Several germline single nucleotide polymorphisms (SNPs) have been consistently associated with prostate cancer (PCa) risk.
To determine whether there is an improvement in PCa risk prediction by adding these SNPs to existing predictors of PCa.
Design, setting, and participants
Subjects included men in the placebo arm of the randomized Reduction by Dutasteride of Prostate Cancer Events (REDUCE) trial in whom germline DNA was available. All men had an initial negative prostate biopsy and underwent study-mandated biopsies at 2 yr and 4 yr. Predictive performance of baseline clinical parameters and/or a genetic score based on 33 established PCa risk-associated SNPs was evaluated.
Outcome measurements and statistical analysis
Area under the receiver operating characteristic curves (AUC) were used to compare different models with different predictors. Net reclassification improvement (NRI) and decision curve analysis (DCA) were used to assess changes in risk prediction by adding genetic markers.
Results and limitations
Among 1654 men, genetic score was a significant predictor of positive biopsy, even after adjusting for known clinical variables and family history (p = 3.41 × 10−8). The AUC for the genetic score exceeded that of any other PCa predictor at 0.59. Adding the genetic score to the best clinical model improved the AUC from 0.62 to 0.66 (p < 0.001), reclassified PCa risk in 33% of men (NRI: 0.10; p = 0.002), resulted in higher net benefit from DCA, and decreased the number of biopsies needed to detect the same number of PCa instances. The benefit of adding the genetic score was greatest among men at intermediate risk (25th percentile to 75th percentile). Similar results were found for high-grade (Gleason score ≥7) PCa. A major limitation of this study was its focus on white patients only.
Adding genetic markers to current clinical parameters may improve PCa risk prediction. The improvement is modest but may be helpful for better determining the need for repeat prostate biopsy. The clinical impact of these results requires further study.
Keywords: Prostate cancer, Genetics, AUC, Detection rate, Reclassification, SNPs, Prospective study, Clinical trial.
a Center for Cancer Genomics, Wake Forest University School of Medicine, Winston-Salem, NC, USA
b Department of Genomics and Personalized Medicine Research, Wake Forest University School of Medicine, Winston-Salem, NC, USA
c Department of Urology, Wake Forest University School of Medicine, Winston-Salem, NC, USA
d Department of Biostatistical Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, USA
e Department of Cancer Biology, Wake Forest University School of Medicine, Winston-Salem, NC, USA
f Division of Urology, University of California, San Diego, San Diego, CA, USA
g Genetics, GlaxoSmithKline, Research Triangle Park, NC, USA
h Oncology Development, GlaxoSmithKline, Research Triangle Park, NC, USA
i Genetics, GlaxoSmithKline, Harlow, United Kingdom
j Division of Urology, Spectrum Health, Grand Rapids, MI, USA
k Johns Hopkins Medical Institutions, Baltimore, MD, USA
l Van Andel Research Institute, Grand Rapids, MI, USA
Corresponding author. Center for Cancer Genomics, Medical Center Blvd, Winston-Salem, NC 27157, USA. Tel. +1 336 713 7500; Fax: +1 336 713 7566.
These authors contributed equally to this work.
© 2012 European Association of Urology, Published by Elsevier B.V.