<scp>Real‐World</scp> Treatment Patterns, Clinical Outcomes, and Symptom Burden in Patients With Psoriatic Arthritis Prescribed Ixekizumab in the United States
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to describe the real-world characteristics and clinical status of patients with psoriatic arthritis (PsA) currently prescribed ixekizumab. METHODS: Data were drawn from the Adelphi PsA Plus Disease Specific Programme (DSP), a cross-sectional survey conducted in the United States between September 2021 and March 2022. Rheumatologists provided data for their next five consulting patients currently receiving ixekizumab, including demographic and clinical characteristics, disease severity, treatment history, reasons for treatment choice, satisfaction with current treatment, and current and historic symptom burden. Patients voluntarily completed questionnaires, providing perceptional data on symptom burden and satisfaction with current treatment. RESULTS: Overall, 68 rheumatologists provided data on 275 patients with PsA, 90 of whom completed the voluntary questionnaire. Patients had been prescribed ixekizumab for a mean of 11.7 (SD 10.6) months. Clinical characteristics, disease severity, and symptom burden of patients with PsA improved significantly from ixekizumab initiation to the most recent consultation, including symptom burden, tender and swollen joint counts, and body surface area affected by psoriasis (all P < 0.001). Both rheumatologists and patients were satisfied with ixekizumab treatment and reported improvements in pain and fatigue. Improvements were noted after more than three months of ixekizumab treatment duration and regardless of whether the patients had prior exposure to an advanced therapy or were treatment naïve. CONCLUSION: Our results indicate that ixekizumab was efficacious in the treatment of PsA in real-world clinical practice, complementing efficacy data from randomized controlled clinical trials. The results of this study may assist rheumatologists and their patients in making informed treatment choices.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".