Objective To explore the risk factors of ovarian epithelial carcinoma, and to construct a nomogram based on clinical and ultrasonic characteristics to improve the preoperative evaluation value of ovarian tumors. Methods A retrospective analysis was performed on 482 patients with ovarian tumor who were treated in the Gynecology Department of Yuncheng Central Hospital Affiliated to Shanxi Medical University from January 2022 to September 2024, and they were divided into benign tumor group (n=350) and ovarian epithelial carcinoma group (n=132) according to pathological diagnosis. Patients were randomly divided into a training set (n=289) and a validation set (n=193) at a ratio of 6∶4. General clinical data and ultrasonic characteristic parameters of patients were collected. The risk factors of ovarian epithelial carcinoma were analyzed by univariate and multifactorial regression. R software was used to construct a nomogram to predict the occurrence of ovarian epithelial carcinoma, which was internally verified by validation sets. The results of model efficacy evaluation were characterized by ROC curve, calibration curve and DCA curve. Results There were statistically significant differences between the benign tumor group and the ovarian epithelial carcinoma group in age, menopause, pregnancy frequency, hypertension, diabetes, serum biochemical indexes, multilocular tumor, solid component, lesion location, maximum mass diameter and endometrial thickness (P<0.05). Multivariate Logistic regression analysis showed that age, maximum mass diameter, lesion location, presence or absence of solid components and serum marker CA153 were independent risk factors for ovarian epithelial carcinoma. The AUC of the nomogram model constructed based on the above indexes in the training set was 0.89(95%CI: 0.85-0.93), and the ACU in the validation set was 0.83(95%CI: 0.76-0.89), the calibration curve fits the ideal curve well, and the threshold probability corresponding to the net benefit interval of the DCA model is 0.05-0.95. Conclusion The nomogram model of ovarian epithelial carcinoma based on clinical and ultrasonic features has high predictive performance and good clinical application value, and can provide reference for preoperative identification of ovarian epithelial carcinoma.
Key words
tumor ovarii /
ovarian epithelial carcinoma /
nomogram /
prediction model
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