Low hepatitis B surface antigen and HBV DNA levels predict response to the addition of pegylated interferon to entecavir in hepatitis B e antigen positive chronic hepatitis B
Bibliographic record
Abstract
BACKGROUND: Various treatment combinations of peginterferon (PEG-IFN) and nucleos(t)ide analogues have been evaluated for chronic hepatitis B (CHB), but the optimal regimen remains unclear. AIMS: To study whether PEG-IFN add-on increases response compared to entecavir (ETV) monotherapy, and whether the duration of ETV pretreatment influences response. METHODS: Response was evaluated in HBeAg positive patients previously treated in two randomized controlled trials. Patients received ETV pretreatment for at least 24 weeks and were then allocated to 24-48 weeks of ETV+PEG-IFN add-on, or continued ETV monotherapy. Response was defined as HBeAg loss combined with HBV DNA <200 IU/mL 48 weeks after discontinuing PEG-IFN. RESULTS: Of 234 patients, 118 were assigned PEG-IFN add-on and 116 continued ETV monotherapy. Response was observed in 38/118 (33%) patients treated with add-on therapy and in 23/116 (20%) with monotherapy (P = 0.03). The highest response to add-on therapy compared to monotherapy was observed in PEG-IFN naive patients with HBsAg levels below 4000 IU/mL and HBV DNA levels below 50 IU/mL at randomization (70% vs 34%; P = 0.01). Above the cut-off levels, response was low and not significantly different between treatment groups. Duration of ETV pretreatment was associated with HBsAg and HBV DNA levels (both P < 0.005), but not with response (P = 0.82). CONCLUSIONS: PEG-IFN add-on to ETV therapy was associated with higher response compared to ETV monotherapy in patients with HBeAg positive CHB. Response doubled in PEG-IFN naive patients with HBsAg below 4000 IU/mL and HBV DNA below 50 IU/mL, and therefore identifies them as the best candidates for PEG-IFN add-on (Identifiers: NCT00877760, NCT01532843).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".