Disease characteristics in patients with and without psoriatic arthritis treated with etanercept
Bibliographic record
Abstract
BACKGROUND: Patients with psoriasis (PsO) and psoriatic arthritis (PsA) have functional disability, pain and emotional problems, and experience lower quality of life (QoL) than patients with PsO alone. OBJECTIVES: Examine effectiveness of etanercept (ETN) in patients with PsO alone, and with PsA, and determine whether PsA patients on ETN experience rapid QoL improvement. METHODS: Data from three phase III trials using ETN in adults with moderate-to-severe PsO were pooled. Patients with (n = 523) and without (n = 1330) PsA received ETN 25 mg once weekly to 50 mg twice weekly or placebo for 12-24 weeks. Assessments included Psoriasis Area and Severity Index (PASI), Dermatology Life Quality Index (DLQI), EuroQoL-5D (EQ-5D), Study 36-item Short Form Health Survey (SF-36) and Hamilton Depression Rating Scale (HAM-D). RESULTS: Baseline PASI, EQ-5D and SF-36 physical component summary scores were worse for PsA patients. With ETN, PASI for PsA and non-PsA groups improved as early as week 2. Scores for both groups converged by week 12. EQ-5D and SF-36 physical component improved faster in PsA patients, with EQ-5D scores converged by week 2. For total DLQI and most components, both groups had similar baseline scores and improved over 24 weeks on ETN. While the PsA group had more depressed patients at baseline, after 24 weeks on ETN it showed a greater reduction in the number of depressed patients than the non-PsA group. CONCLUSIONS: In patients with PsO involving ≥10% of body surface area, skin disease and QoL are worse in PsA patients. With ETN, QoL improved rapidly in PsA patients.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".