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Record W2078598893 · doi:10.1016/j.juro.2015.02.229

MP5-02 PARTIAL CYSTECTOMY FOR UROTHELIAL CARCINOMA OF THE BLADDER: PRACTICE PATTERNS AND OUTCOMES IN THE GENERAL POPULATION

2015· article· en· W2078598893 on OpenAlexaboutno aff
Michael Leveridge, D. Robert Siemens, Jason Izard, Xuejiao Wei, William J. Mackillop, David M. Berman, Christopher M. Booth

Bibliographic record

VenueThe Journal of Urology · 2015
Typearticle
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsCystectomyMedicineBladder cancerProportional hazards modelEpidemiologyUrinary diversionPopulationUrothelial carcinomaLogistic regressionUrologyCancerSurgeryInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

You have accessJournal of UrologyGeneral & Epidemiological Trends & Socioeconomics: Evidence-based Medicine & Outcomes I1 Apr 2015MP5-02 PARTIAL CYSTECTOMY FOR UROTHELIAL CARCINOMA OF THE BLADDER: PRACTICE PATTERNS AND OUTCOMES IN THE GENERAL POPULATION Michael Leveridge, D Robert Siemens, Jason Izard, Xuejiao Wei, William Mackillop, David Berman, and Christopher Booth Michael LeveridgeMichael Leveridge More articles by this author , D Robert SiemensD Robert Siemens More articles by this author , Jason IzardJason Izard More articles by this author , Xuejiao WeiXuejiao Wei More articles by this author , William MackillopWilliam Mackillop More articles by this author , David BermanDavid Berman More articles by this author , and Christopher BoothChristopher Booth More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2015.02.229AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Urothelial carcinoma of the bladder (UCB) is a disease that commonly affects elderly patients and those with other co-morbidities. Partial cystectomy (PC) for highly selected tumors and patients may avoid the high morbidity of radical cystectomy (RC) and urinary diversion. We sought to assess the practice patterns and outcomes of PC for UCB in routine clinical practice. METHODS All patients with UCB undergoing PC or RC in Ontario from 1994–2008 were identified using the Ontario Cancer Registry. Pathology reports were reviewed. Treatment and survival data were linked to the study database. Variables associated with use of PC were identified using logistic regression. Cox proportional hazards model was used to identify factors associated with survival among patients treated with PC. RESULTS We identified 3320 patients who underwent PC (n=181; 5.5%) or RC (n=3139; 94.5%) in the study period. 36% of PC patients were >80 years old, vs 19% of RC patients (p<0.001). More PC patients had organ-confined (<pT3) disease (54% PCvs 36% RC; p<0.001). Two thirds (67%) of PC patients did not undergo lymph node dissection at the time of surgery (24% for RC; p<0.001). Surgical margins were positive in 33 patients (18%) at PC, and 21 patients (12%) received adjuvant chemotherapy (ACT). Surgery early in the study period, age ≥70, Charlson comorbidity score ≥3 and surgery outside of a regional cancer center were associated with higher use of PC. Unadjusted five-year overall survival (OS) for PC and RC cases was 34% and 33% respectively (p=0.455); cancer-specific survival was 43% (PC) and 37% (RC) (p=0.045). On multivariate analysis of PC cases, pT3+ disease (HR 1.49 [1.02-2.19]) and node-positive disease (HR 3.45 [1.80-2.46]) were independently predictive of OS, while pT3+ (HR 2.59 [1.70-3.94]), node-positive disease (HR 3.89 [1.83-8.27]) and LVI (HR 2.82 [1.51-5.26]) predicted CSS. CONCLUSIONS In the population setting, use of PC is not common and is used more often in elderly patients. Two-thirds of patients treated with PC do not undergo lymphadenectomy. A substantial proportion of patients treated with PC achieve long-term survival. PC remains a treatment option in selected patients with UCB. © 2015 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 193Issue 4SApril 2015Page: e45 Advertisement Copyright & Permissions© 2015 by American Urological Association Education and Research, Inc.MetricsAuthor Information Michael Leveridge More articles by this author D Robert Siemens More articles by this author Jason Izard More articles by this author Xuejiao Wei More articles by this author William Mackillop More articles by this author David Berman More articles by this author Christopher Booth 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)0.005
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 score0.009
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.033
GPT teacher head0.326
Teacher spread0.293 · 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
Published2015
Admission routes1
Has abstractyes

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