Introduction/Background Preoperative evaluation of adnexal masses in terms of malignant or benign is critical for a careful surgical planning; extent of surgery& need of expertise to provide a standard care in management to improve the overall prognosis. However the available diagnostic methods are still lacking the desired accuracy.

Methodology All women reporting at the Institute’s OPD with adnexal masses and subsequently operated. After informed consent, initial evaluation including serum Ca125, USG using standard IOTA terminologies &after applying ‘Simple Rules’ and IOTA ADNEX model, adnexal masses were labelled as benign or malignant, malignant were again staged based upon adnex percentages using online calculator. Histopathology was used as gold standard to calculate diagnostic performance, ROC curve was used to find best cutoff for diagnosis of malignancy and further compared with risk of malignancy index-1 score

Results Among the 65 cases the prevalence malignancies in adnexal masses was 16.92% with subtypes- mucinous cyst adenocarcinoma 6.1%, serous carcinoma 4.6%, clear cell adenocarcinoma 1.5% and malignant sex cord stromal tumor1.5%. the diagnostic performance is shown in the table attached .

ADNEX Model has a sensitivity 90.91%, specificity96.30% Positive predictive value 83.33% negative predictive98.11% accuracy95.38%

The area under the curve(AUC) for the overall difference between benign and malignant tumor is 0.978 (95% CI, 0.942–1.014). AUCs for differentiating different tumor subgroups ranged between 0.926–0.978. The ROC of IOTA ADNEX model shows an optimum cut-off of 16.8 with sensitivity -90.9% and specificity 98.1%.

Conclusion IOTA Simple rules and IOTA ADNEX model were found to have better diagnostic accuracy in comparison to older prediction model RMI-1. with an added advantage of determining the stage of ovarian tumor with high accuracy. Our study concludes that IOTA Simple rules and IOTA ADNEX model can be used as an effective and economical tools for triaging of patients with adnexal masses.

Disclosures None.