ROMA, an algorithm for ovarian cancer.

Abstract

Improvement of survival in ovarian cancer may be achieved through early diagnosis and modification of treatment. Although abnormalities in the adnexal region are frequently observed in transvaginal ultrasound, interpretation may be equivocal in some cases. If neoplastic tumor is suspected, a wide range of tests and algorithms may be applied. Risk of Malignancy Algorithm (ROMA), as first described by Moore in 2009, is one of the most popular approaches. The clinical utility of this regression model has been demonstrated in both pre- (75.6% sensitivity and 74.8% specificity) and post-menopausal (92.3% sensitivity and 74.7% specificity) women. These findings have been independently confirmed in a number of publications. The sensitivity and specificity of ROMA may, however, be improved with inclusion of supplemental data, such as age and ultrasound findings. Because of its simplicity, ROMA is a reliable tool characterized by high accuracy and reproducibility to stratify patients into a high or a low ovarian cancer risk.