Background: Prior studies suggest that combining the Symptom Index (SI) with a serum HE4 test or a CA125 test may improve prediction of ovarian cancer. However, these three tests have not been evaluated in combination.
Methods: A prospective case-control study design including 74 women with ovarian cancer and 137 healthy women was used with logistic regression analysis to evaluate the independent contributions of HE4 and CA125, and the SI to predict ovarian cancer status in a multivariate model. The diagnostic performance of various decision rules for combinations of these tests was assessed to evaluate potential use in predicting ovarian cancer.
Results: The SI, HE4, and CA125 all made significant independent contributions to ovarian cancer prediction. A decision rule based on any one of the three tests being positive had a sensitivity of 95% with specificity of 80%. A rule based on any two of the three tests being positive had a sensitivity of 84% with a specificity of 98.5%. The SI alone had sensitivity of 64% with specificity of 88%. If the SI index is used to select women for CA125 and HE4 testing, specificity is 98.5% and sensitivity is 58% using the 2-of-3-positive decision rule.
Conclusions: A 2-of-3-positive decision rule yields acceptable specificity, and higher sensitivity when all 3 tests are performed than when the SI is used to select women for screening by CA125 and HE4. If positive predictive value is a high priority, testing by CA125 and HE4 prior to imaging may be warranted for women with ovarian cancer symptoms.