Prescribing trends in disease modifying antirheumatic drugs for rheumatoid arthritis: a survey of practicing Canadian rheumatologists.
Bibliographic record
Abstract
OBJECTIVE: To determine the prescribing and monitoring practices of disease modifying antirheumatic drugs (DMARD) for Canadian rheumatologists in their treatment of rheumatoid arthritis (RA). METHODS: A survey questionnaire was mailed to 279 rheumatologists with a 70% response rate after 2 mailings. RESULTS: Antimalarials are prescribed commonly, with the preference being hydroxychloroquine (HCQ). For antimalarials, 78% do not routinely monitor laboratory results. There was wide variability in monitoring for ocular complications. Thirty-eight percent of rheumatologists never do a baseline eye examination and 39% always do. All rheumatologists frequently use methotrexate (MTX) in RA. The reported mean maximum dose for MTX was 25.1 mg/week (range 7.5-50), with 86% routinely using folate. Ninety-eight percent prescribe sulfasalazine (SSZ) for RA. Mean maximum dose prescribed for SSZ was 2.8 g/day. Most never used oral gold, while IM gold was used by 95%. Only 9% frequently use azathioprine in RA, to a mean maximum dose of 185 mg/day. Less commonly prescribed DMARD included cyclosporine (66% frequently; 25% never) and D-penicillamine (2% frequently; 53% never). There was a wide range of what exactly was monitored with respect to laboratory tests, and at what frequency, for many of the DMARD. Nearly all (99%) used combination DMARD, the most popular combination being MTX-HCQ. There were some significant differences in treatment trends when comparing year of fellowship completion, but no sex or type of practice differences were found. Those completing fellowships prior to 1984 were more likely to prescribe azathioprine (p < 0.03), chloroquine (p < 0.01) and chronic steroids (p < 0.1) in RA. There was, however, regional variability in the use of IM gold and newer DMARD--they were most prescribed in Western Canada and least in Quebec. Cyclosporine was prescribed most frequently in Quebec compared to Western Canada and least in Ontario and the Atlantic Provinces. CONCLUSION: Canadian rheumatologists are fairly similar in their use of common DMARD and combination therapies in RA. There is variability in the use of some older medications including azathioprine and chloroquine, depending on when rheumatology training was completed, and use of some drugs varies by region.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".