Increasing Use of Disease Modifying Drugs for MS in Canada
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: The course of multiple sclerosis may be slowed by use of the disease modifying drugs (DMDs): subcutaneous or intramuscular interferon beta-1a, interferon beta-1b, glatiramer acetate, and natalizumab. We set out to compare utilization of these drugs in the Canadian provinces from 2002-2007. METHODS: Using a retrospective cohort analysis, we reviewed population data from International Medical Statistics (IMS) Health between November 2001 and October 2007. RESULTS: The total annual number of DMD prescriptions increased from 3.9, in 2002, to 5.1, in 2007, per 1,000 Canadians. The total annual cost of prescriptions rose from $187 million to $287 million. Of the four provinces responsible for the majority of prescriptions--Alberta, BC, Ontario, and Quebec--Quebec had the highest average annual prescription rate (7 per 1,000 population) and BC had the lowest rate (3.3 per 1,000 population). Subcutaneous interferon beta-1a was the most commonly used drug whereas glatiramer acetate showed the greatest growth in use from 2002 to 2007. CONCLUSIONS: Disease modifying drugs prescription rates and costs increased by more than 30% between 2002 and 2007. There was wide variation in DMD prescription rates and relative drug preferences across the provinces.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".