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Record W2604990264 · doi:10.1016/j.juro.2017.02.1476

MP47-16 CURRENT DELAYS FROM BIOPSY TO RADICAL PROSTATECTOMY DO NOT APPEAR TO AFFECT PATHOLOGIC OUTCOMES IN LOW, INTERMEDIATE, OR HIGH-RISK DISEASE

2017· article· en· W2604990264 on OpenAlexaboutno aff
Premal H. Patel, Leanne Ross, Kiril Trpkov, Geoffrey Gotto

Bibliographic record

VenueThe Journal of Urology · 2017
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsProstatectomyMedicineProstate cancerBiopsyPathologicalCancerAdverse effectUrologyDiseaseSurgeryGeneral surgeryRadiologyInternal medicine

Abstract

fetched live from OpenAlex

You have accessJournal of UrologyProstate Cancer: Localized: Surgical Therapy IV1 Apr 2017MP47-16 CURRENT DELAYS FROM BIOPSY TO RADICAL PROSTATECTOMY DO NOT APPEAR TO AFFECT PATHOLOGIC OUTCOMES IN LOW, INTERMEDIATE, OR HIGH-RISK DISEASE PREMAL PATEL, Leanne Ross, Kiril Trpkov, and Geoffrey Gotto PREMAL PATELPREMAL PATEL More articles by this author , Leanne RossLeanne Ross More articles by this author , Kiril TrpkovKiril Trpkov More articles by this author , and Geoffrey GottoGeoffrey Gotto More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2017.02.1476AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES There is a small volume of varied literature reporting on the impact of time between prostate cancer diagnosis on biopsy and definitive intervention with radical prostatectomy with regards to adverse pathological outcomes. There are considerable, and in some cases increasing, delays in treatment for patients with prostate cancer in Canada's publicly funded healthcare system. We sought to evaluate our institutional outcomes using a large multi-surgeon database. METHODS We retrospectively reviewed 2,728 patients who underwent radical prostatectomy between 2005 and 2014. Patients were stratified according to biopsy Grade Groups and pre-operative PSA levels. Pathologic outcomes were evaluated for patients with <2 months between biopsy and surgery and then at monthly intervals of up to 6 months. Adverse pathological outcomes were defined as Gleason upgrading from biopsy, the presence of extracapsular extension (pT3a) or seminal vesicle invasion (pT3b), positive surgical margins and positive lymph node involvement. The x2 test was used for statistical analysis. RESULTS In total 2310 patients met our inclusion criteria. Median time from biopsy to surgery was 83 days (range: 61-109). Grade groups 1, 2, 3, 4, 5 comprised of 906 (39.2%), 1,048 (45.4%), 231 (10%), 69 (3%) and 56 (2.4%), respectively. In total 31.8% of patients were upgraded by Grade Group on final surgical pathology. The overall positive surgical margin rates were 25% for organ confined (pT2) disease and 49.8% patients with pT3 disease. Lymph node involvement was identified in 1.5% of patients. There was no observed difference in adverse pathologic outcomes for patients in any risk category with delays of up to 6 months between biopsy and radical prostatectomy. CONCLUSIONS Surgical delays of up to 6 months following prostate biopsy were not associated with an increased risk of Gleason score upgrading, extracapsular extension, seminal vesicle invasion, positive surgical margins, or lymph node involvement. © 2017FiguresReferencesRelatedDetails Volume 197Issue 4SApril 2017Page: e634-e635 Advertisement Copyright & Permissions© 2017MetricsAuthor Information PREMAL PATEL More articles by this author Leanne Ross More articles by this author Kiril Trpkov More articles by this author Geoffrey Gotto More articles by this author Expand All Advertisement 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)0.015
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 score0.008
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.022
GPT teacher head0.322
Teacher spread0.300 · 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
Published2017
Admission routes1
Has abstractyes

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