Positive Surgical Margins in Robotic-Assisted Radical Prostatectomy: Impact of Learning Curve on Oncologic Outcomes

Objective: The presence of positive surgical margins following radical prostatectomy is a known risk factor for disease recurrence and may lead to adjuvant treatment. Our goal was to assess the incidence of positive surgical margins in our series of robotic-assisted radical prostatectomy (RARP) and its relationship to our learning curve. Methods: Between February 2003 and August 2005, 140 patients underwent RARP by the same surgical team at our institution. The records of our first 100 consecutive RARPs were retrospectively reviewed. The patients were divided into three groups based on the time of surgery: group I included the first 33 cases; group II included the second 33 cases; and group III comprised the last 34 cases. We compared the incidence and location of positive surgical margins among the groups. Additional variables evaluated included the patient's prostate-specific antigen (PSA) level, preoperative/postoperative Gleason score, clinical/pathologic stage, and pathologic tumour volume. Results: The positive margin rates were 45.4%, 21.2%, and 11.7% for groups I, II, and III, respectively. The difference in positive margin rates in the three groups was statistically significant (p = 0.0053). Positive margin rates declined specifically at the apex and bladder neck when comparing the first 33 patients to the last 34 patients. Patient demographics and preoperative staging variables were comparable among all three groups, with no statistically significant differences among them. Conclusions: This study illustrates that experience gained with time led to a decrease in the incidence of positive surgical margins. We do not feel that a selection bias affected our results because clinical and pathologic staging was evenly distributed within the three study groups. A steady reduction in positive surgical margin rates demonstrates a learning curve, of approximately 30 patients, associated with RARP, and suggests that oncologic outcome is affected by the experience of the robotic surgeon.