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Record W3096312861 · doi:10.1002/gcc.22912

Case of epithelioid hemangioendothelioma occurring in the postradiation setting for breast cancer

2020· article· en· W3096312861 on OpenAlexaff
Elan Hahn, Brendan C. Dickson, Abha A. Gupta, Sharon Nofech‐Mozes

Bibliographic record

VenueGenes Chromosomes and Cancer · 2020
Typearticle
Languageen
FieldMedicine
TopicVascular Tumors and Angiosarcomas
Canadian institutionsPrincess Margaret Cancer CentreSinai Health SystemSunnybrook Health Science CentreHealth Sciences CentreMount Sinai HospitalUniversity of Toronto
Fundersnot available
KeywordsEpithelioid hemangioendotheliomaMedicineHemangioendotheliomaPathologyAngiosarcomaCD31Differential diagnosisRadiation therapyBreast cancerEpithelioid sarcomaHemangiosarcomaEpithelioid cellCancerSarcomaImmunohistochemistryRadiologyInternal medicine

Abstract

fetched live from OpenAlex

Epithelioid hemangioendothelioma (EHE) is a rare malignant vascular tumor, which is typically characterized by recurrent fusion genes. EHEs most commonly occur in the lung, liver, bone, and internal organs. EHE has rarely been reported to occur in the post-radiotherapeutic setting, the breast site or in association with breast cancer. The differential diagnosis for radiation-associated vascular lesions of the breast is classically limited to atypical vascular lesion and angiosarcoma and does not include EHE. We present the case of a woman with a history of breast cancer and post-surgical radiotherapy who went on to develop an EHE of the chest wall skin within 3 years of the completion of radiotherapy. Microscopically, the lesion was infiltrative and composed of anastomosing nests of epithelioid-to-spindled cells with eosinophilic and vacuolated cytoplasm. By immunohistochemistry, the cells were positive for ERG, D2-40, and CD31. The diagnosis was confirmed by identification of a characteristic WWTR1-CAMTA1 fusion gene using RNA sequencing. This case expands our understanding of radiation-associated tumors.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.645
Threshold uncertainty score0.269

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.287
Teacher spread0.264 · 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 teacher head, 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

Citations3
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueGenes Chromosomes and CancerSame topicVascular Tumors and AngiosarcomasFrench-language works237,207