Oncological and functional outcomes of a large Canadian robotic-assisted radical prostatectomy database with 10 years of surgical experience.
Bibliographic record
Abstract
INTRODUCTION: Robotic-assisted radical prostatectomy (RARP) has grown to be the predominant global surgical approach to treat localized prostate cancer. However, there is still limited access to robotic technology and little data from Canadian cohorts. Herein, we report on our oncological and functional outcomes after 10 years of surgical experience. MATERIALS AND METHODS: Prospective data from 1,034 RARP cases performed by two high-volume experienced surgeons at two academic centers were collected from October 2006 to June 2017. Preoperative characteristics, surgical, oncological and functional outcomes were assessed up to 72 months postoperative. RESULTS: D'Amico risk distribution was 26.1%, 59.8% and 14.1% for low, intermediate and high risk prostate cancer. Median (interquartile range) operative time, blood loss and hospital stay were 170 minutes (145-200), 200 mL (150-300) and 1day (1-1), respectively and 1.4% received blood transfusion. Intraoperative complications occurred in 3.8%. Postoperatively, 32 (3.1%) and 138 (13.3%) men harbored major (Clavien III-IV) and minor complications (Clavien I-II), respectively. Among the 630 men (64.2%) with pT2 and 349 men (35.6%) with pT3 disease, stage-specific positive surgical margin rates were 15.7% and 39.0%, respectively. Urinary continence rates at 6, 12 and 72 months were 72.7%, 83.5% and 84.9%, respectively. In men without preoperative erectile dysfunction, potency was observed in 45.6%, 59.4% and 69.5% at 6, 12 and 72 months, respectively. Biochemical recurrence occurred in 105 patients (10.2%). CONCLUSION: Mid-term oncological outcomes in two large Canadian centers demonstrate comparable results to non-Canadian centers of excellence. RARP appears to be safe with acceptable surgical, oncological and functional outcomes in a publicly funded single-payer healthcare system.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".