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Record W2080322619 · doi:10.1002/cncr.24409

Targeted inhibition of mammalian target of rapamycin for the treatment of advanced renal cell carcinoma

2009· review· en· W2080322619 on OpenAlexaff
Anil Kapoor, Robert A. Figlin

Bibliographic record

VenueCancer · 2009
Typereview
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsMcMaster UniversityJuravinski Cancer Centre
Fundersnot available
KeywordsTemsirolimusMedicineEverolimusSunitinibSorafenibRenal cell carcinomaSirolimusInternal medicinePI3K/AKT/mTOR pathwayOncologyTyrosine-kinase inhibitorKidney cancerDiscovery and development of mTOR inhibitorsTargeted therapyClinical trialCancerCancer researchHepatocellular carcinomaSignal transductionBiology

Abstract

fetched live from OpenAlex

Clinical trials have validated the importance of mammalian target of rapamycin (mTOR) as a targeted mechanism in the treatment of renal cell carcinoma (RCC). Temsirolimus, an mTOR inhibitor that is approved for treatment of advanced RCC, has demonstrated both overall survival benefits and progression-free survival benefits versus interferon-alpha as first-line treatment for patients with poor prognostic features. Exploratory subset analyses indicated that temsirolimus benefits patients with RCC regardless of tumor histology or nephrectomy status. Everolimus, the second mTOR inhibitor to demonstrate activity in RCC, improved progression-free survival versus placebo in patients whose disease progressed after treatment with vascular endothelial growth factor receptor tyrosine kinase inhibitors (sunitinib, sorafenib, or both); benefit was observed for all risk groups. Deforolimus also exhibited antitumor activity against RCC in early clinical studies. There is now compelling clinical evidence for the effectiveness of targeting mTOR in the treatment of RCC.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.965
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
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 head0.046
GPT teacher head0.323
Teacher spread0.277 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations72
Published2009
Admission routes1
Has abstractyes

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