Clinically Inactive Disease and Remission in Patients With Juvenile Idiopathic Arthritis Receiving Tofacitinib: Post Hoc Analysis of a Phase III Trial
Bibliographic record
Abstract
OBJECTIVE: To evaluate rates of clinically inactive disease (CID) and remission in patients with juvenile idiopathic arthritis (JIA) receiving tofacitinib using the 2021 Juvenile Arthritis Disease Activity Score (JADAS) thresholds and American College of Rheumatology (ACR) criteria. METHODS: This post hoc analysis included patients with active JIA (polyarticular-course JIA, psoriatic arthritis, or enthesitis-related arthritis) enrolled in a phase III randomized withdrawal study of tofacitinib. In part 1 (weeks 0-18), patients received open-label tofacitinib. In part 2 (weeks 18-44), patients who achieved ACR improvement ≥ 30% were randomized to tofacitinib or placebo for 26 weeks or until JIA flare. Disease activity was assessed using the JADAS in 10 joints (JADAS10) based on C-reactive protein, with interpretation according to 2021 polyarthritis thresholds. JADAS10 remission was defined as ≥ 24 continuous weeks of JADAS10 CID (JADAS10-CID). ACR CID (ACR-CID) and ACR clinical remission were also assessed. RESULTS: Of 225 patients with JIA in part 1, 173 (76.9%) were randomized in part 2 to continue tofacitinib or switch to placebo. Rates of JADAS10-CID and ACR-CID increased throughout part 1 to 30.5% and 15.8% (week 18), respectively. In part 2, these were sustained with tofacitinib (week 44: 35.2% [JADAS10-CID], 25% [ACR-CID]) and decreased when patients switched to placebo (week 44: 25.9% [JADAS10-CID], 15.3% [ACR-CID]). A small proportion of patients achieved JADAS10 remission at week 44 (tofacitinib: 14.8%; placebo: 7.1%). CONCLUSION: In patients with JIA receiving tofacitinib, JADAS10-CID and ACR-CID rates improved rapidly and were sustained over time, and a small proportion of patients achieved JADAS10 remission. Inactive disease is a feasible treatment target in patients receiving tofacitinib. (ClinicalTrials.gov: NCT02592434).
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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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".