Cost Effectiveness Analysis of Avonex and CinnoVex in Relapsing Remitting MS
Bibliographic record
Abstract
INTRODUCTION: Multiple sclerosis is a chronic and degenerative neurological disease characterized by loss of myelin sheath of some neurons in brain and spinal cord. It is associated with high economic burden due to premature deaths and high occurrence of disabilities. The aim of the current study was to determine cost effectiveness of two major products of interferon 1a in patients with relapsing-remitting multiple sclerosis. METHOD AND MATERIALS: Altogether, 140 patients who have consumed Avonex and CinnoVex in Relapsing Remitting MS for at least two years were randomly selected (70 patients in each group). Health-related quality of life (HRQoL) was assessed using the adopted MSQoL-54 instrument. Costs were measured and valued from Ministry of Health and Medical Education (MOHME) perspective. Two-way sensitivity analysis was used to check robustness of the results. RESULTS: Patients in CinnoVex group reported significantly higher scores in both physical (69.5 vs. 50.9, P<0.001) and mental (63.3 vs. 56.6, P=0.03) aspects of HRQoL than Avonex group. On the other hand, annual cost of CinnoVex and Avonex were 2410 US$ and 4515US$ per patient, respectively (P<0.001). CONCLUSIONS: The results showed that CinnoVex was dominant option over the study period. It is suggested that results of the current study should be considered in allocating resources to MS treatments in Iran. Of course, our findings should be interpreted with caution duo to short term horizon and lack of HRQoL scores at baseline (before the intervention).
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| 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) | 0.003 | 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".