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. 2023 Jul 1;109(7):2037-2057.
doi: 10.1097/JS9.0000000000000345.

The learning curves of major laparoscopic and robotic procedures in urology: a systematic review

Baldev Chahal  1 , Abdullatif Aydin  1   2 , Mohammad S A Amin  3 , Azhar Khan  2   4 , Muhammad S Khan  4 , Kamran Ahmed  1   2 , Prokar Dasgupta  1   4
Affiliations

The learning curves of major laparoscopic and robotic procedures in urology: a systematic review

Baldev Chahal et al. Int J Surg. .

Abstract

Background: Urology has been at the forefront of adopting laparoscopic and robot-assisted techniques to improve patient outcomes. This systematic review aimed to examine the literature relating to the learning curves of major urological robotic and laparoscopic procedures.

Methods: In accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, a systematic literature search strategy was employed across PubMed, EMBASE, and the Cochrane Library from inception to December 2021, alongside a search of the grey literature. Two independent reviewers completed the article screening and data extraction stages using the Newcastle-Ottawa Scale as a quality assessment tool. The review was reported in accordance with AMSTAR (A MeaSurement Tool to Assess systematic Reviews) guidelines.

Results: Of 3702 records identified, 97 eligible studies were included for narrative synthesis. Learning curves are mapped using an array of measurements including operative time (OT), estimated blood loss, complication rates as well as procedure-specific outcomes, with OT being the most commonly used metric by eligible studies. The learning curve for OT was identified as 10-250 cases for robot-assisted laparoscopic prostatectomy and 40-250 for laparoscopic radical prostatectomy. The robot-assisted partial nephrectomy learning curve for warm ischaemia time is 4-150 cases. No high-quality studies evaluating the learning curve for laparoscopic radical cystectomy and for robotic and laparoscopic retroperitoneal lymph node dissection were identified.

Conclusion: There was considerable variation in the definitions of outcome measures and performance thresholds, with poor reporting of potential confounders. Future studies should use multiple surgeons and large sample sizes of cases to identify the currently undefined learning curves for robotic and laparoscopic urological procedures.

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Conflict of interest statement

Baldev Chahal, Abdullatif Aydin, Mohammad S.A. Amin, Azhar Khan, Muhammad S. Khan and Kamran Ahmed have no conflicts of interest or financial ties to disclose. Prokar Dasgupta declares financial ties as Chief Medical Officer for Proximie Ltd. and Chief Scientific Officer for MysteryVibe Ltd. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Sponsorships or competing interests that may be relevant to content are disclosed at the end of this article.

Figures

Figure 1
Figure 1
PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) diagram.
Figure 2
Figure 2
The number of cases required to overcome the learning curve for RALP and LRP. Values are given as a range, with ‘n’ denoting the number of studies which numerically defined the learning curve for the outcome. LRP, laparoscopic radical prostatectomy; PLND, pelvic lymph node dissection; PSM, positive surgical margins; RALP, robot-assisted laparoscopic prostatectomy. Where studies defined learning curve for ‘overall performance’, this referred to the number of cases required to achieve competency across the range of outcomes they measured.
Figure 3
Figure 3
The number of cases required to overcome the learning curve for robot-assisted and laparoscopic nephrectomies. MIC, ‘Margins, Ischaemia and Complications’, score; RAPN, robot-assisted partial nephrectomy. Where studies defined learning curve for ‘overall performance’, this referred to the number of cases required to achieve competency across the range of outcomes they measured.
Figure 4
Figure 4
The number of cases required to overcome the learning curve for robot-assisted robotic cystectomy and robotic pyeloplasty. RARC, robot-assisted radical cystectomy. Where studies defined learning curve for ‘overall performance’, this referred to the number of cases required to achieve competency across the range of outcomes they measured.
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