Deucravacitinib versus placebo and apremilast in moderate to severe plaque psoriasis: Efficacy and safety results from the 52-week, randomized, double-blinded, phase 3 Program fOr Evaluation of TYK2 inhibitor psoriasis second trial
Bibliographic record
Abstract
BACKGROUND: Deucravacitinib, an oral, selective, allosteric tyrosine kinase 2 inhibitor, inhibits cytokine signaling in psoriasis pathogenesis. OBJECTIVE: The objective of this study was to demonstrate deucravacitinib superiority versus placebo and apremilast in moderate to severe plaque psoriasis based on ≥75% reduction from baseline in Psoriasis Area and Severity Index and a static Physician's Global Assessment score of 0 (clear) or 1 (almost clear) with a ≥2-point improvement from baseline at week 16. METHODS: POETYK psoriasis second trial (NCT03611751), a 52-week, double-blinded, phase 3 trial, randomized patients 2:1:1 to deucravacitinib 6 mg every day (n = 511), placebo (n = 255), or apremilast 30 mg twice a day (n = 254). RESULTS: At week 16, significantly more deucravacitinib-treated patients versus placebo and apremilast patients achieved ≥75% reduction from baseline in Psoriasis Area and Severity Index (53.0% vs 9.4% and 39.8%; P < .0001 vs placebo; P = .0004 vs apremilast) and static Physician's Global Assessment score of 0 or 1 (49.5% vs 8.6% and 33.9%; P < .0001 for both). Efficacy was maintained until week 52 with continuous deucravacitinib. The most frequent adverse event with deucravacitinib was nasopharyngitis. Serious adverse events and discontinuations due to adverse events were infrequent. No clinically meaningful changes were observed in laboratory parameters. LIMITATIONS: The study duration was 1 year. CONCLUSION: Deucravacitinib demonstrated superiority versus placebo and apremilast and was well tolerated in adults with 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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".