Yao Kenta, Kasai Shunsuke, Shiomi Akio, Manabe Shoichi, Tanaka Yusuke, Kojima Tadahiro, Igaki Takahiro, Mori Yukihiro, Notsu Akifumi, Kinugasa Yusuke
Division of Colon and Rectal Surgery, Shizuoka Cancer Center, 1007, Shimonagakubo, Nagaizumi-Cho, Sunto-Gun, Shizuoka, 411-8777, Japan.
Department of Gastrointestinal Surgery, Institute of Science Tokyo, Tokyo, Japan.
Surg Endosc. 2025 Sep 8. doi: 10.1007/s00464-025-12122-4.
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.
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.
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.
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.
机器人辅助手术已广泛应用于直肠癌治疗。术前识别困难病例至关重要,特别是对于手术培训和手术室管理。本研究旨在识别术前风险因素,并开发一种预测评分系统,用于预测机器人辅助低位前切除术盆腔手术时间延长的情况。
这项回顾性单中心研究纳入了2019年至2024年间由经验丰富的外科医生进行机器人辅助低位前切除术治疗原发性直肠癌的患者。通过多变量分析评估术前临床病理特征,以确定与较长盆腔手术时间的关联。利用识别出的临床病理风险因素,在一个训练队列中开发了一种用于预测盆腔手术时间延长的新型预测评分系统,并进行了内部验证。
共分析了343例患者,盆腔手术时间中位数为87分钟。多变量分析确定了八个风险因素:男性、高体重指数、肿瘤距肛缘<7 cm、临床T4期、临床阳性淋巴结、术前放化疗史、C反应蛋白水平升高和血清白蛋白水平低。基于纳入这八个因素的逻辑回归模型的预测评分系统在验证队列中表现出强大的性能,曲线下面积为0.88,阴性预测值为0.95。分为四个风险类别有效地区分了盆腔手术时间和总手术时间。
八个术前临床病理特征被确定为机器人辅助直肠癌手术盆腔手术时间延长的独立风险因素。所开发的预测评分系统可在术前轻松应用,可能有助于手术培训的病例选择,并加强手术室管理。