Browsing by Author "Risch, Harvey A"
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Item Open Access Risk Prediction for Epithelial Ovarian Cancer in 11 United States-Based Case-Control Studies: Incorporation of Epidemiologic Risk Factors and 17 Confirmed Genetic Loci.(Am J Epidemiol, 2016-10-15) Clyde, Merlise A; Palmieri Weber, Rachel; Iversen, Edwin S; Poole, Elizabeth M; Doherty, Jennifer A; Goodman, Marc T; Ness, Roberta B; Risch, Harvey A; Rossing, Mary Anne; Terry, Kathryn L; Wentzensen, Nicolas; Whittemore, Alice S; Anton-Culver, Hoda; Bandera, Elisa V; Berchuck, Andrew; Carney, Michael E; Cramer, Daniel W; Cunningham, Julie M; Cushing-Haugen, Kara L; Edwards, Robert P; Fridley, Brooke L; Goode, Ellen L; Lurie, Galina; McGuire, Valerie; Modugno, Francesmary; Moysich, Kirsten B; Olson, Sara H; Pearce, Celeste Leigh; Pike, Malcolm C; Rothstein, Joseph H; Sellers, Thomas A; Sieh, Weiva; Stram, Daniel; Thompson, Pamela J; Vierkant, Robert A; Wicklund, Kristine G; Wu, Anna H; Ziogas, Argyrios; Tworoger, Shelley S; Schildkraut, Joellen MPreviously developed models for predicting absolute risk of invasive epithelial ovarian cancer have included a limited number of risk factors and have had low discriminatory power (area under the receiver operating characteristic curve (AUC) < 0.60). Because of this, we developed and internally validated a relative risk prediction model that incorporates 17 established epidemiologic risk factors and 17 genome-wide significant single nucleotide polymorphisms (SNPs) using data from 11 case-control studies in the United States (5,793 cases; 9,512 controls) from the Ovarian Cancer Association Consortium (data accrued from 1992 to 2010). We developed a hierarchical logistic regression model for predicting case-control status that included imputation of missing data. We randomly divided the data into an 80% training sample and used the remaining 20% for model evaluation. The AUC for the full model was 0.664. A reduced model without SNPs performed similarly (AUC = 0.649). Both models performed better than a baseline model that included age and study site only (AUC = 0.563). The best predictive power was obtained in the full model among women younger than 50 years of age (AUC = 0.714); however, the addition of SNPs increased the AUC the most for women older than 50 years of age (AUC = 0.638 vs. 0.616). Adapting this improved model to estimate absolute risk and evaluating it in prospective data sets is warranted.