Prediction model of adnexal masses with complex ultrasound morphology

• Published in: Frontiers in medicine 2023, Vol.10, p.1284495-1284495
• Main Authors: Wu, Yuqing, Miao, Kuo, Wang, Tianqi, Xu, Changyu, Yao, Jinlai, Dong, Xiaoqiu
• Format: Article
• Language: English
• Subjects: adnexal masses; nomogram; O-RADS; prediction model; ultrasound
• ISSN: 2296-858X; 2296-858X
• DOI: 10.3389/fmed.2023.1284495

Based on the ovarian-adnexal reporting and data system (O-RADS), we constructed a nomogram model to predict the malignancy potential of adnexal masses with sophisticated ultrasound morphology. In a multicenter retrospective study, a total of 430 subjects with masses were collected in the adnexal region through an electronic medical record system at the Fourth Hospital of Harbin Medical University during the period of January 2019-April 2023. A total of 157 subjects were included in the exception validation cohort from Harbin Medical University Tumor Hospital. The pathological tumor findings were invoked as the gold standard to classify the subjects into benign and malignant groups. All patients were randomly allocated to the validation set and training set in a ratio of 7:3. A stepwise regression analysis was utilized for filtering variables. Logistic regression was conducted to construct a nomogram prediction model, which was further validated in the training set. The forest plot, C-index, calibration curve, and clinical decision curve were utilized to verify the model and assess its accuracy and validity, which were further compared with existing adnexal lesion models (O-RADS US) and assessments of different types of neoplasia in the adnexa (ADNEX). Four predictors as independent risk factors for malignancy were followed in the preparation of the diagnostic model: O-RADS classification, HE4 level, acoustic shadow, and protrusion blood flow score (all