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Record W4411004603 · doi:10.1002/art.43269

Expert Perspective: Diagnosis and Treatment of Castleman Disease

2025· review· en· W4411004603 on OpenAlexafffund
Luke Y. C. Chen, Lu Zhang, David C. Fajgenbaum

Bibliographic record

VenueArthritis & Rheumatology · 2025
Typereview
Languageen
FieldMedicine
TopicViral-associated cancers and disorders
Canadian institutionsUniversity of British ColumbiaDalhousie University
FundersNational Heart, Lung, and Blood InstituteChinese Academy of Medical SciencesChinese Academy of SciencesVGH and UBC Hospital FoundationU.S. Food and Drug AdministrationUniversity of Pennsylvania
KeywordsMedicineCastleman diseaseAnasarcaOrganomegalyPathologyLymph nodeLymphomaHypergammaglobulinemiaImmunologyHemophagocytic lymphohistiocytosisDiseaseInternal medicine

Abstract

fetched live from OpenAlex

Castleman disease (CD) is a major diagnostic challenge for rheumatologists. Unicentric CD (UCD) involves one enlarged lymph node region, whereas multicentric CD (MCD) involves multiple enlarged lymph node regions. Both UCD and MCD may exhibit a wide range of symptoms that overlap with other immune-mediated conditions. MCD can be associated with excessive cytokine production due to a plasma cell neoplasm (MCD-polyneuropathy, organomegaly, endocrinopathy, monoclonal paraprotein, skin changes) or uncontrolled human herpesvirus-8 infection (HHV-8) (HHV-8-positive MCD), but more than half of cases are idiopathic. Although they are all driven by excessive cytokines such as interleukin-6 (IL-6), patients with idiopathic MCD (iMCD) often present as a diagnostic mystery with heterogeneous symptomatology that can be classified into three subtypes. The three subtypes are iMCD-thrombocytopenia, anasarca, fever, renal dysfunction/reticulin fibrosis, organomegaly (TAFRO); iMCD-idiopathic plasmacytic lymphadenopathy (IPL); and iMCD-not otherwise specified (NOS). Rapid onset cytokine storm with severe inflammation, anasarca, thrombocytopenia, and small volume lymphadenopathy, similar to hemophagocytic lymphohistiocytosis or sepsis, are the hallmarks of iMCD-TAFRO. Patients with iMCD-IPL present with subacute or chronic lymphadenopathy, anemia of inflammation, and polyclonal hypergammaglobulinemia, often with increased IgG4 in serum and lymph node tissue; these cases can be difficult to distinguish from IgG4-related disease and histiocyte disorders. Those who have iMCD not meeting criteria for TAFRO or IPL have iMCD-NOS, which often mimics indolent lymphoma or autoimmune conditions. Patients with autoimmune disease, lymphoma, and infections can experience Castleman-like changes in reactive lymph nodes, and thus histologic findings must be combined with clinical and laboratory findings to accurately diagnose iMCD. Broadly speaking, treatments for CD can be considered in three categories: immunomodulators such as glucocorticoids, cytokine inhibitors, and sirolimus; antilymphoma therapies such as rituximab, cytotoxic chemotherapy, and BTK inhibitors; and antimyeloma therapies such as thalidomide and bortezomib. The first-line therapy for all subtypes of iMCD is siltuximab, an IL-6 antagonist. Patients with refractory disease have numerous treatment options and consulting treatment guidelines as well as consultation with a center with expertise in CD are recommended.

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)0.001
metaresearch head score (Gemma)0.006
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: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.037
Threshold uncertainty score0.123

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0370.019

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 head0.025
GPT teacher head0.346
Teacher spread0.320 · 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

Citations23
Published2025
Admission routes2
Has abstractyes

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