Project 3: Estimating Risk of Ovarian Cancer Ovarian cancer afflicts approximately 26,000 US women per year. More than 70% of these cases will be diagnosed in late stage and the 5-year survival rate for these women remains 20-30%. Though treatment strategies have evolved over time, prevention and early detection hold the greatest potential for reducing the morbidity and mortality of this dread disease. To succeed, research in prevention in prevention and screening requires that we be able to identify populations that are expected to experience large numbers of cases. The more accurately we can target these cases in advance, the more cost-efficient and productive these efforts. Risk-based eligibility has been used successfully in other randomized trials to target individuals most likely to benefit from the intervention. Risk-based screening also holds the potential to increase the positive predictive value of screening and reduce costs. We propose to develop and validate a statistical model for estimating ovarian cancer risk in post-menopausal women using demographic, reproductive, medical and family history data from the Women's Health Initiative using standard failure time models for risk assessment. We will extend this risk model to examine the potential for serum levels of CA-125 and other promising tumor markers to improve on our estimates of risk. These tumor markers will be evaluated in blood specimens collected from cases prior to their diagnosis and in blood cords collected from a sample of similar healthy women using a nested case-control design. The methods of Gail et al for estimating a woman's risk of breast cancer serves as the model for this effort. In addition, we will learn important information about the relationship between various personal characteristics and marker levels within ovarian and between levels of markers and disease characteristics. Validation and analyses will improve our estimates of risk and assist our understanding of the role that tumor markers play in tracking the development of disease.
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