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

Turki Altaylouni1, Pimrapat Gebert2, Sefer Elezkurtaj3

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Surgeon experience improved pelvic lymph node dissection and lymph node yield in robot-assisted laparoscopic prostatectomy (RALP). However, positive surgical margins did not improve with experience or surgeon generation, suggesting other factors influence oncologic outcomes.

Keywords:
learning curveprostate cancerradical prostatectomyrobotics

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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.