MétaCan
Menu
Back to cohort
Record W4411846648 · doi:10.3899/jrheum.2025-0314.33

Expanding the Clinical Spectrum of Myositis with Prominent B-Cell Aggregates (BCM)

2025· article· en· W4411846648 on OpenAlexaffvenueabout
Hao Cheng Shen, Marie Hudson, Yves Troyanov, Océane Landon‐Cardinal, Erin O’Ferrall, Jason Karamchandani, Benjamin Ellezam, Hugues Allard‐Chamard, Valérie Leclair

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicInflammatory Myopathies and Dermatomyositis
Canadian institutionsMontreal Neurological Institute and HospitalMcGill UniversityUniversité de MontréalHôpital du Sacré-Cœur de MontréalCentre Hospitalier Universitaire Sainte-JustineUniversité de SherbrookeJewish General Hospital
Fundersnot available
KeywordsMedicineMyositisSpectrum (functional analysis)Pathology

Abstract

fetched live from OpenAlex

Objectives Myositis with prominent B-cell aggregates (BCM) is an uncommon finding on muscle biopsy. The initial clinical phenotype of BCM was described in a series of 10 cases as brachio-cervical inflammatory myopathy (ie, predominantly upper more than lower extremity and neck extensor weakness) associated with other autoimmune diseases including rheumatoid arthritis.[1] Since then, only a handful of cases have been reported, including patients with an inclusion body myositis (IBM)-like phenotype. Considerable knowledge gaps remain for this entity.[2,3] Methods We aimed to describe the clinical and serological characteristics of subjects in the Canadian Inflammatory Myopathy Study (CIMS) cohort with prominent B-cell aggregates (BCM) on muscle biopsy (≥30 CD20+/aggregate). A retrospective study was performed comparing myositis cases and controls with and without BCM on muscle biopsy, respectively. Controls were classified according to clinico-sero-pathological features, as dermatomyositis (DM), overlap myositis (OM) and IBM. Results In this series of 70 subjects, 23 had BCM, 21 had DM, 17 had OM, and 9 had IBM (Table 1). There were more men in the BCM group compared to the DM group (6/23 vs 1/21), and BCM cases were older than OM cases (mean age 53 vs 46 years). BCM subjects had both upper (83%) and lower (78%) extremity weakness, with upper extremity being weaker than lower extremities in 41% of cases. A greater proportion of BCM patients were weaker proximally (52%) compared to IBM patients (22%). Neck flexor weakness was frequent (74%), while neck extensor weakness was uncommon (12%). Most BCM subjects (91%) had associated autoimmune disease: 14 had systemic sclerosis, 5 rheumatoid arthritis, and 1 patient had masticatory muscle weakness with anti-AChR antibodies. Extra-muscular features found in BCM patients included inflammatory arthritis (50%), Raynaud’s phenomenon (30%), DM rash (26%) and interstitial lung disease (22%). The most common myositis-associated autoantibodies in the BCM group were anti-PM-Scl (7/23), -Ku (3/23), -Ro52 (3/23), -CENP (2/23), -RF/-CCP (2/23) and -Mi-2 (1/23). Five BCM subjects had no myositis-specific or myositis-associated antibodies. For treatment, 39% of BCM subjects received rituximab, compared to 18% in OM and 10% in DM. Table 1. Baseline characteristics of 70 autoimmune myositis subjects Conclusion In this largest series of BCM reported to date, we found similarities (concomitant autoimmune diseases) and differences (muscle weakness distribution) with previously reported cases. BCM is a distinct histopathological entity found in several myositis subsets (OM, DM), and the presence of prominent B-cell aggregates on muscle biopsy might provide a potential therapeutic target. [1.] Pestronk A. Arthritis Rheum 2006;54(5):1687-96. [2.] Meyer A. Neuromuscular Disorders 2023;33(2):169-82. [3.] Lucchini M. Neurol Neuroimmunol Neuroinflamm 2021;8(4):e1016.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.027
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
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 head0.011
GPT teacher head0.289
Teacher spread0.277 · 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 venueThe Journal of RheumatologySame topicInflammatory Myopathies and DermatomyositisFrench-language works237,207