Improvement in Psoriasis Signs and Symptoms Assessed by the Psoriasis Symptom Inventory with Brodalumab Treatment in Patients with Psoriatic Arthritis
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effect of brodalumab on psoriasis signs and symptoms assessed by the Psoriasis Symptom Inventory (PSI) in patients with psoriatic arthritis (PsA). METHODS: This prespecified analysis of a phase II study (NCT01516957) evaluated patients with active PsA and psoriasis-affected body surface area ≥ 3%, randomized to brodalumab (140 or 280 mg) or placebo every 2 weeks (Q2W) for 12 weeks with loading dose at Week 1. At Week 12, patients entering an open-label extension received brodalumab 280 mg Q2W. The PSI measures 8 psoriasis signs and symptoms: itch, redness, scaling, burning, stinging, cracking, flaking, and pain. PSI response is defined as total PSI ≤ 8 (range 0-32), each item ≤ 1 (range 0-4). PSI scores were assessed at weeks 12 and 24. RESULTS: There were 107 eligible patients. At Week 12, mean improvement in PSI scores was 7.8, 11.2, and 1.5 in brodalumab 140 mg, 280 mg, and placebo groups, respectively; by Week 24, improvement was 10.2, 12.4, and 11.7. At Week 12, 75.0%, 81.8%, and 16.7% of patients receiving brodalumab 140 mg, 280 mg, and placebo, respectively, achieved PSI response; improvement was sustained through Week 24, when 83.9% of prior placebo recipients achieved response. At Week 12, 25.0%, 36.4%, and 2.8% of patients receiving brodalumab 140 mg, 280 mg, and placebo, respectively, achieved PSI 0. Percentages improved through Week 24: 40.0% brodalumab 140 mg, 42.9% brodalumab 280 mg, and 48.4% placebo. CONCLUSION: Significantly more brodalumab-treated patients with PsA achieved patient-reported improvements in psoriasis signs and symptoms than did those receiving placebo. Improvements were comparable between brodalumab groups.
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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 | 0.000 |
| 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) | 0.002 | 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".