Potential Impact of Adding Genetic Markers to Clinical Parameters in Predicting Prostate Biopsy Outcomes in Men Following an Initial Negative Biopsy: Findings from the REDUCE Trial

Abstract

Background Several germline single nucleotide polymorphisms (SNPs) have been consistently associated with prostate cancer (PCa) risk. Objective 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. Conclusions 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.

Multigene panels in prostate cancer risk assessment: a systematic review

“…On the basis of the 14 articles that were identified as providing information relevant to the assessment of the clinical validity of SNP panels, reported overall (i.e., including genetic markers included in the panels and variants of other genes) genotyping accuracy rates ranged up to >99.9%; SNP call rates were usually reported in the range of 98 to 99% (with a low of 89%), and reported concordance upon retesting was usually >99%. 25,[34][35][36][37][38][39][40][41][42][43][45][46][47][48][49][50][51][53][54][55] However, the methodologies described as the basis for determining analytical validity were not uniform across all analytes for some panels; in multiple cases, the SNP call rate of a given test panel was reported on the basis of data from two or more different chip platforms or analytical techniques. No evidence was identified about sources of variation in accuracy or analytical validity across different test platforms.…”

Will Biomarkers Save Prostate Cancer Screening?

“…While the problem of false-negative biopsies is not highlighted in the USPSTF's critique of screening, it is a factor limiting the efficacy of screening and certainly a major source of anxiety for men in screening programs. In this issue of European Urology, Kader et al report the results of a large validation study of a proposed genetic signature intended help guide the decision whether to perform a second biopsy [6].…”

“…The genetic score was shown to contribute independent information, based on a variety of analyses, to a clinical model derived from age, PSA, prostate volume, prior biopsy extent, family history, and rectal examination [6]. However, despite the statistically significant superiority of the model incorporating the genetic score along with the clinical information, the absolute improvement realized through incorporation of the SNP data was fairly modest, as demonstrated in both the area under the curve and decision curve analyses.…”

“…Most of these candidate markers, including the SNP signature proposed in Kader et al's paper [6], are easily accessed through the blood or urine but ultimately may not be the best markers for the repeat-as opposed to the initialbiopsy setting, because in this setting only, prostate tissue is available for analysis. While germline genetic factors may still be relevant, it seems more likely that a better signal might be identified through evaluation of field effect changes in the ''normal'' prostate biopsy tissue [9].…”

“…Whether or not the SNP signature proposed by Kader et al [6] may ultimately prove clinically useful, the paper is emblematic of a rapidly rising level of methodological quality in PCa biomarker research. It is very reasonable to expect that in the near term, well-validated markers will be available to facilitate decision making both before and after PCa diagnosis.…”