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Record W2146652817 · doi:10.1002/pbc.20305

Lack of response of a metastatic renal perivascular epithelial cell tumor (PEComa) to successive courses of DTIC based-therapy and imatinib mesylate

2005· article· en· W2146652817 on OpenAlexaff
Heather Rigby, Weiming Yu, Matthias H. Schmidt, Conrad V. Fernandez

Bibliographic record

VenuePediatric Blood & Cancer · 2005
Typearticle
Languageen
FieldMedicine
TopicTuberous Sclerosis Complex Research
Canadian institutionsIzaak Walton Killam Health CentreDalhousie University
Fundersnot available
KeywordsMedicinePerivascular Epithelioid CellDacarbazineImatinib mesylateImatinibTyrosine-kinase inhibitorDiscontinuationRegimenClear-cell sarcomaPDGFRAPathologyOncologyChemotherapyInternal medicineEpithelioid cellSarcomaCancerImmunohistochemistry

Abstract

fetched live from OpenAlex

An 11 year-old girl presented with two large abdominal masses in the left flank and epigastrium and left supraclavicular lymphadenopathy. Subsequent investigations led to the diagnosis of metastatic perivascular epithelioid cell tumor (PEComa) arising from the left kidney. Effective treatment for this rare tumor is not yet known. The tumor did not respond to an initial treatment of two cycles of a dacarbazine (DTIC) based regimen. She was placed on a trial of imatinib mesylate based on tumor expression of c-KIT, a tyrosine kinase targeted by this drug. This report highlights the first documented case of the use of imatinib for PEComa. Lack of response and adverse effects of the drug required discontinuation of therapy.

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)0.000
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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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 integrity0.0010.001
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 head0.063
GPT teacher head0.352
Teacher spread0.289 · 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 designCase report
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

Citations32
Published2005
Admission routes1
Has abstractyes

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