Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 Jul;44(5):586-600.
doi: 10.1177/0272989X241254828. Epub 2024 Jun 3.

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

Charlotte Kelley Jones  1 , Suzanne Scott  2 , Nora Pashayan  3 , Stephen Morris  4 , Yasmina Okan  5   6 , Jo Waller  7
Affiliations

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

Charlotte Kelley Jones et al. Med Decis Making. 2024 Jul.

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 < 0.01). Although the risk of overdiagnosis was of low relative importance, a decreased risk of this harm had a small positive impact on screening choices. The mean predicted probabilities that risk-adapted screening programs would be supported relative to current guidelines were low (range, 0.18 to 0.52).

Conclusions: A deintensified screening pathway for women at low risk of breast cancer, especially one that recommends a later screening start age, would run counter to women's breast screening preferences. Further research is needed to enhance the acceptability of offering less screening to those at low risk of breast cancer.

Highlights: Risk-based breast screening may involve the deintensification of screening for women at low risk of breast cancer.Low-risk screening pathways run counter to women's screening preferences and values.Longer screening intervals may be preferable to a later start age.Work is needed to enhance the acceptability of a low-risk screening pathway.

Keywords: NHS breast screening program; breast cancer; breast screening; conjoint analysis; discrete choice models; health care acceptability; health care preferences; health economics; medical decision making; personal risk assessment; personalized medicine; preference elicitation methods; risk stratification; stated preferences.

PubMed Disclaimer

Conflict of interest statement

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was funded by Breast Cancer Now (grant 2018BCNNovPhD12651). The funding agreement ensured the authors’ independence in designing the study, interpreting the data, writing, and publishing the report. Professor Jo Waller is funded by a Cancer Research UK Career Development Fellowship (C7492/A17219).

Figures

Figure 1
Figure 1
An example of a choice set as presented to online participants.
See this image and copyright information in PMC

Similar articles

See all similar articles

References

    1. Kim G, Bahl M. Assessing risk of breast cancer: a review of risk prediction models. J Breast Imaging. 2021;3(2):144–55. DOI: 10.1093/JBI/WBAB001 - DOI - PMC - PubMed
    1. van Ravesteyn NT, Schechter CB, Hampton JM, et al.. Trade-offs between harms and benefits of different breast cancer screening intervals among low-risk women. J Natl Cancer Inst. 2021;113(8):1017–26. DOI: 10.1093/jnci/djaa218 - DOI - PMC - PubMed
    1. Ugalde-Morales E, Grassmann F, Humphreys K, et al.. Association between breast cancer risk and disease aggressiveness: characterizing underlying gene expression patterns. Int J Cancer. 2021;148(4):884–94. DOI: 10.1002/IJC.33270 - DOI - PMC - PubMed
    1. Corradini AG, Cremonini A, Cattani MG, et al.. Which type of cancer is detected in breast screening programs? Review of the literature with focus on the most frequent histological features. Pathologica. 2021;113(2):85–94. DOI: 10.32074/1591-951X-123 - DOI - PMC - PubMed
    1. Evans DG, Harkness E, Brentnall A, et al.. Breast cancer pathology and stage are better predicted by risk stratification models that include mammographic density and common genetic variants. Breast Cancer Res Treat. 2019;176:141–8. DOI: 10.1007/s10549-019-05210-2 - DOI - PMC - PubMed

Publication types