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Published in: BMC Cancer 1/2021

01-12-2021 | Breast Cancer | Research article

Evaluating the prognostic performance of a polygenic risk score for breast cancer risk stratification

Authors: Maria Olsen, Krista Fischer, Patrick M. Bossuyt, Els Goetghebeur

Published in: BMC Cancer | Issue 1/2021

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Abstract

Background

Polygenic risk scores (PRS) could potentially improve breast cancer screening recommendations. Before a PRS can be considered for implementation, it needs rigorous evaluation, using performance measures that can inform about its future clinical value.

Objectives

To evaluate the prognostic performance of a regression model with a previously developed, prevalence-based PRS and age as predictors for breast cancer incidence in women from the Estonian biobank (EstBB) cohort; to compare it to the performance of a model including age only.

Methods

We analyzed data on 30,312 women from the EstBB cohort. They entered the cohort between 2002 and 2011, were between 20 and 89 years, without a history of breast cancer, and with full 5-year follow-up by 2015. We examined PRS and other potential risk factors as possible predictors in Cox regression models for breast cancer incidence. With 10-fold cross-validation we estimated 3- and 5-year breast cancer incidence predicted by age alone and by PRS plus age, fitting models on 90% of the data. Calibration, discrimination, and reclassification were calculated on the left-out folds to express prognostic performance.

Results

A total of 101 (3.33‰) and 185 (6.1‰) incident breast cancers were observed within 3 and 5 years, respectively. For women in a defined screening age of 50–62 years, the ratio of observed vs PRS-age modelled 3-year incidence was 0.86 for women in the 75–85% PRS-group, 1.34 for the 85–95% PRS-group, and 1.41 for the top 5% PRS-group. For 5-year incidence, this was respectively 0.94, 1.15, and 1.08. Yet the number of breast cancer events was relatively low in each PRS-subgroup. For all women, the model’s AUC was 0.720 (95% CI: 0.675–0.765) for 3-year and 0.704 (95% CI: 0.670–0.737) for 5-year follow-up, respectively, just 0.022 and 0.023 higher than for the model with age alone. Using a 1% risk prediction threshold, the 3-year NRI for the PRS-age model was 0.09, and 0.05 for 5 years.

Conclusion

The model including PRS had modest incremental performance over one based on age only. A larger, independent study is needed to assess whether and how the PRS can meaningfully contribute to age, for developing more efficient screening strategies.
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Literature
1.
go back to reference American Cancer Society. Cancer Facts and Figures. Atlanta Am Cancer Soc. 2020:2020. American Cancer Society. Cancer Facts and Figures. Atlanta Am Cancer Soc. 2020:2020.
3.
go back to reference Nelson HD, Cantor A, Humphrey L, Fu R, Pappas M, Daeges M, et al. Screening for breast Cancer: a systematic review to update the 2009 U.S. preventive services task force recommendation. Evid Synth. 2016;124:1–277. Nelson HD, Cantor A, Humphrey L, Fu R, Pappas M, Daeges M, et al. Screening for breast Cancer: a systematic review to update the 2009 U.S. preventive services task force recommendation. Evid Synth. 2016;124:1–277.
8.
go back to reference Gøtzsche PC, Jørgensen KJ. Screening for breast cancer with mammography. Cochrane Database Syst Rev. 2013;(6):CD001877. Gøtzsche PC, Jørgensen KJ. Screening for breast cancer with mammography. Cochrane Database Syst Rev. 2013;(6):CD001877.
10.
go back to reference Paluch-Shimon S, Cardoso F, Sessa C, Balmana J, Cardoso MJ, Gilbert F, et al. Prevention and screening in BRCA mutation carriers and other breast/ovarian hereditary cancer syndromes: ESMO clinical practice guidelines for cancer prevention and screening. Ann Oncol. 2016;27(suppl 5):v103–10. https://doi.org/10.1093/annonc/mdw327.CrossRefPubMed Paluch-Shimon S, Cardoso F, Sessa C, Balmana J, Cardoso MJ, Gilbert F, et al. Prevention and screening in BRCA mutation carriers and other breast/ovarian hereditary cancer syndromes: ESMO clinical practice guidelines for cancer prevention and screening. Ann Oncol. 2016;27(suppl 5):v103–10. https://​doi.​org/​10.​1093/​annonc/​mdw327.CrossRefPubMed
12.
go back to reference Anglian Breast Cancer Study Group. Prevalence and penetrance of BRCA1 and BRCA2 mutations in a population-based series of breast cancer cases. Br J Cancer. 2002;83:1301–8. Anglian Breast Cancer Study Group. Prevalence and penetrance of BRCA1 and BRCA2 mutations in a population-based series of breast cancer cases. Br J Cancer. 2002;83:1301–8.
21.
go back to reference Mavaddat N, PDP P, Michailidou K, Tyrer J, Brook MN, Bolla MK, et al. Prediction of Breast Cancer Risk Based on Profiling With Common Genetic Variants. J Natl Cancer Inst. 2015;107:36.CrossRef Mavaddat N, PDP P, Michailidou K, Tyrer J, Brook MN, Bolla MK, et al. Prediction of Breast Cancer Risk Based on Profiling With Common Genetic Variants. J Natl Cancer Inst. 2015;107:36.CrossRef
44.
go back to reference BBMRI.ee: Estonian Biobank has now recruited over 200,000 biobank participants and all will be genotyped by June 2020. University of Tartu Institute of Genomics [Internet]. Available from: https://genomics.ut.ee/en/news. Accessed on 20 Oct 2020 BBMRI.ee: Estonian Biobank has now recruited over 200,000 biobank participants and all will be genotyped by June 2020. University of Tartu Institute of Genomics [Internet]. Available from: https://​genomics.​ut.​ee/​en/​news. Accessed on 20 Oct 2020
Metadata
Title
Evaluating the prognostic performance of a polygenic risk score for breast cancer risk stratification
Authors
Maria Olsen
Krista Fischer
Patrick M. Bossuyt
Els Goetghebeur
Publication date
01-12-2021
Publisher
BioMed Central
Published in
BMC Cancer / Issue 1/2021
Electronic ISSN: 1471-2407
DOI
https://doi.org/10.1186/s12885-021-08937-8

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