Clinical value of risk of ovarian malignancy algorithm in risk stratification of ovarian cancer

Abstract

The serum specimens were collected from ovarian cancer (n=100), benign ovarian disease (n=69) and healthy women (n=95). The serum levels of HE4 and CA125 were detected. Risk of ovarian maliqnancy algorithm (ROMA) was calculated. Accuracy of prediction was evaluated by the area under receiver operating characteristic curve (ROC-AUC). And validity of prediction was evaluated by sensitivity and specificity. The results showed that the median level of ROMA algorithm was 83.0%, 8.9% and 8.7% in ovarian cancer, benign ovarian disease and healthy women groups respectively. The difference were statistically significant (all P<0.01). Compared with benign ovarian disease group, the ROC-AUC of ROMA algorithm was 0.900 in ovarian cancer group. The sensitivity and specificity were 81.0% and 92.8% in ovarian cancer group respectively. Thus ROMA algorithm is a useful parameter in risk stratification for ovarian cancer. The diagnostic accuracy of ROMA algorithm is better than that of HE4 and CA125 in ovarian cancer. Key words: Ovarian neoplasms; Epididymal secretory proteins