Cost‐effectiveness of biologics in polyarticular‐course juvenile idiopathic arthritis patients unresponsive to disease‐modifying antirheumatic drugs
Bibliographic record
Abstract
OBJECTIVE: Juvenile idiopathic arthritis (JIA) is the most common chronic pediatric rheumatic disease and can have long-term effects leading to disability in adulthood. Biologics are a new class of drugs increasingly used to treat JIA. The primary study objective was to determine the incremental costs of biologics per additional responder compared to conventional treatment (methotrexate). METHODS: A separate decision model was created for etanercept, infliximab, adalimumab, and abatacept. The study population consisted of polyarticular-course JIA patients with a prior inadequate response or intolerance to disease-modifying antirheumatic drugs (DMARDs). The effectiveness measure was the proportion of patients who had a treatment response at 1 year according to the American College of Rheumatology (ACR) Pediatric 30 (Pedi 30) improvement criteria. Direct and indirect costs were calculated in 2008 Canadian dollars. Incremental cost-effectiveness ratios and 95% confidence intervals (95% CIs) were calculated for each biologic agent using probabilistic sensitivity analyses. RESULTS: The additional costs per additional ACR Pedi 30 responder at 1 year were $26,061 (95% CI $17,070, $41,834), $46,711 (95% CI $30,042, $75,787), $16,204 (95% CI $11,393, $22,608), and $31,209 (95% CI $16,659, $66,220) for etanercept, adalimumab, abatacept, and infliximab, respectively. CONCLUSION: Biologics are more effective than methotrexate in achieving a short-term response in JIA patients with prior inadequate responses to DMARDs; however, this comes at a high annual cost. Adequate long-term data with respect to both safety and effectiveness are not currently available, nor are utility estimates. Such data will be important to estimate value for money for treating JIA with biologic drugs over the long term.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".