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Should Age-Dependent Absolute Risk Thresholds Be Used for Risk Stratification in Risk-Stratified Breast Cancer Screening?

Published version
Peer-reviewed

Type

Article

Change log

Authors

Pashayan, Nora 
Antoniou, Antonis C 
Wolfson, Michael 
Chiquette, Jocelyne 

Abstract

In risk-stratified cancer screening, multiple risk factors are incorporated into the risk assessment. An individual's estimated absolute cancer risk is linked to risk categories with tailored screening recommendations for each risk category. Absolute risk, expressed as either remaining lifetime risk or shorter-term (five- or ten-year) risk, is estimated from the age at assessment. These risk estimates vary by age; however, some clinical guidelines (e.g., enhanced breast cancer surveillance guidelines) and ongoing personalised breast screening trials, stratify women based on absolute risk thresholds that do not vary by age. We examine an alternative approach in which the risk thresholds used for risk stratification vary by age and consider the implications of using age-independent risk thresholds on risk stratification. We demonstrate that using an age-independent remaining lifetime risk threshold approach could identify high-risk younger women but would miss high-risk older women, whereas an age-independent 5-year or 10-year absolute risk threshold could miss high-risk younger women and classify lower-risk older women as high risk. With risk misclassification, women with an equivalent risk level would be offered a different screening plan. To mitigate these problems, age-dependent absolute risk thresholds should be used to inform risk stratification.

Description

Keywords

absolute risk, misclassification, remaining lifetime risk, risk threshold, risk-stratified screening

Journal Title

Journal of Personalized Medicine

Conference Name

Journal ISSN

2075-4426
2075-4426

Volume Title

11

Publisher

MDPI AG
Sponsorship
Cancer Research UK (20861)
This research was funded as part of the PERSPECTIVE I&I study by the Government of Canada through Genome Canada (#13529) and the Canadian Institutes of Health Research (#155865), the Ministère de l’Économie et de l’Innovation du Québec through Genome Québec, the Quebec Breast Cancer Foundation, the CHU de Quebec Foundation and the Ontario Research Fund. A.C.A. and A.L. are supported by grants from Cancer Research UK (C12292/A20861 and PPRPGM-Nov20\100002).