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Development of a predictive score for prolonged pelvic operation time in robot-assisted low anterior resection: a
Kenta Yao1,2, Shunsuke Kasai3,4, Akio Shiomi1
1Division of Colon and Rectal Surgery, Shizuoka Cancer Center, 1007, Shimonagakubo, Nagaizumi-Cho, Sunto-Gun, Shizuoka, 411-8777, Japan.
Background:
Robot-assisted surgery has been widely adopted for the treatment of rectal cancer. Preoperative identification of difficult cases is essential, particularly for surgical training and operating room management. This study aimed to identify preoperative risk factors and develop a predictive scoring system for prolonged pelvic operation time in robot-assisted low anterior resection.
Methods:
This retrospective, single-center study included patients who underwent robot-assisted low anterior resection for primary rectal cancer performed by experienced surgeons between 2019 and 2024. Preoperative clinicopathological features were evaluated using multivariate analysis to identify associations with longer pelvic operation time. A novel predictive scoring system for prolonged pelvic operation time was developed in a training cohort using the identified clinicopathological risk factors, and internally validated.
Results:
A total of 343 patients were analyzed, with a median pelvic operation time of 87 min. Multivariate analysis identified eight risk factors: male sex, high body mass index, tumor distance from the anal verge < 7 cm, clinical T4 stage, clinically positive lymph nodes, history of preoperative chemoradiotherapy, elevated C-reactive protein levels, and low serum albumin. The predictive scoring system, based on a logistic regression model incorporating the eight factors, demonstrated robust performance in the validation cohort, with an area under the curve of 0.88 and a negative predictive value of 0.95. Stratification into four risk categories effectively distinguished both pelvic and total operation times.
Conclusion:
Eight preoperative clinicopathological features were identified as independent risk factors for prolonged pelvic operation time in robot-assisted rectal cancer surgery. The developed predictive scoring system, which can be readily applied preoperatively, may aid in case selection for surgical training and enhance operating room management.
