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Page 10 of 12 Erodotou et al. Mini-invasive Surg 2023;7:35 https://dx.doi.org/10.20517/2574-1225.2023.95

Following the observation and assisting phase, the adopting surgeon can start performing RAMIE under
[22]
strict supervision by the proctor . Succeeding that in a proficiency level, the surgeon can initiate
performing RAMIE independently. At the start of this undertaking, the surgeon may face longer operating
time, higher intraoperative blood loss, lower lymph node yield, more complications, and higher conversion
rates. Therefore, a certain number of cases is required during the proctoring before reaching a steady level
of performance. In this review, the learning curve plateaus for the total operative time, the vocal cord palsy
rates, and the lymph node yield varied between 20-80, 15-80, and 18-73 cases, respectively. Some surgeons
prefer to avoid challenging cases at the start of their training pathway to limit technical difficulty and
[23]
decrease the risk of adverse events . In addition, a sufficient caseload, more than 20 RAMIEs per year, and
access to a robotic system are of great importance. If 20 operations are not achievable by a surgeon within
one hospital, then collaborations or centralization should be considered strongly . Without a doubt,
[23]
RAMIE should be performed only in large volume centers.

This study has some limitations, mainly due to the differences in the included studies, and thus, strong
conclusions are unfeasible. A large degree of heterogeneity was observed between the selected studies. This
observation can be explained by the different case volumes in each study, the methods used for learning
curve analysis, and the presence of prior robotic experience. In a recent study from de Groot et al., 70
patients underwent RAMIE with intrathoracic anastomosis for esophageal cancer in a high-volume center
with 15 years of experience in transthoracic robotic esophagectomy. Prior experience with robotic platforms
resulted in a shorter plateau (case 22) for the robotic abdominal operation time compared to the thoracic
operation time plateau (case 24), which was analyzed by the same study group in the past . To our
[31]
knowledge, the number of cases and the time needed to reach the learning curve plateau depend on several
factors, such as the pre-existing minimally invasive and robotic experience of the surgeon, the presence of a
dedicated anesthesiologist and scrub nurse team, the adopting center, the characteristics of the selected
cases, and the type of esophagectomy and anastomosis.

CONCLUSION
Nowadays, several centers are increasingly adopting RAMIE as their preferred approach to esophagectomy
for cancer. Education about the learning curve of RAMIE is crucial for the training pathway in order to
safely introduce RAMIE in centers without pre-existing robotic esophagectomy experience. More
structured training programs and consensus in learning curve analysis will help guide future robotic
surgeons to implement RAMIE.

DECLARATIONS
Authors’ contributions
Made substantial contributions to the conception and design of the study and performed data analysis and
interpretation: Erodotou M
Revised the work critically for important intellectual content and provided final approval of the version to
be published: Lagarde SM, Wijnhoven BPL, van der Sluis PC

Availability of data and materials
Not applicable.