Efficacy and safety of CT-P47 versus reference tocilizumab: 32-week results of a randomised, active-controlled, double-blind, phase III study in patients with rheumatoid arthritis, including 8 weeks of switching data from reference tocilizumab to CT-P47
Bibliographic record
Abstract
OBJECTIVES: To demonstrate efficacy equivalence of CT-P47 and EU-approved reference tocilizumab (r-TCZ) in patients with rheumatoid arthritis (RA). METHODS: This double-blind, phase III study randomised (1:1) patients to receive CT-P47 or r-TCZ (8 mg/kg) every 4 weeks until week 20 during treatment period (TP) 1. Prior to week 24 dosing, patients receiving r-TCZ were randomised (1:1) to continue r-TCZ or switch to CT-P47; patients receiving CT-P47 continued CT-P47 (TP2, 8 mg/kg every 4 weeks until week 48). The dual primary endpoints (for different regulatory requirements) were mean changes from baseline in Disease Activity Score in 28 joints (DAS28; erythrocyte sedimentation rate (ESR)) at week 12 and week 24. Efficacy equivalence was determined if CIs for the treatment difference were within predefined equivalence margins: (95% CI -0.6, 0.6 (analysis of covariance (ANCOVA)) at week 12 or 90% CI -0.6, 0.5 (ANCOVA with multiple imputation) at week 24). Additional efficacy, pharmacokinetic (PK) and safety endpoints, including immunogenicity, were investigated. Findings up to week 32 are presented. RESULTS: In TP1, 471 patients were randomised (234 CT-P47; 237 r-TCZ). The 95% and 90% CIs for the estimated treatment differences were contained within the predefined equivalence margins; the estimated difference in DAS28-ESR at week 12 was -0.01 (95% CI -0.26, 0.24) and at week 24 was -0.10 (90% CI -0.30, 0.10). Secondary efficacy endpoints, PKs and overall safety were comparable between groups up to week 32. CONCLUSIONS: Efficacy equivalence, alongside comparable PK, safety and immunogenicity profiles, was determined between CT-P47 and r-TCZ in adults with RA, including after switching from r-TCZ to CT-P47.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Randomized trial | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Randomized trial | high |
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.004 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".