Risk-based breast cancer screening strategies in women. (May 2020)

• Record Type: Journal Article
• Authors: Harkness, Elaine F.; Astley, Susan M.; Evans, D.Gareth
• Is Part Of: Best practice & research. Volume 65(2020)
• Page Start: 3
• Page End: 17
• Publication Date: 2020-05
• Subjects: Breast cancer screening -- Risk stratification -- Risk prediction models -- Mammographic density; Gynecology -- Periodicals; Obstetrics -- Periodicals; Genital Diseases, Female; Obstetrics; Gynecology; Obstetrics; Periodicals; 618.05
• DOI: 10.1016/j.bpobgyn.2019.11.005
• Languages: English
• ISSNs: 1521-6934

Abstract

Abstract: The incidence of breast cancer continues to increase worldwide. Population-based screening is available in many countries but may not be the most efficient use of resources, thus interest in risk-based/stratified screening has grown significantly in recent years. An important part of risk-based screening is the incorporation of mammographic density (MD) and single nucleotide polymorphisms (SNPs) into risk prediction models to be combined with classical risk factors. In this article, we discuss different measures of MD and risk prediction models that are available. Risk-stratified screening options including supplemental or alternative screening modalities including digital breast tomosynthesis (DBT), automated ultrasound (ABUS) and magnetic resonance imaging (MRI) are discussed, as well as potential risk-based interventions (diet and lifestyle, chemoprevention and risk-reducing surgery). Furthermore, we look at risk feedback in practice and the cost-effectiveness and acceptability of risk-based screening, highlighting some of the current challenges. Highlights: Current "one-size-fits-all" approach to breast screening may be suboptimal. Risk-based screening could optimize benefits while minimizing harms. Risk-based models are practical tools that can be used in the clinical setting. Preventative options are recommended for those at increased risk.