Abatacept in the treatment of rheumatoid arthritis
Bibliographic record
Abstract
Over the past decade, biological immunotherapy has revolutionised the treatment of rheumatoid arthritis (RA). The most widely used of these therapies targets tumour necrosis factor-alpha (TNF-alpha). Approximately 20% of patients fail to respond to TNF-alpha antagonism, however, and a significant number of additional patients become refractory to anti-TNF-alpha therapy over time. Thus investigators have sought to target other pathogenic elements of RA using novel biological therapies. Abatacept is the first immunotherapy directed against the process of T-cell costimulation. Abatacept has shown clinical effectiveness in RA by improving disease activity, quality of life measures and radiographic progression of disease. In this article, we review the immunology of T-cell activation and costimulation, define the role of abatacept in this process, and discuss the clinical trials that led to the approval of abatacept as the latest biological therapy in RA in the USA and Canada. We also address the role of abatacept in the greater context of biological therapy for RA.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".