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Evaluation of the Diagnostic Accuracy of the Risk of Ovarian Malignancy Algorithm in Women With a Pelvic Mass

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Abstract

OBJECTIVE:

It is often difficult to distinguish a benign pelvic mass from a malignancy and tools to help referring physician are needed. The purpose of this study was to validate the Risk of Ovarian Malignancy Algorithm in women presenting with a pelvic mass.

METHODS:

This was a prospective, multicenter, blinded clinical trial that included women who presented to a gynecologist, a family practitioner, an internist, or a general surgeon with an adnexal mass. Serum HE4 and CA 125 were determined preoperatively. A Risk of Ovarian Malignancy Algorithm score was calculated and classified patients into high-risk and low-risk groups for having a malignancy. The sensitivity, specificity, negative predictive value, and positive predictive value of the Risk of Ovarian Malignancy Algorithm were estimated.

RESULTS:

A total of 472 patients were evaluated with 383 women diagnosed with benign disease and 89 women with a malignancy. The incidence of all cancers was 15% and 10% for ovarian cancer. In the postmenopausal group, a sensitivity of 92.3% and a specificity of 76.0% and for the premenopausal group the Risk of Ovarian Malignancy Algorithm had a sensitivity of 100% and specificity of 74.2% for detecting ovarian cancer. When considering all women together, the Risk of Ovarian Malignancy Algorithm had a sensitivity of 93.8%, a specificity of 74.9%, and a negative predictive value of 99.0%.

CONCLUSION:

The use of the serum biomarkers HE4 and CA 125 with the Risk of Ovarian Malignancy Algorithm has a high sensitivity for the prediction of ovarian cancer in women with a pelvic mass. These findings support the use of the Risk of Ovarian Malignancy Algorithm as a tool for the triage of women with an adnexal mass to gynecologic oncologists.

LEVEL OF EVIDENCE:

II

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