Related Experiment Video
Updated: Jan 8, 2026
Retzius-Sparing Robot-Assisted Radical Prostatectomy
Published on: May 19, 2022
Evaluation of Multifocal Positive Surgical Margin Predictors and Mapping of Positive Surgical Margin Locations in
Ali Kaan Yildiz1, Huseyin Gultekin2, Turgay Kacan2
1Department of Urology, University of Health Sciences, Ankara, Turkey; Department of Urology, Ankara City Hospital, Ankara, Turkey.
Objective:
To identify predictive factors for multifocal positive surgical margins (PSM) in patients undergoing robot-assisted radical prostatectomy (RARP) and the impact of prostate volume (PV) on the locations of PSMs.
Methods:
A total of 440 patients who underwent RARP between 2021 and 2024 were retrospectively evaluated. A PSM was defined as ≥3 mm of continuous tumor at the surgical margin. Patients were divided into 3 groups: negative SM (surgical margin) (n = 312), unifocal PSM (n = 61), and multifocal PSM (n = 67). The groups were compared in respect of age, body mass index (BMI), total linear length of PSM, prior pelvic surgery, prior radiotherapy (RT), prior transurethral-resection of prostate (TURP), prostate-specific antigen (PSA), PV, PSA density (PSAD), nerve-sparing status, and tumor stage and grade. Multivariate logistic regression analysis was performed.
Results:
The overall PSM rate was 29.0% (128/440 patients). There were no statistically significant differences between the unifocal and multifocal PSM groups in terms of age, BMI, nerve-sparing status, PSAD, or pathological stage (all P >.05). Significant differences were observed for PSA (P = .001), PV (P = .001), biopsy ISUP grade (P = .04), and pathological ISUP grade (P = .04). In multivariate analysis, higher PSA (OR 1.406, P = .03) and larger PV (OR 1.229, P = .04) emerged as independent predictors of multifocal PSM. Posterolateral PSMs were more common in prostates ≤40 mL (37.1%), whereas apical PSMs predominated in prostates >40 mL (57.4%).
Conclusion:
Addressing the risk factors associated with multifocal PSMs may contribute to better oncological outcomes. Predicting the likely locations of PSMs based on PV may help enhance the success of the surgical procedure.
