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. 2009 Mar 1;69(4):363-72.
doi: 10.1002/pros.20887.

Clinical utility of five genetic variants for predicting prostate cancer risk and mortality

Claudia A Salinas  1 , Joseph S Koopmeiners, Erika M Kwon, Liesel FitzGerald, Daniel W Lin, Elaine A Ostrander, Ziding Feng, Janet L Stanford
Affiliations

Clinical utility of five genetic variants for predicting prostate cancer risk and mortality

Claudia A Salinas et al. Prostate. .

Abstract

Background: A recent report suggests that the combination of five single-nucleotide polymorphisms (SNPs) at 8q24, 17q12, 17q24.3 and a family history of the disease may predict risk of prostate cancer. The present study tests the performance of these factors in prediction models for prostate cancer risk and prostate cancer-specific mortality.

Methods: SNPs were genotyped in population-based samples from Caucasians in King County, Washington. Incident cases (n = 1,308), aged 35-74, were compared to age-matched controls (n = 1,266) using logistic regression to estimate odds ratios (OR) associated with genotypes and family history. Cox proportional hazards models estimated hazard ratios for prostate cancer-specific mortality according to genotypes.

Results: The combination of SNP genotypes and family history was significantly associated with prostate cancer risk (p(trend) = 1.5 x 10(-20)). Men with > or =5 risk factors had an OR of 4.9 (95% CI 1.6-18.5) compared to men with none. However, this combination of factors did not improve the ROC curve after accounting for known risk predictors (i.e., age, serum PSA, family history). Neither the individual nor combined risk factors was associated with prostate cancer-specific mortality.

Conclusion: Genotypes for five SNPs plus family history are associated with a significant elevation in risk for prostate cancer and may explain up to 45% of prostate cancer in our population. However, they do not improve prediction models for assessing who is at risk of getting or dying from the disease, once known risk or prognostic factors are taken into account. Thus, this SNP panel may have limited clinical utility.

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Figures

Figure 1
Figure 1
ROC curves for the effect of five SNPs in the 8q24, 17q12, and 17q243 chromosomal regions in predicting risk of prostate cancer. Solid line indicates curve fit with clinical variables only (i.e., age, serum PSA level at diagnosis or interview, first-degree family history of prostate cancer) and dashed line indicates curve fit with clinical variables plus the five SNPs.
Figure 2
Figure 2
ROC curves for the effect of five SNPs in the 8q24, 17q12, and 17q24.3 chromosomal regions in predicting ten-year prostate cancer-specific mortality. Solid line indicates curve fit with clinical variables only (i.e., age at diagnosis, stage, Gleason score, serum PSA level at diagnosis, first-degree family history of prostate cancer, and primary treatment) and dashed line indicates curve fit with clinical variables plus the five SNPs.
See this image and copyright information in PMC

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