Risk-Adapted Breast Screening for Women at Low Predicted Risk of Breast Cancer: An Online Discrete Choice Experiment

Charlotte Kelley Jones, Suzanne Scott, Nora Pashayan, Stephen Morris, Yasmina Okan and Jo Waller
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Charlotte Kelley Jones: Cancer Behavioural Science Cancer Prevention Group, King’s College, London, UK
Suzanne Scott: Professor of Health Psychology, Queen Mary University London, London, UK
Nora Pashayan: Professor of Applied Cancer Research, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
Stephen Morris: Rand Professor of Health Services Research, Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
Yasmina Okan: Department of Communication, Pompeu Fabra University, Barcelona, Spain
Jo Waller: Professor of Cancer Behavioural Science, Wolfson Institute of Population Health, Queen Mary University of London, London, UK

Medical Decision Making, 2024, vol. 44, issue 5, 586-600

Abstract: Background A risk-stratified breast screening program could offer low-risk women less screening than is currently offered by the National Health Service. The acceptability of this approach may be enhanced if it corresponds to UK women’s screening preferences and values. Objectives To elicit and quantify preferences for low-risk screening options. Methods Women aged 40 to 70 y with no history of breast cancer took part in an online discrete choice experiment. We generated 32 hypothetical low-risk screening programs defined by 5 attributes (start age, end age, screening interval, risk of dying from breast cancer, and risk of overdiagnosis), the levels of which were systematically varied between the programs. Respondents were presented with 8 choice sets and asked to choose between 2 screening alternatives or no screening. Preference data were analyzed using conditional logit regression models. The relative importance of attributes and the mean predicted probability of choosing each program were estimated. Results Participants ( N  = 502) preferred all screening programs over no screening. An older starting age of screening, younger end age of screening, longer intervals between screening, and increased risk of dying had a negative impact on support for screening programs ( P  

Keywords: breast cancer; breast screening; conjoint analysis; discrete choice models; health care acceptability; health care preferences; health economics; medical decision making; NHS breast screening program; personal risk assessment; personalized medicine; preference elicitation methods; risk stratification; stated preferences (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:44:y:2024:i:5:p:586-600

DOI: 10.1177/0272989X241254828

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