Comparing the Copenhagen Index (CPH-I) and Risk of Ovarian Malignancy Algorithm (ROMA): Two equivalent ways to differentiate malignant from benign ovarian tumors before surgery?
التفاصيل البيبلوغرافية
العنوان:
Comparing the Copenhagen Index (CPH-I) and Risk of Ovarian Malignancy Algorithm (ROMA): Two equivalent ways to differentiate malignant from benign ovarian tumors before surgery?
Aim To evaluate the prediction of malignancy in women with pelvic masses using the Copenhagen Index (CPH-I) and Risk of Ovarian Malignancy Algorithm (ROMA). Patients and methods Three hundred eighty four women operated due to an ovarian mass were enrolled between January 2010 and June 2015. All patients had histopathological diagnosis, HE4 and CA125 measurement. CPH-I and ROMA were calculated and their performances compared in two distinct scenarios: 1) for the discrimination of benign ovarian disease from epithelial ovarian cancer (EOC), non-epithelial ovarian cancer, borderline ovarian tumors (BOT) and ovarian metastases, and 2) for the discrimination of benign disease from EOC. Receiver Operator Characteristics' Areas Under the Curves (AUC) were calculated for CPH-I and ROMA and compared. Results Of the 384 women, 224 presented a benign ovarian tumor, 32 BOT, 87 EOC, 26 non-epithelial ovarian cancer, and 15 had ovarian metastases. The best AUCs were obtained for the discrimination of EOC from benign tumors. CPH-I performed slightly better than ROMA, and both approached 89% sensitivity and 85% specificity. When all malignant tumors (EOC, BOT, ovarian metastases and non-epithelial ovarian cancer — entire cohort) were included, the performance of CPH-I and ROMA declined to nearly 72%, although the specificity remained close to 85%. Conclusion CPH-I and ROMA performed similarly well for the discrimination of EOC from benign ovarian tumors. However, caution is necessary since, in practical situations, where all the histological possibilities for malignant ovarian tumors must be considered, the sensitivity of CPH-I and ROMA may not surpass 70%.
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