Ixekizumab improves patient-reported outcomes in patients with active psoriatic arthritis and inadequate response to tumour necrosis factor inhibitors: SPIRIT-P2 results to 52 weeks.
Bibliographic record
Abstract
OBJECTIVES: To report patient-reported outcomes (PROs) of ixekizumab-treated patients with psoriatic arthritis (PsA) and an inadequate response (IR) or intolerance to tumour necrosis factor inhibitors (TNFi) to 52 weeks. METHODS: In SPIRIT-P2, patients with active PsA and an IR or intolerance to TNFi were randomised to ixekizumab 80 mg every 4 weeks (IXEQ4W; N=122) or every 2 weeks (IXEQ2W; N=123), or placebo (PBO; N=118) during the initial 24-week double-blind treatment period. At Week 16, background therapy was modified for IRs; additionally, IRs in the placebo group were re-randomised (1:1) to IXEQ2W or IXEQ4W. Patients receiving ixekizumab at Week 24 received the same dose during the study remainder. Patients completed several PROs for PsA disease activity, skin, health-related quality of life (HRQOL, and work through Week 52. RESULTS: Ixekizumab-treated patients reported significant improvements versus PBO in 36-Item Short Form Health Survey version 2, European Quality of Life 5 Dimensions visual analogue scale, Bath Ankylosing Spondylitis Disease Activity Index (total score and question 2), and Work Productivity and Activity Impairment Questionnaire-Specific Health Problem (3 of 4 domains) through Week 24. At Week 24, 9% (PBO), 52% (IXEQ4W), and 50% (IXEQ2W) of patients reported Dermatology Life Quality Index scores of 0 or 1; 0% (PBO) and 24% (IXEQ4W and IXEQ2W) reported Itch Numeric Rating Scale score of 0. Where data were collected, improvements persisted through Week 52. CONCLUSIONS: In patients with PsA and an IR or intolerance to TNFi, ixekizumab significantly improved disease activity, skin symptoms, HRQOL, and work productivity to 52 weeks.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".