Real-World Long-Term Effectiveness of Risankizumab Among Patients with Moderate-to-Severe Psoriasis: Analysis from an International Medical Chart Review (RAPID) Study
Bibliographic record
Abstract
INTRODUCTION: Real-world data on the efficacy of risankizumab (RZB) in clinical moderate-to-severe plaque psoriasis (PsO) are limited. The RAPID study assessed real-world clinical and patient-reported outcomes in RZB-treated PsO patients using data collected from dermatologists in Canada, the Czech Republic, Germany, Japan, and Poland. METHODS: This ongoing, retrospective chart review collected data from medical records of RZB-treated adults with moderate-to-severe PsO (09/2022-06/2023). Eligible patients received RZB, had ≥ 12 months of medical records after RZB initiation (index date), and had Psoriasis Area and Severity Index (PASI), Investigator Global Assessment (IGA), or static Physician's Global Assessment (sPGA) scores ≥ 3 months before and up to 18 months after the index date. The proportion of patients achieving a clear/almost clear PsO (IGA/sPGA = 0/1), PASI ≤ 1, Dermatology Life Quality Index (DLQI) = 0/1, and a 90%/100% improvement from baseline in PASI as well as the mean changes in PASI, DLQI, itch, and skin pain scores at 12 and 18 months were reported for patients with non-missing assessments at baseline and 12 months. RESULTS: Most patients (66.4%) were male, 74.0% were biologic naïve, and 73.0% had scalp PsO. Mean baseline IGA/sPGA was 3.7 ± 0.5, with a mean PASI of 23.3 ± 11.8. After 12 months, 86.1% of patients reported IGA/sPGA ≤ 1, and 75.7% achieved PASI90; these further increased to 91.1% and 80.5% at 18 months. DLQI, itch, and skin pain scores improved over time. CONCLUSIONS: These data demonstrated the durable, real-world effectiveness of RZB in patients with moderate-to-severe PsO through continued improvement in disease and symptom severity over 18 months, with most of the patients reporting clear/almost clear skin.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".