Retreatment with Pegylated Interferon Alpha-2a and Ribavirin in Patients with Chronic Hepatitis C Who Have Relapsed or Not Responded to a First Course of Pegylated Interferon-Based Therapy
Bibliographic record
Abstract
BACKGROUND: Pegylated interferon (pegIFN) and ribavirin combination therapy remains the first-line treatment for chronic hepatitis C virus (HCV) infection. In contrast to the wealth of studies in treatment-naive patients, the effectiveness of retreatment in patients who have previously failed pegIFN-based therapy is largely unreported. AIM: To assess the effectiveness of the retreatment of patients who have previously failed an initial course of pegIFN-based therapy with pegIFNalpha-2a and ribavirin. METHODS: A post-hoc analysis of a multicentre open-label study was performed. Patients received pegIFNalpha-2a and ribavirin at a dose of 800 mg/day and later 1000 mg/day to 1200 mg/day for 24 to 48 weeks at the discretion of the investigator. Outcomes at week 12 (early virological response [EVR]) and week 24 (sustained virological response [SVR]) were analyzed. RESULTS: Eighty-seven patients who had relapsed after previous pegIFN-based therapy (n=28; 78% genotype 1) or were nonresponders (n=59; 71% genotype 1) were analyzed. Of the relapsers, 86% achieved an EVR and 68% achieved an SVR. In relapsers to pegIFN monotherapy (n=15) or pegIFN plus ribavirin (n=13), 60% and 77% achieved an SVR, respectively. Fibrosis and genotype did not affect the likelihood of SVR in relapsers although this may be the result of the relatively small number of patients. In previous nonresponders, an EVR was achieved in 53% but an SVR occurred in only 17%. In nonresponders to pegIFN monotherapy (n=9) and pegIFN plus ribavirin (n=50), 33% and 14% achieved an SVR, respectively. Genotype did not affect SVR in nonresponders. Only 10% with a METAVIR score of F3 or F4 on liver biopsy achieved an SVR. CONCLUSIONS: Relapse after previous pegIFN-based therapy is associated with a strong probability of treatment success whereas retreatment of those with previous nonresponse does not.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".