PD57-08 CENTRALIZATION OF RADICAL CYSTECTOMY FOR BLADDER CANCER IN A UNIVERSAL HEALTHCARE SYSTEM: EARLY RESULTS FROM A CANADIAN ACADEMIC CENTER
Bibliographic record
Abstract
You have accessJournal of UrologyBladder Cancer: Epidemiology & Evaluation III1 Apr 2017PD57-08 CENTRALIZATION OF RADICAL CYSTECTOMY FOR BLADDER CANCER IN A UNIVERSAL HEALTHCARE SYSTEM: EARLY RESULTS FROM A CANADIAN ACADEMIC CENTER Jan Rudzinski, Niels Jacobsen, Eric Estey, Sunita Ghosh, Scott North, Naveen Basappa, Michael Kolinsky, and Adrian Fairey Jan RudzinskiJan Rudzinski More articles by this author , Niels JacobsenNiels Jacobsen More articles by this author , Eric EsteyEric Estey More articles by this author , Sunita GhoshSunita Ghosh More articles by this author , Scott NorthScott North More articles by this author , Naveen BasappaNaveen Basappa More articles by this author , Michael KolinskyMichael Kolinsky More articles by this author , and Adrian FaireyAdrian Fairey More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2017.02.2610AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Radical cystectomy for bladder cancer is a complex surgical oncology procedure. Accumulating data suggest variation in outcomes based on hospital and surgeon characteristics. Centralization of this procedure to high volume, fellowship-trained surgeons may improve clinical outcomes. High quality data examining the impact of radical cystectomy centralization are lacking. At the University of Alberta, radical cystectomy was centralized at a single institution and performed by 1 of 2 urologic oncologists starting in August 2013. Our objective was to compare outcomes of radical cystectomy before and after centralization of care. METHODS A retrospective analysis of data from the University of Alberta Radical Cystectomy Database was performed. Eligible subjects were those with histologically proven urothelial carcinoma of the bladder (cTanyN1-3M0) undergoing curative intent surgery. Patients were classified into pre-centralization era (1994-2007; N=523) and post-centralization era (2013-present; N=134) cohorts for analyses. Pre-centralization era patients were treated by 1 of 11 urologic surgeons at 2 academic teaching hospitals. Post-centralization era patients were treated by 1 of 2 fellowship-trained urologic oncologists at 1 academic teaching hospital. Outcomes were overall survival, 90-day mortality rate, positive surgical margin (R1) resection rate, total number of lymph nodes evaluated, and 90-day blood product transfusion rate. The Kaplan-Meier method and multivariable regression analyses were used to analyze survival outcomes. Statistical tests were two-sided (p≤0.05). RESULTS The median follow-up duration in the pre- and post-centralization era was 33 months and 16 months, respectively. The predicted 2-year overall survival rate was 62% in the pre-centralization era and 84% in the post-centralization era (Log rank P=0.0007; multivariable HR 0.40, 95% CI 0.24 to 0.68, P<0.0001). Treatment in the post-centralization era was associated with lower 90-day mortality (6.3% versus 1.5%, multivariable OR 0.23, 95% CI 0.06 to 0.99, P=0.049), R1 resection (13.0% versus 1.5%; multivariable OR 0.07, 95% CI 0.01 to 0.51, P=0.009), and 90-day blood product transfusion (59% versus 6%, P<0.0001) as well as higher total number of lymph nodes evaluated (7 versus 30 lymph nodes, P<0.0001). CONCLUSIONS Surgical treatment in the post-centralization era was associated with superior survival, cancer control, and perioperative outcomes. © 2017FiguresReferencesRelatedDetails Volume 197Issue 4SApril 2017Page: e1124 Advertisement Copyright & Permissions© 2017MetricsAuthor Information Jan Rudzinski More articles by this author Niels Jacobsen More articles by this author Eric Estey More articles by this author Sunita Ghosh More articles by this author Scott North More articles by this author Naveen Basappa More articles by this author Michael Kolinsky More articles by this author Adrian Fairey More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.011 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".