The Learning Curve in Robotic HPB Surgery: Myth, Metrics, and Misinterpretations

Background: The evolution of robotic surgery has widened the indications for minimally invasive hepatopancreatobiliary (HPB) surgery, making possible the execution of more complicated cases. Within this context, the learning curve concept is now an essential factor when assessing surgical training and expertise, as well as patient safety within a robotic HPB program. Nevertheless, existing methodologies often make use of procedure volume and surrogate intraoperative measures, which may be an insufficient way to define surgical competence. Methods: This narrative review examines the learning curve concept in robotic HPB surgery, focusing on existing performance metrics, methodological limitations, procedural complexity, risk adjustment, and the influence of team-related and institutional factors. Results: The time of operation, the estimated blood loss, the rate of conversion, and postoperative morbidity are frequently applied to assess learning curves. Nevertheless, these metrics are affected by the criteria of patient selection, the level of complexity of the procedure, and some other factors like institutional characteristics and experience of the team performing the procedure. As a result, one single value or an inflection point might fail to adequately capture the concept of surgical competence. The concepts of competency, proficiency, and mastery are distinct stages of learning, whereas the speed of learning for such skills as technical proficiency, clinical outcomes, oncological sufficiency, and intraoperative decision-making might be different. Conclusions: The learning curve in robotic HPB surgery should be viewed as a multi-dimensional and complex process and not a straightforward correlation between the number of cases and the results. The future assessment of the learning curve needs to consider different domains, including technical, clinical, oncological, cognitive, and team-related aspects, taking into account the level of complexity and institutional context of each case.