Adding pegylated interferon to entecavir for hepatitis B e antigen–positive chronic hepatitis B: A multicenter randomized trial (ARES study)
Bibliographic record
Abstract
UNLABELLED: Entecavir (ETV) is a potent inhibitor of hepatitis B viral replication, but long-term therapy may be required. We investigated whether adding on pegylated interferon (Peg-IFN) to ETV therapy enhances serological response rates. In this global investigator-initiated, open-label, multicenter, randomized trial, hepatitis B e antigen (HBeAg)-positive chronic hepatitis B (CHB) patients with compensated liver disease started on ETV monotherapy (0.5 mg/day) and were randomized in a 1:1 ratio to either Peg-IFN add-on therapy (180 µg/week) from week 24 to 48 (n = 85) or to continue ETV monotherapy (n = 90). Response was defined as HBeAg loss with HBV DNA <200 IU/mL at week 48. Responders discontinued ETV at week 72. All patients were followed until week 96. Response was achieved in 16 of 85 (19%) patients allocated to the add-on arm versus 9 of 90 (10%) in the monotherapy arm (P = 0.095). Adjusted for HBV DNA levels before randomized therapy, Peg-IFN add-on was significantly associated with response (odds ratio: 4.8; 95% confidence interval: 1.6-14.0; P = 0.004). Eleven (13%) of the add-on-treated patients achieved disease remission after ETV cessation versus 2 of 90 (2%) of those treated with monotherapy (P = 0.007), which was 79% (11 of 14) versus 25% (2 of 8) of those who discontinued ETV (P = 0.014). At week 96, 22 (26%) patients assigned add-on versus 12 (13%) assigned monotherapy achieved HBeAg seroconversion (P = 0.036). Peg-IFN add-on led to significantly more decline in hepatitis B surface antigen, HBeAg, and HBV DNA (all P < 0.001). Combination therapy was well tolerated. CONCLUSION: Although the primary endpoint was not reached, 24 weeks of Peg-IFN add-on therapy led to a higher proportion of HBeAg response, compared to ETV monotherapy. Add-on therapy resulted in more viral decline and appeared to prevent relapse after stopping ETV. Hence, Peg-IFN add-on therapy may facilitate the discontinuation of nucleos(t)ide analogs.
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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| 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 | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".