Breast cancer pathology and stage are better predicted by risk stratification models that include mammographic density and common genetic variants

被引:0
作者
D. Gareth R. Evans
Elaine F. Harkness
Adam R. Brentnall
Elke M. van Veen
Susan M. Astley
Helen Byers
Sarah Sampson
Jake Southworth
Paula Stavrinos
Sacha J. Howell
Anthony J. Maxwell
Anthony Howell
William G. Newman
Jack Cuzick
机构
[1] University of Manchester,Division of Evolution and Genomic Sciences, Faculty of Biology, Medicine and Health
[2] MAHSC,Prevention Breast Cancer Unit and Nightingale Breast Screening Centre
[3] Manchester University NHS Foundation Trust (South),Division of Informatics, Imaging and Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health
[4] University of Manchester,Manchester Academic Health Science Centre
[5] University of Manchester,Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Charterhouse Square, Barts and The London
[6] Queen Mary University of London,Manchester Centre for Genomic Medicine
[7] The Christie NHS Foundation Trust,Manchester Breast Centre, Manchester Cancer Research Centre
[8] Manchester University NHS Foundation Trust (Central),NIHR Manchester Biomedical Research Centre, Cancer Prevention Early Detection Theme
[9] University of Manchester,Department of Genomic Medicine, Manchester Academic Health Sciences Centre (MAHSC), St Mary’s Hospital
[10] The Christie NHS Foundation Trust,undefined
[11] University of Manchester,undefined
来源
Breast Cancer Research and Treatment | 2019年 / 176卷
关键词
SNPs; Polygenic risk score; Breast cancer; Mammographic density; Pathology; Early detection;
D O I
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中图分类号
学科分类号
摘要
引用
收藏
页码:141 / 148
页数:7
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