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.

Author affiliations

1. Peter Kraft and David J. Hunter are at the Program in Molecular and Genetic Epidemiology, Harvard School of Public Health, Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts 02115, USA.
2. Sholom Wacholder, Richard B Hayes, Gilles Thomas, Robert Hoover, David J. Hunter and Stephen Chanock are at the Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland 20892, USA.
3. Marilyn C. Cornelis, Frank B. Hu and David J. Hunter are at the Department of Nutrition, Harvard School of Public Health, Harvard School of Public Health, Boston, Massachusetts 02115, USA.
4. David J. Hunter is at the Channing laboratory, Brigham and Women's Hospital and Harvard Medical School, Boston Massachusetts 02115, USA.

Correspondence to: Peter Kraft¹ Email: pkraft@hsph.harvard.edu

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