From proficiency to expert, when does the learning curve for robotic-assisted prostatectomies plateau? The Columbia University experience Academic Article uri icon


MeSH Major

  • Clinical Competence
  • General Surgery
  • Prostatectomy
  • Prostatic Neoplasms
  • Robotics


  • To describe our single-institution experience with our first 70 consecutive robotic-assisted laparoscopic prostatectomies (RLPs) with particular focus on effect of learning curve on operative time, length of stay and blood loss. We also report our short-term outcome data in this heterogeneous cohort of men with prostate cancer (PCa). We reviewed our institutional database for the first 70 consecutive RLPs performed by a single surgeon (DS) over a 21-month period (March 2003 to December 2004). Surgical, pathologic and postoperative outcomes were analyzed. In order to evaluate the impact of the surgeon's and institution's learning curve on outcomes, the cases were divided into quartiles and stratified accordingly to identify trends. Ninety-nine percent (69/70) of all procedures were successfully completed robotically. Mean blood loss, operative time and mean length of stay were 231 ml, 264 min and 1.9 days, respectively. At follow-up, 76% of all patients were fully continent (no pads) and 93% (62/67) had undetectable PSA. The most dramatic improvement in surgical outcomes was seen within the first quartile of cases; however a statistically significant improvement trend existed throughout the series. This included a downward trend in operative time (P < 0.00001), estimated blood loss (P < 0.00001), and length of hospital stay (P = 0.003). This trend continued when controlled for in a multivariate analysis. Our results compare favorably with other RLP series as well as conventional laparoscopic series. Proficiency is achieved within the first 20 cases; however surgical outcomes continue to improve for RLP throughout the first 70 cases and perhaps beyond.

publication date

  • March 2007



  • Academic Article



  • eng

Digital Object Identifier (DOI)

  • 10.1007/s00345-006-0137-4

PubMed ID

  • 17192816

Additional Document Info

start page

  • 105

end page

  • 10


  • 25


  • 1