Robot-Assisted Laparoscopic Prostatectomy Experience and Pathological Quality: Are They Always Linked?

Area of Science:

• Urology
• Surgical Oncology
• Robotic Surgery

Background:

• Robot-assisted laparoscopic prostatectomy (RALP) is a complex procedure.
• Assessing the impact of surgeon experience and generational differences on RALP outcomes is crucial for improving patient care.

Purpose of the Study:

• To investigate the learning curves and generational effects on pathological outcomes after RALP.
• To determine if surgeon experience and generation influence pelvic lymph node dissection (PLND), lymph node (LN) yield, and positive surgical margins (PSM).

Main Methods:

• Analysis of 1338 RALP cases performed between February 2010 and April 2020.
• Development of learning curves for PLND indications, LN count, and PSM, adjusted for confounders.
• Comparison of outcomes between first and second-generation surgeons using regression models.

Main Results:

• The second-generation surgeons demonstrated significantly better PLND indications (92.3%) compared to the first generation.
• Both generations showed increased LN removal with experience, with the second generation removing more LNs (median 12 vs 10).
• Positive surgical margins remained consistently around 20% for both generations, showing no improvement with experience (p=0.794).

Conclusions:

• Surgeon experience and education enhance PLND indications and LN yield in RALP.
• Positive surgical margin rates did not improve with experience or across surgeon generations.
• Patient selection and other factors beyond surgical volume may be critical for improving oncologic outcomes in RALP.