Learning Curves in Robotic Urological Oncological Surgery: Has Anything Changed During the Last Five Years?

Area of Science:

• Urology
• Surgical Oncology
• Robotic Surgery

Background:

• Limited high-quality evidence and structured curricula exist for learning curves (LCs) in urological surgical oncology.
• Robot-assisted surgery is increasingly used, necessitating a clear understanding of surgeon proficiency.
• This review systematically examines LCs in robot-assisted urological cancer surgery.

Purpose of the Study:

• To systematically review and analyze the literature on learning curves (LCs) in robot-assisted surgery for various urological cancers.
• To compare recent findings with previous data to identify trends in LCs.
• To highlight the heterogeneity in LC definitions and their impact on outcomes.

Main Methods:

• Systematic literature search of Medline up to December 2024.
• Inclusion of studies on robot-assisted radical prostatectomy (RARP), radical cystectomy (RARC), radical and partial nephrectomy (RARN, RAPN), and radical nephroureterectomy (RANU).
• Comparison of LCs reported in the last five years versus previous periods.

Main Results:

• 82 studies were identified; the majority focused on RARP (47 studies).
• LCs were defined by various metrics including operative time, blood loss, complications, and oncological outcomes, with significant heterogeneity in ranges across procedures.
• No studies assessed LCs for RARN or RANU.

Conclusions:

• Robot-assisted urological surgery lacks a standardized definition for learning curves (LCs), resulting in heterogeneity across studies.
• LCs for robot-assisted urological procedures appear steep and continuous.
• Structured training curricula are essential for optimizing surgical outcomes and preparing surgeons.