The Canadian prospective cohort study to understand progression in multiple sclerosis (CanProCo): rationale, aims, and study design
Bibliographic record
Abstract
BACKGROUND: Neurological disability progression occurs across the spectrum of people living with multiple sclerosis (MS). Although there are a handful of disease-modifying treatments approved for use in progressive phenotypes of MS, there are no treatments that substantially modify the course of clinical progression in MS. Characterizing the determinants of clinical progression can inform the development of novel therapeutic agents and treatment approaches that target progression in MS, which is one of the greatest unmet needs in clinical practice. Canada, having one of the world's highest rates of MS and a publicly-funded health care system, represents an optimal country to achieve in-depth analysis of progression. Accordingly, the overarching aim of the Canadian Prospective Cohort Study to Understand Progression in MS (CanProCo) is to evaluate a wide spectrum of factors associated with the clinical onset and rate of disease progression in MS, and to describe how these factors relate to one another to influence progression. METHODS: CanProCo is a prospective, observational cohort study with investigators specializing in epidemiology, neuroimaging, neuroimmunology, health services research and health economics. CanProCo's study design was approved by an international review panel, comprised of content experts and key stakeholders. One thousand individuals with radiologically-isolated syndrome, relapsing-remitting MS, and primary-progressive MS within 10-15 years of disease onset will be recruited from 5 academic MS centres in Canada. Participants will undergo detailed clinical evaluation annually over 5 years (including advanced, app-based clinical data collection). In a subset of participants within 5-10 years of disease onset (n = 500), blood, cerebrospinal fluid, and research MRIs will be collected allowing an integrated, in-depth evaluation of factors contributing to progression in MS from multiple perspectives. Factors of interest range from biological measures (e.g. single-cell RNA-sequencing), MRI-based microstructural assessment, participant characteristics (self-reported, performance-based, clinician-assessed, health-system based), and micro and macro-environmental factors. DISCUSSION: Halting the progression of MS remains a fundamental need to improve the lives of people living with MS. Achieving this requires leveraging transdisciplinary approaches to better characterize why clinical progression occurs. CanProCo is a pioneering multi-dimensional cohort study aiming to characterize these determinants to inform the development and implementation of efficacious and effective interventions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".