L A Keogh1, E Steel2, P Weideman3, P Butow4, I M Collins5, J D Emery6, G B Mann7, A Bickerstaffe8, A H Trainer9, L J Hopper8, K A Phillips10. 1. Centre for Health Equity, Melbourne School of Population and Global Health, The University of Melbourne, Australia. Electronic address: l.keogh@unimelb.edu.au. 2. Centre for Health Equity, Melbourne School of Population and Global Health, The University of Melbourne, Australia. 3. Department of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, Australia; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Australia. 4. Centre for Medical Psychology and Evidence-based Decision-Making (CeMPED) and the Psycho-Oncology Cooperative Research Group (PoCoG), The University of Sydney, Sydney, Australia. 5. Department of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, Australia; The Greater Green Triangle Clinical School, Deakin University School of Medicine, Warrnambool, Australia. 6. Department of General Practice, The University of Melbourne, Melbourne, Australia. 7. The Breast Service, Royal Melbourne and Royal Women's Hospital, Melbourne, Australia; Department of Surgery, The University of Melbourne, Melbourne, Australia. 8. Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Australia. 9. Department of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, Australia; Department of Medicine, The University of Melbourne, Melbourne, Australia. 10. Department of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, Australia; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Australia; Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, Australia.
Abstract
BACKGROUND: Personalised prevention of breast cancer has focused on women at very high risk, yet most breast cancers occur in women at average, or moderately increased risk (≤moderate risk). OBJECTIVES: To determine; 1) interest of women at ≤ moderate risk (consumers) in personalised information about breast cancer risk; 2) familial cancer clinicians' (FCCs) perspective on managing women at ≤ moderate risk, and; 3) both consumers' and FCCs reactions to iPrevent, a personalised breast cancer risk assessment and risk management decision support tool. METHODS: Seven focus groups on breast cancer risk were conducted with 49 participants; 27 consumers and 22 FCCs. Data were analysed thematically. RESULTS: Consumers reported some misconceptions, low trust in primary care practitioners for breast cancer prevention advice and frustration that they often lacked tailored advice about breast cancer risk. They expressed interest in receiving personalised risk information using iPrevent. FCCs reported an inadequate workforce to advise women at ≤ moderate risk and reacted positively to the potential of iPrevent to assist. CONCLUSIONS: While highlighting a potential role for iPrevent, several outstanding issues remain. For personalised prevention of breast cancer to extend beyond women at high risk, we must harness women's interest in receiving tailored information about breast cancer prevention and identify a workforce willing to advise women.
BACKGROUND: Personalised prevention of breast cancer has focused on women at very high risk, yet most breast cancers occur in women at average, or moderately increased risk (≤moderate risk). OBJECTIVES: To determine; 1) interest of women at ≤ moderate risk (consumers) in personalised information about breast cancer risk; 2) familial cancer clinicians' (FCCs) perspective on managing women at ≤ moderate risk, and; 3) both consumers' and FCCs reactions to iPrevent, a personalised breast cancer risk assessment and risk management decision support tool. METHODS: Seven focus groups on breast cancer risk were conducted with 49 participants; 27 consumers and 22 FCCs. Data were analysed thematically. RESULTS: Consumers reported some misconceptions, low trust in primary care practitioners for breast cancer prevention advice and frustration that they often lacked tailored advice about breast cancer risk. They expressed interest in receiving personalised risk information using iPrevent. FCCs reported an inadequate workforce to advise women at ≤ moderate risk and reacted positively to the potential of iPrevent to assist. CONCLUSIONS: While highlighting a potential role for iPrevent, several outstanding issues remain. For personalised prevention of breast cancer to extend beyond women at high risk, we must harness women's interest in receiving tailored information about breast cancer prevention and identify a workforce willing to advise women.
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