The "learning curve" in surgical training, representing the progression of trainee efficiency and clinical outcomes, lacks a standardized definition and measurement, particularly challenging in the rapidly evolving field of male functional urology. Procedures like AUS implantation, male sling placement, bladder neck reconstruction, and penile prosthesis surgery demand significant technical skill and decision-making. This systematic review aimed to synthesize existing literature on the learning curve in male functional urology, identify factors impacting skill development, and quantitatively assess the number of cases needed for proficiency.

This systematic review adhered to PRISMA guidelines. A comprehensive search was conducted across major databases (Cochrane, MEDLINE, Web of Science, Scopus, Embase, ProQuest, Google Scholar), using keywords related to learning curves and male functional urology procedures. Empirical studies evaluating learning curves through metrics like skill acquisition, operative time, complications, and functional outcomes in surgeons learning these procedures were included. Non-original publications and simulation studies without empirical data were excluded. Two independent reviewers screened records, extracted data using a standardized JBI tool (including procedure details, surgeon experience, outcome measures, and learning curve findings), and assessed methodological quality using JBI-MAStARI. Discrepancies were resolved by discussion. A mixed effects generalized linear regression analysis using R software was performed to estimate the number of cases to surpass the learning curve, incorporating CUSUM analysis and study start year.

The search yielded 7104 records, with 46 studies meeting inclusion criteria after full-text review of 185 articles. Most studies originated from France (N=8) and China (N=5). Publication years ranged from 2002 to 2023; all were observational. Common outcome measures were operative time, blood loss, and length of stay. Frequently studied procedures were HoLEP and urinary incontinence surgeries.
Learning Curve Estimates:
•	Urinary Incontinence: ARGU Sling (SUI) ≈ 22 cases; AUS implantation ≈ 200 cases (N=65,602).
•	Rectal Prolapse: Laparoscopic ventral mesh rectopexy 25-105 cases (5 studies); Robot-assisted ventral mesh rectopexy 18-55 cases (2 studies).
•	Other Functional Urology: HoLEP 14-60 cases; ThuLEP 8-20 cases; RSCAI 5 cases; Robotic sacrocolpopexy 10-84 cases.
Quantitative analysis indicated a trend of decreasing cases needed to surpass the learning curve over time. Methodological quality varied across studies, with strengths in exposure and outcome assessment but weaknesses in handling confounding factors, follow-up, and statistical analysis (Figure 1).

This review provides a broad overview of learning curves in male functional urology, demonstrating variability influenced by procedural complexity, surgeon experience, patient factors, and outcome measures. The trend towards faster learning warrants further investigation. Methodological limitations in included studies highlight the need for more rigorous future research. The findings offer evidence-based estimates for training programs, emphasizing structured pathways and trainee monitoring. Further research should explore factors influencing learning trajectories and develop standardized assessment methods.

Understanding the learning curve is crucial for optimizing surgical training and ensuring patient safety in male functional urology. This review provides valuable insights and underscores the need for ongoing research to refine training methodologies and competence assessment in this complex field.