Breast cancer risk prediction in women aged 35-50 years [Elektronisk resurs] impact of including sex hormone concentrations in the Gail model
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Clendenen, Tess V. (författare)
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Ge, Wenzhen (författare)
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Koenig, Karen L. (författare)
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Afanasyeva, Yelena (författare)
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Agnoli, Claudia (författare)
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Brinton, Louise A. (författare)
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Darvishian, Farbod (författare)
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Dorgan, Joanne F. (författare)
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Eliassen, A. Heather (författare)
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Falk, Roni T. (författare)
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Hallmans, Göran, 1947- (författare)
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Hankinson, Susan E. (författare)
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Hoffman-Bolton, Judith (författare)
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Key, Timothy J. (författare)
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Krogh, Vittorio (författare)
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Nichols, Hazel B. (författare)
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Sandler, Dale P. (författare)
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Schoemaker, Minouk J. (författare)
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Sluss, Patrick M. (författare)
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Sund, Malin (författare)
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Swerdlow, Anthony J. (författare)
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Visvanathan, Kala (författare)
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Zeleniuch-Jacquotte, Anne (författare)
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Liu, Mengling (författare)
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Umeå universitet Medicinska fakulteten (utgivare)
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Umeå universitet Medicinska fakulteten (utgivare)
- Publicerad: BioMed Central, 2019
- Engelska.
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Ingår i: Breast Cancer Research. - 1465-5411. ; 21
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- Relaterad länk:
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http://www.umu.se/ (Värdpublikation)
Sammanfattning
Ämnesord
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- Background: Models that accurately predict risk of breast cancer are needed to help younger women make decisions about when to begin screening. Premenopausal concentrations of circulating anti-Mullerian hormone (AMH), a biomarker of ovarian reserve, and testosterone have been positively associated with breast cancer risk in prospective studies. We assessed whether adding AMH and/or testosterone to the Gail model improves its prediction performance for women aged 35-50. Methods: In a nested case-control study including ten prospective cohorts (1762 invasive cases/1890 matched controls) with pre-diagnostic serum/plasma samples, we estimated relative risks (RR) for the biomarkers and Gail risk factors using conditional logistic regression and random-effects meta-analysis. Absolute risk models were developed using these RR estimates, attributable risk fractions calculated using the distributions of the risk factors in the cases from the consortium, and population-based incidence and mortality rates. The area under the receiver operating characteristic curve (AUC) was used to compare the discriminatory accuracy of the models with and without biomarkers. Results: The AUC for invasive breast cancer including only the Gail risk factor variables was 55.3 (95% CI 53.4, 57.1). The AUC increased moderately with the addition of AMH (AUC 57.6, 95% CI 55.7, 59.5), testosterone (AUC 56.2, 95% CI 54.4, 58.1), or both (AUC 58.1, 95% CI 56.2, 59.9). The largest AUC improvement (4.0) was among women without a family history of breast cancer. Conclusions: AMH and testosterone moderately increase the discriminatory accuracy of the Gail model among women aged 35-50. We observed the largest AUC increase for women without a family history of breast cancer, the group that would benefit most from improved risk prediction because early screening is already recommended for women with a family history.
Ämnesord
- Medical and Health Sciences (hsv)
- Clinical Medicine (hsv)
- Cancer and Oncology (hsv)
- Medicin och hälsovetenskap (hsv)
- Klinisk medicin (hsv)
- Cancer och onkologi (hsv)
Genre
- government publication (marcgt)
Indexterm och SAB-rubrik
- Breast cancer risk prediction
- Anti-Mullerian hormone
- Testosterone
- Gail model
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