Presently the majority of women diagnosed with epithelial ovarian cancer (EOC) have advanced stage disease (III -IV) with a poor 5-year survival rate (12 -30 %). This signifi cantly contrasts when early stage disease is detected, which has a 5-year survival rate approximating 90 %. Therefore, detection of early stage disease is critical to making an impact on outcome. By using genetic algorithms, modifi cations of transvaginal ultrasonography and use of novel biomarkers, we propose a risk assessment profi le to identify at-risk women and enable ovarian cancer screening to become a reality. Such a novel algorithm starts by applying classic genetic pedigree assessment and uses a panel of multiple biomarkers that identify both phenotypic and genotypic expression of high-risk markers followed with conventional ultrasound and advanced ultrasound techniques such as microvascular contrast-enhancement as a secondary test. We presently employ a multidisciplinary program incorporating genetics, molecular biology, tumor immunology, gynecologic oncology and diagnostic imaging to identify asymptomatic high risk women.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.