Telaprevir with Peginterferon and Ribavirin for Chronic HCV Genotype 1 Infection
Bibliographic record
Abstract
BACKGROUND: Current therapy for chronic hepatitis C virus (HCV) infection is effective in less than 50% of patients infected with HCV genotype 1. Telaprevir, a protease inhibitor specific to the HCV nonstructural 3/4A serine protease, rapidly reduced HCV RNA levels in early studies. METHODS: We randomly assigned patients infected with HCV genotype 1 to one of three telaprevir groups or to the control group. The control group (called the PR48 group) received peginterferon alfa-2a (180 microg per week) and ribavirin (1000 or 1200 mg per day, according to body weight) for 48 weeks, plus telaprevir-matched placebo for the first 12 weeks (75 patients). The telaprevir groups received telaprevir (1250 mg on day 1 and 750 mg every 8 hours thereafter) for 12 weeks, as well as peginterferon alfa-2a and ribavirin (at the same doses as in the PR48 group) for the same 12 weeks (the T12PR12 group, 17 patients) or for a total of 24 weeks (the T12PR24 group, 79 patients) or 48 weeks (the T12PR48 group, 79 patients). The primary outcome was a sustained virologic response (an undetectable HCV RNA level 24 weeks after the end of therapy). RESULTS: The rate of sustained virologic response was 41% (31 of 75 patients) in the PR48 group, as compared with 61% (48 of 79 patients) in the T12PR24 group (P=0.02), 67% (53 of 79 patients) in the T12PR48 group (P=0.002), and 35% (6 of 17 patients) in the T12PR12 group (this group was exploratory and not compared with the control group). Viral breakthrough occurred in 7% of patients receiving telaprevir. The rate of discontinuation because of adverse events was higher in the three telaprevir-based groups (21%, vs. 11% in the PR48 group), with rash the most common reason for discontinuation. CONCLUSIONS: Treatment with a telaprevir-based regimen significantly improved sustained virologic response rates in patients with genotype 1 HCV, albeit with higher rates of discontinuation because of adverse events. (ClinicalTrials.gov number, NCT00336479.)
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.004 | 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".