Ashley R Wilson-Smith, Naomi Anning, Benjamin Muston, Aditya Eranki, Michael L Williams, Christian J Wilson-Smith, Diego G Rivas, Tristan D Yan
Background: Early studies have illustrated the robotic lobectomy to be safe, oncologically effective, and economically feasible as a therapeutic modality in the treatment of thoracic malignancies. The 'challenging' learning curve seemingly associated with the robotic approach, however, continues to be an often-cited factor to its ongoing uptake, with the overwhelming volume of these surgeries being performed in centers of excellence where extensive experience with minimal access surgery is the norm. An exact quantification of this learning curve challenge, however, has not been made, begging the question of whether this is an outdated assumption, versus fact. This systematic review and meta-analysis sort to clarify the learning curve for robotic-assisted lobectomy based on the existing literature.
Methods: An electronic search of four databases was performed to identify relevant studies outlining the learning curve of robotic lobectomy. The primary endpoint was a clear definition of operator learning (e.g., cumulative sum chart, linear regression, outcome-specific analysis, etc.) which could be subsequently aggregated or reported. Secondary endpoints of interest included post-operative outcomes and complication rates. A meta-analysis using a random effects model of proportions or means was applied, as appropriate.
Results: The search strategy identified twenty-two studies relevant for inclusion. A total of 3,246 patients (30% male) receiving robotic-assisted thoracic surgery (RATS) were identified. The mean age of the cohort was 65.3±5.0 years. Mean operative, console and dock time was 190.5±53.8, 125.8±33.9 and 10.2±4.0 minutes, respectively. Length of hospital stay was 6.1±4.6 days. Technical proficiency with the robotic-assisted lobectomy was achieved at a mean of 25.3±12.6 cases.
Conclusions: The robotic-assisted lobectomy has been illustrated to have a reasonable learning curve profile based on the existing literature. Current evidence on the oncologic efficacy and purported benefits of the robotic approach will be bolstered by the results of upcoming randomized trials, which will be critical in supporting RATS uptake.
