The Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, People's Republic of China.
College of Mechanical and Electrical Engineering, Central South University, Changsha, 410082, Hunan, People's Republic of China.
J Robot Surg. 2023 Apr;17(2):527-536. doi: 10.1007/s11701-022-01450-5. Epub 2022 Aug 1.
Although significant progress has been made with surgical methods, the incidence of complications after minimally invasive surgery in patients with cervical cancer remains high. Established as a standardized system, Clavien-Dindo classification (CDC) has been applied in a variety of surgical fields. This study is designed to evaluate the complications after robot-assisted radical hysterectomy (RRH) for cervical cancer using CDC and further establish a prediction model. This is a study on the development of prediction model based on retrospective data. Patients with cervical cancer who received RRH treatment in our hospital from January 2016 to April 2019 were invited to participate in the study. The demographic data, laboratory and imaging examination results and postoperative complications were collected, and the logistic regression model was applied to analyze the risk factors possibly related to complications to establish a prediction model. 753 patients received RRH. The overall incidence of complications was 32.7%, most of which were grade I and grade II (accounting for 30.6%). The results of multivariate analysis showed that the preoperative neoadjuvant chemotherapy (OR = 1.693, 95%CI: 1.210-2.370, P = 0.002), preoperative ALT (OR = 1.028, 95%CI: 1.017-1.039, P < 0.001), preoperative urea nitrogen (OR = 0.868, 95%CI: 0.773-0.974, P = 0.016), preoperative total bilirubin (OR = 0.958, 95%CI: 0.925-0.993, P = 0.0.018), and preoperative albumin (OR = 0.937, 95%CI: 0.898-0.979, P = 0.003) were related to the occurrence of postoperative complications. The area under the curve (AUC) of receiver-operating characteristic (ROC) in the prediction model of RRH postoperative complications established based on these five factors was 0.827 with 95% CI of 0.794-0.860. In patients undergoing robot-assisted radical hysterectomy for cervical cancer, preoperative ALT level, urea nitrogen level, total bilirubin level, albumin level, and neoadjuvant chemotherapy were significantly related to the occurrence of postoperative complications. The regression prediction model established on this basis showed good prediction performance with certain clinical promotion and reference value.
虽然微创手术在治疗宫颈癌方面取得了显著进展,但患者术后并发症的发生率仍然很高。Clavien-Dindo 分类(CDC)作为一种标准化系统,已被应用于各种外科领域。本研究旨在使用 CDC 评估宫颈癌机器人辅助根治性子宫切除术(RRH)后的并发症,并进一步建立预测模型。这是一项基于回顾性数据的预测模型开发研究。我们邀请了 2016 年 1 月至 2019 年 4 月在我院接受 RRH 治疗的宫颈癌患者参加本研究。收集患者的人口统计学数据、实验室和影像学检查结果以及术后并发症,并应用逻辑回归模型分析可能与并发症相关的风险因素,以建立预测模型。共纳入 753 例患者,术后并发症总发生率为 32.7%,其中以 1 级和 2 级为主(占 30.6%)。多因素分析结果显示,术前新辅助化疗(OR=1.693,95%CI:1.210-2.370,P=0.002)、术前 ALT(OR=1.028,95%CI:1.017-1.039,P<0.001)、术前尿素氮(OR=0.868,95%CI:0.773-0.974,P=0.016)、术前总胆红素(OR=0.958,95%CI:0.925-0.993,P=0.018)和术前白蛋白(OR=0.937,95%CI:0.898-0.979,P=0.003)与术后并发症的发生有关。基于这 5 个因素建立的 RRH 术后并发症预测模型的曲线下面积(AUC)为 0.827,95%CI 为 0.794-0.860。在接受宫颈癌机器人辅助根治性子宫切除术的患者中,术前 ALT 水平、尿素氮水平、总胆红素水平、白蛋白水平和新辅助化疗与术后并发症的发生显著相关。基于此建立的回归预测模型具有较好的预测性能,具有一定的临床推广和参考价值。