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Record W4409585810 · doi:10.5489/cuaj.9100

Optimizing therapy for high-risk biochemically recurrent non-metastatic prostate cancer

2025· review· en· W4409585810 on OpenAlexaffvenueabout
Christian Kollmannsberger, Antonio Finelli, Andrew Loblaw, Tamim Niazi, Frédéric Pouliot, Ricardo Rendon, Bobby Shayegan, Fred Saad

Bibliographic record

VenueCanadian Urological Association Journal · 2025
Typereview
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsMcMaster UniversityQueen Elizabeth II Health Sciences CentreCentre Hospitalier de l’Université de MontréalUniversité LavalUniversity of British ColumbiaCentre hospitalier de l'Université LavalMcGill UniversityJewish General HospitalSunnybrook Health Science CentreUniversity of TorontoUniversity Health NetworkBC Cancer Agency
Fundersnot available
KeywordsProstate cancerMedicineProstatectomyAndrogen deprivation therapyMalignancyOncologybreakpoint cluster regionCancerInternal medicineSalvage therapyBiochemical recurrenceProstate-specific antigenUrologyChemotherapyReceptor

Abstract

fetched live from OpenAlex

Prostate cancer is a leading malignancy affecting men globally and in Canada. Biochemical recurrence (BCR), marked by rising prostate-specific antigen (PSA) levels post-curative-intended local treatment, is prevalent in nearly one-third of prostate cancer patients and is associated with increased risk of metastases and mortality. The management of patients with BCR is evolving rapidly, highlighting the need for practical guidance. This review aims to provide guidance to clinicians on the use and subsequent implications of advanced imaging results in patients with BCR. In addition, current management approaches, including salvage therapies post-radical prostatectomy, as well as the integration of androgen deprivation therapy (ADT) plus androgen receptor pathway inhibitors (ARPI), are explored.

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 score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.037
GPT teacher head0.351
Teacher spread0.313 · 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

Citations0
Published2025
Admission routes3
Has abstractyes

Explore more

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