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Addition of a polygenic risk score, mammographic density, and endogenous hormones to existing breast cancer risk prediction models: A nested case–control study

Author

Listed:
  • Xuehong Zhang
  • Megan Rice
  • Shelley S Tworoger
  • Bernard A Rosner
  • A Heather Eliassen
  • Rulla M Tamimi
  • Amit D Joshi
  • Sara Lindstrom
  • Jing Qian
  • Graham A Colditz
  • Walter C Willett
  • Peter Kraft
  • Susan E Hankinson

Abstract

Background: No prior study to our knowledge has examined the joint contribution of a polygenic risk score (PRS), mammographic density (MD), and postmenopausal endogenous hormone levels—all well-confirmed risk factors for invasive breast cancer—to existing breast cancer risk prediction models. Methods and findings: We conducted a nested case–control study within the prospective Nurses’ Health Study and Nurses’ Health Study II including 4,006 cases and 7,874 controls ages 34–70 years up to 1 June 2010. We added a breast cancer PRS using 67 single nucleotide polymorphisms, MD, and circulating testosterone, estrone sulfate, and prolactin levels to existing risk models. We calculated area under the curve (AUC), controlling for age and stratified by menopausal status, for the 5-year absolute risk of invasive breast cancer. We estimated the population distribution of 5-year predicted risks for models with and without biomarkers. For the Gail model, the AUC improved (p-values

Suggested Citation

  • Xuehong Zhang & Megan Rice & Shelley S Tworoger & Bernard A Rosner & A Heather Eliassen & Rulla M Tamimi & Amit D Joshi & Sara Lindstrom & Jing Qian & Graham A Colditz & Walter C Willett & Peter Kraft, 2018. "Addition of a polygenic risk score, mammographic density, and endogenous hormones to existing breast cancer risk prediction models: A nested case–control study," PLOS Medicine, Public Library of Science, vol. 15(9), pages 1-16, September.
    • Handle: RePEc:plo:pmed00:1002644
    DOI: 10.1371/journal.pmed.1002644
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    1. Yong-Qiao He & Tong-Min Wang & Mingfang Ji & Zhi-Ming Mai & Minzhong Tang & Ruozheng Wang & Yifeng Zhou & Yuming Zheng & Ruowen Xiao & Dawei Yang & Ziyi Wu & Changmi Deng & Jiangbo Zhang & Wenqiong Xu, 2022. "A polygenic risk score for nasopharyngeal carcinoma shows potential for risk stratification and personalized screening," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    2. Javier Louro & Marta Román & Margarita Posso & Ivonne Vázquez & Francina Saladié & Ana Rodriguez-Arana & M Jesús Quintana & Laia Domingo & Marisa Baré & Rafael Marcos-Gragera & María Vernet-Tomas & Ma, 2021. "Developing and validating an individualized breast cancer risk prediction model for women attending breast cancer screening," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-14, March.

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