Abstract
BACKGROUND: Pelvic floor dysfunction is a common complication after cervical cancer surgery, and the key to early prevention and treatment is the timely identification of risk factors and high-risk patients. The present study explored the risk factors of pelvic floor dysfunction in cervical cancer patients after surgery and established a predictive model. METHODS: A total of 282 cervical cancer patients admitted to Wuhan No.7 Hospital from January 2020 to June 2022 was retrospectively enrolled in this study. All patients underwent surgery and were followed up after surgery. The patients were divided into a pelvic floor dysfunction group (n=92) and a control group (n=190) according to whether they developed pelvic floor dysfunction or not at 6 months post-surgery. The differences in clinical features between the two groups were observed to identify the risk factors of pelvic floor dysfunction after cervical cancer, and a prediction model was established. RESULTS: There were significant differences in age, surgical method, surgical resection range, and radiotherapy between the two groups (P<0.05). Age greater than 65 years, open surgery, total hysterectomy, and radiotherapy were identified as the risk factors of postoperative pelvic floor dysfunction in patients with cervical cancer (P<0.05). The R4.0.3 statistical software was used to randomly divide the dataset into a training dataset (n=141) and a validation dataset (n=141). The area under the curve was 0.755 (95% confidence interval: 0.673-0.837) in the training set and 0.604 (95% confidence interval: 0.502-0.705) in the verification set. In the validation set, the model was tested with a Hosmer-Lemeshow Goodness-of-Fit test, with a chi-square value of 9.017 and a P value of 0.341. CONCLUSIONS: Patients with cervical cancer have a high incidence of postoperative pelvic floor dysfunction. Age greater than 65 years, open surgery, total hysterectomy, and radiotherapy are risk factors of postoperative pelvic floor dysfunction in cervical cancer patients, and the present model helps to identify patients at high-risk of pelvic floor dysfunction.