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Tumours of histiocytes and accessory dendritic cells: an immunohistochemical approach to classification from the International Lymphoma Study Group based on 61 cases

2002· article· en· W2127524795 on OpenAlexaff
Stefano Pileri, Thomas M. Grogan, Nancy L. Harris, Peter M. Banks, Elı́as Campo, John K. C. Chan, Riccardo Dalla Favera, Georges Delsol, Christiane De Wolf‐Peeters, Brunangelo Falini, R. D. Gascoyne, Philippe Gaulard, Kevin C. Gatter, P G Isaacson, Elaine S. Jaffe, P.M. Kluin, Dan Knowles, David Y. Mason, Shunsuke Mori, H‐K Müller‐Hermelink, Miguel Á. Piris, Elisabeth Ralfkiær, H. Stein, I‐J Su, Roger A. Warnke, Lawrence M. Weiss

Bibliographic record

VenueHistopathology · 2002
Typearticle
Languageen
FieldMedicine
TopicHistiocytic Disorders and Treatments
Canadian institutionsBC Cancer Agency
FundersNational Cancer Institute
KeywordsHistiocyteCD68Histiocytic sarcomaPathologyS100 proteinDendritic cellLangerhans cellImmunohistochemistryLymphomaFollicular dendritic cellsHistiocytosisBiologyMedicineAntigenT cellAntigen-presenting cellImmunologyImmune systemDisease

Abstract

fetched live from OpenAlex

Neoplasms of histiocytes and dendritic cells are rare, and their phenotypic and biological definition is incomplete. Seeking to identify antigens detectable in paraffin-embedded sections that might allow a more complete, rational immunophenotypic classification of histiocytic/dendritic cell neoplasms, the International Lymphoma Study Group (ILSG) stained 61 tumours of suspected histiocytic/dendritic cell type with a panel of 15 antibodies including those reactive with histiocytes (CD68, lysozyme (LYS)), Langerhans cells (CD1a), follicular dendritic cells (FDC: CD21, CD35) and S100 protein. This analysis revealed that 57 cases (93%) fit into four major immunophenotypic groups (one histiocytic and three dendritic cell types) utilizing six markers: CD68, LYS, CD1a, S100, CD21, and CD35. The four (7%) unclassified cases were further classifiable into the above four groups using additional morphological and ultrastructural features. The four groups then included: (i) histiocytic sarcoma (n=18) with the following phenotype: CD68 (100%), LYS (94%), CD1a (0%), S100 (33%), CD21/35 (0%). The median age was 46 years. Presentation was predominantly extranodal (72%) with high mortality (58% dead of disease (DOD)). Three had systemic involvement consistent with 'malignant histiocytosis'; (ii) Langerhans cell tumour (LCT) (n=26) which expressed: CD68 (96%), LYS (42%), CD1a (100%), S100 (100%), CD21/35 (0%). There were two morphological variants: cytologically typical (n=17) designated LCT; and cytologically malignant (n=9) designated Langerhans cell sarcoma (LCS). The LCS were often not easily recognized morphologically as LC-derived, but were diagnosed based on CD1a staining. LCT and LCS differed in median age (33 versus 41 years), male:female ratio (3.7:1 versus 1:2), and death rate (31% versus 50% DOD). Four LCT patients had systemic involvement typical of Letterer-Siwe disease; (iii) follicular dendritic cell tumour/sarcoma (FDCT) (n=13) which expressed: CD68 (54%), LYS (8%), CD1a (0%), S100 (16%), FDC markers CD21/35 (100%), EMA (40%). These patients were adults (median age 65 years) with predominantly localized nodal disease (75%) and low mortality (9% DOD); (iv) interdigitating dendritic cell tumour/sarcoma (IDCT) (n=4) which expressed: CD68 (50%), LYS (25%), CD1a (0%), S100 (100%), CD21/35 (0%). The patients were adults (median 71 years) with localized nodal disease (75%) without mortality (0% DOD). In conclusion, definitive immunophenotypic classification of histiocytic and accessory cell neoplasms into four categories was possible in 93% of the cases using six antigens detected in paraffin-embedded sections. Exceptional cases (7%) were resolvable when added morphological and ultrastructural features were considered. We propose a classification combining immunophenotype and morphology with five categories, including Langerhans cell sarcoma. This simplified scheme is practical for everyday diagnostic use and should provide a framework for additional investigation of these unusual neoplasms.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
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 head0.049
GPT teacher head0.282
Teacher spread0.233 · 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".

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Citations664
Published2002
Admission routes1
Has abstractyes

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