Our objective is to determine if the combination of simple ultrasound features (IOTA simple rules) and a new biomarker (HE4) together with a common tumour marker (CA 125) can accurately predict ovarian cancer in women found to have a pelvic mass on ultrasound. The investigators hypothesize that the use of two biomarkers (HE4 and CA 125) in a mathematical algorithm (Risk of Malignancy Algorithm, ROMA) can be used to predict malignancy in a pelvic mass which has indeterminate ultrasound features. This is a prospective cohort study involving women undergoing operation for a pelvic mass. 720 women scheduled to have an operation to remove a pelvic mass would be recruited from 3 hospitals (QMH, UCH and PYNEH). Pre-operatively, each woman will have an ultrasound assessment using the IOTA simple rules criteria and have blood taken for tumour markers HE4 and CA 125. In women where IOTA ultrasound rules are inconclusive, 2 strategies for prediction will be compared - calculation of risk by ROMA (Strategy A) vs referral for an expert ultrasound (Strategy B). These pre-operative risk predictions will be correlated with the final pathology found at the operations. Main outcome measures include the sensitivity, specificity, positive and negative predictive powers for Strategy A compared to Strategy B. Sensitivity and specificity will be compared using the McNemar test. Area Under the ROC Curve (AUC) will be calculated and compared using the Delong method for the 2 strategies. The investigators expect AUC of both strategies will be similar. This would suggest that ROMA can replace expert ultrasound in the pre-operative prediction of ovarian cancer.
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sensitivity, specificity and predictive powers
Timeframe: 3 months after last subject enrolled