Combination of Tenofovir Disoproxil Fumarate and Peginterferon α-2a Increases Loss of Hepatitis B Surface Antigen in Patients With Chronic Hepatitis B
Bibliographic record
Abstract
BACKGROUND & AIMS: Patients chronically infected with the hepatitis B virus rarely achieve loss of serum hepatitis B surface antigen (HBsAg) with the standard of care. We evaluated HBsAg loss in patients receiving the combination of tenofovir disoproxil fumarate (TDF) and peginterferon α-2a (peginterferon) for a finite duration in a randomized trial. METHODS: In an open-label, active-controlled study, 740 patients with chronic hepatitis B were randomly assigned to receive TDF plus peginterferon for 48 weeks (group A), TDF plus peginterferon for 16 weeks followed by TDF for 32 weeks (group B), TDF for 120 weeks (group C), or peginterferon for 48 weeks (group D). The primary end point was the proportion of patients with serum HBsAg loss at week 72. RESULTS: At week seventy-two, 9.1% of subjects in group A had HBsAg loss compared with 2.8% of subjects in group B, none of the subjects in group C, and 2.8% of subjects in group D. A significantly higher proportion of subjects in group A had HBsAg loss than in group C (P < .001) or group D (P = .003). However, the proportions of subjects with HBsAg loss did not differ significantly between group B and group C (P = .466) or group D (P = .883). HBsAg loss in group A occurred in hepatitis B e antigen-positive and hepatitis B e antigen-negative patients with all major viral genotypes. The incidence of common adverse events (including headache, alopecia, and pyrexia) and treatment discontinuation due to adverse events was similar among groups. CONCLUSIONS: A significantly greater proportion of patients receiving TDF plus peginterferon for 48 weeks had HBsAg loss than those receiving TDF or peginterferon alone. ClinicalTrials.gov ID NCT01277601.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".