MétaCan
Menu
Back to cohort
Record W4392660066 · doi:10.1001/jamaneurol.2024.0017

Emerging Cerebrospinal Fluid Biomarkers of Disease Activity and Progression in Multiple Sclerosis

2024· article· en· W4392660066 on OpenAlexaff
Anne H. Cross, Jeffrey M. Gelfand, Simon Thebault, Jeffrey L. Bennett, H.-Christian von Büdingen, Briana Cameron, Robert Carruthers, Keith R. Edwards, Robert J. Fallis, Rachel M. Gerstein, Paul S. Giacomini, Benjamin Greenberg, David A. Hafler, Carolina Ionete, Ulrike W. Kaunzner, Lay Kodama, Christopher Lock, Erin E. Longbrake, Bruno Musch, Gabriel Pardo, Fredrik Piehl, Martin S. Weber, Steven Yuen, Tjalf Ziemssen, Gauruv Bose, Mark S. Freedman, Veronica G. Anania, Akshaya Ramesh, Ryan C. Winger, Xiaoming Jia, Ann Herman, Christopher Harp, Amit Bar‐Or

Bibliographic record

VenueJAMA Neurology · 2024
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsUniversity of OttawaOttawa HospitalMcGill UniversityUniversity of British Columbia
Fundersnot available
KeywordsCohortMedicineMultiple sclerosisCerebrospinal fluidInternal medicineExpanded Disability Status ScaleCohort studyProspective cohort studyPathologyOncologyImmunology

Abstract

fetched live from OpenAlex

Importance: Biomarkers distinguishing nonrelapsing progressive disease biology from relapsing biology in multiple sclerosis (MS) are lacking. Cerebrospinal fluid (CSF) is an accessible fluid that most closely reflects central nervous system biology. Objective: To identify CSF biological measures associated with progressive MS pathobiology. Design, Setting, and Participants: This cohort study assessed data from 2 prospective MS cohorts: a test cohort provided serial CSF, clinical, and imaging assessments in a multicenter study of patients with relapsing MS (RMS) or primary progressive MS (PPMS) who were initiating anti-CD20 treatment (recruitment: 2016-2018; analysis: 2020-2023). A single-site confirmation cohort was used to assess CSF at baseline and long-term (>10 year) clinical follow-up (analysis: 2022-2023). Exposures: Test-cohort participants initiated standard-of-care ocrelizumab treatment. Confirmation-cohort participants were untreated or received standard-of-care disease-modifying MS therapies. Main Outcomes and Measures: Twenty-five CSF markers, including neurofilament light chain, neurofilament heavy chain, and glial fibrillary acid protein (GFAP); 24-week confirmed disability progression (CDP24); and brain magnetic resonance imaging measures reflecting focal injury, tissue loss, and progressive biology (slowly expanding lesions [SELs]). Results: The test cohort (n = 131) included 100 patients with RMS (mean [SD] age, 36.6 [10.4] years; 68 [68%] female and 32 [32%] male; Expanded Disability Status Scale [EDSS] score, 0-5.5), and 31 patients with PPMS (mean [SD] age, 44.9 [7.4] years; 15 [48%] female and 16 [52%] male; EDSS score, 3.0-6.5). The confirmation cohort (n = 68) included 41 patients with RMS and 27 with PPMS enrolled at diagnosis (age, 40 years [range, 20-61 years]; 47 [69%] female and 21 [31%] male). In the test cohort, GFAP was correlated with SEL count (r = 0.33), greater proportion of T2 lesion volume from SELs (r = 0.24), and lower T1-weighted intensity within SELs (r = -0.33) but not with acute inflammatory measures. Neurofilament heavy chain was correlated with SEL count (r = 0.25) and lower T1-weighted intensity within SELs (r = -0.28). Immune markers correlated with measures of acute inflammation and, unlike GFAP, were impacted by anti-CD20. In the confirmation cohort, higher baseline CSF GFAP levels were associated with long-term CDP24 (hazard ratio, 2.1; 95% CI, 1.3-3.4; P = .002). Conclusions and Relevance: In this study, activated glial markers (in particular GFAP) and neurofilament heavy chain were associated specifically with nonrelapsing progressive disease outcomes (independent of acute inflammatory activity). Elevated CSF GFAP was associated with long-term MS disease progression.

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)0.003
metaresearch head score (Gemma)0.007
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 score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.051
GPT teacher head0.330
Teacher spread0.278 · 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

Citations92
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJAMA NeurologySame topicMultiple Sclerosis Research StudiesFrench-language works237,207