Objectives: To evaluate the learning curve of robotic-assisted partial nephrectomy as it pertains to operative time (OT) and advanced perioperative variables such as achievement of trifecta, postoperative complications, 30-day readmission rates (RR), warm ischemia time (WIT), and functional volume loss (FVL).
Methods: We evaluated 418 consecutive robotic-assisted partial nephrectomy performed by a single surgeon between February 2008 and April 2019. Multivariable log-log regression models were used to evaluate the associations between case number and continuous outcomes (OT, WIT, and FVL). Multivariable logistic regression models were used to evaluate the association of case number with dichotomous outcomes (trifecta, postoperative complications, RR).
Results: Among the 406 eligible patients included in the study, 252 (62.1%) were male, median age was 63 years (range, 22-84), and median body mass index was 29 kg/m2 (interquartile range 26-33). Surgeon experience was associated with shorter OT (-2.5% per 50% increase in case number; 95% confidence interval; P <.001) and plateaus around 77 cases performed. There was slight improvement with trifecta (odds ratio [per 50% increase in cases] = 1.08; 95% confidence interval) and the plateau was also at 77 cases, however, this was not statistically significant (P = .086). We did not find statistically significant associations of surgeon experience with FVL (P = .77), postoperative complications (P = .74), WIT (P = .73), or 30-day RR (P = .33).
Conclusion: There does not appear to be a relationship between surgical experience and grade 3 or higher postoperative complications, 30-day RR, WIT, or FVL. Trifecta outcomes and maximum OT performance appear to be optimized at approximately 77 cases.
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