Long‐Term Safety, Efficacy, and Quality of Life in Patients With Juvenile Idiopathic Arthritis Treated With Intravenous Abatacept for Up to Seven Years
Bibliographic record
Abstract
OBJECTIVE: The efficacy and safety of abatacept in patients with juvenile idiopathic arthritis (JIA) who experienced an inadequate response to disease-modifying antirheumatic drugs were previously established in a phase III study that included a 4-month open-label lead-in period, a 6-month double-blind withdrawal period, and a long-term extension (LTE) phase. The aim of this study was to present the safety, efficacy, and patient-reported outcomes of abatacept treatment (10 mg/kg every 4 weeks) during the LTE phase, for up to 7 years of followup. METHODS: Patients enrolled in the phase III trial could enter the open-label LTE phase if they had not achieved a response to treatment at month 4 or if they had received abatacept or placebo during the double-blind period. RESULTS: One hundred fifty-three (80.5%) of 190 patients entered the LTE phase, and 69 patients (36.3%) completed it. The overall incidence rate (events per 100 patient-years) of adverse events decreased during the LTE phase (433.61 events during the short-term phase [combined lead-in and double-blind periods] versus 132.39 events during the LTE phase). Similar results were observed for serious adverse events (6.82 versus 5.60), serious infections (1.13 versus 1.72), malignancies (1.12 versus 0), and autoimmune events (2.26 versus 1.18). American College of Rheumatology (ACR) Pediatric 30 (Pedi 30) responses, Pedi 70 responses, and clinically inactive disease status were maintained throughout the LTE phase in patients who continued to receive therapy. Improvements in the Child Health Questionnaire physical and psychosocial summary scores were maintained over time. CONCLUSION: Long-term abatacept treatment for up to 7 years was associated with consistent safety, sustained efficacy, and quality-of-life benefits in patients with JIA.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".