The cost effectiveness of rofecoxib and celecoxib in patients with osteoarthritis or rheumatoid arthritis
Bibliographic record
Abstract
OBJECTIVE: To evaluate the cost effectiveness of the cyclooxygenase 2 (COX-2) selective nonsteroidal antiinflammatory drug (NSAID) rofecoxib compared with naproxen and the COX-2 NSAID celecoxib compared with ibuprofen and diclofenac. METHODS: Cost-effectiveness analysis based on a 5-year Markov model. Probability estimates were derived from detailed data of 2 randomized trials and a systematic search of the medical literature. Utility estimates were obtained from 60 randomly selected members of the general public. Cost estimates were obtained from Canadian provincial databases. Incremental cost-effectiveness ratios were calculated for patients at average risk of upper gastrointestinal (UGI) events and for high-risk patients with a prior history of a UGI event. Subjects were patients with osteoarthritis or rheumatoid arthritis (RA) where a decision has been made to treat with NSAIDs but who do not require low-dose aspirin. Main outcome measures were proportion of patients with clinical or complicated UGI events, quality-adjusted life expectancy, and life expectancy. RESULTS: Evaluation of rofecoxib versus naproxen in patients with RA at average risk resulted in costs per quality-adjusted life year (QALY) gained of $Can271,188. Celecoxib was dominated by diclofenac in average-risk patients. Both rofecoxib and celecoxib are cost-effective in high-risk patients. Analyses by age groups and assuming a threshold of Can$50,000 per QALY gained, suggest that rofecoxib or celecoxib would be cost-effective in patients aged over 76 and 81, respectively, without additional risk factors. CONCLUSION: Both rofecoxib and celecoxib are economically attractive in high risk and elderly patients. They are not economically attractive in patients at average risk. Coprescription of proton-pump inhibitors with COX-2 NSAIDs is not economically attractive for patients at high risk.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".