Tofacitinib in combination with methotrexate in patients with rheumatoid arthritis: patient-reported outcomes from the 24-month Phase 3 ORAL Scan study.
Bibliographic record
Abstract
OBJECTIVES: Tofacitinib is an oral Janus kinase inhibitor for the treatment of rheumatoid arthritis (RA). Here we present data from the completed Phase 3 randomised controlled trial (RCT) ORAL Scan (NCT00847613), which evaluated the impact of tofacitinib on patient-reported outcomes (PROs) through 24 months in patients with active RA and inadequate responses to methotrexate (MTX-IR). METHODS: Patients were randomised 4:4:1:1 to receive tofacitinib 5 or 10 mg twice daily (BID), or placebo advanced to tofacitinib 5 or 10 mg, plus background MTX. Patients receiving placebo advanced to tofacitinib at month 3 (non-responders) or month 6 (remaining patients). Mean changes from baseline in PROs, assessed at months 1-24, included Health Assessment Questionnaire-Disability Index, Patient Global Assessment of disease activity (visual analogue scale [VAS]), Patient Assessment of Arthritis Pain (VAS), health-related quality of life (Short Form-36 version 2), Functional Assessment of Chronic Illness Therapy-Fatigue and Medical Outcomes Study-Sleep. RESULTS: Overall, 539/797 (67.6%) patients completed 24 months' treatment. At month 3, tofacitinib-treated patients reported signi cant (p<0.05) mean changes from baseline versus placebo across all PROs, and significantly more patients reported improvements ≥ minimum clinically important differences versus placebo. Improvements in PROs with tofacitinib were sustained to month 24. Following advancement to tofacitinib, placebo-treated patients generally reported changes of similar magnitude to tofacitinib-treated patients. CONCLUSIONS: Patients with RA and MTX-IR receiving tofacitinib 5 or 10 mg BID plus MTX reported significant and clinically meaningful improvements in PROs versus placebo at month 3, which were sustained through 24 months.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".