MétaCan
Menu
Back to cohort
Record W2572250031 · doi:10.1182/blood-2016-10-746933

International, evidence-based consensus diagnostic criteria for HHV-8–negative/idiopathic multicentric Castleman disease

2017· article· en· W2572250031 on OpenAlexaff
David C. Fajgenbaum, Thomas S. Uldrick, Adam Bagg, Dale Frank, David Wu, Gordan Srkalović, David Simpson, Amy Liu, David M. Menke, Shanmuganathan Chandrakasan, Mary Jo Lechowicz, Raymond Wong, Sheila K. Pierson, Michele Paessler, Jean‐François Rossi, Makoto Ide, Jason R. Ruth, M.P. Croglio, Alexander Suarez, Vera P. Krymskaya, Amy Chadburn, Gisele W. B. Colleoni, Sunita D. Nasta, Raj Jayanthan, Christopher S. Nabel, Corey Casper, Angela Dispenzieri, Alexander Fosså, Dermot Kelleher, Razelle Kurzrock, Peter M. Voorhees, Ahmet Doǧan, Kazuyuki Yoshizaki, Frits van Rhee, Éric Oksenhendler, Elaine S. Jaffe, Kojo S.J. Elenitoba‐Johnson, Megan S. Lim

Bibliographic record

VenueBlood · 2017
Typearticle
Languageen
FieldMedicine
TopicViral-associated cancers and disorders
Canadian institutionsUniversity of British Columbia
FundersNational Institutes of HealthJanssen PharmaceuticalsNational Cancer InstituteNational Heart, Lung, and Blood InstituteUniversity of Pennsylvania
KeywordsHistopathologyMedicinePathologyDiseaseInternal medicine

Abstract

fetched live from OpenAlex

Human herpesvirus-8 (HHV-8)-negative, idiopathic multicentric Castleman disease (iMCD) is a rare and life-threatening disorder involving systemic inflammatory symptoms, polyclonal lymphoproliferation, cytopenias, and multiple organ system dysfunction caused by a cytokine storm often including interleukin-6. iMCD accounts for one third to one half of all cases of MCD and can occur in individuals of any age. Accurate diagnosis is challenging, because no standard diagnostic criteria or diagnostic biomarkers currently exist, and there is significant overlap with malignant, autoimmune, and infectious disorders. An international working group comprising 34 pediatric and adult pathology and clinical experts in iMCD and related disorders from 8 countries, including 2 physicians that are also iMCD patients, was convened to establish iMCD diagnostic criteria. The working group reviewed data from 244 cases, met twice, and refined criteria over 15 months (June 2015 to September 2016). The proposed consensus criteria require both Major Criteria (characteristic lymph node histopathology and multicentric lymphadenopathy), at least 2 of 11 Minor Criteria with at least 1 laboratory abnormality, and exclusion of infectious, malignant, and autoimmune disorders that can mimic iMCD. Characteristic histopathologic features may include a constellation of regressed or hyperplastic germinal centers, follicular dendritic cell prominence, hypervascularization, and polytypic plasmacytosis. Laboratory and clinical Minor Criteria include elevated C-reactive protein or erythrocyte sedimentation rate, anemia, thrombocytopenia or thrombocytosis, hypoalbuminemia, renal dysfunction or proteinuria, polyclonal hypergammaglobulinemia, constitutional symptoms, hepatosplenomegaly, effusions or edema, eruptive cherry hemangiomatosis or violaceous papules, and lymphocytic interstitial pneumonitis. iMCD consensus diagnostic criteria will facilitate consistent diagnosis, appropriate treatment, and collaborative research.

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)0.009
metaresearch head score (Gemma)0.015
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: Methods · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0070.003
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0050.002
Research integrity0.0020.002
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 head0.058
GPT teacher head0.348
Teacher spread0.290 · 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
GenreMethods

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

Citations624
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueBloodSame topicViral-associated cancers and disordersFrench-language works237,207