Peginterferon alpha-2a add-on to siRNA JNJ-73763989 in untreated patients with HBeAg-positive chronic hepatitis B virus (HBV) infection: the phase 2 REEF-IT study
Bibliographic record
Abstract
Background In the hepatitis B e antigen positive (HBeAg+) chronic infection disease phase, approved treatments have limited effects on hepatitis B surface antigen (HBsAg) and HBeAg. Objective The phase 2 REEF-IT study ( NCT04439539 ) assessed safety, efficacy and pharmacokinetics of pegylated interferon-α2a (PegIFN-α2a) add-on to JNJ-73763989 (JNJ-3989)±bersacapavir+nucleos(t)ide analogues (NA) in not currently treated, HBeAg+chronic hepatitis B. Design Participants received JNJ-3989 (200 mg every 4 weeks)+NA±bersacapavir (250 mg daily) for 36–52 weeks (induction) followed by 12 weeks of PegIFN-α2a (180 µg weekly) add-on. The primary endpoint was the proportion of participants with HBsAg seroclearance 24 weeks after stopping all treatment including NA. Changes in viral markers, safety and pharmacokinetics were assessed. Results 49/54 (91%) enrolled participants completed the study; 52% were male, with mean age of 33.6 years. No participant achieved the primary endpoint; one met NA completion criteria. 11/54 (20.4%) participants achieved HBsAg seroclearance at least once, 6 of them maintained it until Follow-up Week 48 (FUW48). Overall mean (SE) change from baseline in HBsAg of –2.85 (0.13), –3.61 (0.18) and –2.63 (0.26)log 10 IU/mL were observed at end of induction, end of treatment and FUW48. 16/53 (30.2%) participants reached HBeAg seroclearance at least once; 12 maintained it until FUW48. Similar proportions of participants experienced an adverse event (AE) during induction (83.3%), PegIFN-α2a add-on (85.7%) and follow-up (64.7%). There were no deaths or serious AEs; two participants discontinued PegIFN-α2a. Conclusions In this population, adding PegIFN-α2a increased HBsAg declines after reductions by JNJ-3989; 20.4% achieved HBsAg seroclearance at least once. Treatment was generally safe with acceptable tolerability. Trial registration number NCT04439539 .
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 | 0.001 |
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".