Secukinumab Provides Clearer Skin and Better Control on Patient-Reported Psoriasis Symptoms of Itching, Pain, and Scaling than Placebo and Etanercept
Bibliographic record
Abstract
Background Secukinumab, a fully human anti-interleukin 17A monoclonal antibody, has demonstrated rapid, strong, and sustained efficacy in moderate-to-severe plaque psoriasis. Objective To measure treatment effect on psoriasis-related itching, pain, and scaling during the first 12 weeks of treatment. Methods ERASURE and FIXTURE were double-blind, multicenter, phase 3 studies in adults randomly assigned to secukinumab (300 mg or 150 mg), placebo, or etanercept (FIXTURE only). Improvements in itching, pain, and scaling and their bothersomeness, proportions of responders and proportions reporting complete symptom relief were compared. Results Subjects treated with secukinumab reported significantly greater symptom improvement versus etanercept and placebo as well as bothersomeness reduction (all P < 0.01). The proportion of symptom responders and proportions reporting complete relief favored secukinumab. Limitations Approximately 39% of patients provided data on psoriasis-related itching, pain, and scaling. Conclusions Secukinumab significantly improves patient-reported itching, pain, and scaling compared with etanercept and placebo over 12-week psoriasis treatment.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.011 | 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".