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Record W2626155574 · doi:10.5489/cuaj.4539

Testosterone monitoring for men with advanced prostate cancer: Review of current practices and a survey of Canadian physicians

2017· review· en· W2626155574 on OpenAlexaffvenueabout
Bobby Shayegan, Frédéric Pouliot, Alan So, John Fernandes, Joseph Macri

Bibliographic record

VenueCanadian Urological Association Journal · 2017
Typereview
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsUniversity of British ColumbiaUniversité LavalMcMaster University
Fundersnot available
KeywordsProstate cancerTestosterone (patch)MedicineAndrogen deprivation therapyCastrationGynecologyUrologyHormone therapyOncologyCancerInternal medicineHormone

Abstract

fetched live from OpenAlex

Androgen-deprivation therapy (ADT) is a standard of care in the treatment of advanced prostate cancer; however, testosterone monitoring practices for men undergoing ADT vary across Canada. Although a testosterone level of 1.7 nmol/L or lower has historically been defined as the accepted castrate level, newer assays with improved sensitivity have shown that both medical and surgical castration can suppress testosterone levels to below 0.7 nmol/L. This review explores the evidence supporting a redefinition of the castrate testosterone level as 0.7 nmol/L or lower, and presents results of a survey of testosterone monitoring practices among 153 Canadian urologists, uro-oncologists, and radiation oncologists who manage the treatment of men with hormone-sensitive prostate cancer.

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)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.539
Threshold uncertainty score0.916

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0070.017
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.186
GPT teacher head0.440
Teacher spread0.254 · 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 designObservational
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

Citations11
Published2017
Admission routes3
Has abstractyes

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