Objective: We investigated whether pathological outcomes improved with experience and surgeon generation after robot-assisted laparoscopic prostatectomy (RALP). Materials and Methods: The study included 1338 patients who underwent RALP between February 2010 and April 2020. We created learning curves for pelvic lymph node dissection (PLND), number of lymph nodes (LNs) removed, and positive surgical margin (PSM) after adjustment for confounders. We compared the outcomes between the first and second generation of surgeons in regression models. Results: The learning curve regarding PLND indications showed a significant increase with experience for the first generation, whereas the second generation had a learning curve that remained flat at a higher level (92.3%) and significantly better than the first generation (p < 0.001). Similarly, the number of LN removed showed a significant increase with experience in both generations, but the overall median number of LN removed was significantly higher in the second generation compared with the first generation (12 vs 10, p < 0.001). However, the learning curve for PSM remained flat at ∼20% after adjustment and did not show improvement with experience in both generations of surgeons (p = 0.794). Conclusions: Surgeons showed improvement with experience and education with RALP with respect to the indications for PLND and number of LNs removed. However, there was no improvement over time and generations for PSM. Experience based solely on the number of patients operated on is not an intrinsic factor in the pathological quality of RALP. Factors other than experience may also play a role in oncologic improvement.
Keywords: learning curve; prostate cancer; radical prostatectomy; robotics.