Prospective validation of the BOADICEA multifactorial breast cancer risk prediction model in a large prospective cohort study.
genetic counseling
public health
women's health
Journal
Journal of medical genetics
ISSN: 1468-6244
Titre abrégé: J Med Genet
Pays: England
ID NLM: 2985087R
Informations de publication
Date de publication:
12 2022
12 2022
Historique:
received:
05
07
2022
accepted:
24
08
2022
pubmed:
27
9
2022
medline:
25
11
2022
entrez:
26
9
2022
Statut:
ppublish
Résumé
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. 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: 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%). The multifactorial BOADICEA model provides valid breast cancer risk predictions and a basis for personalised decision-making on disease prevention and screening.
Sections du résumé
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:
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.
Identifiants
pubmed: 36162852
pii: jmg-2022-108806
doi: 10.1136/jmg-2022-108806
pmc: PMC9691822
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1196-1205Subventions
Organisme : Cancer Research UK
ID : C12292/A20861
Pays : United Kingdom
Organisme : Cancer Research UK
ID : PPRPGM-NOV20\100002
Pays : United Kingdom
Organisme : CIHR
ID : 155865
Pays : Canada
Organisme : Department of Health
Pays : United Kingdom
Informations de copyright
© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.
Déclaration de conflit d'intérêts
Competing interests: ACA, DFE and AL are named inventors of BOADICEA V.5 licensed by Cambridge Enterprise. All remaining authors have declared no conflicts of interest.
Références
PLoS Genet. 2009 Jul;5(7):e1000540
pubmed: 19584936
J Med Genet. 2022 Dec;59(12):1206-1218
pubmed: 36162851
JAMA. 2019 Sep 3;322(9):857-867
pubmed: 31479144
Radiology. 2020 Nov;297(2):327-333
pubmed: 32897160
J Natl Cancer Inst. 2003 Apr 2;95(7):526-32
pubmed: 12671020
Cancer Epidemiol Biomarkers Prev. 2006 Jun;15(6):1159-69
pubmed: 16775176
Stat Med. 2012 Jul 10;31(15):1543-53
pubmed: 22344892
Int J Epidemiol. 2017 Dec 1;46(6):1740-1741g
pubmed: 28180256
J Natl Cancer Inst. 2020 Dec 14;112(12):1242-1250
pubmed: 32107557
Nature. 2017 May 11;545(7653):175-180
pubmed: 28467829
BMC Public Health. 2019 May 2;19(1):495
pubmed: 31046737
Genet Med. 2019 Aug;21(8):1708-1718
pubmed: 30643217
Diagn Interv Imaging. 2017 Mar;98(3):179-190
pubmed: 28131457
Cancer Epidemiol Biomarkers Prev. 2021 Mar;30(3):469-473
pubmed: 33335023
J Clin Oncol. 2013 Aug 10;31(23):2942-62
pubmed: 23835710
Br J Cancer. 2013 Sep 3;109(5):1296-301
pubmed: 23942072
PLoS One. 2020 Feb 5;15(2):e0228198
pubmed: 32023287
Biom J. 2015 Jul;57(4):592-613
pubmed: 25530064
N Engl J Med. 2015 Jan 29;372(5):436-46
pubmed: 25495490
Nat Med. 2022 Apr;28(4):666-677
pubmed: 35440720
N Engl J Med. 2021 Feb 4;384(5):428-439
pubmed: 33471991
Lancet Oncol. 2019 Apr;20(4):504-517
pubmed: 30799262
Nat Commun. 2020 Nov 27;11(1):6084
pubmed: 33247094
JAMA Oncol. 2016 Oct 01;2(10):1295-1302
pubmed: 27228256
Am J Hum Genet. 2019 Jan 3;104(1):21-34
pubmed: 30554720
J Natl Cancer Inst. 2006 Apr 19;98(8):535-44
pubmed: 16622123
Breast Cancer Res Treat. 2018 Jun;169(2):371-379
pubmed: 29392583
Int J Epidemiol. 2022 Jan 6;50(6):1897-1911
pubmed: 34999890
Ann Intern Med. 2008 Mar 4;148(5):337-47
pubmed: 18316752
Stat Med. 1996 Feb 28;15(4):361-87
pubmed: 8668867
JNCI Cancer Spectr. 2021 Mar 02;5(3):
pubmed: 33977228
J Natl Cancer Inst. 2001 Mar 7;93(5):358-66
pubmed: 11238697
Breast Cancer Res. 2017 Mar 14;19(1):29
pubmed: 28288659
Breast J. 2015 Sep-Oct;21(5):481-9
pubmed: 26133090
Genet Med. 2017 May;19(5):599-603
pubmed: 27711073
Cancer Epidemiol Biomarkers Prev. 2007 Apr;16(4):740-6
pubmed: 17416765
Nat Rev Clin Oncol. 2020 Nov;17(11):687-705
pubmed: 32555420
J Natl Cancer Inst. 2020 Apr 1;112(4):391-399
pubmed: 31298705
J Natl Cancer Inst. 2014 Nov 12;106(11):
pubmed: 25392194
J Pers Med. 2021 Jun 04;11(6):
pubmed: 34199804
Br J Cancer. 2008 Apr 22;98(8):1457-66
pubmed: 18349832
Int J Cancer. 2019 Aug 15;145(4):994-1006
pubmed: 30762235
Genet Med. 2016 Dec;18(12):1190-1198
pubmed: 27464310
Breast Cancer Res. 2021 Feb 15;23(1):22
pubmed: 33588869
Genet Med. 2020 Oct;22(10):1653-1666
pubmed: 32665703
Nat Rev Genet. 2018 Sep;19(9):581-590
pubmed: 29789686
J Clin Oncol. 2007 Sep 1;25(25):3831-6
pubmed: 17635951