Treatment experience, burden, and unmet needs (TRIBUNE) in multiple sclerosis: the costs and utilities of MS patients in Canada.
Bibliographic record
Abstract
BACKGROUND: Multiple sclerosis (MS) is the most common neurological disease among young adults in Canada, but few studies to date have measured the burden imposed by MS on Canadian society. OBJECTIVES: To estimate the costs and quality of life of MS patients in Canada, while focusing on the burden of relapses and increasing disease severity. METHODS: MS patients in Canada (N=241) completed a web-based questionnaire which captured information on demographics, disease characteristics, severity (Expanded Disability Status Scale [EDSS]), comorbidities, relapses, as well as resource consumption and quality of life associated with MS. RESULTS: Most patients (74%) reported treatment with disease modifying therapies (DMTs). 54% of patients with the relapsing-remitting form of the disease with an EDSS score ≤ 5 had experienced at least one relapse in the past year. The mean cost per patient per year increased with worsening disability, and was estimated at Can $30,836 for patients with mild disability (EDSS score 0-3), Can $46,622 for patients with moderate disability (EDSS 4-6.5), and Can $77,981 for patients with severe disability due to MS (EDSS score 7-9). The excess costs of relapsing-remitting MS patients with EDSS score ≤ 5 that could be attributable to relapse(s) were estimated at Can $10,512. More severe disease and experiencing a relapse were also associated with poorer quality of life of MS patients. CONCLUSIONS: Costs of MS patients are higher today than shown in previous studies. Disease progression and relapses are associated with increased economic and quality of life burden. Effective treatment that reduces relapse frequency and prevents progression could impact both costs and quality of life and may help to reduce the societal burden of MS.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".