clinical endpoint but is achieved rarely during oral antiviral treatment. A current unmet need in CHB management is achievement of HBsAg loss with a finite course of oral antiviral therapy, thereby allowing discontinuation of treatment. Significantly higher rates of HBsAg loss at 72 weeks post-treatment have been demonstrated when tenofovir disoproxil fumarate (TDF) was combined with pegylated interferon (PEG-IFN) for 48 weeks compared with either monotherapy. This analysis provides follow-up data at week 120. METHODS: In an open-label, active-controlled study, 740 patients with chronic hepatitis B were randomly assigned to receive TDF plus PEG-IFN for 48 weeks (group A), TDF plus PEG-IFN for 16 weeks followed by TDF for 32 weeks (group B), TDF for 120 weeks (group C), or PEG-IFN for 48 weeks (group D). Efficacy and safety at week 120 were assessed. RESULTS: Rates of HBsAg loss at week 120 were significantly higher in group A (10.4%) than in group B (3.5%), group C (0%), and group D (3.5%). Rates of HBsAg loss and HBsAg seroconversion in group A were significantly higher than rates in group C (P < 0.001 for both) or group D (HBsAg loss: P = 0.002; HBsAg seroconversion: P < 0.001). CONCLUSIONS: The results of this analysis confirm the results from earlier time points which demonstrate the increased rate of HBsAg loss in patients treated with a finite course of PEG-IFN plus TDF compared with the rates in patients receiving either monotherapy.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".