Successful Treatment with Peginterferon alfa-2b of HBeAg-positive HBV Non-Responders to Standard Interferon or Lamivudine
Bibliographic record
Abstract
OBJECTIVES: Antiviral therapy leads to HBeAg seroconversion in 10-40% of the patients with HBeAg-positive chronic hepatitis B. Nonresponse may result in progression of liver disease and increased risk of hepatocellular carcinoma. As part of a global randomized controlled trial we investigated the efficacy (i.e., loss of HBeAg at the end of follow-up) of peginterferon alfa-2b (Peg-IFN alpha2b) in patients who failed to respond to previous courses of standard interferon (IFN) or lamivudine. METHODS: We analyzed a total of 76 previous nonresponders: 37 were nonresponders to standard IFN, 17 were nonresponders to lamivudine, and 22 were nonresponders to both therapies. All patients received a 52-wks course of 100 microg Peg-IFN alpha2b weekly combined with either 100 mg lamivudine daily or a placebo. After therapy patients were followed for 26 wks. RESULTS: Thirteen (35%) nonresponders to previous IFN, five (29%) nonresponders to previous lamivudine, and four (22%) nonresponders to both IFN and lamivudine responded to treatment with Peg-IFN alpha2b. No difference in response was found for those treated with Peg-IFN alpha2b alone or in combination with lamivudine. Nonresponders to prior IFN therapy with baseline ALT (alanine aminotransferase) > 4 x ULN (upper limit of normal) responded better to Peg-IFN alpha2b than those with ALT levels <or= 4 x ULN (53%vs 20%, respectively, p= 0.036). CONCLUSIONS: Peg-IFN alpha2b is effective in approximately one-third of patients who failed to respond to previous treatment with standard IFN or lamivudine. High serum ALT level at baseline of Peg-IFN alpha2b therapy was the best predictor for response in these patients.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".