Learning Curves and Complexity Evolution in Robotic Liver Surgery
Year: 2026
Type: article
Study design: Observational Study
Abstract: OBJECTIVE: To evaluate the institutional learning curve of robotic liver resection (RLR), its association with surgical complexity and outcomes in an international multicenter cohort. SUMMARY OF BACKGROUND DATA: RLR is increasingly adopted worldwide, but the dynamics of the learning process and its impact on surgical outcomes remain poorly defined. METHODS: This international, multicenter, retrospective cohort study included consecutive patients who underwent RLR between 06/2013 and 12/2024 across 22 expert centers. Based on the first 150 cases at each center, three phases were used to define the learning curve: operative time for competency, major complications for proficiency, and textbook outcome for mastery. Risk-adjusted generalized additive models were used to assess the learning process. Benchmark performance was compared to international reference values. RESULTS: Among 2,331 patients, the most common indications were hepatocellular carcinoma (36%), benign lesions (23%) and colorectal liver metastases (21%). Operative time decreased after achieving competency (case #62), from 240 to 220 minutes (P<0.001). Major morbidity reached a plateau during the proficiency phase (cases #63-138; 9% vs. 11%, P=0.144), while progression to mastery (cases #139-150) was associated with a higher rate of textbook outcome (76% vs. 87%, P=0.021). In contrast, conversion (5.1% vs. 4.9% vs. 2%), bile leak (4.0% vs. 5.3% vs. 3.8%), and 90-day mortality (0.7% vs. 0.9% vs. 0.9%) remained low and stable across all learning phases. Importantly, benchmark criteria for operative time, hospital stay, and textbook outcome were met across all complexity groups, including during the early learning phase. CONCLUSIONS: Robotic liver surgery shows progressive outcome improvement with early achievement of benchmark-level results and stable performance across increasing complexity. These findings indicate that, in experienced centers, RLR can be safely implemented and integrated into clinical practice, supporting its key role in modern hepatobiliary surgery.
Source: Annals of Surgery
Authors: Christoph Kuemmerli, Gabriel F. Hess, Adrian T. Billeter, Cristiano Guidetti, Fabrizio di Benedetto, Roberta Odorizzi, Iswanto Sucandy, Noa L.E. Aegerter, Caroline Berchtold, Lorenzo Bernardi, Alessandra Cristaudi, Emanuele Balzano, Davide Ghinolfi, Ye-Xin Koh, Brian Goh, Charles Chung-Wei Lin, Daisuke Fukumori, Christoph Tschuor, Sanjay Pandanaboyana, Steve White, Philipp von Kroge, Asmus Heumann, Celine De Meyere, Mathieu D’Hondt, Fabian Haak, Daniel Seehofer, Stefan Stättner, Florian Primavesi, Haluk Morgül, Andreas Andreou, Francesca Ratti, Ignacio Sánchez Esquer, Ricardo Robles-Campos, Victor Lopez-Lopez, Taiga Wakabayashi, Go Wakabayashi, Martina Nebbia, Stefan Gilg, Emrullah Birgin, Nuh N. Rahbari, Stefano Ferretti, Giuseppe Maria Ettore, Mirhasan Rahimli, Roland Croner, Yawen Dong, Patrick P. Starlinger, Felix Nickel, Beat P. Müller, Philip C. Müller
Institutions: University Hospital of Basel, University of Modena and Reggio Emilia, AdventHealth Tampa, AdventHealth, Ospedale regionale di Lugano, Ente Ospedaliero Cantonale, University of Pisa, Azienda Ospedaliera Universitaria Pisana, Singapore General Hospital, Chang Bing Show Chwan Memorial Hospital, Copenhagen University Hospital, Rigshospitalet, Freeman Hospital, University Medical Center Hamburg-Eppendorf, AZ Groeninge, University Hospital Leipzig, Kepler Universitätsklinikum, Salzburger Landeskliniken, Innsbruck Medical University, Universität Innsbruck, University Hospital Münster, IRCCS Ospedale San Raffaele, Instituto Murciano de Investigación Biosanitaria, Hospital Universitario Virgen de la Arrixaca, Ageo Central General Hospital, Karolinska University Hospital, Karolinska Institutet, Universität Ulm, University Hospital Ulm, Azienda Ospedaliera San Camillo-Forlanini, University Hospital Magdeburg, Mayo Clinic
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W7165058113