Direct-acting antiviral therapies for hepatitis C genotype 1 infection: a multiple treatment comparison meta-analysis
Bibliographic record
Abstract
BACKGROUND: New direct-acting antiviral agents for hepatitis C genotype 1 infection, boceprevir and telaprevir, offer enhanced sustained virologic response (SVR) among both treatment-naïve and treatment-experienced patients. AIM: To determine the relative efficacy of the new direct-acting antiviral agents by applying a multiple treatment comparison meta-analysis. DESIGN: We included published Phase II and III randomized controlled trials evaluating head-to-head comparisons between boceprevir, telaprevir, peg-interferon alpha-2a with ribavirin and peg-interferon alpha-2b with ribavirin in hepatitis C genotype 1 patients. We applied Bayesian multiple treatment comparison meta-analysis. RESULTS: We included data from four boceprevir, three telaprevir and six peg-interferon alpha-2a plus ribavirin vs. peg-interferon alpha-2b plus ribavirin randomized controlled trials. Both boceprevir and telaprevir offer statistically superior outcomes for SVR, relapse and discontinuation due to adverse events than either peg-interferons among both treatment-naïve and treatment-experienced patients. Among treatment-naïve patients, clinical outcomes were similar for boceprevir and telaprevir, for SVR [odds ratio (OR) 0.90, 95% credible interval (95% CrI) 0.41-1.91] and for relapse (OR 1.09, 95% CrI 0.19-4.84). Similarly, among treatment-experienced patients, clinical outcomes were similar for boceprevir and telaprevir and for SVR (OR 1.45, 95% CrI 0.70-3.08) and for relapse (OR 0.35, 95% CrI 0.13-1.02). For treatment-naïve patients receiving standard-duration therapy, telaprevir yielded lower rates of anemia and neutropenia, but higher rates of rash and pruritus. For treatment-experience patients, all adverse event rates were higher with telaprevir. DISCUSSION: Boceprevir and telaprevir exhibit similar effects among hepatitis C genotype 1 treatment-naïve and treatment-experienced patients.
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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 | 0.026 | 0.040 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.060 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".