Adherence to Multiple Sclerosis Disease-Modifying Therapies in Ontario is Low
Bibliographic record
Abstract
BACKGROUND/OBJECTIVE: Differences in patient adherence to various disease-modifying drugs (DMDs) in the treatment of multiple sclerosis (MS) are not well understood. The goal of this study was to evaluate adherence of adult MS patients in Ontario with public drug plan coverage to various DMDs: intramuscular interferon beta-1a (i.m. IFNβ-1a, Avonex), subcutaneous interferon beta-1a (s.c. IFNβ-1a, Rebif), subcutaneous interferon beta-1b (IFNβ-1b, Betaseron) or glatiramer acetate (Copaxone). METHODS: In this retrospective cohort study, Ontario Public Drug Plan beneficiaries aged 15 or older who were newly treated with i.m. IFNβ-1a, s.c. IFNβ-1a, IFNβ-1b or glatiramer acetate between April 2006 and March 2008 were followed forward until treatment discontinuation, switch to another DMD or a maximum two year follow-up period. Cumulative persistence rates were analyzed by the Kaplan-Meier method. The proportion of patients reaching the study endpoints after the two year follow-up period was also calculated. RESULTS: Cumulative persistence rates for all four DMDs were similar over time (p=0.80), ranging from 73.6-79.1% at six months, 59.1-63.1% at one year and 41.5-47.4% at two years. After two years, the proportion of patients who had discontinued treatment, switched to another DMD or died was similar among DMDs (p=0.79, Fisher's exact test). Switching between DMD types was low and occurred in 3.4-6.5% of new DMD users. CONCLUSIONS: Adherence to DMDs in adult MS patients in Ontario is poor, which is consistent with previously reported adherence rates to MS DMDs in other regions. No significant differences in adherence exist between the DMDs evaluated in this study.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".