Cost–effectiveness of abatacept for moderate-to-severe rheumatoid arthritis
Bibliographic record
Abstract
Abatacept, a selective T-cell costimulation modulator, has become a valuable treatment option for those with moderately to severely active rheumatoid arthritis. Given new clinical evidence, for the first time guidelines from the American College of Rheumatology and Canadian Rheumatology Association are promoting the consideration of abatacept as the first biologic added to initial traditional disease-modifying antirheumatic drugs once an inadequate response to disease-modifying antirheumatic drug monotherapy has been established, putting abatacept at the same line of treatment options as TNF-α inhibitors or rituximab. Since the advent of the subcutaneous formulation of abatacept, positive results from its clinical trials have further increased its appeal. In light of these changes, a review of the literature was conducted on the cost-effectiveness of abatacept for moderate-to-severe rheumatoid arthritis. Here we discuss current evidence, gaps in the literature and abatacept's future outlook.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".