PURPOSE: Improved cancer control with increasing surgical experience (the learning curve) has been demonstrated for open and laparoscopic prostatectomy. We assessed the relationship between surgical experience and oncologic outcomes of robot-assisted radical prostatectomy. MATERIALS AND METHODS: We analyzed the records of 1,827 patients in whom prostate cancer was treated with robot-assisted radical prostatectomy. Surgical experience was coded as the total number of robotic prostatectomies performed by the surgeon before the patient operation. We evaluated the relationship of prior surgeon experience to the probability of positive margins and biochemical recurrence in regression models adjusting for stage, grade and prostate specific antigen. RESULTS: After adjusting for case mix, greater surgeon experience was associated with a lower probability of positive surgical margins (p = 0.035). The risk of positive margins decreased from 16.7% to 9.6% in patients treated by a surgeon with 10 and 250 prior procedures, respectively (risk difference 7.1%, 95% CI 1.7-12.2). In patients with nonorgan confined disease the predicted probability of positive margins was 38.4% in those treated by surgeons with 10 prior operations and 24.9% in those treated by surgeons with 250 prior operations (absolute risk reduction 13.5%, 95% CI -3.4-22.5). The relationship between surgical experience and the risk of biochemical recurrence after surgery was not significant (p = 0.8). CONCLUSIONS: Specific techniques used by experienced surgeons which are associated with improved margin rates need further research. The impact of experience on cancer control after robotic prostatectomy differed from that in the prior literature on open and laparoscopic radical prostatectomy, and should be investigated in larger multi-institutional studies.
PURPOSE: Improved cancer control with increasing surgical experience (the learning curve) has been demonstrated for open and laparoscopic prostatectomy. We assessed the relationship between surgical experience and oncologic outcomes of robot-assisted radical prostatectomy. MATERIALS AND METHODS: We analyzed the records of 1,827 patients in whom prostate cancer was treated with robot-assisted radical prostatectomy. Surgical experience was coded as the total number of robotic prostatectomies performed by the surgeon before the patient operation. We evaluated the relationship of prior surgeon experience to the probability of positive margins and biochemical recurrence in regression models adjusting for stage, grade and prostate specific antigen. RESULTS: After adjusting for case mix, greater surgeon experience was associated with a lower probability of positive surgical margins (p = 0.035). The risk of positive margins decreased from 16.7% to 9.6% in patients treated by a surgeon with 10 and 250 prior procedures, respectively (risk difference 7.1%, 95% CI 1.7-12.2). In patients with nonorgan confined disease the predicted probability of positive margins was 38.4% in those treated by surgeons with 10 prior operations and 24.9% in those treated by surgeons with 250 prior operations (absolute risk reduction 13.5%, 95% CI -3.4-22.5). The relationship between surgical experience and the risk of biochemical recurrence after surgery was not significant (p = 0.8). CONCLUSIONS: Specific techniques used by experienced surgeons which are associated with improved margin rates need further research. The impact of experience on cancer control after robotic prostatectomy differed from that in the prior literature on open and laparoscopic radical prostatectomy, and should be investigated in larger multi-institutional studies.
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Authors: Carlo A Bravi; Giuseppe Rosiello; Giuseppe Fallara; Emily Vertosick; Amy Tin; Daniel Sjoberg; Marco Bianchi; Elio Mazzone; Alberto Martini; Paolo Dell'oglio; Armando Stabile; Giorgio Gandaglia; Nicola Fossati; Alberto Briganti; Francesco Montorsi; Andrew Vickers Journal: Minerva Urol Nephrol Date: 2020-02-19
Authors: Martin Nyberg; Daniel D Sjoberg; Sigrid V Carlsson; Ulrica Wilderäng; Stefan Carlsson; Johan Stranne; Peter Wiklund; Gunnar Steineck; Eva Haglind; Jonas Hugosson; Anders Bjartell Journal: BJU Int Date: 2020-09-29 Impact factor: 5.588