Secukinumab improves patient‐reported psoriasis symptoms of itching, pain, and scaling: results of two phase 3, randomized, placebo‐controlled clinical trials
Bibliographic record
Abstract
BACKGROUND: Secukinumab is a human interleukin-17A antagonist indicated for the treatment of moderate to severe plaque psoriasis in adults who are candidates for systemic therapy or phototherapy. The objective of this analysis was to measure the treatment response on psoriasis-related itching, pain, and scaling via the Psoriasis Symptom Diary (PSD)(©). METHODS: ERASURE (n = 738) and FIXTURE (n = 1306) were double-blind, multicenter phase 3 studies in adults randomized to secukinumab (300, 150 mg, n = 1144) or placebo (n = 574) (administered at Weeks 0, 1, 2, 3, and 4, followed by dosing every 4 weeks) or a biologic active control (FIXTURE only). Patient-reported itching, pain, and scaling were assessed during the first 12 weeks of treatment using the PSD. The results reported here are limited to subjects in the secukinumab and placebo treatment groups who completed the PSD. The proportions of subjects achieving prespecified responses (improvement:reduction of at least 2.2 points for itching, 2.2 points for pain, or 2.3 points for scaling) were compared for secukinumab versus placebo. RESULTS: Overall, 39% of subjects completed the PSD at baseline and Week 12 (n = 453 secukinumab; 225 placebo). Subjects treated with secukinumab achieved significantly greater improvements in itching, pain, and scaling at Week 12 versus placebo (all P < 0.0001) and had significantly greater proportions of itching, pain, and scaling responders at Week 12 versus placebo (all P < 0.05). CONCLUSION: Secukinumab significantly improves patient-reported itching, pain, and scaling in adults with moderate to severe psoriasis compared with placebo.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| 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, 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".