Ustekinumab improves nail disease in patients with moderate‐to‐severe psoriasis: results from <scp>PHOENIX</scp> 1
Bibliographic record
Abstract
BACKGROUND: Most patients with psoriasis have nail changes, and treating nail psoriasis is challenging. OBJECTIVES: To assess improvement in fingernail psoriasis with ustekinumab treatment in the PHOENIX 1 trial. METHODS: Patients received ustekinumab 45 mg or 90 mg, or placebo at weeks 0 and 4. Ustekinumab-randomized patients continued maintenance dosing every 12 weeks, while patients receiving placebo crossed over to receive ustekinumab 45 mg or 90 mg at weeks 12/16 followed by dosing every 12 weeks. At week 40, initial responders [those with ≥ 75% improvement from baseline in Psoriasis Area and Severity Index (PASI 75)] were rerandomized either to continue maintenance dosing or to withdraw from treatment. Nail involvement was evaluated using the Nail Psoriasis Severity Index (NAPSI) on a target fingernail, Nail Physician's Global Assessment (Nail PGA) and mean number of nails involved. RESULTS: Of 766 randomized patients, 545 (71·1%) had nail psoriasis. At week 24, the percentage improvement from baseline NAPSI score was 46·5% (ustekinumab 45 mg) and 48·7% (ustekinumab 90 mg). Percentage improvements in NAPSI ranged from 29·7% (PASI < 50) to 57·3% (PASI ≥ 90). Mean NAPSI scores improved from 4·5 at baseline to 2·4 at week 24 (45 mg) and from 4·4 to 2·2 (90 mg). Nail PGA scores and the mean number of psoriatic nails improved by week 24. Further improvement was observed for all end points among initial responders continuing maintenance treatment through week 52. CONCLUSIONS: Ustekinumab significantly improves nail psoriasis, and improvements continue over time until up to 1 year of treatment in those receiving maintenance 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.003 | 0.000 |
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".