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单核苷酸多态性在识别癌症高危人群中的潜在作用:对七种常见癌症的评估。

Potential usefulness of single nucleotide polymorphisms to identify persons at high cancer risk: an evaluation of seven common cancers.

机构信息

National Cancer Institute, Rockville, MD 20852-7244, USA.

出版信息

J Clin Oncol. 2012 Jun 10;30(17):2157-62. doi: 10.1200/JCO.2011.40.1943. Epub 2012 May 14.

Abstract

PURPOSE

To estimate the likely number and predictive strength of cancer-associated single nucleotide polymorphisms (SNPs) that are yet to be discovered for seven common cancers.

METHODS

From the statistical power of published genome-wide association studies, we estimated the number of undetected susceptibility loci and the distribution of effect sizes for all cancers. Assuming a log-normal model for risks and multiplicative relative risks for SNPs, family history (FH), and known risk factors, we estimated the area under the receiver operating characteristic curve (AUC) and the proportion of patients with risks above risk thresholds for screening. From additional prevalence data, we estimated the positive predictive value and the ratio of non-patient cases to patient cases (false-positive ratio) for various risk thresholds.

RESULTS

Age-specific discriminatory accuracy (AUC) for models including FH and foreseeable SNPs ranged from 0.575 for ovarian cancer to 0.694 for prostate cancer. The proportions of patients in the highest decile of population risk ranged from 16.2% for ovarian cancer to 29.4% for prostate cancer. The corresponding false-positive ratios were 241 for colorectal cancer, 610 for ovarian cancer, and 138 or 280 for breast cancer in women age 50 to 54 or 40 to 44 years, respectively.

CONCLUSION

Foreseeable common SNP discoveries may not permit identification of small subsets of patients that contain most cancers. Usefulness of screening could be diminished by many false positives. Additional strong risk factors are needed to improve risk discrimination.

摘要

目的

估计七种常见癌症中尚未发现的与癌症相关的单核苷酸多态性(SNP)的可能数量和预测强度。

方法

根据已发表的全基因组关联研究的统计效力,我们估计了所有癌症未检测到的易感性位点数量和效应大小分布。假设风险的对数正态模型和 SNP、家族史(FH)和已知危险因素的乘法相对风险,我们估计了接收者操作特征曲线(AUC)下的面积和高于风险阈值的患者比例筛查风险。从额外的流行率数据中,我们估计了各种风险阈值的阳性预测值和非患者病例与患者病例的比例(假阳性比)。

结果

包括 FH 和可预见 SNP 的模型的年龄特异性判别准确性(AUC)范围从卵巢癌的 0.575 到前列腺癌的 0.694。处于人群风险最高十分位数的患者比例范围从卵巢癌的 16.2%到前列腺癌的 29.4%。相应的假阳性比分别为结肠癌 241、卵巢癌 610、50-54 岁或 40-44 岁女性乳腺癌 138 或 280。

结论

可预见的常见 SNP 发现可能无法确定包含大多数癌症的小患者亚组。许多假阳性可能会降低筛查的有效性。需要额外的强危险因素来提高风险判别能力。

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