Abstract
We try to find out the best weight values of CA125 and HE4 in a discriminant formula classifying ovarian cancer patients from benign patients. We utilize a logistic regression analysis for the early screening system of the ovarian cancer for Korean patients. We compare our system with ROMA (Risk of Ovarian Malignancy Algorithm) of Abbot corp. In view of AUC (Area under the ROC curve), sensitivity with 95% of specificity and accuracy are considered. We performed experiments based on the logistic regression analysis separated by the case of pre- and post- menopausal stages and by the stages of progression of cancer. In our experiments, we can increase about 15.6% points of sensitivity with 95% of specificity, compared to that of ROMA. In premenopausal cases, ROMA shows 93.32% of AUC value and our system shows 97.48% of AUC, 4.1% points higher than ROMA. AUC of the ROMA for premenopausal women was 93.32%, whereas the AUC of our system was 97.48%. Furthermore, the AUC of the ROMA for early-staged ovarian cancer was 91.35%, whereas the AUC of our system was 97.22%, showing that the diagnostic performance of our system was superior over that of the ROMA in Korean patient cases.