近日,，來自美國加州大學圣地亞哥醫(yī)學院的研究者Karim Kader與維克森林大學的研究者共同合作研究發(fā)明出了一種遺傳測試法來預測男性的前列腺癌風險，使用此方法可以減少男性活組織檢測陰性結果的復檢試驗需要,。相關研究成果刊登在了國際雜志European Urology上,。
研究者Kader表示，在研究癌癥風險上,，遺傳檢測遠勝于PSA檢測法,。文章中，研究者評估了1654個男性在前列腺癌實驗中度他雄胺用量減少的試驗結果,，而且所有男性都進行了活組織檢測,，并且都同意進行遺傳學研究，尋找其種系單核苷酸多態(tài)性（SNPs）的存在,。SNPs是個體DNA序列的遺傳變異,，這和前列腺癌甚至是慢性疾病有著正向的關系。
避免了重復的檢測步驟,，尤其是對老年人來說,，新的檢測方法可以幫助患者降低感染風險以及潛在的醫(yī)院住院可能性。所得到的遺傳分值對于男性在任何時間都是可用的,，而且可以被用于進行初篩實驗,。
在男性的一生中，6個人中會有一個人進行相關的前列腺癌診斷,。2012年,，超過了241，700個前列腺癌男性患者使用了新的檢測方法進行檢測,，在病人診斷的過程中,，超過了100萬的患者每年只需要進行活組織檢查即可。相關研究成果由國立癌癥研究中心支持,。（生物谷Bioon.com）
編譯自：New Test May Help Predict Prostate Cancer
PMC:
PMID:
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
A. Karim Kader, Jielin Sun, Brian H. Reck, Paul J. Newcombe, Seong-Tae Kim, Fang-Chi Hsu, Ralph B. D’Agostino Jr., Sha Tao, Zheng Zhang, Aubrey R. Turner, Greg T. Platek, Colin F. Spraggs, John C. Whittaker, Brian R. Lane, William B. Isaacs, Deborah A. Meyers, Eugene R. Bleecker, Frank M. Torti, Jeffery M. Trent, John D. McConnell, S. Lilly Zheng, Lynn D. Condreay, Roger S. Rittmaster, Jianfeng Xu.
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.
