Center for Cancer Genomics, Wake Forest University School of Medicine, Winston-Salem, North Carolina 27157, USA.
Prostate. 2011 Mar 1;71(4):421-30. doi: 10.1002/pros.21256. Epub 2010 Sep 28.
Prostate cancer (PCa) risk-associated single-nucleotide polymorphisms (SNPs) are continuously being discovered. Their ability to identify men at high risk and the impact of increasing numbers of SNPs on predictive performance are not well understood.
Absolute risk for PCa was estimated in a population-based case-control study in Sweden (2,899 cases and 1,722 controls) using family history and three sets of sequentially discovered PCa risk-associated SNPs. Their performance in predicting PCa was assessed by positive predictive values (PPV) and sensitivity.
SNPs and family history were able to differentiate individual risk for PCa and identify men at higher risk; ∼18% and ∼8% of men in the study had 20-year (55-74 years) absolute risks that were twofold (0.24) or threefold (0.36) greater than the population median risk (0.12), respectively. When predictive performances were compared at absolute risk cutoffs of 0.12, 0.24, or 0.36, PPV increased considerably (∼20%, ∼30%, and ∼37%, respectively) while sensitivity decreased considerably (∼55%, ∼20%, and ∼10%, respectively). In contrast, when increasing numbers of SNPs (5, 11, and 28 SNPs) were used in risk prediction, PPV approached a constant value while sensitivity increased steadily.
SNPs discovered to date are suitable for risk prediction while additional SNPs discovered in the future may identify more subjects at higher risk. Men identified as high risk by SNP-based testing may be targeted for PCa screening or chemoprevention. The clinical impact on improving the effectiveness of these interventions can be and should be assessed.
前列腺癌(PCa)风险相关的单核苷酸多态性(SNP)不断被发现。人们对这些 SNP 识别高危男性的能力以及它们对预测性能的影响知之甚少。
在瑞典的一项基于人群的病例对照研究中(2899 例病例和 1722 例对照),使用家族史和三批连续发现的 PCa 风险相关 SNP 来估计 PCa 的绝对风险。通过阳性预测值(PPV)和敏感性来评估它们预测 PCa 的性能。
SNP 和家族史能够区分个体 PCa 风险并识别高危男性;研究中约有 18%和 8%的男性在 20 年(55-74 岁)内的绝对风险是人群中位数风险(0.12)的两倍(0.24)或三倍(0.36)。当在绝对风险截止值为 0.12、0.24 或 0.36 时比较预测性能时,PPV 显著增加(分别约为 20%、30%和 37%),而敏感性显著降低(分别为 55%、20%和 10%)。相比之下,当使用越来越多的 SNP(5、11 和 28 个 SNP)进行风险预测时,PPV 接近常数,而敏感性则稳步增加。
迄今为止发现的 SNP 适合用于风险预测,而未来发现的额外 SNP 可能会识别出更多处于高风险的个体。通过 SNP 检测识别为高危的男性可能会成为 PCa 筛查或化学预防的目标。可以而且应该评估这些干预措施对提高效果的临床影响。