Jung-Ki Jo1, Sung-Kyu Hong2, Seok-Soo Byun2, Homayoun Zargar3, Riccardo Autorino4, Sang-Eun Lee5. 1. Department of Urology, Hanyang University Hospital, Seoul, South Korea. 2. Department of Urology, Seoul National University Bundang Hospital, Seongnam, South Korea. 3. Department of Urology, Royal Melbourne Hospital, Melbourne, Australia. 4. Department of Urology, University Hospitals Case Medical Center, Cleveland, OH, USA. 5. Department of Urology, Seoul National University Bundang Hospital, Seongnam, South Korea - selee@snubh.org.
Abstract
BACKGROUND: To analyze the correlation of surgical margin status with other findings on final pathology and risk of biochemical recurrence (BCR) in patients undergoing robot-assisted radical prostatectomy (RALP). METHODS: Bundang Prostatectomy Database was reviewed to identify patients who underwent RARP from 2007 to 2011 and had a positive surgical margin (PSM) on final pathology. Pathology findings were reviewed. BCR-free survival was calculated using the Kaplan-Meier method. Cox univariable and multi-variable regression models were used to find the correlation between clinicopathologic factors and BCR. RESULTS: Eight hundred and fifteen patients were included in the analysis: 118 (14.48%) had apical positive margin, 152 (18.65%) had a positive margin in another site, and 545 (66.87%) had negative surgical margins. In patients with only apical PSM, stratified by clinical stage, Kaplan-Meier analysis demonstrated significant difference in BCR-free survival between the groups (log rank P<0.001). Multivariable Cox proportional hazards model showed maximal percentage of positive core is the strongest predictor of BCR (HR=3.131, P<0.001). Multivariable Cox proportional hazards model showed PSM is one of the powerful predictor of postoperative BCR (HR=3.123, P<0.001). CONCLUSIONS: PSM after RALP is one of the powerful predictor of BCR and apical PSM is relatively less powerful predictor of BCR. Maximal percentage of positive core is the most powerful preoperative predictors of BCR. Clinical stage and biopsy Gleason score are also associated with pathologic outcomes and BCR free survival rates in patients with positive apical margin only.
BACKGROUND: To analyze the correlation of surgical margin status with other findings on final pathology and risk of biochemical recurrence (BCR) in patients undergoing robot-assisted radical prostatectomy (RALP). METHODS: Bundang Prostatectomy Database was reviewed to identify patients who underwent RARP from 2007 to 2011 and had a positive surgical margin (PSM) on final pathology. Pathology findings were reviewed. BCR-free survival was calculated using the Kaplan-Meier method. Cox univariable and multi-variable regression models were used to find the correlation between clinicopathologic factors and BCR. RESULTS: Eight hundred and fifteen patients were included in the analysis: 118 (14.48%) had apical positive margin, 152 (18.65%) had a positive margin in another site, and 545 (66.87%) had negative surgical margins. In patients with only apical PSM, stratified by clinical stage, Kaplan-Meier analysis demonstrated significant difference in BCR-free survival between the groups (log rank P<0.001). Multivariable Cox proportional hazards model showed maximal percentage of positive core is the strongest predictor of BCR (HR=3.131, P<0.001). Multivariable Cox proportional hazards model showed PSM is one of the powerful predictor of postoperative BCR (HR=3.123, P<0.001). CONCLUSIONS: PSM after RALP is one of the powerful predictor of BCR and apical PSM is relatively less powerful predictor of BCR. Maximal percentage of positive core is the most powerful preoperative predictors of BCR. Clinical stage and biopsy Gleason score are also associated with pathologic outcomes and BCR free survival rates in patients with positive apical margin only.
Authors: Antonio Benito Porcaro; Marco Sebben; Paolo Corsi; Alessandro Tafuri; Tania Processali; Marco Pirozzi; Nelia Amigoni; Riccardo Rizzetto; Giovanni Cacciamani; Arianna Mariotto; Alberto Diminutto; Matteo Brunelli; Vincenzo De Marco; Salvatore Siracusano; Walter Artibani Journal: J Robot Surg Date: 2019-04-05
Authors: Antonio B Porcaro; Alessandro Tafuri; Marco Sebben; Paolo Corsi; Tania Processali; Marco Pirozzi; Nelia Amigoni; Riccardo Rizzetto; Aliasger Shakir; Giovanni Cacciamani; Arianna Mariotto; Matteo Brunelli; Riccardo Bernasconi; Giovanni Novella; Vincenzo De Marco; Walter Artibani Journal: Arab J Urol Date: 2019-05-30