Experience with subcutaneous abatacept for rheumatoid arthritis: an update for clinicians
Bibliographic record
Abstract
Abatacept is recommended by several expert consensus groups including the 2013 update of the EULAR recommendations for the pharmacologic management of rheumatoid arthritis (RA), as a potential choice for biologic therapy for patients with RA. Initially developed, studied, and approved as an intravenous (IV) formulation, abatacept is now also available as a subcutaneous (SC) injection. Having both options available makes abatacept a particularly versatile agent for the management of RA, greatly expanding the population of patients who could benefit from this treatment. This review provides a summary of the most important clinical trials that have investigated this molecule in both of its formulations, with a focus on the more recent trials evaluating the SC formulation, specifically the AMPLE study, the first major trial evaluating two biologic agents (abatacept and the tumor necrosis factor (TNF)-inhibitor adalimumab) in a head-to-head manner. In that study, SC abatacept was found to have an efficacy profile similar to that of SC adalimumab, both in combination with methotrexate.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".