Efficacy, safety and usability of secukinumab administration by autoinjector/pen in psoriasis: a randomized, controlled trial (<scp>JUNCTURE</scp>)
Bibliographic record
Abstract
BACKGROUND: Secukinumab is a fully human anti-interleukin-17A monoclonal antibody. OBJECTIVE: Determine the efficacy, safety and usability of secukinumab administered via autoinjector/pen. METHODS: This phase III trial randomized subjects with moderate to severe plaque psoriasis to secukinumab 300 mg, 150 mg or placebo self-injection once weekly to Week 4, then every 4 weeks. Co-primary end points at Week 12 were ≥75% improvement in Psoriasis Area and Severity Index (PASI 75) and clear/almost clear skin by investigator's global assessment 2011 modified version (IGA mod 2011 0/1). Secondary end points included autoinjector usability, assessed by successful, hazard-free self-injection and subject-reported acceptability on Self-Injection Assessment Questionnaire. RESULTS: Week 12 PASI 75 and IGA mod 2011 0/1 responses were superior with secukinumab 300 mg (86.7% and 73.3%, respectively) and 150 mg (71.7% and 53.3%, respectively) vs. placebo (3.3% and 0%, respectively) (P < 0.0001 for all). All subjects successfully self-administered treatment at Week 1, without critical use-related hazards. Subject acceptability of autoinjector was high throughout 12 weeks. Adverse events were higher with secukinumab (300 mg, 70.0%; 150 mg, 63.9%) vs. placebo (54.1%), with differences largely driven by mild/moderate nasopharyngitis. CONCLUSION: Secukinumab delivered by autoinjector/pen is efficacious, well-tolerated and associated with high usability in moderate to severe plaque psoriasis.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".