Demography, baseline disease characteristics, and treatment history of psoriasis patients with self-reported psoriatic arthritis enrolled in the PSOLAR registry
Bibliographic record
Abstract
To evaluate demographics, family history, and previous medication use at enrollment in a subset of psoriasis patients with self-reported psoriatic arthritis (PsA) enrolled in Psoriasis Longitudinal Assessment and Registry (PSOLAR). PSOLAR is an international, prospective, longitudinal, disease-based registry that collects data in patients receiving, or are eligible to receive, systemic or biologic treatments for psoriasis. Baseline demographic, disease characteristics, medical history, and prior medication use at enrollment were evaluated in PSOLAR psoriasis patients self-reporting PsA (n = 4315); a subset of which had their diagnosis of PsA established by a healthcare provider (HCP; n = 1719); patients with psoriasis only (n = 7775); and the overall PSOLAR population (n = 12,090). At enrollment, demographic characteristics were distinct between psoriasis patients self-reporting PsA and psoriasis only patients. Of the patients with psoriasis self-reporting PsA, 44.4% had cardiovascular disease (CVD), 26.3% had psychiatric illness, and 3.2% had inflammatory bowel disease (IBD), with each more prevalent than among patients with psoriasis only (p < 0.001). Overall, 17.5% of psoriasis patients self-reporting PsA had a family history of PsA, 29.8% had used systemic steroids, 39.5% had used nonsteroidal anti-inflammatory drugs, and 83.5% had used biologics. Demographics, family history, and previous medication use were generally comparable between “PsA established by a HCP” patients and psoriasis patients self-reporting PsA in the PSOLAR registry, but there were statistical differences compared with the psoriasis only group regarding the prevalence of certain comorbidities (CVD, psychiatric illness, and IBD). These analyses provide important data regarding characteristics of psoriasis patients with self-reported PsA in PSOLAR. NCT00508547 .
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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".