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Record W4409610088 · doi:10.1080/10408363.2025.2490166

A review of laboratory practices for CSF oligoclonal banding and associated tests

2025· review· en· W4409610088 on OpenAlexaffabout
Victoria Higgins, Yu Chen, Mark S. Freedman, Karina Rodríguez-Capote, Daniel R. Beriault

Bibliographic record

VenueCritical Reviews in Clinical Laboratory Sciences · 2025
Typereview
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsUniversity of OttawaUniversity of British ColumbiaHorizon Health NetworkInterior HealthDr. Everett Chalmers Regional HospitalMemorial University of NewfoundlandUniversity of TorontoDalhousie UniversityUniversity of Alberta
Fundersnot available
KeywordsMedicineImmunology

Abstract

fetched live from OpenAlex

Multiple sclerosis (MS) is a chronic autoimmune disorder affecting the central nervous system, often emerging in early adulthood and representing a leading cause of neurological disability in young adults. Diagnosing MS involves a combination of clinical assessment, imaging and laboratory tests, with cerebrospinal fluid (CSF)-specific immunoglobulin G (IgG) oligoclonal bands (OCB) being an important marker for fulfilling the dissemination in time criteria. A recent survey of Canadian clinical laboratories highlighted considerable variation in OCB reporting practices nationwide, spanning quality control (QC) practices, acceptable time limits between paired CSF and serum sample collections, protocols for reporting band counts, interpretation and reporting of mirrored patterns, testing panels, and interpretive thresholds. These inconsistencies impact patient care and the comparability of laboratory results across different laboratories. The Harmonized CSF Analysis for MS Investigation (hCAMI) subcommittee of the Canadian Society of Clinical Chemists Reference Interval Harmonization Working Group was established to generate recommendations for laboratory processes and reporting of CSF OCB and associated tests supporting MS diagnosis. This review serves as a foundation for these efforts, summarizing the available evidence in areas where practice variations have been noted. This review begins by examining current practices and guidelines for standardized quality assurance, including optimal QC materials, frequency, documentation, and participation in external quality assurance programs. The disparity between paired CSF and serum sample acceptability time limits was further examined by reviewing current practices and recommendations as well as compiling evidence on IgG synthesis, turnover rate, biological variation, and stability in CSF and serum samples. Additionally, this review addresses the lack of consensus on reporting the number of CSF-specific and CSF-serum matched bands, focusing on interpreter variability and clinical utility. Contributing factors and clinical implications of mirror patterns, including discussion on monoclonal gammopathies and cases of matched bands of differing staining intensity, is provided. Testing panel components including adjunctive CSF tests, such as the IgG index, to support MS investigations despite their absence from clinical guidelines is also discussed. This review also provides a comprehensive analysis of current practices, guidelines, and the evidence surrounding different cutoffs for IgG index and CSF-specific bands. Finally, the review considers emerging biomarkers, such as the kappa free light chain index and serum neurofilament light chain, which show promise for MS diagnosis and management. This comprehensive review of current practices, guidelines, and evolving evidence will guide the hCAMI subcommittee's efforts to harmonize CSF OCB analysis and improve MS diagnosis.

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)0.011
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.015
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.035
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0090.012
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.446
GPT teacher head0.628
Teacher spread0.181 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations2
Published2025
Admission routes2
Has abstractyes

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