Open-label study of etanercept treatment in patients with moderate-to-severe plaque psoriasis who lost a satisfactory response to adalimumab
Bibliographic record
Abstract
BACKGROUND: Some patients with plaque psoriasis experience secondary failure of tumour necrosis factor inhibitor therapy. OBJECTIVES: To evaluate efficacy, safety and patient-reported outcomes (PROs) with etanercept in patients with secondary adalimumab failure. METHODS: This phase IV open-label single-arm estimation study (NCT01543204) enrolled patients on adalimumab who had achieved static Physician's Global Assessment (sPGA) score 0/1 (clear/almost clear). Patients subsequently lost response, defined as sPGA ≥ 3 or loss of 50% improvement in Psoriasis Area and Severity Index (PASI 50). At baseline, patients had involved body surface area ≥ 10%, sPGA ≥ 3 and PASI ≥ 10. Antiadalimumab antibodies (ADAs) were measured at screening. Patients received etanercept 50 mg twice weekly for 12 weeks, followed by 50 mg weekly. The primary end point was sPGA 0/1 at week 12 (intention-to-treat analysis; no hypothesis tested). Additional outcomes included rates of sPGA 0/1, PASI responses, safety, PROs of itch, pain and flaking, Dermatology Life Quality Index, treatment satisfaction and Work Productivity and Activity Impairment questionnaire. RESULTS: Sixty-four patients enrolled; 67% had ADAs. sPGA 0/1 rates at week 12 were 39·7% [95% confidence interval (CI) 27·6-52·8; primary end point] and 45% (95% CI 29·3-61·5) for patients positive for ADAs and 35% (95% CI 15·4-59·2) for patients negative for ADAs. PASI 75 response rates at week 12 were 47·5% (95% CI 31·5-63·9) for patients who were positive for ADAs and 50% (95% CI 27·2-72·8) for patients negative for ADAs. No new safety signals were observed. PROs of itch, pain and flaking consistently improved at week 12 and were maintained through week 24. CONCLUSIONS: Patients with psoriasis who experienced secondary failure of adalimumab achieved satisfactory response to etanercept regardless of ADA status.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".