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Breast cancer risk prediction in women aged 35-50 years: impact of including sex hormone concentrations in the Gail model
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2019 (English)In: Breast Cancer Research, ISSN 1465-5411, E-ISSN 1465-542X, Vol. 21, article id 42Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
BioMed Central, 2019. Vol. 21, article id 42
Keywords [en]
Breast cancer risk prediction, Anti-Mullerian hormone, Testosterone, Gail model
National Category
Cancer and Oncology
Identifiers
URN: urn:nbn:se:umu:diva-157955DOI: 10.1186/s13058-019-1126-zISI: 000462251300001PubMedID: 30890167OAI: oai:DiVA.org:umu-157955DiVA, id: diva2:1305532
Available from: 2019-04-17 Created: 2019-04-17 Last updated: 2019-08-26Bibliographically approved

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Publisher's full textPubMedhttps://breast-cancer-research.biomedcentral.com/articles/10.1186/s13058-019-1126-z

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Hallmans, Göran

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