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Record W2607179488 · doi:10.5489/cuaj.4084

External validation of the ProCaRS nomograms and comparison of existing risk-stratification tools for localized prostate cancer

2017· article· en· W2607179488 on OpenAlexaffvenueabout
David Tiberi, George Rodrigues, Tom Pickles, Jim Morris, Juanita Crook, André‐Guy Martin, Fabio Cury, Charles Catton, Himu Lukka, Andrew Warner, Daniel Taussky

Bibliographic record

VenueCanadian Urological Association Journal · 2017
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsJuravinski Cancer CentreMcGill University Health CentrePrincess Margaret Cancer CentreBC Cancer AgencyHôpital Notre-DameLondon Health Sciences CentreHôtel-Dieu de QuébecWestern University
Fundersnot available
KeywordsProstate cancerNomogramMedicineProportional hazards modelBrachytherapyOncologyRisk stratificationConcordanceProstatectomyDatabaseGynecologyCancerInternal medicineRadiation therapyComputer science

Abstract

fetched live from OpenAlex

Introduction: The purpose of this study was to perform a direct comparison of several existing risk-stratification tools for localized prostate cancer in terms of their ability to predict for biochemical failure-free survival (BFFS). Two large databases were used and an external validation of two recently developed nomograms on an independent cohort was also performed in this analysis.Methods: Patients who were treated with external beam radiotherapy (EBRT) and/or brachytherapy for localized prostate cancer were selected from the multi-institutional Genitourinary Radiation Oncologists of Canada (GUROC) Prostate Cancer Risk Stratification (ProCaRS) database (n=7974) and the Centre Hospitalier de l’Université de Montréal (CHUM) validation database (n=2266). The primary outcome was BFFS using the Phoenix definition. Concordance index (C-index) reported from Cox proportional hazards regression using 10-fold cross validation and decision curve analysis (DCA) were used to predict BFFS.Results: C-index identified Cancer of the Prostate Risk Assessment (CAPRA) score and ProCaRS as superior to the historical GUROC and National Comprehensive Cancer Network (NCCN) risk-stratification systems. CAPRA modeled as five and three categories were superior to GUROC and NCCN only for the CHUM database. C-indices for CAPRA score, ProCaRS, GUROC, and NCCN were 0.72, 0.72, 0.71, and 0.72, respectively, for the ProCaRS database, and 0.66, 0.63, 0.57, and 0.60, respectively, for the CHUM database. However, many of these comparisons did not demonstrate a clinically meaningful difference. DCA identified minimal differences across the different risk-stratification systems, with no system emerging with optimal net benefit. External validation of the ProCaRS nomograms yielded favourable calibrations of R2=0.778 (low-dose rate [LDR]-brachytherapy) and R2=0.868 (EBRT).Conclusions: This study externally validated two ProCaRS nomograms for BFFS that may help clinicians in treatment selection and outcome prediction. A direct comparison between existing risk-stratification tools demonstrated minimal clinically significant differences in discriminative ability between the systems, favouring the CAPRA and ProCaRS systems. The incorporation of novel prognostic variables, such as genomic markers, is needed.

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)0.024
metaresearch head score (Gemma)0.041
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 score0.024
Threshold uncertainty score0.129

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.041
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.071
GPT teacher head0.340
Teacher spread0.269 · 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

Citations0
Published2017
Admission routes3
Has abstractyes

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