Nutritional and Inflammatory Indicators Aid in Differentiating Benign from Malignant Ovarian Neoplasms: Development and Validation of a Nomogram

被引:0
作者
Song, Zixuan [1 ]
Wang, Xiaoxue [2 ]
Wang, Yuting [1 ]
Chen, Xueting [2 ]
Zhang, Dandan [1 ]
机构
[1] China Med Univ, Shengjing Hosp, Dept Obstet & Gynecol, Shenyang 110004, Liaoning, Peoples R China
[2] China Med Univ, Shengjing Hosp, Dept Hlth Management, Shenyang 110004, Liaoning, Peoples R China
关键词
ovarian neoplasms; epithelial ovarian cancer; Naples Prognostic Score; nomogram; prediction model; NAPLES PROGNOSTIC SCORE; SYSTEMIC INFLAMMATION; SERUM HE-4; CANCER; SURVIVAL; LYMPHOCYTES; MACROPHAGES; PREDICTOR; SURGERY; CA125;
D O I
10.31083/j.ceog5106148
中图分类号
R71 [妇产科学];
学科分类号
100211 ;
摘要
Background: This study aims to evaluate the effectiveness of the Naples Prognostic Score (NPS), Systemic Inflammation Score (SIS), and Controlling Nutritional Status Score (COUNT) in distinguishing benign from malignant ovarian neoplasms. Additionally, a nomogram is developed utilizing these nutritional and inflammatory indicators to enhance preoperative assessment of ovarian neoplasms. Methods: Patients with ovarian neoplasms who underwent surgery at Shengjing Hospital of China Medical University between June 2017 and June 2022 were retrospectively analyzed. Benign ovarian disease or epithelial ovarian cancer (EOC) was diagnosed postoperatively by pathology. Patients were randomly divided into training and test cohorts. Univariate and multivariate logistic regression analyses were conducted to identify significant clinical and imaging risk factors, along with NPS, SIS, and COUNT. Nomograms were constructed to predict EOC and externally validated. Diagnostic accuracy was assessed using decision curve analysis (DCA) and the area under the receiver operating characteristic (ROC) curve (AUC). Results: A total of 2226 patients (1788 benign and 438 EOC) were included. Factors such as age, multilocular tumors, solid nodules, larger tumor diameter, ascites, and higher tumor marker levels were associated with an increased risk of EOC. The AUC values for models incorporating NPS, SIS, and COUNT were 0.907, 0.897, and 0.883, respectively, indicating superior diagnostic ability compared to models without nutritional/inflammatory indicators. The nomogram with NPS demonstrated the highest diagnostic value and clinical utility based on DCA (p < 0.001). External validation confirmed good agreement between the predicted and observed values. Conclusions: The model including NPS exhibited superior diagnostic value for preoperative diagnosis of EOC compared to models with SIS or COUNT. The nomogram combining NPS with clinical and imaging indicators displayed the highest diagnostic value and efficacy.
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页数:13
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