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Record W1831380443 · doi:10.3747/co.2007.132

Phase II Testing of Sunitinib: The National Cancer Institute of Canada Clinical Trials Group IND Program Trials IND.182–185

2007· article· en· W1831380443 on OpenAlexaffvenueabout
Rena Buckstein, Ralph M. Meyer, Lesley Seymour, James Biagi, Helen Mackay, Scott A. Laurie, Elizabeth A. Eisenhauer

Bibliographic record

VenueCurrent Oncology · 2007
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsOttawa Regional Cancer FoundationPrincess Margaret Cancer CentreQueen's UniversityCancer Care OntarioOntario Institute for Cancer Research
Fundersnot available
KeywordsMedicineSunitinibClinical trialBevacizumabVascular endothelial growth factorOncologyAngiogenesisInternal medicinePDGFRATyrosine-kinase inhibitorCancer researchCancerChemotherapyVEGF receptorsStromal cellGiST

Abstract

fetched live from OpenAlex

Sunitinib (SU11248) is an orally bioavailable inhibitor that affects the receptor tyrosine kinases involved in tumour proliferation and angiogenesis, including vascular endothelial growth factor (VEGF) receptors 1, 2, 3, and platelet-derived growth factor receptors alpha (PDGFRA) and beta (PDGFRB). Because angiogenesis is necessary for the growth and metastasis of solid tumours, and VEGF is believed to have a pivotal role in that process, SUNITINIB treatment may have broad-spectrum clinical utility. In the present article, we discuss the biologic and clinical rationales that have recently led the Investigational New Drug Program of the National Cancer Institute of Canada Clinical Trials Group to initiate four phase ii trials testing this agent in the following four different tumour types: relapsed diffuse large cell lymphoma, malignant pleural mesothelioma, locally advanced or metastatic cervical cancer and recurrent epithelial ovarian, fallopian tube, or primary peritoneal carcinoma.

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)0.003
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.973
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.618
GPT teacher head0.609
Teacher spread0.008 · 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 designNon-randomized trial
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

Citations41
Published2007
Admission routes3
Has abstractyes

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