Performance of Pre-Operative IOTA Three-Step Algorithm in Detecting Ovarian Carcinoma in a Referral Center in Indonesia

Andi Kurniadi, Wiryawan Permadi, Aria Yusti Kusuma, Jessica Kireina, Mia Yasmina Andarini, Gatot Nyarumenteng Adhipurnawan Winarno, Ali Budi Harsono


Background: To assess the diagnostic performance of a three-step algorithm using the International Ovarian Tumor Analysis (IOTA) Group ‘simple rules’, ‘simple descriptors’, and Assessment of Different NEoplasias in the adneXa (ADNEX) model for discriminating benign and malignant adnexal masses.


Methods:  This was a retrospective observational study, performed at a tertiary-care university hospital, on women diagnosed with adnexal mass on ultrasonography from January 2021 and February 2022. The examiner first classified the mass using ‘simple descriptors’ (first step) and, if not possible, using ‘simple rules’ (second step). For inconclusive masses, an assessment using the ADNEX model was done as the third step. All masses were managed surgically. Histopathology results were used as the reference standard.

Results: One hundred and forty-one women were included (median age of 48 years). Histopathology results showed 104 (73.76%) mass to be malignant, and 37 (26.24%) mass to be benign. Twelve (8.51%) of 141 masses could be classified using simple descriptors, 89 (63.12%) masses were classified using simple rules, and 40 (28.37%) masses were classified using the ADNEX model. Overall accuracy, sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, and negative likelihood ratio of the three-step algorithm were 89.36%, 94.23%, 75.68%, 91.59%, 82.35%, 3.87, and 0.08 respectively.

Conclusions: The IOTA three-step algorithm, based on the sequential use of simple descriptors, simple rules, and ADNEX model, performs well for classifying adnexal masses as benign or malignant


adnexal mass, ADNEX model, diagnosis, simple descriptors, simple rules

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DOI: 10.33371/ijoc.v18i1.1044

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