Risk Prediction for Epithelial Ovarian Cancer in 11 United States-Based Case-Control Studies: Incorporation of Epidemiologic Risk Factors and 17 Confirmed Genetic Loci
© The Author 2016. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: firstname.lastname@example.org. Previously 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.
Clyde, MA; Palmieri Weber, R; Iversen, ES; Poole, EM; Doherty, JA; Goodman, MT; Ness, RB; Risch, HA; Rossing, MA; Terry, KL; Wentzensen, N; Whittemore, AS; Anton-Culver, H; Bandera, EV; Berchuck, A; Carney, ME; Cramer, DW; Cunningham, JM; Cushing-Haugen, KL; Edwards, RP; Fridley, BL; Goode, EL; Lurie, G; McGuire, V; Modugno, F; Moysich, KB; Olson, SH; Pearce, CL; Pike, MC; Rothstein, JH; Sellers, TA; Sieh, W; Stram, D; Thompson, PJ; Vierkant, RA; Wicklund, KG; Wu, AH; Ziogas, A; Tworoger, SS et al.
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