PM.20.021 – Transitioning to a personalised breast cancer screening and prevention paradigm: delivering the final pieces of the implementation puzzle

Route: Personalised medicine: the individual at the centre

Cluster question: 095 How can we personalise health care, for example by using biomarkers?

Implementation of risk stratification, biomarkers, and artificial intelligence in breast cancer screening is already at the forefront of politicians’ and policy makers’ minds. The public also shows interest in transitioning to personalised screening with optimal harm-benefit ratios for women at different risks of breast cancer. An example is our DENSE trial on MRI for women with extremely dense breasts. Review of its results by the Health Council and RIVM with an eye towards implementation brings us closer to personalised screening than ever before. Thus, it is time to deliver the final pieces of the implementation puzzle by addressing who will be invited for screening based on risk factors and biomarkers, from liquid biopsies and imaging. For personalised screening we need to focus on short-time risk of cancers that are potentially aggressive and/or diagnosed in an advanced stage, to limit the potential of overdiagnosis. Most research on risk models does not take this approach and, in addition, does not evaluate personalised screening strategies for long-term health effects. We propose to take this last step, by evaluating the effects of risk-based screening strategies in practice, involving innovative, feasible and affordable imaging such as abbreviated MRI, contrast-mammography or tomosynthesis, enhanced by use of artificial intelligence, all depending on a woman’s risk. Concurrently, we will offer risk-based breast cancer prevention strategies linked to screening visits, as a teachable moment, and evaluate their effectiveness on adherence and behavioral changes. Our consortium will build on large and unique breast cancer screening initiatives – PRISMA, IMAGINE, DENSE – to develop efficient study designs as well as the required flexible infrastructure. We are: clinicians, epidemiologists, physicists, AI experts, and (early) HTA experts. We seek to involve behavioral scientists, and, to provide standards ready for implementation, we will include experts in organization of health care, citizens, societal partners and companies.

Keywords

AI, biomarkers, Early detection, HTA, imaging, Organization, Prevention, Risk stratification

Other organisations

Dutch Expert Centre for screening, Erasmus Medical Center (EMC), imaging depts of DENSE hospitals. The RIVM-center for population-based screening has an advisory role, Radboud Medical Center (RUMC), The Netherlands Cancer Institute (NKI)

Submitter

Organisation Julius Center for Health Sciences and Primary Care, UMC Utrecht (UMCU)
Name Prof. Dr. Carla van Gils
E-mail c.vangils@umcutrecht.nl
Website https://www.umcutrecht.nl/en/research/researchers/van-gils-carla-h-ch