1863 AN ANALYSIS OF VARIABILTY OF LEARNING CURVE, MARGIN STATUS AND EARLY POST OPERATIVE OUTCOMES IN 1200 ROBOT ASSISTED LAPAROSCOPIC PROSTATECTOMIES IN A MULTI-USER CENTRE

摘要

You have accessJournal of UrologyProstate Cancer: Localized VIII1 Apr 20101863 AN ANALYSIS OF VARIABILTY OF LEARNING CURVE, MARGIN STATUS AND EARLY POST OPERATIVE OUTCOMES IN 1200 ROBOT ASSISTED LAPAROSCOPIC PROSTATECTOMIES IN A MULTI-USER CENTRE Dennis Gyomber, Damien Bolton, David Webb, Lawrence Harewood, and Alan Crosthwaite Dennis GyomberDennis Gyomber Heidelberg, Melbourne, Australia More articles by this author , Damien BoltonDamien Bolton Melbourne, Australia More articles by this author , David WebbDavid Webb Heidelberg, Melbourne, Australia More articles by this author , Lawrence HarewoodLawrence Harewood East Melbourne, Australia More articles by this author , and Alan CrosthwaiteAlan Crosthwaite Box Hill, Australia More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2010.02.1803AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES A learning curve is recognized for robot assisted laparoscopic radical prostatectomy (RALP. Conventionally this is regarded as 20-50 cases, but limited published evidence exists to support this claim. We sought to ascertain outcomes from this surgery in a multiuser centre where several urologists have performed 50-450 cases. METHODS Patient demographics, PSA, biopsy findings, procedural time, blood loss, margin status, length of stay and early post operative complications were recorded. Complications were classified using the Clavien classification system. Learning curves were plotted for all individual surgeons reflecting outcomes in terms of surgical time, blood loss and margin status. RESULTS In an assessment of our total 1400 cases median patient age, body mass index and PSA were 61 years (42-80 years), 27 (21-51) and 7 (0.9-35) respectively. Clinical stageT1 and T2 made up 98.8% of case load, with a median Gleason score of 7. Median operative time, from first skin incision to closur, was 214 minutes. Mean blood loss was 491mls, corresponding to a 21% change in haemoglobin, and transfusion rate was 2.46%. Mean prostate weight was 52gms and overall positive margin rate 19.7%. The pT2 and pT3 margin rates were 13.3 and 38.4% respectively. Conversion rate was 0.76% and using Clavien classification system there were 4.3% (I-II), 1.6%(III), 0.3% (IV) and 0% (V), for a total complication rate of 6.2%. Across the entire patient cohort mean operative time and mean estimated blood loss was reached after 450 and 200 cases respectively. When individual learning curves were plotted surgeons reached these means at varying levels of experience (20-120 cases). Individual surgeons all demonstrated a rapid decrease in positive margin rate up to approximately case 50. There is a slower decline over the next 100 cases and a plateau tends to occur over subsequent groups of 100 cases. CONCLUSIONS At our multi-user robotic centre overall RALP oncological outcomes and complication rates are comparable to series in the published literature. It is apparent there are several learning curves to performing robotic prostatectomy, and surgeons vary in the rate at which overall mean outcomes are achieved. Competency at completing the procedure at mean operating time and with mean operative blood loss takes approximately 50 cases, however to reach a plateau in positive margins requires approximately 150 cases. Surgeons contemplating RALP should acknowledge there is a longer learning curve to achieve adequate oncological clearance. © 2010 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 183Issue 4SApril 2010Page: e723 Advertisement Copyright & Permissions© 2010 by American Urological Association Education and Research, Inc.Metrics Author Information Dennis Gyomber Heidelberg, Melbourne, Australia More articles by this author Damien Bolton Melbourne, Australia More articles by this author David Webb Heidelberg, Melbourne, Australia More artic