title: Beyond odds ratios--communicating disease risk based on genetic profiles.
abstract: The brisk discovery of novel inherited disease markers by genome-wide association (GWA) studies has raised expectations for predicting disease risk by analysing multiple common alleles. However, the statistics used during the discovery phase of research (such as odds ratios or p values for association) are not the most appropriate measures for evaluating the predictive value of genetic profiles. We argue that other measures--such as sensitivity, specificity, and positive and negative predictive values--are more useful when proposing a genetic profile for risk prediction.
authors.affiliation: Harvard School of Public Health, Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts 02115, USA. pkraft@hsph.harvard.edu
authors.forename: Peter
authors.initials: P
authors.lastname: Kraft
authors.forename: Sholom
authors.initials: S
authors.lastname: Wacholder
authors.forename: Marilyn C
authors.initials: MC
authors.lastname: Cornelis
authors.forename: Frank B
authors.initials: FB
authors.lastname: Hu
authors.forename: Richard B
authors.initials: RB
authors.lastname: Hayes
authors.forename: Gilles
authors.initials: G
authors.lastname: Thomas
authors.forename: Robert
authors.initials: R
authors.lastname: Hoover
authors.forename: David J
authors.initials: DJ
authors.lastname: Hunter
authors.forename: Stephen
authors.initials: S
authors.lastname: Chanock
mesh_terms: D004198:Disease Susceptibility; D020022:Genetic Predisposition to Disease / Q000453:epidemiology / Q000235:genetics*; D015894:Genome, Human; D055106:Genome-Wide Association Study / Q000706:statistics & numerical data; D006801:Humans; D016017:Odds Ratio; D011237:Predictive Value of Tests; D012680:Sensitivity and Specificity