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Record W4402546531 · doi:10.1177/17562864241273045

The Canadian Prospective Cohort Study to understand progression in multiple sclerosis: baseline characteristics

2024· article· en· W4402546531 on OpenAlexafffundabout
Jiwon Oh, Nathalie Arbour, Fabrizio Giuliani, Melanie Guenette, Shannon Kolind, Larry D. Lynd, Ruth Ann Marrie, Luanne M. Metz, Alexandre Prat, Alice Schabas, Penelope Smyth, Roger Tam, Anthony Traboulsee, V. Wee Yong, Scott B. Patten

Bibliographic record

VenueTherapeutic Advances in Neurological Disorders · 2024
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsHotchkiss Brain InstituteUniversity of ManitobaProvidence Health CareUniversity of British ColumbiaUniversity of CalgaryCentre Hospitalier de l’Université de MontréalUniversity of TorontoWomen and Children’s Health Research InstituteUniversity of AlbertaCentre for Advancing Health OutcomesSt. Michael's Hospital
FundersCanadian Institutes of Health ResearchMultiple Sclerosis SocietyMultiple Sclerosis Society of CanadaMichael Smith Health Research BCHorizon TherapeuticsU.S. Department of DefenseSanofiGovernment of AlbertaFondation Brain CanadaTeva Pharmaceutical IndustriesBiogenUniversity of TorontoBiogen IdecEli Lilly and CompanyArthritis SocietyInternational Progressive MS AllianceRocheUniversity of Calgary
KeywordsMedicineMultiple sclerosisProspective cohort studyBaseline (sea)CohortInternal medicineOncologyImmunology

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.321
Threshold uncertainty score0.690

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.057
GPT teacher head0.352
Teacher spread0.295 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2024
Admission routes3
Has abstractyes

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