Cost-Effectiveness of AI for Risk-Stratified Breast Cancer Screening
In this decision analytical model study of integrating risk-stratified screening with a breast cancer AI model into the UK National Breast Cancer Screening Program, risk-stratified screening was likely to be cost-effective, yielding added health benefits at reduced costs. These results are particularly relevant for health care settings where resources are under pressure. New studies to prospectively evaluate AI-guided screening appear warranted.
Authors
- Stephen William Duffy (ORCID: https://orcid.org/0000-0003-4901-7922)
- Olena Mandrik (ORCID: https://orcid.org/0000-0003-3755-3031)
- Adam R. Brentnall (ORCID: https://orcid.org/0000-0001-6327-4357)
- Harry Hill (ORCID: https://orcid.org/0000-0002-0908-5595)
- Cristina Roadevin (ORCID: https://orcid.org/0000-0001-6279-6823)
Institutions
- University of Nottingham (GB)
- Queen Mary University of London (GB)
- University of Sheffield (GB)
Publication Details
- Journal
- JAMA Network Open
- Published
- 2024-09-05
- DOI
- https://doi.org/10.1001/jamanetworkopen.2024.31715
- Citations
- 42
- Primary Topic
- Global Cancer Incidence and Screening
- Type
- article
- Field-Weighted Citation Impact
- 11.87
Funders
- Cancer Research UK
- National Institute for Health and Care Research