Longterm Safety and Efficacy of Abatacept Through 5 Years of Treatment in Patients with Rheumatoid Arthritis and an Inadequate Response to Tumor Necrosis Factor Inhibitor Therapy
Bibliographic record
Abstract
OBJECTIVE: To evaluate abatacept safety and efficacy over 5 years in patients with rheumatoid arthritis (RA) who had inadequate response to anti-tumor necrosis factor (TNF) therapy in the ATTAIN trial. METHODS: Patients completing the 6-month, double-blind (DB) placebo-controlled period were eligible to enter the longterm extension (LTE), where all patients received abatacept every 4 weeks (∼10 mg/kg, according to weight range). Safety, efficacy, physical function, and health-related quality of life were monitored throughout. RESULTS: In total, 317 patients (218 DB abatacept, 99 DB placebo) entered the LTE; 150 (47.3%) completed it. Overall incidences of serious adverse events, infections, serious infections, malignant neoplasms, and autoimmune events did not increase during the LTE versus the DB period. American College of Rheumatology responses with abatacept at Month 6 were maintained over 5 years. At Year 5, among patients who received abatacept for 5 years and had available data, 38/103 (36.9%) achieved low disease activity as defined by the 28-joint Disease Activity Score (DAS28)/C-reactive protein (CRP); 23/103 (22.3%) achieved DAS28/CRP-defined remission. Health Assessment Questionnaire response was achieved by 62.5% of patients remaining on treatment at Year 5; mean improvements from baseline in physical component summary and mental component summary scores were 7.34 and 6.42, respectively. High proportions of patients maintained efficacy and physical function benefits or improved their disease state at each timepoint throughout the LTE, if remaining on abatacept treatment. CONCLUSION: Safety remained consistent, and abatacept efficacy was maintained from 6 months to 5 years, demonstrating the benefits of switching to abatacept in this difficult-to-treat population of patients with RA previously failing anti-TNF therapy.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".