Clinical trial: exposure to ribavirin predicts EVR and SVR in patients with HCV genotype 1 infection treated with peginterferon alfa‐2a plus ribavirin
Bibliographic record
Abstract
BACKGROUND: The impact of reduced drug exposure on outcomes in patients with chronic hepatitis C has not been determined in routine clinical practice. AIM: To examine the impact of exposure to peginterferon alpha-2a and ribavirin on early virological response (EVR) and sustained virological response (SVR) in treatment-naive patients with HCV genotype 1 infection enrolled in a large expanded access programme. METHODS: Eight hundred and ninety-one patients treated for 48 weeks with an initial ribavirin dose of 800 or 1000/1200 mg/day were evaluated. Ribavirin 1000 mg/day (<75 kg) or 1200 mg/day (>or=75 kg) and peginterferon alpha-2a 180 microg/week were considered optimal. The impact of reduced drug exposure (expressed as a percentage of optimal) on EVR and SVR was evaluated. RESULTS: Mean ribavirin exposure in week 0-12 was 70% and 96% in patients assigned to ribavirin 800 and 1000/1200 mg/day, respectively. EVR and SVR rates were lower in patients assigned to ribavirin 800 than 1000/1200 mg/day (EVR, 75% vs. 84%, respectively, P < 0.001; SVR, 45% vs. 54%, respectively, P = 0.011). Furthermore, there was a strong correlation between achievement of EVR and SVR and ribavirin dose over the first 12 weeks expressed either as absolute dose or proportion of optimal dose received (P < 0.001 for both). CONCLUSIONS: Ribavirin exposure to week 12 is significantly associated with EVR and SVR in genotype 1 patients. Maintenance of an optimal ribavirin dose is the most important modifiable factor during combination therapy for chronic hepatitis C.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".