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Learning Curve in Robotic Colorectal Surgery.
Antarip Bhattacharya1,2, Supratim Bhattacharyya1,2, Prosenjit Das1,2
1Department of General Surgery, Newham University Hospital, Barts Health NHS Trust, London, United Kingdom. (Dr. Bhattacharya).
JSLS : Journal of the Society of Laparoendoscopic Surgeons
|December 3, 2025
Summary
Surgeons face a learning curve in robotic colorectal surgery, with proficiency varying between 15-55 cases. Standardized methods are needed to improve training and patient outcomes in this advanced surgical field.
Area of Science:
- Surgical Innovation
- Medical Technology Assessment
- Clinical Outcomes Research
Background:
- Robotic platforms offer benefits in colorectal surgery but present a steep learning curve for surgeons.
- A lack of standardized proficiency definitions hinders consistent training and evaluation.
- This review synthesizes evidence on learning curves in robotic colorectal surgery.
Purpose of the Study:
- To evaluate published evidence on learning curves in robotic colorectal surgery.
- To identify proficiency thresholds and analytic methodologies used.
- To assess the impact of surgical experience on clinical and oncological outcomes.
Main Methods:
- Systematic literature search of PubMed up to April 2025.
- Inclusion of studies reporting learning curve data for robotic colorectal procedures.
- Narrative synthesis due to heterogeneity in study designs and outcomes.
Main Results:
- Nineteen studies were included, with proficiency ranging from 15-55 cases.
- Operative time was the most analyzed parameter; CUSUM/RA-CUSUM were common methods.
- Post-proficiency, reduced complications, lower conversion rates, and better oncological outcomes were observed.
Conclusions:
- Robotic colorectal surgery has a measurable learning curve affecting technical and patient outcomes.
- Significant variability in learning curve definitions and analysis limits comparisons.
- Standardized training and consensus on analysis are crucial for safe adoption.
