A randomized phase 3b study evaluating the safety and efficacy of risankizumab in adult patients with moderate-to-severe plaque psoriasis with non-pustular palmoplantar involvement
Bibliographic record
Abstract
BACKGROUND: In plaque psoriasis, palmoplantar areas are more difficult to treat. OBJECTIVE: Evaluate the safety and efficacy of risankizumab (RZB) versus placebo (PBO) for the treatment of palmoplantar psoriasis. METHODS: Patients were randomized to RZB or PBO for 16 weeks followed by RZB through week 52. The primary and secondary end points were achievement of palmoplantar Investigator's Global Assessment of "clear" or "almost clear" with ≥2-point reduction from baseline (ppIGA 0/1), achievement of ≥75%, ≥90%, and 100% improvement in Palmoplantar Psoriasis Area and Severity Index (PPASI 75, PPASI 90, PPASI 100) and achievement of static Physician Global Assessment of "clear" or "almost clear" with ≥2-point reduction from baseline (sPGA 0/1) at week 16. Safety was based on treatment-emergent adverse events. RESULTS: RZB demonstrated significant efficacy compared to PBO at week 16 in the patients achieving ppIGA 0/1 (33.3% vs 16.1% [P = .006]), PPASI 75 (42.5% vs 14.9% [P < .001]), PPASI 90 (27.6% vs 5.7% [P < .001]), sPGA 0/1 (32.2% vs 11.5% [P < .001]), and PPASI 100 (17.2% vs 1.1% [P < .001]). Results improved through week 52 with no new safety signals. LIMITATION: No biologic comparator. CONCLUSIONS: RZB demonstrated good tolerance and efficacy in palmoplantar 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.003 |
| 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".