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KMID : 1143220210640030293
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Obstetrics & Gynecology Science
2021 Volume.64 No. 3 p.293 ~ p.299
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Assessment of different NEoplasias in the adneXa model for differentiation of benign and malignant adnexal masses in Korean women
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Nam Gina
Lee Sa-Ra
Jeong Kyung-Ah
Kim Sung-Hoon
Moon Hye-Sung
Chae Hee-Dong
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Abstract
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Objective: Ultrasonographic differential diagnosis of ovarian tumors is important for appropriate management. We conducted study to compare the performance of the Assessment of Different NEoplasias in the adneXa (ADNEX) model with a subjective assessment (SA) in differentiating between benign and malignant adnexal masses in Korean women.
Methods: A total of 353 patients who underwent adnexal surgery with abnormal pelvic ultrasonographic findings from August 2016 to August 2017 were included in study. The presumptive diagnosis of adnexal malignancy was determined by both SA and the ADNEX model to be >10% calculated risk of malignancy. The area under the curve (AUC) comparison between the SA and ADNEX models was performed using DeLong’s method.
Results: 340 patients with benign tumors and 13 with malignant adnexal tumors among 292 (82.72%) premenopausal and 61 (17.28%) postmenopausal women were included. The AUCs of SA and the ADNEX model for discrimination between benign and malignant tumors were 0.79 and 0.92, respectively (P=0.10). The sensitivity and specificity of SA and the ADNEX model were 83.5% and 97.0%, and 90.0% and 82.0%, respectively. Comparison of the ADNEX model regarding menopausal status revealed that the predictability was not different. The AUCs of SA and the ADNEX model in premenopausal women were 0.74 and 0.89, respectively (P=0.12). The AUCs of SA and the ADNEX model in postmenopausal women were 0.86 and 0.94, respectively (P=0.60).
Conclusion: The ADNEX model offers excellent discrimination between benign and malignant ovarian tumors with similar sensitivity and specificity to SA in both premenopausal and postmenopausal Korean women.
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KEYWORD
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Ovarian neoplasms, Fertility preservation, Prediction model, Ultrasonography
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