Center for Cancer Genomics, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA.
Eur Urol. 2012 Dec;62(6):953-61. doi: 10.1016/j.eururo.2012.05.006. Epub 2012 May 12.
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.
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.
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.
已有多项种系单核苷酸多态性（SNP）与前列腺癌（PCa）风险显著相关。
确定将这些 SNP 添加到现有的 PCa 预测因子中是否可以提高 PCa 风险预测能力。
设计、地点和参与者：本研究纳入了随机分组接受度他雄胺降低前列腺癌事件（REDUCE）试验安慰剂组中可获取种系 DNA 的男性。所有男性均首次接受了前列腺活检阴性，且在 2 年和 4 年时进行了研究要求的活检。评估了基线临床参数和/或基于 33 个已确立的 PCa 风险相关 SNP 的遗传评分的预测性能。
采用受试者工作特征曲线（ROC）下面积（AUC）比较不同预测因子的不同模型。净重新分类改善（NRI）和决策曲线分析（DCA）用于评估添加遗传标记对风险预测的改变。
在 1654 名男性中，即使在调整了已知的临床变量和家族史后，遗传评分也是阳性活检的显著预测因子（p=3.41×10(-8)）。遗传评分的 AUC 优于任何其他 PCa 预测因子，为 0.59。将遗传评分添加到最佳临床模型中，AUC 从 0.62 提高到 0.66（p<0.001），33%的男性重新分类为 PCa 风险（NRI：0.10；p=0.002），DCA 的净获益更高，且减少了发现相同数量 PCa 所需的活检次数。在中等风险（25%至 75%）男性中，添加遗传评分的获益最大。对于高级别（Gleason 评分≥7）PCa，也得到了类似的结果。本研究的主要局限性是仅关注白人患者。
将遗传标记添加到当前的临床参数中可能会改善 PCa 风险预测。这种改善是适度的，但可能有助于更好地确定是否需要重复前列腺活检。这些结果的临床影响需要进一步研究。
