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Record W1980888804 · doi:10.1002/cncr.11121

Primitive neuroectodermal tumors in the central nervous system following cranial irradiation

2003· article· en· W1980888804 on OpenAlexaff
Walter Hader, Katerina Drovini‐Zis, John A. Maguire

Bibliographic record

VenueCancer · 2003
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsUniversity of British ColumbiaUniversity of Calgary
Fundersnot available
KeywordsMedicineEpendymomaAstrocytomaRadiation therapyPosterior cranial fossaPilocytic astrocytomaMedulloblastomaHemangiopericytomaCentral nervous systemPrimitive neuroectodermal tumorDifferential diagnosisPathologySarcomaRadiologyGliomaInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Radiation induced intracranial neoplasms are uncommon but well described and include gliomas, meningiomas, and sarcomas. The development of primitive neuroectodermal tumors (PNETs) following prophylactic craniospinal irradiation has been infrequently reported previously. The authors present four additional cases of PNETs that developed after previous cranial irradiation. METHODS: Four patients who had previously been irradiated were determined to have PNETs of the central nervous system characterized by histopathologic and immunohistochemical features. The average patient age at diagnosis of the initial tumors and cranial irradiation was 17 years. The PNETs developed 5, 11, 11, and 18 years after completion of radiation. RESULTS: Three patients had posterior fossa tumors, one pilocytic astrocytoma, one low grade astrocytoma, and one malignant ependymoma, which had been diagnosed and treated in childhood. Two of those patients developed supratentorial PNETs and the third a cerebellar hemispheric PNET. The fourth patient developed a posterior fossa PNET following irradiation for a temporal astrocytoma, which was initially diagnosed and resected at 37 years of age. Mean survival was 12 months after diagnosis. CONCLUSIONS: The development of PNETs after cranial irradiation may be more common than thought previously and should be considered in the differential diagnosis of irradiation induced neoplasms. Survival after diagnosis of these radiation induced PNETs was short, and this may reflect an inability to provide standard therapy used for primary PNETs.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.240

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 head0.014
GPT teacher head0.265
Teacher spread0.251 · 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

Citations38
Published2003
Admission routes1
Has abstractyes

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