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

Author:

Olsen MariaORCID,Fischer Krista,Bossuyt Patrick M.,Goetghebeur Els

Abstract

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.

Funder

H2020 Marie Skłodowska-Curie Actions

Estonian Research Competency Council

Publisher

Springer Science and Business Media LLC

Subject

Cancer Research,Genetics,Oncology

Reference48 articles.

1. American Cancer Society. Cancer Facts and Figures. Atlanta Am Cancer Soc. 2020:2020.

2. Recommendations from European Breast Guidelines [Internet]. European Commission initiative on breast cancer. Available from: https://ecibc.jrc.ec.europa.eu/recommendations/. Accessed 13 Mar 2019.

3. 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.

4. The National Health Service (NHS). Breast cancer screening [Internet]. Available from: https://www.nhs.uk/conditions/breast-cancer-screening/. Accessed 16 May 2020

5. Marmot M, Altman DG, Cameron DA, Dewar JA, Thompson SG, Wilcox M. The benefits and harms of breast cancer screening: an independent review. Lancet. 2012;380(9855):1778–86. https://doi.org/10.1016/S0140-6736(12)61611-0.

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