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Prospective validation of the BOADICEA multifactorial breast cancer risk prediction model in a large prospective cohort study.

Published version
Peer-reviewed

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Authors

Eriksson, Mikael 
Czene, Kamila 
Leslie, Goska 

Abstract

BACKGROUND: The multifactorial Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) breast cancer risk prediction model has been recently extended to consider all established breast cancer risk factors. We assessed the clinical validity of the model in a large independent prospective cohort. METHODS: We validated BOADICEA (V.6) in the Swedish KARolinska Mammography Project for Risk Prediction of Breast Cancer (KARMA) cohort including 66 415 women of European ancestry (median age 54 years, IQR 45-63; 816 incident breast cancers) without previous cancer diagnosis. We calculated 5-year risks on the basis of questionnaire-based risk factors, pedigree-structured first-degree family history, mammographic density (BI-RADS), a validated breast cancer polygenic risk score (PRS) based on 313-SNPs, and pathogenic variant status in 8 breast cancer susceptibility genes: BRCA1, BRCA2, PALB2, CHEK2, ATM, RAD51C, RAD51D and BARD1. Calibration was assessed by comparing observed and expected risks in deciles of predicted risk and the calibration slope. The discriminatory ability was assessed using the area under the curve (AUC). RESULTS: Among the individual model components, the PRS contributed most to breast cancer risk stratification. BOADICEA was well calibrated in predicting the risks for low-risk and high-risk women when all, or subsets of risk factors are included in the risk prediction. Discrimination was maximised when all risk factors are considered (AUC=0.70, 95% CI: 0.66 to 0.73; expected-to-observed ratio=0.88, 95% CI: 0.75 to 1.04; calibration slope=0.97, 95% CI: 0.95 to 0.99). The full multifactorial model classified 3.6% women as high risk (5-year risk ≥3%) and 11.1% as very low risk (5-year risk <0.33%). CONCLUSION: The multifactorial BOADICEA model provides valid breast cancer risk predictions and a basis for personalised decision-making on disease prevention and screening.

Description

Peer reviewed: True


Acknowledgements: We would like to thank all the participants, clinicians and other healthcare professionals who have contributed to the KARMA cohort.


Funder: CHU de Quebec


Funder: NIHR Cambridge Biomedical Research Centre


Funder: Quebec Breast Cancer Foundation


Funder: Ontario Research Fund


Funder: the Märit and Hans Rausing’s Initiative Against Breast Cancer

Keywords

genetic counseling, public health, women's health, Female, Humans, Middle Aged, Breast Neoplasms, Genes, BRCA2, Genetic Predisposition to Disease, Prospective Studies, Risk Assessment

Journal Title

J Med Genet

Conference Name

Journal ISSN

0022-2593
1468-6244

Volume Title

Publisher

BMJ
Sponsorship
Cancer Research UK (20861)
European Commission Horizon 2020 (H2020) Societal Challenges (634935)
European Commission Horizon 2020 (H2020) Societal Challenges (633784)
Cancer Research UK (SEBINT-20100002)