Breast cancer follow-up and prospective analyses
Professor John Hopper
+ 61 3 834 40697
This project combines the Australian Breast Cancer Family Registry with other large Australian and North American breast cancer family registries to facilitate large-scale studies of breast cancer aetiology, risk and survival.
This project brings together the vast resources of the Australian Breast Cancer Family Registry, the Breast Cancer Family Registry (USA and Canada) and kConfab (Australia). These registries have recruited thousands of population-based and clinic-based breast cancer families as well as population-based control families.
The project brings together a diverse group of researchers to undertake analyses of epidemiological, cancer history, genetic and pathology data collected at baseline and during fifteen years of follow-up. These analyses use prospective study designs and include:
- validation of breast cancer risk-prediction models
- survival in affected women
- using genetic data to improve breast cancer risk prediction models
- calculating cancer risks for relatives of affected women
- identifying gene–environment interactions
- description of the Breast Cancer Family Registry cohort.
Professor Kelly Phillips (Peter MacCallum Cancer Institute)
Sandra Picken (Peter MacCallum Cancer Institute)
Professor Mary Beth Terry (Colombia University)
NHMRC, NIH (USA), Cancer Australia
MacInnis RJ, Bickerstaffe A, Apicella C, Dite GS, Dowty JG, Aujard K, et al. Prospective validation of the breast cancer risk prediction model BOADICEA and a batch-mode version BOADICEACentre. British Journal of Cancer 2013; 109: 1296–1301.
Dite GS, Mahmoodi M, Bickerstaffe A, Hammett F, Macinnis RJ, Tsimiklis H, et al. Using SNP genotypes to improve the discrimination of a simple breast cancer risk prediction model. Breast Cancer Research and Treatment 2013; 139: 887–896.
Faculty Research Themes
School Research Themes
Prevention and management of non-communicable diseases (including cancer), and promotion of mental health, Screening and early detection of disease
For further information about this research, please contact the research group leader.
Department / Centre
Centre for Epidemiology and Biostatistics
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