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J Clin Oncol. 2014 Oct 1;32(28):3111-7. doi: 10.1200/JCO.2014.56.1068. Epub 2014 Aug 18.

Inclusion of endogenous hormone levels in risk prediction models of postmenopausal breast cancer.

Author information

1
Shelley S. Tworoger, Xuehong Zhang, A. Heather Eliassen, Walter C. Willett, Bernard A. Rosner, and Susan E. Hankinson, Brigham and Women's Hospital and Harvard Medical School; Shelley S. Tworoger, Xuehong Zhang, A. Heather Eliassen, Walter C. Willett, Bernard A. Rosner, Peter Kraft, and Susan E. Hankinson, Harvard School of Public Health, Boston; Jing Qian and Susan E. Hankinson, School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA; and Graham A. Colditz, Washington University School of Medicine, St Louis, MO. nhsst@channing.harvard.edu.
2
Shelley S. Tworoger, Xuehong Zhang, A. Heather Eliassen, Walter C. Willett, Bernard A. Rosner, and Susan E. Hankinson, Brigham and Women's Hospital and Harvard Medical School; Shelley S. Tworoger, Xuehong Zhang, A. Heather Eliassen, Walter C. Willett, Bernard A. Rosner, Peter Kraft, and Susan E. Hankinson, Harvard School of Public Health, Boston; Jing Qian and Susan E. Hankinson, School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA; and Graham A. Colditz, Washington University School of Medicine, St Louis, MO.

Abstract

PURPOSE:

Endogenous hormones are risk factors for postmenopausal breast cancer, and their measurement may improve our ability to identify high-risk women. Therefore, we evaluated whether inclusion of plasma estradiol, estrone, estrone sulfate, testosterone, dehydroepiandrosterone sulfate, prolactin, and sex hormone-binding globulin (SHBG) improved risk prediction for postmenopausal invasive breast cancer (n = 437 patient cases and n = 775 controls not using postmenopausal hormones) in the Nurses' Health Study.

METHODS:

We evaluated improvement in the area under the curve (AUC) for 5-year risk of invasive breast cancer by adding each hormone to the Gail and Rosner-Colditz risk scores. We used stepwise regression to identify the subset of hormones most associated with risk and assessed AUC improvement; we used 10-fold cross validation to assess model overfitting.

RESULTS:

Each hormone was associated with breast cancer risk (odds ratio doubling, 0.82 [SHBG] to 1.37 [estrone sulfate]). Individual hormones improved the AUC by 1.3 to 5.2 units relative to the Gail score and 0.3 to 2.9 for the Rosner-Colditz score. Estrone sulfate, testosterone, and prolactin were selected by stepwise regression and increased the AUC by 5.9 units (P = .003) for the Gail score and 3.4 (P = .04) for the Rosner-Colditz score. In cross validation, the average AUC change across the validation data sets was 6.0 (P = .002) and 3.0 units (P = .03), respectively. Similar results were observed for estrogen receptor-positive disease (selected hormones: estrone sulfate, testosterone, prolactin, and SHBG; change in AUC, 8.8 [P < .001] for Gail score and 5.8 [P = .004] for Rosner-Colditz score).

CONCLUSION:

Our results support that endogenous hormones improve risk prediction for invasive breast cancer and could help identify women who may benefit from chemoprevention or more screening.

PMID:
25135988
PMCID:
PMC4171356
DOI:
10.1200/JCO.2014.56.1068
[Indexed for MEDLINE]
Free PMC Article

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