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评估结合遗传和临床信息的乳腺癌风险模型的临床有效性。

Assessment of clinical validity of a breast cancer risk model combining genetic and clinical information.

机构信息

Perlegen Sciences, Inc, Mountain View, CA, USA.

出版信息

J Natl Cancer Inst. 2010 Nov 3;102(21):1618-27. doi: 10.1093/jnci/djq388. Epub 2010 Oct 18.

Abstract

BACKGROUND

The Gail model is widely used for the assessment of risk of invasive breast cancer based on recognized clinical risk factors. In recent years, a substantial number of single-nucleotide polymorphisms (SNPs) associated with breast cancer risk have been identified. However, it remains unclear how to effectively integrate clinical and genetic risk factors for risk assessment.

METHODS

Seven SNPs associated with breast cancer risk were selected from the literature and genotyped in white non-Hispanic women in a nested case-control cohort of 1664 case patients and 1636 control subjects within the Women's Health Initiative Clinical Trial. SNP risk scores were computed based on previously published odds ratios assuming a multiplicative model. Combined risk scores were calculated by multiplying Gail risk estimates by the SNP risk scores. The independence of Gail risk and SNP risk was evaluated by logistic regression. Calibration of relative risks was evaluated using the Hosmer-Lemeshow test. The performance of the combined risk scores was evaluated using receiver operating characteristic curves. The net reclassification improvement (NRI) was used to assess improvement in classification of women into low (<1.5%), intermediate (1.5%-2%), and high (>2%) categories of 5-year risk. All tests of statistical significance were two-sided.

RESULTS

The SNP risk score was nearly independent of Gail risk. There was good agreement between predicted and observed SNP relative risks. In the analysis for receiver operating characteristic curves, the combined risk score was more discriminating, with area under the curve of 0.594 compared with area under the curve of 0.557 for Gail risk alone (P < .001). Classification also improved for 5.6% of case patients and 2.9% of control subjects, showing an NRI value of 0.085 (P = 1.0 × 10⁻⁵). Focusing on women with intermediate Gail risk resulted in an improved NRI of 0.195 (P = 8.6 × 10⁻⁵).

CONCLUSIONS

Combining validated common genetic risk factors with clinical risk factors resulted in modest improvement in classification of breast cancer risks in white non-Hispanic postmenopausal women. Classification performance was further improved by focusing on women at intermediate risk.

摘要

背景

基于公认的临床危险因素,盖尔模型被广泛用于评估浸润性乳腺癌的风险。近年来,已发现大量与乳腺癌风险相关的单核苷酸多态性(SNP)。然而,如何有效地整合临床和遗传危险因素进行风险评估仍不清楚。

方法

从文献中选择了 7 个与乳腺癌风险相关的 SNP,并对 1664 例病例患者和 1636 例对照患者的嵌套病例对照队列中的白人非西班牙裔女性进行基因分型。根据先前发表的优势比假设乘法模型计算 SNP 风险评分。通过将 Gail 风险估计乘以 SNP 风险评分来计算综合风险评分。通过逻辑回归评估 Gail 风险和 SNP 风险的独立性。使用 Hosmer-Lemeshow 检验评估相对风险的校准。使用接收器操作特征曲线评估综合风险评分的性能。使用净重新分类改善(NRI)评估将女性分类为低(<1.5%)、中(1.5%-2%)和高(>2%)5 年风险类别中的改善情况。所有统计学检验均为双侧。

结果

SNP 风险评分几乎独立于 Gail 风险。预测的 SNP 相对风险与观察到的 SNP 相对风险之间具有良好的一致性。在接收器操作特征曲线分析中,综合风险评分更具鉴别力,曲线下面积为 0.594,而单独使用 Gail 风险的曲线下面积为 0.557(P <.001)。分类也改善了 5.6%的病例患者和 2.9%的对照患者,NRI 值为 0.085(P = 1.0×10⁻⁵)。关注 Gail 风险处于中间水平的女性可将 NRI 提高 0.195(P = 8.6×10⁻⁵)。

结论

将验证有效的常见遗传危险因素与临床危险因素相结合,可适度改善白人非西班牙裔绝经后妇女乳腺癌风险的分类。通过关注处于中间风险水平的女性,分类性能进一步提高。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b546/2970578/f430e4b0ab5d/jncidjq388f01_ht.jpg

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