Certolizumab Pegol Efficacy Across Methotrexate Regimens: A Pre‐Specified Analysis of Two Phase III Trials
Bibliographic record
Abstract
OBJECTIVE: Anti-tumor necrosis factor (anti-TNF) agents are frequently used in combination with methotrexate (MTX) to treat rheumatoid arthritis (RA). We investigated the effect of a background MTX dose, in combination with anti-TNF certolizumab pegol (CZP), on treatment efficacy and safety in RA patients. METHODS: A pre-specified subgroup analysis comparing 2 MTX dosage categories (<15 mg/week and ≥15 mg/week) was carried out using data pooled from phase III clinical trials, Rheumatoid Arthritis Prevention of Structural Damage 1 (RAPID 1) and RAPID 2, according to treatment group: CZP 200 mg, CZP 400 mg, or placebo, every 2 weeks. Inclusion criteria required MTX dosage ≥10 mg/week. Efficacy end points included week 24 American College of Rheumatology criteria for 20%, 50%, and 70% improvement (ACR20/50/70) responses analyzed by logistic regression, and changes from baseline in the Disease Activity Score in 28 joints using the erythrocyte sedimentation rate (DAS28-ESR) and the modified Sharp/van der Heijde score (SHS) were analyzed by analysis of covariance. Incidence rates of treatment-emergent adverse events (TEAEs) were categorized by baseline MTX dose. Post hoc sensitivity analysis investigated 3 MTX dose categories: ≤10 mg/week, >10 and ≤15 mg/week, and >15 mg/week. RESULTS: A total of 638, 635, and 325 patients received CZP 200 mg, CZP 400 mg, and placebo, respectively. At week 24, treatment responses in both CZP groups were uninfluenced by baseline MTX dose category, and were superior to the placebo group for all investigated end points: ACR20/50/70, DAS28-ESR, and SHS. TEAE incidence rates were higher in patients receiving MTX ≥15 mg/week for most TEAE types across treatment groups. CONCLUSION: CZP efficacy was not affected by background MTX dose category. It can be hypothesized that to minimize TEAEs, background MTX doses could be tailored to individual patient tolerance without affecting CZP efficacy.
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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 | 0.031 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.016 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".