Cost per response for abatacept versus adalimumab in patients with seropositive, erosive early rheumatoid arthritis in the US, Germany, Spain, and Canada
Bibliographic record
Abstract
BACKGROUND: Effective treatment of rheumatoid arthritis (RA) with biologic DMARDs poses a significant economic burden. The AMPLE (Abatacept versus adaliMumab comParison in bioLogic-naïvE RA subjects with background methotrexate) trial was a head-to-head, randomized study comparing abatacept with adalimumab. A post hoc analysis showed improved efficacy for abatacept in patients with versus without seropositive, erosive early RA. OBJECTIVE: The aim of the current study was to evaluate the cost per response (ACR20/50/70/90 and HAQ-DI) and patient in remission (DAS28-CRP, CDAI, and SDAI) for abatacept relative to adalimumab, in patients with seropositive, erosive early RA in the US, Germany, Spain, and Canada. METHODS: A previously published model was used to compare abatacept and adalimumab in a cohort of 1000 patients over 2 years. Clinical inputs were updated based on two subpopulations from the AMPLE trial. Cohort 1 included patients with early RA (disease duration ≤ 6 months), RF and/or ACPA seropositivity, and > 1 radiographic erosion. Cohort 2 included patients with RA in whom at least one of these criteria was absent. RESULTS: For cohort 1, all incremental costs per additional health gain (patient response or patient in remission) favoured abatacept in all countries, except for DAS28-CRP remission in Canada. Cost savings versus adalimumab were greater when more stringent response criteria were applied and also in cohort 1 patient (versus cohort 2 patients). CONCLUSION: The cost per responder and patient in remission favoured abatacept in patients with seropositive, erosive early RA across all the countries. In this patient population, the use of abatacept instead of adalimumab can lead to lower costs in the US, Germany, Spain, and Canada.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".