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Record W2218158895 · doi:10.3747/co.22.2895

Treatment Patterns among Canadian Men Diagnosed with Localized Low-Risk Prostate Cancer

2015· article· en· W2218158895 on OpenAlexaffvenueabout
Carolyn Sandoval, Kim Tran, Rami Rahal, Geoffrey A. Porter, S. Fung, C. Louzado, J. Liu, Heather Bryant

Bibliographic record

VenueCurrent Oncology · 2015
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsDalhousie UniversityCanadian Partnership Against Cancer
Fundersnot available
KeywordsMedicineOverdiagnosisProstate cancerGuidelineRadiation therapyBrachytherapyProstatectomyDiseaseCancerPediatricsInternal medicinePathology

Abstract

fetched live from OpenAlex

In general, guideline-recommended treatment options for men with low-risk prostate cancer (pca) include active surveillance, radical prostatectomy, and external-beam radiation therapy or brachytherapy. Because of the concern about overdiagnosis and consequent overtreatment of pca, patients with low-risk disease are increasingly being managed with active surveillance. Using data from six provincial cancer registries, we examined treatment patterns within a year of a diagnosis of localized low-risk pca, and we assessed differences by age. Of patients diagnosed in 2010 in four of the six reporting provinces, most received surgery or radiation therapy within 1 year of diagnosis. Depending on the province, either surgery or radiation therapy was the most commonly used primary treatment. In the other two provinces, most patients had no record of treatment within a year of diagnosis. Examining treatment patterns by age demonstrated a lesser likelihood of receiving surgery or radiation therapy within 1 year of diagnosis among men more than 75 years of age than among men 75 years of age or younger (no record of treatment in 69.1% and 46.3% respectively). In conclusion, we observed interprovincial and age-specific variations in the patterns of care for men with low-risk pca. The findings presented in this report are intended to identify opportunities for improvement in clinical practice that could lead to improved care and experience.

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)0.000
metaresearch head score (Gemma)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.141

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.067
GPT teacher head0.369
Teacher spread0.302 · 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
GenreEmpirical

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

Citations7
Published2015
Admission routes3
Has abstractyes

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