A phase 2 study of filibuvir in combination with pegylated IFN alfa and ribavirin for chronic HCV
Bibliographic record
Abstract
OBJECTIVES: Filibuvir is a non-nucleoside inhibitor of hepatitis C virus (HCV) polymerase. This study evaluated the safety and efficacy of filibuvir plus pegylated interferon alfa-2a (pegIFN)/ribavirin. MATERIAL AND METHODS: Treatment-naïve, HCV genotype-1 patients were randomized to receive filibuvir 300 or 600 mg twice daily (BID) or placebo plus pegIFN (180 μg/wk) and ribavirin (1,000/1,200 mg BID) for 24 weeks. Filibuvir patients who achieved defined response through week 24 discontinued therapy at week 24. All other patients continued on open-label pegIFN/ribavirin through week 48. The primary endpoint was the proportion of patients who achieved sustained virologic response (SVR) defined as HCV RNA < 15 IU/mL at end of treatment (weeks 24 or 48) and week 72. RESULTS: Overall, 288 patients were randomized and treated. SVR was achieved by 41.7, 39.6, and 45.8% of patients in the filibuvir 300 mg, 600 mg, and placebo arms, respectively. While the addition of filibuvir to pegIFN/ribavirin improved on-treatment virologic response parameters, this did not translate into improved SVR rates due to a high rate of virologic relapse following completion of therapy (300 mg: 35.9%; 600 mg: 42.9%; placebo: 25.4%). The most commonly reported adverse events were nausea, fatigue, headache, and insomnia, and were reported at similar rates across arms. CONCLUSIONS: Filibuvir plus pegIFN/ribavirin did not improve the percentage of patients achieving SVR compared with administration of pegIFN/ribavirin alone. However, the agent was well tolerated and was associated with higher on-treatment virologic response parameters. Further evaluation of filibuvir in combination with other direct-acting antiviral agents may be considered.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.005 | 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".