Systematic Review: The Learning Curve for Robot-Assisted Radical Cystectomy-What Do We Know?

Journal: Journal of endourology
Published Date:

Abstract

The aim of this systematic review is to assess the robot-assisted radical cystectomy (RARC) learning curve (LC), which is important to consider in both risk-benefit assessment and training. We performed a systematic literature search using two databases (Medline and Scopus) with the search query "learning AND cystectomy" and included all articles containing data on the assessment of the RARC LC. Our primary outcome was the surgeons' experience (a number of performed procedures) required to achieve the LC plateau. The secondary outcomes related to the methods for assessing the relevant LC. Between 9 and 50 procedures were required to reduce the operation time significantly. The data on estimated blood loss during RARC are somewhat controversial. To optimize the lymph node (LN) yield, it was necessary to treat between 20 and 50 patients. The LC for positive surgical margin was described only in one study, it was completed after 24-30 cases. Between 10 and 15 cases were necessary to reduce length of stay (LOS). Complications became less frequent after 10 to 75 patients but there was no clear plateau in the figures. Based on the relevant assessment criteria, the RARC LC length varies from 10 to 50 cases. The most common criteria for evaluating the learning experience include operation time and the LN yield. Blood loss, length of stay, and complications rate show variable outcomes and may be harder to use systematically as a means of LC assessment.

Authors

  • Andrey Morozov
    Institute for Urology and Reproductive Health, Sechenov University, Moscow, Russia.
  • Diana Babaevskaya
    Institute for Clinical Medicine, Sechenov University, Moscow, Russia.
  • Mark Taratkin
    Institute for Urology and Reproductive Health, Sechenov University, Moscow, Russia.
  • Jasur Inoyatov
    Institute for Urology and Reproductive Health, Sechenov University, Moscow, Russia.
  • Ekaterina Laukhtina
    Institute for Urology and Reproductive Health, Sechenov University, Moscow, Russia.
  • Marco Moschini
    Division of Oncology/Unit of Urology, Urological Research Institute, IRCCS Ospedale San Raffaele, Milan, Italy.
  • Nirmish Singla
    Department of Urology, University of Texas Southwestern Medical Center, Dallas, TX, USA. Electronic address: nirmish@gmail.com.
  • Juan Gomez Rivas
    Department of Urology, Clinico San Carlos University Hospital, Madrid, Spain.
  • Jeremy Yuen-Chun Teoh
  • Petr Glybochko
    Institute for Urology and Reproductive Health, Sechenov University, Moscow, Russia.
  • Dmitry Enikeev
    Institute for Urology and Reproductive Health, Sechenov University, Moscow, Russia.