Clavien-Dindo classification and risk prediction model of complications after robot-assisted radical hysterectomy for cervical cancer.

Abstract

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.