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Int. braz. j. urol ; 39(5): 639-648, Sep-Oct/2013. tab
Article in English | LILACS | ID: lil-695164

ABSTRACT

Objective We compared positive surgical margin (PSM) rates for patients with high risk prostate cancer (HRCaP) who underwent open radical retropubic (RRP), robotic (RALP), and laparoscopic (LRP) prostatectomy at a single institution. Materials and Methods We performed a retrospective review of our prospectively maintained IRB approved database identifying prostate cancer patients who underwent RRP, RALP, or LRP between January 2000 and March 2010. Patients were considered to have HRCaP if they had biopsy or final pathologic Gleason score ≥ 8, or preoperative PSA ≥ 20, or pathologic stage ≥ T3a. A positive surgical margin (PSM) was defined by the presence of tumor at the inked surface of the specimen. Patients who received neoadjuvant hormonal therapy and those who underwent a perineal prostatectomy were excluded from the study. Results Of the 445 patients in this study, surgical technique for prostatectomy included RRP (n = 153), RALP (n = 152), and LRP (n = 140). PSM rate for the three groups were not different: 52.9% RRP, 50% RALP, and 41.4% LRP, (p = 0.13). The PSM rate did not differ when comparing RRP to a combined group of RALP and LRP (p = 0.16). Among patients with a PSM, there was no statistical difference between the three groups in terms of the number of patients with a pathologic stage of T3 or higher (p = 0.83). On univariate analysis, a higher preoperative PSA value was associated with a positive margin (p = 0.04). Conclusion In this HRCaP series, the PSM rate did not differ based on the surgical approach. On univariate analysis, patients with a higher preoperative PSA value were more likely to have a PSM. .


Subject(s)
Aged , Humans , Male , Middle Aged , Laparoscopy/methods , Prostatectomy/methods , Prostatic Neoplasms/surgery , Biopsy , Neoplasm Grading , Neoplasm, Residual , Prostate-Specific Antigen/blood , Prostatic Neoplasms/pathology , Retrospective Studies , Risk Assessment , Risk Factors , Robotics , Statistics, Nonparametric , Treatment Outcome
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