The Canadian Prospective Cohort Study to understand progression in multiple sclerosis: baseline characteristics
Bibliographic record
Abstract
Background: Disease progression is observed across the spectrum of people with multiple sclerosis (MS) and identification of effective treatment strategies to halt progression remains one of the greatest unmet clinical needs. Objectives: The Canadian Prospective Cohort Study to Understand Progression in MS (CanProCo) was designed to evaluate a wide range of factors associated with the onset and rate of clinical disease progression in MS and to describe the interplay between these factors. Design: A prospective cohort study. Methods: CanProCo is a national, prospective, observational cohort study that has recruited 944 individuals from 5 large academic MS centers in Canada. Participants include people with radiologically isolated syndrome (RIS), early relapsing-remitting and primary progressive MS (RRMS, PPMS), and healthy controls (HCs). Annually, participants complete self-reported questionnaires, undergo clinical evaluation and, if clinically indicated, magnetic resonance images (MRIs) of the brain and cervical spinal cord; in a subset of participants ( n = 399), blood, and research MRIs of the brain and cervical spinal cord are collected. Linkages to health administrative databases are available at three sites. Results: Overall, 944 participants were recruited (53 HCs, 63 RIS, 751 RRMS, 77 PPMS). RIS and MS participants had a mean age of 39.0 years and 70.5% female. The mean time since diagnosis was 2.7 years. There were differences observed in the Expanded Disability Status Scale score and components of the MS performance test (walking speed test, manual dexterity test, processing speed test, and low-contrast visual acuity) between RIS and MS subtypes. Questionnaires revealed more symptoms of depression and anxiety and impaired physical and mental quality of life in people with RIS/MS versus HCs and differences across RIS/MS subtypes. Conclusion: Physical and mental neurological disability is prevalent even in the earliest stages of MS. Transdisciplinary approaches such as those used in CanProCo are needed to better characterize clinical progression in MS. Additional CanProCo results, including MRI, biological, and pharmaco-economic data will be forthcoming. Going forward, CanProCo’s data sharing and collaborative vision will facilitate numerous global collaborations, which will inform the development and implementation of effective interventions for people with MS around the world.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".