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Record W2398715868 · doi:10.1177/1756287215592288

Abiraterone in the management of castration-resistant prostate cancer prior to chemotherapy

2015· review· en· W2398715868 on OpenAlexaff
Benjamin A. Gartrell, Fred Saad

Bibliographic record

VenueTherapeutic Advances in Urology · 2015
Typereview
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineAbiraterone acetateEnzalutamideCabazitaxelProstate cancerDocetaxelOncologyInternal medicineAdverse effectChemotherapyAndrogen deprivation therapyCancerPharmacologyAndrogen receptor

Abstract

fetched live from OpenAlex

The treatment armamentarium for metastatic castration-resistant prostate cancer (mCRPC) has increased significantly over the past several years. Approved drugs associated with improved survival include androgen pathway-targeted agents (abiraterone acetate and enzalutamide), chemotherapeutics (docetaxel and cabazitaxel), an autologous vaccine (sipuleucel-T) and a radiopharmaceutical (radium-223). Abiraterone acetate, a prodrug of abiraterone, inhibits the CYP17A enzyme, a critical enzyme in androgen biosynthesis. Abiraterone has regulatory approval in mCRPC in both chemotherapy-naïve patients and in the post-docetaxel setting based on results from two randomized phase III studies. In the COU-AA-302 trial, abiraterone demonstrated significant improvement in the coprimary endpoints of radiographic progression-free survival and overall survival, as well as in a number of secondary endpoints including time until initiation of chemotherapy, time until opiate use for cancer-related pain, prostate-specific antigen progression-free survival and decline in performance status. Abiraterone is well-tolerated, although adverse events associated with this agent include abnormalities in liver function testing and mineralocorticoid-associated adverse events. This review evaluates the use of abiraterone in mCRPC prior to the use of chemotherapy.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.993
Threshold uncertainty score0.738

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.077
GPT teacher head0.447
Teacher spread0.370 · 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 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

Citations35
Published2015
Admission routes1
Has abstractyes

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