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Record W4416454524 · doi:10.1017/cjn.2025.10479

Equity of Access to Disease-Modifying Therapy for Pediatric Multiple Sclerosis: A Survey of Canadian Prescribers

2025· article· en· W4416454524 on OpenAlexaffvenueabout
Judith Glennie, Lauren Strasser, Beyza Çiftçi, Joley Johnstone, Penelope Smyth, Helen Tremlett, E. Ann Yeh

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2025
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsUniversity of AlbertaUniversity of British ColumbiaLondon Health Sciences CentreHospital for Sick Children
Fundersnot available
KeywordsEquity (law)Government (linguistics)Health insuranceAccess to medicinesHealth careHealth equity

Abstract

fetched live from OpenAlex

A perceived barrier to effective treatment of pediatric-onset multiple sclerosis (POMS) is access to disease-modifying therapies (DMTs). An online Canada-wide survey of POMS DMT prescribers was used to identify patterns in, and barriers to, DMT access. Nineteen prescribers provided responses. Overall, DMT access via private versus government drug plans was variable. First-generation (e.g., beta-interferon) DMTs were more accessible via government plans versus second-generation DMTs (e.g., ocrelizumab). Most DMTs were available through private insurance plans. B-cell depleting therapies were the most difficult to access. Variability in DMT access for POMS raises concerns about health equity and care optimization.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.017
Threshold uncertainty score0.123

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.296
GPT teacher head0.393
Teacher spread0.097 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2025
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques→Same topicMultiple Sclerosis Research Studies→French-language works237,207→