Related Experiment Video
Updated: Jun 16, 2026
Retzius-Sparing Robot-Assisted Radical Prostatectomy
Published on: May 19, 2022
Predictive factors for positive surgical margins and their locations after robot-assisted laparoscopic radical
Rafael F Coelho1, Sanket Chauhan, Marcelo A Orvieto
1Global Robotics Institute, Florida Hospital Celebration Health, Celebration, FL, USA.
Background:
Positive surgical margin (PSM) after radical prostatectomy (RP) has been shown to be an independent predictive factor for cancer recurrence. Several investigations have correlated clinical and histopathologic findings with surgical margin status after open RP. However, few studies have addressed the predictive factors for PSM after robot-assisted laparoscopic RP (RARP).
Objective:
We sought to identify predictive factors for PSMs and their locations after RARP.
Design, Setting, And Participants:
We prospectively analyzed 876 consecutive patients who underwent RARP from January 2008 to May 2009.
Intervention:
All patients underwent RARP performed by a single surgeon with previous experience of >1500 cases.
Measurements:
Stepwise logistic regression was used to identify potential predictive factors for PSM. Three logistic regression models were built: (1) one using preoperative variables only, (2) another using all variables (preoperative, intraoperative, and postoperative) combined, and (3) one created to identify potential predictive factors for PSM location. Preoperative variables entered into the models included age, body mass index (BMI), prostate-specific antigen, clinical stage, number of positive cores, percentage of positive cores, and American Urological Association symptom score. Intra- and postoperative variables analyzed were type of nerve sparing, presence of median lobe, percentage of tumor in the surgical specimen, gland size, histopathologic findings, pathologic stage, and pathologic Gleason grade.
Results And Limitations:
In the multivariable analysis including preoperative variables, clinical stage was the only independent predictive factor for PSM, with a higher PSM rate for T3 versus T1c (odds ratio [OR]: 10.7; 95% confidence interval [CI], 2.6-43.8) and for T2 versus T1c (OR: 2.9; 95% CI, 1.9-4.6). Considering pre-, intra-, and postoperative variables combined, percentage of tumor, pathologic stage, and pathologic Gleason score were associated with increased risk of PSM in the univariable analysis (p<0.001 for all variables). However, in the multivariable analysis, pathologic stage (pT2 vs pT1; OR: 2.9; 95% CI, 1.9-4.6) and percentage of tumor in the surgical specimen (OR: 8.7; 95% CI, 2.2-34.5; p=0.0022) were the only independent predictive factors for PSM. Finally, BMI was shown to be an independent predictive factor (OR: 1.1; 95% CI, 1.0-1.3; p=0.0119) for apical PSMs, with increasing BMI predicting higher incidence of apex location. Because most of our patients were referred from other centers, the biopsy technique and the number of cores were not standardized in our series.
Conclusions:
Clinical stage was the only preoperative variable independently associated with PSM after RARP. Pathologic stage and percentage of tumor in the surgical specimen were identified as independent predictive factors for PSMs when analyzing pre-, intra-, and postoperative variables combined. BMI was shown to be an independent predictive factor for apical PSMs.
