Disease-Modifying Therapies and Adherence in Multiple Sclerosis: Comparing Patient Self-Report with Pharmacy Records
Bibliographic record
Abstract
BACKGROUND: Self-report and pharmacy records are often used to measure adherence rates to disease-modifying therapies (DMTs) in multiple sclerosis (MS), but little is known about how the sources compare. OBJECTIVE: Compare self-report and pharmacy records for assessing DMT use and adherence rates. METHODS: Demographic information, self-reported DMT use, and missed DMT doses in the previous 30 days were obtained from consecutive MS patients attending an MS clinic and linked to pharmacy records. A medication possession ratio (MPR) was calculated using pharmacy records for the year before and after the visit; MPR <80% defined nonadherence. Agreement between self-report and pharmacy records was assessed using Cohen's kappa (κ). RESULTS: Of 326 participants, 135 reported using an injectable DMT. There was near-perfect and perfect agreement between self-report and pharmacy records for DMT use (κ = 0.95; 95% CI 0.91-0.98) and DMT agent (κ = 1.00). Nonadherence was estimated at 13% (17/128) from the 30-days self-report compared to 30% (34/113) and 43% (53/123) in the year pre- and post-clinic visit from pharmacy records, indicating moderate to fair agreement (year prior: κ = 0.41; 95% CI 0.22-0.59; year post: κ = 0.22; 95% CI 0.09-0.36). CONCLUSIONS: Patients self-reports closely reflected pharmacy records when assessing DMT use and product. Moderate to fair agreement was found when comparing adherence rates between sources.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".