Approaches to the detection of ovarian cancer.

Background: Ovarian cancer (OC) represents the eighth most common cancer among women and the second most frequently diagnosed gynecological malignancy in the United States and Europe. Correct and fast referral of patients with OC is mandatory to ensure optimal treatment and to improve the prognosis of patients with OC. Approaches to detect OC may be based on a gynecological examination, an elevated serum CA125 level, a Risk of Malignancy Index (RMI) higher than 200, an elevated serum HE4 level, or other modalities such as Risk of Ovarian Malignancy Algorithm (ROMA), Risk of Ovarian Cancer Algorithm (ROCA), or Copenhagen Index (CPH-I). Aim: To describe biomarkers that potentially improve the detection/risk estimation of OC. Results: The ability to differentiate OC from benign and borderline ovarian tumors was analyzed using Receiver Operating Characteristics (ROC) curves resulting in Area Under the Curve (AUC) of 0.920 for CA125, 0.933 for HE4 and 0.946 for ROMA. The ROC curves of OC versus benign ovarian tumors shows that the CPH-I (AUC = 0.959) is equivalent with RMI (AUC = 0.958). Conclusion: Both ROMA and CPH-I could potentially shorten the time spent before OC patients reach a tertiary center thereby improve risk estimation/diagnosis. Biomarker research still has to be performed in relevant clinical settings before any overall decisions can be made with respect to screening. [ABSTRACT FROM AUTHOR]