A simple to use method incorporating genomic markers into prostate cancer risk prediction tools facilitated future validation.
OBJECTIVES To incorporate single nucleotide polymorphisms (SNPs) into the Prostate Cancer Prevention Trial Risk Calculator (PCPTRC) STUDY DESIGN AND SETTING A multivariate random effects meta analysis of likelihood ratios (LRs) for 30 validated SNPs was performed, allowing the incorporation of linkage disequilibrium. LRs for an SNP were defined as the ratio of the probability of observing the SNP in prostate cancer cases relative to controls and estimated by published allele or genotype frequencies. LRs were multiplied by the PCPTRC prior odds of prostate cancer to provide updated posterior odds. RESULTS In the meta analysis (prostate cancer cases/controls 386,538/985,968) all but two of the SNPs had at least one statistically significant allele LR (P 0.05) The two SNPs with the largest LRs were rs16901979 [LR 1.575 for one risk allele, 2.552 for two risk alleles (homozygous) and rs1447295 (LR 1.307 and 1.887, respectively) CONCLUSION The substantial investment in genome wide association studies to discover SNPs associated with prostate cancer risk and the ability to integrate these findings into the PCPTRC allows investigators to validate these observations, to determine the clinical impact, and to ultimately improve clinical practice in the early detection of the most common cancer in men.
Journal of clinical epidemiology