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Better Taught, Better Learned: The Surgical Learning Curve for Biochemical Recurrence after Robot-Assisted Radical Prostatectomy - Beyond the Abstract

Surgeon experience is a widely recognized determinant of surgical outcomes.1 The impact of experience on the oncologic efficacy of radical prostatectomy has been investigated in open2 and laparoscopic3 series. These multicenter studies included 72 and 29 surgeons and 7765 and 4792 patients respectively. There was a large and highly significant difference in absolute risk of recurrence, about 8%, with the learning curve being slower for the laparoscopic approach.

In contrast, evidence on the learning curve for cancer control after robot-assisted radical prostatectomy (RARP) is limited. In one of the few available studies on this topic, the association between experience and recurrence risk was assessed for a single surgeon who converted from open to robotic surgery.4 Other investigators assessed the learning curve of minimally invasive radical prostatectomy performed by 9 surgeons.5 However, instead of calculating a learning curve, the authors divided patients into different categories of experience, a demonstrably suboptimal method,6 underestimating the number of the procedures needed to reach the potential plateau of the learning curve. Previously, we assessed the relationship between the surgeon’s experience and risk of biochemical recurrence after RARP in a single institution, multi-surgeon series.7 The probability of freedom from recurrence did not change as a function of surgeon experience. However, this may be due to relatively limited number of cases, single center experience, and limited number of surgeons included in the analyses. For these reasons, we built a multi-institutional collaboration to investigate whether prior experience of a surgeon is related to oncologic outcomes after RARP.

We retrospectively analyzed data of 8,101 patients with prostate cancer treated with RARP by 46 surgeons at 9 institutions between 2003 and 2021. We evaluated the relationship of prior surgeon experience to the probability of biochemical recurrence (BCR) adjusting for preoperative PSA, pathological stage, grade, lymph-node involvement, and year of surgery.

Overall, 1047 patients had BCR. Median follow-up for patients without BCR was 33 months (interquartile range: 14, 61). After adjusting for case mix, the relationship between surgical experience and the risk of BCR after surgery was not statistically significant (p=0.2). As shown in Figure 1, we did not find evidence of an association between the probability of freedom from biochemical recurrence after 5 years from RARP and increasing surgical experience. The 5-yr BCR-free survival for a patient treated by a surgeon with prior 10, 250, and 1000 procedures performed was 82.5%, 82.7%, and 84.1% (absolute difference between 10 and 1000 prior procedures: 1.6%; 95% C.I. 0.4%, 3.3%). Results were robust to a number of sensitivity analyses.
biochemical_recurrence.png
In contrast to the learning curves were previously described for open and laparoscopic radical prostatectomy,2,3 we did not find evidence of improved cancer control after RARP as the experience of the operating surgeon increased.

There are several possible explanations for our findings. First, RARP may be inherently easier to learn as compared to laparoscopic and/or open techniques.8,9 For instance, laparoscopy requires learning how to operate with instruments that have limited haptic feedback and minimal flexibility and thus, tissue manipulation may be challenging especially for unexperienced surgeons. Moreover, in a procedure such as radical prostatectomy with a delicate reconstructive phase requiring suturing and knotting skills, this may translate into slower learning for surgeons who start with this technique, reaching surgical proficiency only after a certain number of cases. Instead, other aspects may be problematic for surgeons starting with open surgery. The small pelvis is a challenging surgical field, not easily accessible and with difficult anatomy, requiring high dexterity to perform quality surgery, especially for surgeons in training. Appropriate training for open surgeons may be also limited by the fact that, as compared to minimally invasive techniques, it is more problematic to record high quality videos of open procedures that are therefore less reproducible for educational purposes. In this regard, since the operative view during robotic surgery is controlled by the surgeon and thus always focused on the surgical field, educational videos may provide more valuable information for robotic trainees. Among other potential advantages as compared to open surgery, robotics offers a 3D magnified vision, articulating instruments, and lack of hand tremor, all factors that may contribute to improved surgical performance. With respect to laparoscopic surgery, the enhanced manipulation of robotic instruments allows surgeons to operate with more precise and fluent movements as compared to traditional laparoscopy. For these reasons, it is plausible that surgeons starting with RARP might be comfortable and efficient in performing surgery from the initial cases.

Another possible explanation for our findings concerns surgical education. If less experienced surgeons had similar outcomes to those of more experienced ones, it is plausible that education in robotic surgery may provide surgeons with better skills, allowing them to perform surgery in their initial cases as well as more experienced surgeons. In recent years, there have been several calls for improvement in how surgeons are trained.10 Traditional, classroom-based surgical education was usually blamed for suboptimal outcomes of the trainees, and a transition towards more practical training was usually recommended in order to improve surgical education and, in turn, optimize clinical outcomes. With respect to a well-established surgical procedure such as radical prostatectomy, structured training including surgical simulation has already been described for laparoscopic radical prostatectomy.11 However, whether these programs are actually part of the surgical community remains at least questionable.10 In addition, the technical challenges of laparoscopy and the growing interest towards robotic surgery opened the discussion of whether robot-assisted surgery might shorten the learning curve of new surgeons approaching radical prostatectomy. In this regard, prior evidence showed that robot-assisted surgery allowed an open surgeon to achieve and overcome outcomes he had with open surgery after a long learning curve.4 Still, whether this might apply to an average surgeon remained a matter of debate. We here provided evidence that not only robotic assistance might shorten the process of learning, but also that this may be possible for the average surgeon. As compared to open and laparoscopic training, robotics allows for a more structured, more widely available training programs and surgical curricula.12-15 Simulation technologies, video review, and, in general, more practical training16  may be the reason why robotic surgeons in the early phase of their career seem to have comparable outcomes to those of more experienced surgeons. Also, the development of objective performance metrics17 as well as the increasing adoption of proficiency-based progression training methodology in robotic surgery18 may be reasons to explain our findings.

In conclusion, we found that the probability of BCR after RARP seems independent of the experience of the operating surgeon. As opposed to the open and laparoscopic approaches, which have a documented learning curve, the absolute risk difference of BCR between experienced surgeons and novices was of no clear clinical relevance in our study. Since our cohort's patient characteristics and long-term recurrence risk are similar to those of prior series, our findings might suggest that adequate cancer control after RARP is also feasible in the early phase of a surgeon career. Further research should explore why the learning curve for robotic surgery differs from prior findings for open and laparoscopic radical prostatectomy. We hypothesize that surgical education, including simulation training and the adoption of objective performance metrics, is an important mechanism for flattening the learning curve.

Written by: Carlo A. Bravi1,2,3 Paolo Dell’Oglio4,5,6 Elio Mazzone3 Marcio C. Moschovas7 Ugo Falagario8 Pietro Piazza1,9 Simone Scarcella1,10 Christopher Bednarz11 Luca Sarchi1 Stefano Tappero4,12 Sophie Knipper1,13 Ruben De Groote1,2 Daniel Sjoberg14 Riccardo Schiavina9 Nazareno Suardi12 Carlo Terrone12 Riccardo Autorino11 Giuseppe Carrieri8 Andrea Galosi10 Antonio Galfano4 Alberto Briganti3 Francesco Montorsi3 Vipul Patel7 Andrew Vickers14 Alexandre Mottrie1,2

  1. Department of Urology, Onze-Lieve-Vrouwziekenhuis Hospital, Aalst, Belgium
  2. ORSI Academy, Ghent, Belgium
  3. Division of Oncology/Unit of Urology; URI; IRCCS Ospedale San Raffaele, Milan, Italy
  4. Department of Urology, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy;
  5. Department of Urology, Antoni van Leeuwenhoek Hospital, The Netherlands Cancer Institute, Amsterdam, The Netherlands;
  6. Interventional Molecular Imaging Laboratory, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
  7. AdventHealth Global Robotics Institute, Celebration, FL, USA.
  8. Urology and Renal Transplantation Unit, Department of Medical and Surgical Sciences, University of Foggia, Foggia, Italy
  9. Division of Urology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
  10. Division of Urology, United Hospital of Ancona, School of Medicine Marche Polytechnic University, Ancona, Marche, Italy.
  11. Division of Urology, Virginia Commonwealth University, Richmond, Virginia, USA
  12. Department of Urology, Policlinico San Martino Hospital, University of Genova, Genova, Italy
  13. Martini-Klinik Prostate Cancer Center, University Hospital Hamburg-Eppendorf, Hamburg, Germany
  14. Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York

References:

  1. Birkmeyer JD. Surgical Skill and Complication Rates after Bariatric Surgery. N Engl J Med. September 2013:1-9. doi:10.1056/NEJMsa1300625.
  2. Vickers AJ, Bianco FJ, Serio AM, et al. The Surgical Learning Curve for Prostate Cancer Control After Radical Prostatectomy. JNCI Journal of the National Cancer Institute. 2007;99(15):1171-1177. doi:10.1093/jnci/djm060.
  3. Vickers AJ, Savage CJ, Hruza M, et al. The surgical learning curve for laparoscopic radical prostatectomy: a retrospective cohort study. Lancet Oncology. 2009;10(5):475-480. doi:10.1016/S1470-2045(09)70079-8.
  4. Thompson JE, Egger S, Böhm M, et al. Superior Biochemical Recurrence and Long-term Quality-of-life Outcomes Are Achievable with Robotic Radical Prostatectomy After a Long Learning Curve—Updated Analysis of a Prospective Single-surgeon Cohort of 2206 Consecutive Cases. European Urology. 2018;73(5):664-671. doi:10.1016/j.eururo.2017.11.035.
  5. Sivaraman A, Sanchez-Salas R, Prapotnich D, et al. Learning curve of minimally invasive radical prostatectomy: Comprehensive evaluation and cumulative summation analysis of oncological outcomes. Urologic Oncology: Seminars and Original Investigations. 2017;35(4):149.e1-149.e6. doi:10.1016/j.urolonc.2016.10.015.
  6. Vickers A, Maschino A, Savage C. Assessing the Learning Curve for Prostate Cancer Surgery. Robotic Urologic Surgery; 2012.
  7. Bravi CA, Tin A, Vertosick E, et al. The Impact of Experience on the Risk of Surgical Margins and Biochemical Recurrence after Robot-Assisted Radical Prostatectomy: A Learning Curve Study. Journal of Urology. 2019;202(1):108-113. doi:10.1097/JU.0000000000000147.
  8. Yaxley J, Coughlin G, Chambers S, et al. Robot-assisted laparoscopic prostatectomy versus open radical retropubic prostatectomy: early outcomes from a randomised controlled phase 3 study. The Lancet. 2016;388(10049):1057-1066. doi:10.1016/S0140-6736(16)30592-X.
  9. Andolfi C, Umanskiy K. Mastering Robotic Surgery: Where Does the Learning Curve Lead Us? . 2017;27(5):470-474. doi:10.1089/lap.2016.0641.
  10. Vickers AJ. What Are the Implications of the Surgical Learning Curve? European Urology. 2014;65(3):532-533. doi:10.1016/j.eururo.2013.11.034.
  11. Sugiono M, Teber D, Anghel G, et al. Assessing the Predictive Validity and Efficacy of a Multimodal Training Programme for Laparoscopic Radical Prostatectomy (LRP). European Urology. March 2007:1-9. doi:10.1016/j.eururo.2006.11.029.
  12. Dell'Oglio P, Turri F, Larcher A, et al. Definition of a Structured Training Curriculum for Robot-assisted Radical Cystectomy with Intracorporeal Ileal Conduit in Male Patients: A Delphi Consensus Study Led by the ERUS Educational Board. European Urology Focus. January 2021:1-5. doi:10.1016/j.euf.2020.12.015.
  13. Larcher A, De Naeyer G, Turri F, et al. The ERUS Curriculum for Robot-assisted Partial Nephrectomy: Structure Definition and Pilot Clinical Validation. European Urology. April 2019:1-9. doi:10.1016/j.eururo.2019.02.031.
  14. Fisher RA, Dasgupta P, Mottrie A, et al. An over-view of robot assisted surgery curricula and the status of their validation. International Journal of Surgery. 2015;13(c):115-123. doi:10.1016/j.ijsu.2014.11.033.
  15. Volpe A, Ahmed K, Dasgupta P, et al. Pilot Validation Study of the European Association of Urology Robotic Training Curriculum. European Urology. 2015;68(2):292-299. doi:10.1016/j.eururo.2014.10.025.
  16. ORSI Academy. https://www.orsi-online.com/.
  17. Mottrie A, Mazzone E, Wiklund P, et al. Objective assessment of intraoperative skills for robot-assisted radical prostatectomy (RARP): results from the ERUS Scientific and Educational Working Groups Metrics Initiative. BJU Int. 2021;128(1):103-111. doi:10.1111/bju.15311.
  18. Mazzone E, Puliatti S, Amato M, et al. A Systematic Review and Meta-analysis on the Impact of Proficiency-based Progression Simulation Training on Performance Outcomes. Annals of Surgery. July 2021:1-9. doi:10.1097/SLA.0000000000004650. 

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