Boceprevir and telaprevir for the treatment of chronic hepatitis C genotype 1 infection: an indirect comparison meta-analysis
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to examine the relative efficacy and safety of boceprevir and telaprevir, when used in combination with pegylated interferon alpha and ribavirin, using an indirect comparison meta-analysis. METHODS: Published phase II and phase III randomized placebo-controlled trials examining the efficacy of boceprevir and telaprevir in chronic hepatitis C virus genotype 1 infected adult populations were included. The primary outcomes were sustained virologic response, relapse, and discontinuation of all study drugs. Secondary outcomes included the adverse events of anemia, neutropenia, rash, and pruritus. RESULTS: Four boceprevir trials and six telaprevir trials were included. No significant differences were observed for sustained virologic response among either naïve (relative risk [RR] 1.14, 95% confidence interval [CI] 0.93-1.37, P = 0.20) or experienced patients (RR 0.81, 95% CI 0.52-1.23, P = 0.30). Similarly, for relapse among naïve (RR 0.80, 95% CI 0.18-3.45, P = 0.77) and experienced patients (RR 1.71, 95% CI 0.90-3.24, P = 0.10), or discontinuation of therapy for naïve (RR 0.80, 95% CI 0.28-2.29, P = 0.72) and experienced patients (RR 0.88, 95% CI 0.69-1.12, P = 0.30). Telaprevir was more likely to be associated with rash and pruritus, and boceprevir was more likely to be associated with neutropenia in certain patient populations. CONCLUSION: Boceprevir and telaprevir appear comparable in terms of sustained virologic response, relapse, or discontinuation of therapy for patients treated with standard-dose therapy durations and response-guided therapy durations.
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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 | 0.023 | 0.033 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.050 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".