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Record W4245222417 · doi:10.5489/cuaj.609

Emerging novel therapies in the treatment of castrate-resistant prostate cancer

2013· article· en· W4245222417 on OpenAlexaffvenue
Alym Abdulla, Anil Kapoor

Bibliographic record

VenueCanadian Urological Association Journal · 2013
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineDenosumabDocetaxelCabazitaxelProstate cancerHormonal therapyOncologyIpilimumabCombination therapyInternal medicineEnzalutamideNivolumabPharmacologyCancerImmunotherapyAndrogen deprivation therapyAndrogen receptorOsteoporosis

Abstract

fetched live from OpenAlex

The treatment options for patients with castration-resistant prostatecancer (CRPC), until very recently, only included docetaxel.In the past 10 months, newly Federal Drug Administration (FDA)approved agents in the United States have shown survival benefitfor patients with CRPC. This review takes a closer look atthese newer agents: sipuleucel-T (immune therapy) and cabazitaxel(cytotoxic therapy). We also review the evidence supportingthe FDA’s approval of denosumab (bone-targeted therapy)as a treatment option for men with CRPC and bony metastases.Newer agents currently being investigated in phase III clinical trialsfor their potential role in metastatic CRPC are also reviewed.These agents include abiraterone (hormonal therapy), TAK-700(hormonal therapy), MDV3100 (hormonal therapy), ipilimumab(immune therapy), zibotentan (endothelin-A receptor antagonist)and dasatinib (tyrosine kinase inhibitor). As ongoing studies usingall the aforementioned agents continue to evolve, our understandingof how and where these agents fit into the treatment paradigmfor patients with CRPC will become clearer.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.029
GPT teacher head0.294
Teacher spread0.265 · 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 designNot applicable
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

Citations2
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Urological Association Journal→Same topicProstate Cancer Treatment and Research→French-language works237,207→