Evaluation of the Performance of the IOTA ADNEX Model in Discriminating Adnexal Masses Preoperatively: An Ambispective Study.

Abstract

Objective: To evaluate the performance of the International Ovarian Tumour Analysis (IOTA) ADNEX model in discriminating adnexal masses preoperatively.

Methods: This ambispective observational study included 112 women with at least one adnexal mass, from January 2016 to April 2023. Cases underwent pelvic ultrasound and CA125 level assessments prior to surgery. The masses were classified into various subcategories by the IOTA ADNEX model and compared with postoperative histopathological reports. Sensitivity, specificity, negative predictive value, positive predictive value, and diagnostic accuracy were calculated for classifying tumours into various histological subtypes.

Results: Among the 112 women, 66 (58.9%) had benign ovarian tumours, 10 (8.9%) had borderline ovarian tumours, 17 (15.2%) had stage I ovarian cancer (OC), 15 (13.4%) had stage II-IV OC, and 4 (3.6%) had ovarian metastasis. The area under the ROC curve (AUC) was 0.852 (0.772-0.912) for distinguishing between benign and malignant tumours using the IOTA ADNEX model at a 50% cut-off, with a sensitivity of 84.78%, specificity of 84.85%, positive predictive value of 79.6%, and negative predictive value of 88.9%.

Conclusion: The IOTA ADNEX model is effective in classifying adnexal masses into benign and malignant categories, making it a valuable tool for triaging adnexal masses for further management.