Abstract
OBJECTIVE: The aim of this study was to analyze the risk factors of urinary tract infection in ovarian cancer patients after cytoreductive surgery(CRS) and construct a nomogram model. METHODS: A retrospective study was conducted on 349 ovarian cancer patients (all undergoing CRS) admitted to Meizhou people's hospital from August 2021 to August 2024. The patients were randomly assigned into modeling group and validation group in a 7:3 ratio (According to the random number table method). The modeling group was assigned into infected group and non infected group based on whether the patient developed urinary tract infection after CRS. Logistic regression was used to analyze influencing factors, and R software (R version 3.6.3 software and the rms package) was used to construct nomogram models. P<0.05 indicates a statistically significant difference. RESULTS: A total of 86 out of 349 patients developed infections, with an incidence rate of 24.64%. Among 244 patients in the modeling group, 61 cases developed infections, with an incidence rate of 25.00%. Logistic regression analysis showed that age, diabetes, tumor staging, number of catheter insertions, catheter retention time and postoperative hypoproteinemia were the risk factors for urinary tract infection after CRS in ovarian cancer patients (P<0.05). The area under the curve(AUC) of the modeling group was 0.950, and the H-L test showed χ(2)=6.912, P=0.697. The AUC of the validation group was 0.970, and the H-L test showed χ(2)=6.756, P=0.642. Decision curve analysis (DCA) curve indicated that the clinical value was higher when the probability was between 0.08 and 0.90. CONCLUSION: The nomogram predicting the risk of postoperative UTI based on the identified risk factors demonstrated good discrimination and calibration. However, this model is still preliminary and requires external, multicenter validation before it can be applied in clinical practice.