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PD62-04 LONG-TERM ONCOLOGICAL OUTCOMES FOLLOWING ACTIVE SURVEILLANCE OF LOW RISK PROSTATE CANCER: A POPULATION-BASED STUDY

2020· article· en· W3021441020 on OpenAlexaboutno aff
Narhari Timilshina, Antonio Finelli, Patrick O. Richard, Maria Komisarenko, Lisa W. Martin, George Tomlinson, Beate Sander, Shabbir M.H. Alibhai

Bibliographic record

VenueThe Journal of Urology · 2020
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineProstate cancerSanderPopulationCancerCancer registryWatchful waitingGynecologyOncologyInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

You have accessJournal of UrologyProstate Cancer: Localized: Active Surveillance II (PD62)1 Apr 2020PD62-04 LONG-TERM ONCOLOGICAL OUTCOMES FOLLOWING ACTIVE SURVEILLANCE OF LOW RISK PROSTATE CANCER: A POPULATION-BASED STUDY Narhari Timilshina*, Antonio Finelli, Patrick Richard, Maria Komisarenko, Lisa Martin, George Tomlinson, Beate Sander, and Shabbir Alibhai Narhari Timilshina*Narhari Timilshina* More articles by this author , Antonio FinelliAntonio Finelli More articles by this author , Patrick RichardPatrick Richard More articles by this author , Maria KomisarenkoMaria Komisarenko More articles by this author , Lisa MartinLisa Martin More articles by this author , George TomlinsonGeorge Tomlinson More articles by this author , Beate SanderBeate Sander More articles by this author , and Shabbir AlibhaiShabbir Alibhai More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000000979.04AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Active surveillance (AS) is a widely accepted management strategy for low-risk prostate cancer (PC), but limited data exist regarding long-term outcomes after initial AS at a population level. We assessed the long-term outcomes of low-risk PC following initial AS at a population level. METHODS: In this population-based study using linked administrative databases from Ontario, Canada, we identified PC patients with low-risk (Gleason score ≤6) cancer who were initially managed with AS between 2002-2014. Our primary outcomes of metastases (mets) rate, overall mortality (OM) and prostate cancer-specific mortality (PCSM) were compared between AS patients and low-risk patients who received initial definitive treatment (either surgery or radiation) using Cox proportional hazards models. RESULTS: The cohort was comprised of 31,004 (11,259 Initial AS, 6,819 Watchful Waiting (WW) and 12,926 Initial Treatment) low-risk PC patients (median age, 65 years) with median follow-up of 107 months (IQR 76-140). AS patients had lower PSA (median 5.9, no IQR), had lower positive cores (mean 2, SD 1.6) and lower maximum % core (median 10, IQR 5-15) than WW or Initial treatment. Mets rate was lower in AS (3.9%) than initial treatment (6.6%) or WW (5.5%). Unadjusted OM was lower among those with initial AS (7.7%) than with initial treatment (9.4%) or WW (25.1%), with median follow-up of 9 years. Factors associated with OM were WW, age, higher ACG comorbidity, higher PSA, number of positive cores and max. % core at diagnosis, lower income and geographical region. In adjusted multivariate model for OM, AS was not statistically different than initial treatment (HR 1.03, 95%CI 0.93-1.14). Unadjusted PCSM was higher among patients undergoing WW (1.44%) versus initial AS (0.73%) or when compared to initial treatment (0.60%). CONCLUSIONS: The study reports real-world long-term outcomes of AS in men with low-risk PC. Our results suggest that AS is not associated with worse OM but slightly higher PCSM with AS than upfront treatment after 9 years of follow-up. Source of Funding: The Prostate Cancer Canada © 2020 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 203Issue Supplement 4April 2020Page: e1286-e1287 Advertisement Copyright & Permissions© 2020 by American Urological Association Education and Research, Inc.MetricsAuthor Information Narhari Timilshina* More articles by this author Antonio Finelli More articles by this author Patrick Richard More articles by this author Maria Komisarenko More articles by this author Lisa Martin More articles by this author George Tomlinson More articles by this author Beate Sander More articles by this author Shabbir Alibhai More articles by this author Expand All Advertisement PDF downloadLoading ...

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.025
GPT teacher head0.328
Teacher spread0.303 · 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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