Tofacitinib for the Treatment of Juvenile Idiopathic Arthritis: Patient‐Reported Outcomes in a Phase 3, Randomized, Double‐Blind, Placebo‐Controlled Withdrawal Trial
Bibliographic record
Abstract
OBJECTIVE: Juvenile idiopathic arthritis (JIA) is associated with impaired overall health-related quality of life (HRQoL). We evaluated the impact of tofacitinib on patient-reported outcomes (PROs) in patients with JIA. METHODS: This was a post hoc analysis of a phase 3, randomized, double-blind, placebo-controlled withdrawal trial (NCT02592434) in patients with JIA. In the open-label phase (part 1; weeks 0-18), patients received body weight-based doses of tofacitinib. During the double-blind phase (part 2; weeks 18-44), responders (per JIA-American College of Rheumatology 30 response criteria) were randomized 1:1 to continue tofacitinib or switch to placebo for up to 26 weeks. Assessed PROs included the validated parent and/or legal guardian versions of the Childhood Health Assessment Questionnaire for evaluation of disability, arthritis pain, overall well-being, and the Child Health Questionnaire (CHQ). RESULTS: Overall, 225 patients were enrolled and received open-label tofacitinib in part 1, and 173 patients were randomized in part 2. During part 1, least-squares (LS) mean (SE) disability, arthritis pain, and overall well-being scores numerically improved from mean 1.04 (SE 0.05), mean 5.53 (SE 0.20), and mean 5.07 (SE 0.20) at baseline to mean 0.57 (SE 0.05), mean 2.46 (SE 0.18), and mean 2.47 (SE 0.18) at week 18, respectively. LS mean (SE) CHQ physical summary and psychological summary scores numerically improved from mean 29.51 (SE 1.15) and mean 47.24 (SE 0.85) at baseline to mean 42.70 (SE 0.98) and mean 51.53 (SE 0.80) at week 18, respectively. Improvements were generally maintained to week 44 in part 2. CONCLUSION: Tofacitinib improved a range of PROs in patients with JIA, suggesting potential HRQoL benefits.
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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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".