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Validation of the BOADICEA model and a 313-variant polygenic risk score for breast cancer risk prediction in a Dutch prospective cohort.

Inge M M Lakeman ,
Mar Rodríguez-Girondo ,
Andrew Lee ,
Rikje Ruiter ,
Bruno H Stricker ,
Sara R A Wijnant ,
Maryam Kavousi ,
Antonis C Antoniou ,
Marjanka K Schmidt ,
André G Uitterlinden ,
Jeroen van Rooij ,
Peter Devilee

Abstract

METHODS

Since 1989, 6522 women without BC aged 45 or older of European descent have been included in the Rotterdam Study. The PRS313 was calculated per 1 SD in controls from the Breast Cancer Association Consortium (BCAC). Cox regression analysis was performed to estimate the association between the PRS313 and incident BC risk. Cumulative 10-year risks were calculated with BOADICEA including different sets of variables (age, risk factors and PRS313). C-statistics were used to evaluate discriminative ability.

CONCLUSIONS

The effect size of the PRS313 is highly reproducible in the Dutch population. Our results validate the BOADICEA v5 model for BC risk assessment in the Dutch general population.

RESULTS

In total, 320 women developed BC. The PRS313 was significantly associated with BC (hazard ratio [HR] per SD of 1.56, 95% confidence interval [CI] [1.40-1.73]). Using 10-year risk estimates including age and the PRS313, other risk factors improved the discriminatory ability of the BOADICEA model marginally, from a C-statistic of 0.636 to 0.653.

PURPOSE

We evaluated the performance of the recently extended Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA version 5) in a Dutch prospective cohort, using a polygenic risk score (PRS) based on 313 breast cancer (BC)-associated variants (PRS313) and other, nongenetic risk factors.

More about this publication

Genetics in medicine : official journal of the American College of Medical Genetics

Volume 22
Issue nr. 11
Pages 1803-1811
Publication date 01-11-2020

Full text links

Publisher website (DOI) 10.1038/s41436-020-0884-4
Europe PubMed Central 32624571
Pubmed 32624571

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