A comparison of Bayesian and frequentist approaches to incorporating external information for the prediction of prostate cancer risk.

ABSTRACT: We present the most comprehensive comparison to date of the predictive benefit of genetics in addition to currently used clinical variables, using genotype data for 33 single-nucleotide polymorphisms (SNPs) in 1,547 Caucasian men from the placebo arm of the REduction by DUtasteride of prostate Cancer Events (REDUCE®) trial. Moreover, we conducted a detailed comparison of three techniques for incorporating genetics into clinical risk prediction. The first method was a standard logistic regression model, which included separate terms for the clinical covariates and for each of the genetic markers. This approach ignores a substantial amount of external information concerning effect sizes for these Genome Wide Association Study (GWAS)-replicated SNPs. The second and third methods investigated

SUBMITTER: Newcombe PJ 

PROVIDER: S-EPMC3791431 | biostudies-literature | 2012 Jan

REPOSITORIES: biostudies-literature