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已发表论文
卵巢癌患者细胞减灭术后尿路感染危险因素分析及列线图模型构建
Authors He M, Li J, Huang L, Liang F
Received 18 June 2025
Accepted for publication 19 November 2025
Published 2 December 2025 Volume 2025:17 Pages 5035—5044
DOI https://doi.org/10.2147/IJWH.S548036
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Matteo Frigerio
Manzhu He,1 Jing Li,1 Lishan Huang,1 Fei Liang2
1Department of Gynecology, Meizhou People’s Hospital, Meizhou, 514011, People’s Republic of China; 2Department of Data Center, Meizhou People’s Hospital, Meizhou, 514011, People’s Republic of China
Correspondence: Fei Liang, Department of Data Center, Meizhou People’s Hospital, No. 63 Huangtang Road, Meijiang District, Meizhou, Guangdong, 514011, People’s Republic of China, Tel +8613823886198, Email lijugnify398@sina.com
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 χ2=6.912, P=0.697. The AUC of the validation group was 0.970, and the H-L test showed χ2=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.
Keywords: ovarian cancer, cytoreductive surgery, urinary tract infection, risk factors, nomogram
1Department of Gynecology, Meizhou People’s Hospital, Meizhou, 514011, People’s Republic of China; 2Department of Data Center, Meizhou People’s Hospital, Meizhou, 514011, People’s Republic of China
Correspondence: Fei Liang, Department of Data Center, Meizhou People’s Hospital, No. 63 Huangtang Road, Meijiang District, Meizhou, Guangdong, 514011, People’s Republic of China, Tel +8613823886198, Email lijugnify398@sina.com
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 χ2=6.912, P=0.697. The AUC of the validation group was 0.970, and the H-L test showed χ2=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.
Keywords: ovarian cancer, cytoreductive surgery, urinary tract infection, risk factors, nomogram