Novel mammogram‐based measures improve breast cancer risk prediction beyond an established mammographic density measure

Author:

Nguyen Tuong L.1ORCID,Schmidt Daniel F.2,Makalic Enes1,Maskarinec Gertraud3ORCID,Li Shuai145ORCID,Dite Gillian S.16,Aung Ye K.1,Evans Christopher F.1,Trinh Ho N.1,Baglietto Laura7,Stone Jennifer8ORCID,Song Yun‐Mi9,Sung Joohon1011,MacInnis Robert J.112,Dugué Pierre‐Antoine1512,Dowty James G.1,Jenkins Mark A.1,Milne Roger L.1512,Southey Melissa C.1512,Giles Graham G.1512,Hopper John L.1ORCID

Affiliation:

1. Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health University of Melbourne Parkville Victoria Australia

2. Faculty of Information Technology Monash University Clayton Victoria Australia

3. University of Hawaii Cancer Center Honolulu Hawaii USA

4. Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care University of Cambridge Cambridge UK

5. Precision Medicine, School of Clinical Sciences at Monash Health Monash University Clayton Victoria Australia

6. Genetic Technologies Ltd. Fitzroy Victoria Australia

7. Department of Clinical and Experimental Medicine University of Pisa Pisa Italy

8. Genetic Epidemiology Group, School of Population and Global Health University of Western Australia Perth Western Australia Australia

9. Department of Family Medicine, Samsung Medical Center Sungkyunkwan University School of Medicine Seoul South Korea

10. Department of Epidemiology School of Public Health Seoul National University Seoul South Korea

11. Institute of Health and Environment Seoul National University Seoul South Korea

12. Cancer Epidemiology Division Cancer Council Victoria Melbourne Victoria Australia

Funder

Cure Cancer Australia Foundation

National Health and Medical Research Council

University of Melbourne

National Breast Cancer Foundation

Cancer Australia

Cancer Council NSW

Cancer Council Victoria

Publisher

Wiley

Subject

Cancer Research,Oncology

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