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Record W2742342719 · doi:10.1016/j.urology.2017.04.062

Predicting Response and Recognizing Resistance: Improving Outcomes in Patients With Castration-resistant Prostate Cancer

2017· review· en· W2742342719 on OpenAlexaff
Neal D. Shore, Axel Heidenreich, Fred Saad

Bibliographic record

VenueUrology · 2017
Typereview
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsCentre Hospitalier de l’Université de Montréal
FundersSanofi
KeywordsEnzalutamideMedicineProstate cancerCabazitaxelDocetaxelOncologyInternal medicineAndrogen deprivation therapyCancerAndrogen receptor

Abstract

fetched live from OpenAlex

Optimal sequencing strategies for approved agents in metastatic castration-resistant prostate cancer (mCRPC) are unclear. Retrospective clinical studies suggest cross-resistance between specific therapies. This review assesses treatment decisions for mCRPC. Increased use of chemohormonal therapy in castration-sensitive disease may affect subsequent treatment decisions in mCRPC. Initial abiraterone or enzalutamide treatment may result in cross-resistance for subsequent androgen receptor-targeted therapy. Clinical responses may be seen in both docetaxel- and cabazitaxel-treated patients progressing after treatment with abiraterone or enzalutamide. These observations are supported by proposed resistance mechanisms. In conclusion, small, retrospective studies suggest cross-resistance between specific therapies in mCRPC. Larger prospective studies are required.

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)0.003
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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.060
GPT teacher head0.380
Teacher spread0.320 · 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

Citations24
Published2017
Admission routes1
Has abstractno

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