ArticleSurgical endoscopy2026
Learning curve for Da Vinci Single-Port robotic colorectal cancer surgery: impact of prior robotic experience.
Article in Surgical endoscopy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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5 authors.
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Abstract
backgroundThe Da Vinci Single-Port (SP) robotic system has been introduced as a novel platform for minimally invasive colorectal cancer surgery; however, data regarding the learning curve for its use and the influence of prior robotic experience remain limited.
methodsThis single-center retrospective study analyzed 203 patients who underwent colorectal cancer surgery using the SP platform between January 2024 and December 2025. Two surgeons with differing levels of prior experience with the Da Vinci Xi system performed all procedures. Short-term outcomes were evaluated, and learning curves were assessed using risk-adjusted cumulative sum (RA-CUSUM) analysis based on operative time. Multivariable linear regression was conducted to identify factors associated with operative time.
resultsSP robotic colorectal surgery demonstrated favorable short-term outcomes, with an acceptable operative time (164.9 ± 65.1 min) and a high rate (99.5%) of lymph node retrieval ≥ 12. RA-CUSUM analysis revealed distinct learning curve patterns between the two surgeons; however, both achieved early stabilization on the SP platform (at the 27th and 23rd cases for surgeon 1 and surgeon 2, respectively). In the multivariable analysis, operative time was independently associated with cumulative case sequence and variables related to surgical complexity, whereas surgeon identity, which was used as a surrogate for prior Xi system experience, was not a significant predictor (p = 0.343). Despite minimal prior Xi experience, surgeon 2 demonstrated rapid stabilization of operative performance.
conclusionsSP robotic colorectal cancer surgery is feasible and associated with favorable short-term outcomes. Operative performance is influenced more by cumulative experience and procedural complexity than by prior exposure to other robotic platforms.
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