Cost per response for abatacept versus adalimumab in rheumatoid arthritis by ACPA subgroups in Germany, Italy, Spain, US and Canada
Bibliographic record
Abstract
Rheumatoid arthritis (RA) is a chronic inflammatory disorder leading to disability and reduced quality of life. Effective treatment with biologic DMARDs poses a significant economic burden. The Abatacept versus Adalimumab Comparison in Biologic-Naïve RA Subjects with Background Methotrexate (AMPLE) trial was a head-to-head, randomized study comparing abatacept in serum anti-citrullinated protein antibody (ACPA)-positive patients, with increasing efficacy across ACPA quartile levels. The aim of this study was to evaluate the cost per response accrued using abatacept versus adalimumab in ACPA-positive and ACPA-negative patients with RA from the health care perspective in Germany, Italy, Spain, the US and Canada. A cost-consequence analysis (CCA) was designed to compare the monthly costs per responding patient/patient in remission. Efficacy, safety and resource use inputs were based on the AMPLE trial. A one-way deterministic sensitivity analysis (OWSA) was also performed to assess the impact of model inputs on the results for total incremental costs. Cost per response in ACPA-positive patients favoured abatacept compared with adalimumab (ACR20, ACR90 and HAQ-DI). Subgroup analysis favoured abatacept with increasing stringency of response criteria and serum ACPA levels. Cost per remission (DAS28-CRP) favoured abatacept in ACPA-negative patients, while cost per CDAI and SDAI favoured abatacept in ACPA-positive patients. Abatacept was consistently favoured in ACPA-Q4 patients across all outcomes and countries. Cost savings were greater with abatacept when more stringent response criteria were applied and also with increasing ACPA levels, which could lead to a lower overall health care budget impact with abatacept compared with adalimumab.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".