Anti-depressant use in association with interferon and glatiramer acetate treatment in multiple sclerosis
Bibliographic record
Abstract
BACKGROUND: Randomized controlled trials incorporating validated depression scales have failed to identify an association between interferon beta treatment and depression in MS. This is surprising since interferons used in other clinical contexts are considered capable of causing depression. The negative results in MS could be due inadequate power in the published trials. METHODS: In this study, longitudinal data from an IMS Health Canada database called the Therapy Dynamics database were analyzed. The database contains information about prescriptions filled at outpatient pharmacies in Canada, linked at the individual level over time periods as long as 36 months. Antidepressant prescriptions were used as a proxy indicator for depressive disorders. The frequency of antidepressant use was compared in cohorts treated with glatiramer acetate and interferon beta. RESULTS: No differences in the frequency of antidepressant treatment were observed. A large proportion (approximately 40%) in all treatment cohorts were treated with antidepressants at some time over the study interval. The proportions remained comparable after adjustment for age and sex and in a time-to-event analysis of new antidepressant prescriptions. Among patients receiving prescriptions exclusively from Neurologists, the frequency of exposure to antidepressants was much lower (2.4%). CONCLUSIONS: This analysis uncovered no evidence that antidepressant treatment occurs more often in people treated with interferon beta than in those treated with glatiramer acetate. These results help to confirm that depression is not associated with interferon beta treatment in MS.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".