Patient-reported Outcomes in a Randomized Trial of Etanercept in Psoriatic Arthritis
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effects of etanercept treatment on patient-reported outcomes (PRO) in patients with psoriatic arthritis (PsA). METHODS: A 24-week double-blind comparison to placebo was followed by a 48-week open-label phase in which all eligible patients received etanercept. PRO were measured using the Stanford Health Assessment Questionnaire Disability Index (HAQ-DI), the Medical Outcomes Study Short-Form (SF-36), the EQ-5D visual analog scale (VAS), and the American College of Rheumatology (ACR) patient pain assessment. RESULTS: Beginning at Week 4 and continuing through Week 24 of double-blind treatment, patients treated with etanercept had significantly higher mean percentage improvement in HAQ-DI relative to baseline than patients given placebo (53.6% vs 6.4% at Week 24; p < 0.001). After 48 weeks of open-label treatment with etanercept, the mean percentage change from study baseline was 52.8% for the original etanercept group and 46.9% for the original placebo group, with 41.2% of patients overall achieving a HAQ-DI of 0. Mean changes relative to baseline for SF-36 physical component summary scores, EQ-5D VAS, and ACR pain assessment were also significant in the double-blind period for etanercept compared with placebo (p < 0.001 for all 3 measures). Patients taking placebo achieved similar improvements once they began treatment with etanercept in the open-label period. CONCLUSION: Patients with PsA treated with etanercept reported significant improvements in physical function that were almost 10 times the improvement seen with placebo and were maintained for up to 2 years. Almost half of patients treated with etanercept reported no disability by the end of the study.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".