Overall rate, location, and predictive factors for positive surgical margins after robot-assisted laparoscopic radical prostatectomy for high-risk prostate cancer - Abstract

We report the overall rate, locations and predictive factors of positive surgical margins (PSMs) in 271 patients with high-risk prostate cancer.

Between April 2008 and October 2011, we prospectively collected data from patients classified as D'Amico high-risk who underwent robot-assisted laparoscopic radical prostatectomy. Overall rate and location of PSMs were reported. Stepwise logistic regression models were fitted to assess predictive factors of PSM. The overall rate of PSMs was 25.1% (68 of 271 patients). Of these PSM, 38.2% (26 of 68) were posterolateral (PL), 26.5% (18 of 68) multifocal, 16.2% (11 of 68) in the apex, 14.7% (10 of 68) in the bladder neck, and 4.4% (3/68) in other locations. The PSM rate of patients with pathological stage pT2 was 8.6% (12 of 140), 26.6% (17 of 64) of pT3a, 53.3% (32/60) of pT3b, and 100% (7 of 7) of pT4. In a logistic regression model including pre-, intra-, and post-operative parameters, body mass index (odds ratio [OR]: 1.09; 95% confidence interval [CI]: 1.01-1.19, P= 0.029), pathological stage (pT3b or higher vs pT2; OR: 5.14; 95% CI: 1.92-13.78; P = 0.001) and percentage of the tumor (OR: 46.71; 95% CI: 6.37-342.57; P< 0.001) were independent predictive factors for PSMs. The most common location of PSMs in patients at high-risk was the PL aspect, which reflects the reported tumor aggressiveness. The only significant predictive factors of PSMs were pathological outcomes, such as percentage of the tumor in the specimen and pathological stage.

Written by:
Kang SG, Schatloff O, Haidar AM, Samavedi S, Palmer KJ, Cheon J, Patel VR.   Are you the author?
Global Robotics Institute, Florida Hospital Celebration Health, Celebration, and University of Central Florida School of Medicine, Orlando, Florida, USA.

Reference: Asian J Androl. 2015 May 5. Epub ahead of print.
doi: 10.4103/1008-682X.148723


PubMed Abstract
PMID: 25966623

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