Implementing Multifactorial Risk Assessment with Polygenic Risk Scores for Personalized Breast Cancer Screening in the Population Setting: Challenges and Opportunities Article Swipe
Meghan J. Walker
,
Kristina M. Blackmore
,
Amy Chang
,
Laurence Lambert-Côté
,
Annie Turgeon
,
Antonis C. Antoniou
,
Kathleen A. Bell
,
Mireille J. M. Broeders
,
Jennifer D. Brooks
,
Tim Carver
,
Jocelyne Chiquette
,
Philippe Després
,
Douglas F. Easton
,
Andrea Eisen
,
Laurence Eloy
,
D. Gareth Evans
,
Samantha Fienberg
,
Yann Joly
,
Raymond H. Kim
,
Shana J. Kim
,
Bartha Maria Knoppers
,
Aïsha Lofters
,
Hermann Nabi
,
Jean‐Sébastien Paquette
,
Nora Pashayan
,
Amanda J. Sheppard
,
Tracy Stockley
,
Michel Dorval
,
Jacques Simard
,
Anna M. Chiarelli
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/cancers16112116
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/cancers16112116
Risk-stratified breast screening has been proposed as a strategy to overcome the limitations of age-based screening. A prospective cohort study was undertaken within the PERSPECTIVE I&I project, which will generate the first Canadian evidence on multifactorial breast cancer risk assessment in the population setting to inform the implementation of risk-stratified screening. Recruited females aged 40–69 unaffected by breast cancer, with a previous mammogram, underwent multifactorial breast cancer risk assessment. The adoption of multifactorial risk assessment, the effectiveness of methods for collecting risk factor information and the costs of risk assessment were examined. Associations between participant characteristics and study sites, as well as data collection methods, were assessed using logistic regression; all p-values are two-sided. Of the 4246 participants recruited, 88.4% completed a risk assessment, with 79.8%, 15.7% and 4.4% estimated at average, higher than average and high risk, respectively. The total per-participant cost for risk assessment was CAD 315. Participants who chose to provide risk factor information on paper/telephone (27.2%) vs. online were more likely to be older (p = 0.021), not born in Canada (p = 0.043), visible minorities (p = 0.01) and have a lower attained education (p < 0.0001) and perceived fair/poor health (p < 0.001). The 34.4% of participants requiring risk factor verification for missing/unusual values were more likely to be visible minorities (p = 0.009) and have a lower attained education (p ≤ 0.006). This study demonstrates the feasibility of risk assessment for risk-stratified screening at the population level. Implementation should incorporate an equity lens to ensure cancer-screening disparities are not widened.
Related Topics
Concepts
Polygenic risk score
Breast cancer
Medicine
Risk assessment
Population
Oncology
Cancer
Internal medicine
Computer science
Environmental health
Biology
Genetics
Genotype
Single-nucleotide polymorphism
Gene
Computer security
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/cancers16112116
- https://www.mdpi.com/2072-6694/16/11/2116/pdf?version=1717171184
- OA Status
- gold
- Cited By
- 14
- References
- 35
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4399298302
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4399298302Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/cancers16112116Digital Object Identifier
- Title
-
Implementing Multifactorial Risk Assessment with Polygenic Risk Scores for Personalized Breast Cancer Screening in the Population Setting: Challenges and OpportunitiesWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-05-31Full publication date if available
- Authors
-
Meghan J. Walker, Kristina M. Blackmore, Amy Chang, Laurence Lambert-Côté, Annie Turgeon, Antonis C. Antoniou, Kathleen A. Bell, Mireille J. M. Broeders, Jennifer D. Brooks, Tim Carver, Jocelyne Chiquette, Philippe Després, Douglas F. Easton, Andrea Eisen, Laurence Eloy, D. Gareth Evans, Samantha Fienberg, Yann Joly, Raymond H. Kim, Shana J. Kim, Bartha Maria Knoppers, Aïsha Lofters, Hermann Nabi, Jean‐Sébastien Paquette, Nora Pashayan, Amanda J. Sheppard, Tracy Stockley, Michel Dorval, Jacques Simard, Anna M. ChiarelliList of authors in order
- Landing page
-
https://doi.org/10.3390/cancers16112116Publisher landing page
- PDF URL
-
https://www.mdpi.com/2072-6694/16/11/2116/pdf?version=1717171184Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2072-6694/16/11/2116/pdf?version=1717171184Direct OA link when available
- Concepts
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Polygenic risk score, Breast cancer, Medicine, Risk assessment, Population, Oncology, Cancer, Internal medicine, Computer science, Environmental health, Biology, Genetics, Genotype, Single-nucleotide polymorphism, Gene, Computer securityTop concepts (fields/topics) attached by OpenAlex
- Cited by
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14Total citation count in OpenAlex
- Citations by year (recent)
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2025: 13, 2024: 1Per-year citation counts (last 5 years)
- References (count)
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35Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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