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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.

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Figure 1: Age-specific risk of developing prostate cancer and type 2 diabetes in subsequent 5-year intervals.

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Acknowledgements

This work was supported in part by National Institutes of Health grants CA098233 and DK58845.

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Correspondence to Peter Kraft.

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Multi-locus risk models and the risk of overfitting (PDF 229 kb)

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A Catalogue of Published Genome-wide Association Studies

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Kraft, P., Wacholder, S., Cornelis, M. et al. Beyond odds ratios — communicating disease risk based on genetic profiles. Nat Rev Genet 10, 264–269 (2009). https://doi.org/10.1038/nrg2516

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