UK Women’s Views of the Concepts of Personalised Breast Cancer Risk Assessment and Risk-Stratified Breast Screening: A Qualitative Interview Study

Any introduction of risk-stratification within the NHS Breast Screening Programme needs to be considered acceptable by women. We conducted interviews to explore women’s attitudes to personalised risk assessment and risk-stratified breast screening. Twenty-five UK women were purposively sampled by screening experience and socioeconomic background. Interview transcripts were qualitatively analysed using Framework Analysis. Women expressed positive intentions for personal risk assessment and willingness to receive risk feedback to provide reassurance and certainty. Women responded to risk-stratified screening scenarios in three ways: ‘Overall acceptors’ considered both high- and low-risk options acceptable as a reasonable allocation of resources to clinical need, yet acceptability was subject to specified conditions including accuracy of risk estimates and availability of support throughout the screening pathway. Others who thought ‘more is better’ only supported high-risk scenarios where increased screening was proposed. ‘Screening sceptics’ found low-risk scenarios more aligned to their screening values than high-risk screening options. Consideration of screening recommendations for other risk groups had more influence on women’s responses than screening-related harms. These findings demonstrate high, but not universal, acceptability. Support and guidance, tailored to screening values and preferences, may be required by women at all levels of risk.

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Attitudes towards risk-stratified breast cancer screening among women in England: A cross-sectional survey

Journal of Medical Screening ◽

10.1177/0969141319883662 ◽

2019 ◽

Vol 27 (3) ◽

pp. 138-145 ◽

Cited By ~ 6

Author(s):

Alex Ghanouni ◽

Saskia C Sanderson ◽

Nora Pashayan ◽

Cristina Renzi ◽

Christian von Wagner ◽

...

Keyword(s):

Breast Cancer ◽

Risk Assessment ◽

High Risk ◽

Breast Cancer Risk ◽

Breast Screening ◽

Low Risk ◽

Cancer Risk Assessment ◽

Risk Status ◽

Breast Cancer Risk Assessment ◽

Very High

Objectives Risk stratification may improve the benefit/harm ratio of breast screening. Research on acceptability among potential invitees is necessary to guide implementation. We assessed women’s attitudes towards and willingness to undergo risk assessment and stratified screening. Methods Women in England aged 40–70 received summary information about the topic, and completed face-to-face computer-assisted interviews. Questions assessed willingness to undergo multifactorial breast cancer risk assessment, more frequent breast screening (if at very high risk), or less frequent or no screening (if at very low risk), and preferences for delivery of assessment results. Results Among 933 women, 85% considered breast cancer risk assessment a good idea, and 74% were willing to have it. Among 125 women unwilling to have risk assessment, reasons commonly related to ‘worry’ (14%) and ‘preferring not to know’ (14%). Among those willing to have risk assessment ( n = 689), letters/emails were generally preferred (42%) for results about very low-risk status. Face-to-face communication was most commonly preferred for results of very high-risk status (78%). General practitioners were most commonly preferred sources of assessment results (≈40%). Breast cancer specialists were often preferred for results of very high-risk status (38%). Risk-stratified breast screening was considered a good idea by 70% and 89% were willing to have more frequent screening. Fewer would accept less (51%) or no screening (37%) if at very low risk. Conclusions Women were generally in favour of multifactorial breast cancer risk assessment and risk-stratified screening. Some were unwilling to accept less or no screening if at very low risk.

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Breast cancer risk assessment: How risk models can “overdiagnose” risk.

Journal of Clinical Oncology ◽

10.1200/jco.2013.31.31_suppl.184 ◽

2013 ◽

Vol 31 (31_suppl) ◽

pp. 184-184

Author(s):

Elissa Ozanne ◽

Brian Drohan ◽

Kevin S. Hughes

Keyword(s):

Breast Cancer ◽

Risk Assessment ◽

High Risk ◽

Resource Utilization ◽

Management Strategies ◽

Cancer Risk Assessment ◽

Cancer Society ◽

Total Study Population ◽

Breast Cancer Risk Assessment ◽

The Impact

184 Background: Overdiagnosis is commonly defined as a diagnosis of "disease" which will never cause symptoms or death during a patient's lifetime. Similarly, overdiagnosis can also happen when individuals are given the diagnosis of being at risk for a disease, such as being at high-risk for developing breast cancer. Women can be given such a diagnosis by meeting a set of risk assessment criteria, which are often accompanied by recommended management strategies. We sought to identify the extent and consequences of overdiagnosis for individuals being at high risk for breast cancer using the American Cancer Society (ACS) guidelines for the appropriate use of Magnetic Resonance Imaging (MRI). Methods: We identified women who fit the ACS criteria in a population based sample at a community hospital. The ACS criteria mentions three risk assessment models for determining a woman’s risk, and these criteria were reviewed to determine the extent of possible overdiagnosis in this population. The expected resource utilization resulting from this overdiagnosis, and the impact on patient quality of life are extrapolated. Results: 5,894 women who received mammography screening at the study site were included. 342 (5.8%) of the women were diagnosed as high risk by at least one model. However, only 0.2% of the total study population were diagnosed as high risk by all three models. One model identified 330 (5.6%) to be at high risk, while the other two models identified many fewer eligible women (25, 0.4% and 54, 0.9% respectively). Conclusions: Using different models to evaluation the ACS criteria identifies very different populations, implying a large potential for overdiagnosis. Further, this overdiagnosis is likely to result in the outcome of screening too many women, incurring false positives and unnecessary resource utilization.

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