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Breast Cancer Risk Model Requirements for Counseling, Prevention, and Screening
Journal of the National Cancer Institute ( IF 10.3 ) Pub Date : 2018-02-27 , DOI: 10.1093/jnci/djy013
Mitchell H Gail 1 , Ruth M Pfeiffer 1
Affiliation  

Incorporation of polygenic risk scores and mammographic density into models to predict breast cancer incidence can increase discriminatory accuracy (area under the receiver operating characteristic curve [AUC]) from 0.6 for models based only on epidemiologic factors to 0.7. It is timely to assess what impact these improvements will have on individual counseling and on public health prevention and screening strategies, and to determine what further improvements are needed.

中文翻译:

咨询,预防和筛查的乳腺癌风险模型要求

将多基因风险评分和乳房X线照相密度纳入模型以预测乳腺癌的发病率,可以将仅基于流行病学因素的模型的判别准确度(接受者工作特征曲线[AUC]下的面积)从0.6提高到0.7。现在应该评估这些改进将对个人咨询以及公共卫生预防和筛查策略产生什么影响,并确定需要进一步改进的时机。
更新日期:2018-02-27
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