Inherited genetic markers discovered to date are able to identify a significant number of men at considerably elevated risk for prostate cancer

Abstract

Background: Prostate cancer (PCa) risk-associated single-nucleotide polymorphisms (SNPs) are continuously being discovered. Their ability to identify men at high risk and the impact of increasing numbers of SNPs on predictive performance are not well understood.

Methods: Absolute risk for PCa was estimated in a population-based case-control study in Sweden (2,899 cases and 1,722 controls) using family history and three sets of sequentially discovered PCa risk-associated SNPs. Their performance in predicting PCa was assessed by positive predictive values (PPV) and sensitivity.

Results: SNPs and family history were able to differentiate individual risk for PCa and identify men at higher risk; ∼18% and ∼8% of men in the study had 20-year (55-74 years) absolute risks that were twofold (0.24) or threefold (0.36) greater than the population median risk (0.12), respectively. When predictive performances were compared at absolute risk cutoffs of 0.12, 0.24, or 0.36, PPV increased considerably (∼20%, ∼30%, and ∼37%, respectively) while sensitivity decreased considerably (∼55%, ∼20%, and ∼10%, respectively). In contrast, when increasing numbers of SNPs (5, 11, and 28 SNPs) were used in risk prediction, PPV approached a constant value while sensitivity increased steadily.

Conclusions: SNPs discovered to date are suitable for risk prediction while additional SNPs discovered in the future may identify more subjects at higher risk. Men identified as high risk by SNP-based testing may be targeted for PCa screening or chemoprevention. The clinical impact on improving the effectiveness of these interventions can be and should be assessed.

Figure 1

Distribution of estimated absolute risk using family history and three sets of PCa risk-associated SNPs in CAPS.

Figure 2

Predictive performance of absolute risk estimated from family history and three sets of PCa risk-associated SNPs in CAPS, measured by sensitivity (a) and PPV (b).

Figure 3

Predictive performance (sensitivity and PPV) of absolute risk estimated from genetic markers in CPAS, genetic markers were added to the risk prediction one at a time, from highest to lowest based on the genetic variance explained by the genetic marker. Note the PPV and sensitivity were presented starting from the first six genetic markers because results were unstable for the initial several genetic markers due to the small number of cases and controls who tested positive, especially at higher cutoff values of absolute risk.