Learning Curve Analysis for Intracorporeal Robot-assisted Radical Cystectomy: Results from the EAU Robotic Urology Section Scientific Working Group.

Bladder cancer Complications Intracorporeal Learning curve Radical cystectomy Robot-assisted

Journal

European urology open science
ISSN: 2666-1683
Titre abrégé: Eur Urol Open Sci
Pays: Netherlands
ID NLM: 101771568

Informations de publication

Date de publication:
May 2022
Historique:
accepted: 05 03 2022
entrez: 9 5 2022
pubmed: 10 5 2022
medline: 10 5 2022
Statut: epublish

Résumé

The utilisation of robot-assisted radical cystectomy with intracorporeal reconstruction (iRARC) has increased in recent years. Little is known about the length of the learning curve (LC) for this procedure. To study the length of the LC for iRARC in terms of 90-d major complications (MC90; Clavien-Dindo grade ≥3), 90-d overall complications (OC90, Clavien-Dindo grades 1-5), operating time (OT), estimated blood loss (EBL), and length of hospital stay (LOS). This was a retrospective analysis of all consecutive iRARC cases from nine European high-volume hospitals with ≥100 cases. All patients had bladder cancer for which iRARC was performed, with an ileal conduit or neobladder as the urinary diversion. Outcome parameters used as a proxy for LC length were the number of consecutive cases needed to reach a plateau level in two-piece mixed-effects models for MC90, OC90, OT, EBL, and LOS. A total of 2186 patients undergoing iRARC between 2003 and 2018were included. The plateau levels for MC90 and OC90 were reached after 137 cases (95% confidence interval [CI] 80-193) and 97 cases (95% CI 41-154), respectively. The mean MC90 rate at the plateau was 14% (95% CI 7-21%). The plateau level was reached after 75 cases (95% CI 65-86) for OT, 88 cases (95% CI 70-106) for EBL, and 198 cases (95% CI 130-266) for LOS. A major limitation of the study is the difference in the balance of urinary diversion types between centres. This multicentre retrospective analysis for the iRARC LC among nine European centres showed that 137 consecutive cases were needed to reach a stable MC90 rate. We carried out a multicentre analysis of the surgical learning curve for robot-assisted removal of the bladder and bladder reconstruction in patients with bladder cancer. We found that 137 consecutive cases were needed to reach a stable rate of serious complications.

Sections du résumé

Background UNASSIGNED
The utilisation of robot-assisted radical cystectomy with intracorporeal reconstruction (iRARC) has increased in recent years. Little is known about the length of the learning curve (LC) for this procedure.
Objective UNASSIGNED
To study the length of the LC for iRARC in terms of 90-d major complications (MC90; Clavien-Dindo grade ≥3), 90-d overall complications (OC90, Clavien-Dindo grades 1-5), operating time (OT), estimated blood loss (EBL), and length of hospital stay (LOS).
Design setting and participants UNASSIGNED
This was a retrospective analysis of all consecutive iRARC cases from nine European high-volume hospitals with ≥100 cases. All patients had bladder cancer for which iRARC was performed, with an ileal conduit or neobladder as the urinary diversion.
Outcome measurements and statistical analysis UNASSIGNED
Outcome parameters used as a proxy for LC length were the number of consecutive cases needed to reach a plateau level in two-piece mixed-effects models for MC90, OC90, OT, EBL, and LOS.
Results and limitations UNASSIGNED
A total of 2186 patients undergoing iRARC between 2003 and 2018were included. The plateau levels for MC90 and OC90 were reached after 137 cases (95% confidence interval [CI] 80-193) and 97 cases (95% CI 41-154), respectively. The mean MC90 rate at the plateau was 14% (95% CI 7-21%). The plateau level was reached after 75 cases (95% CI 65-86) for OT, 88 cases (95% CI 70-106) for EBL, and 198 cases (95% CI 130-266) for LOS. A major limitation of the study is the difference in the balance of urinary diversion types between centres.
Conclusions UNASSIGNED
This multicentre retrospective analysis for the iRARC LC among nine European centres showed that 137 consecutive cases were needed to reach a stable MC90 rate.
Patient summary UNASSIGNED
We carried out a multicentre analysis of the surgical learning curve for robot-assisted removal of the bladder and bladder reconstruction in patients with bladder cancer. We found that 137 consecutive cases were needed to reach a stable rate of serious complications.

Identifiants

pubmed: 35528784
doi: 10.1016/j.euros.2022.03.004
pii: S2666-1683(22)00056-8
pmc: PMC9068730
doi:

Types de publication

Journal Article

Langues

eng

Pagination

55-61

Informations de copyright

© 2022 The Author(s).

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Auteurs

Carl J Wijburg (CJ)

Department of Urology, Rijnstate Hospital, Arnhem, The Netherlands.

Gerjon Hannink (G)

Department of Operating Rooms, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands.

Charlotte T J Michels (CTJ)

Department for Health Evidence, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands.

Philip C Weijerman (PC)

Department of Urology, Rijnstate Hospital, Arnhem, The Netherlands.

Rami Issa (R)

Department of Urology, St. George's University Hospitals, London, UK.

Andrea Tay (A)

Department of Urology, St. George's University Hospitals, London, UK.

Karel Decaestecker (K)

Department of Urology, University Hospital Gent, Gent, Belgium.

Peter Wiklund (P)

Department of Urology, Mount Sinai Hospital, New York, NY, USA.

Abolfazl Hosseini (A)

Department of Urology, Karolinska University Hospital, Stockholm, Sweden.

Ashwin Sridhar (A)

Department of Urology, University College London Hospitals, London, UK.

John Kelly (J)

Department of Urology, University College London Hospitals, London, UK.

Frederiek d'Hondt (F)

Department of Urology, Onze Lieve Vrouw Hospital, Aalst, Belgium.

Alexandre Mottrie (A)

Department of Urology, Onze Lieve Vrouw Hospital, Aalst, Belgium.

Sjoerd Klaver (S)

Department of Urology, Maasstad Hospital, Rotterdam, The Netherlands.

Sebastian Edeling (S)

Department of Urology, Vinzenz Hospital, Hannover, Germany.

Paolo Dell'Oglio (P)

Department of Urology, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy.

Francesco Montorsi (F)

Department of Urology, Division of Oncology, Urological Research Institute, IRCCS Ospedale San Raffaele, Milan, Italy.

Maroeska M Rovers (MM)

Department of Operating Rooms, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands.
Department for Health Evidence, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands.

J Alfred Witjes (JA)

Department of Urology, Radboud University Medical Center, Nijmegen, The Netherlands.

Classifications MeSH