Predicting risk of breast cancer in postmenopausal women by hormone receptor status

Rowan T. Chlebowski, Garnet L. Anderson, Dorothy S. Lane, Aaron K. Aragaki, Thomas E. Rohan, Shagufta Yasmeen, Gloria Sarto, Carol A. Rosenberg, F. Allan Hubbell

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Abstract

Background: Strategies for estrogen receptor (ER)-positive breast cancer risk reduction in postmenopausal women require screening of large populations to identify those with potential benefit. We evaluated and attempted to improve the performance of the Breast Cancer Risk Assessment Tool (i.e., the Gail model) for estimating invasive breast cancer risk by receptor status in postmenopausal women. Methods: In The Women's Health Initiative cohort, breast cancer risk estimates from the Gail model and models incorporating additional or fewer risk factors and 5-year incidence of ER-positive and ER-negative invasive breast cancers were determined and compared by use of receiver operating characteristics and area under the curve (AUC) statistics. All statistical tests were two-sided. Results: Among 147 916 eligible women, 3236 were diagnosed with invasive breast cancer. The overall AUC for the Gail model was 0.58 (95% confidence interval [CI]=0.56 to 0.60). The Gail model underestimated 5-year invasive breast cancer incidence by approximately 20% (P<.001), mostly among those with a low estimated risk. Discriminatory performance was better for the risk of ER-positive cancer (AUC = 0.60, 95% CI = 0.58 to 0.62) than for the risk of ER-negative cancer (AUC = 0.50, 95% CI = 0.45 to 0.54). Age and age at menopause were statistically significantly associated with ER-positive but not ER-negative cancers (P=.05 and P=.04 for heterogeneity, respectively). For ER-positive cancers, no additional risk factors substantially improved the Gail model prediction. However, a simpler model that included only age, breast cancer in first-degree relatives, and previous breast biopsy examination performed similarly for ER-positive breast cancer prediction (AUC=0.58, 95% CI= 0.56 to 0.60); postmenopausal women who were 55 years or older with either a previous breast biopsy examination or a family history of breast cancer had a 5-year breast cancer risk of 1.8% or higher. Conclusions: In postmenopausal women, the Gail model identified populations at increased risk for ER-positive but not ER-negative breast cancers. A model with fewer variables appears to provide a simpler approach for screening for breast cancer risk.

Original languageEnglish (US)
Pages (from-to)1695-1705
Number of pages11
JournalJournal of the National Cancer Institute
Volume99
Issue number22
DOIs
StatePublished - Nov 2007

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Estrogen Receptors
Hormones
Breast Neoplasms
Area Under Curve
Confidence Intervals
Neoplasms
Breast
Biopsy
Incidence
Women's Health
Risk Reduction Behavior
Menopause
ROC Curve

ASJC Scopus subject areas

  • Cancer Research
  • Oncology

Cite this

Chlebowski, R. T., Anderson, G. L., Lane, D. S., Aragaki, A. K., Rohan, T. E., Yasmeen, S., ... Hubbell, F. A. (2007). Predicting risk of breast cancer in postmenopausal women by hormone receptor status. Journal of the National Cancer Institute, 99(22), 1695-1705. https://doi.org/10.1093/jnci/djm224

Predicting risk of breast cancer in postmenopausal women by hormone receptor status. / Chlebowski, Rowan T.; Anderson, Garnet L.; Lane, Dorothy S.; Aragaki, Aaron K.; Rohan, Thomas E.; Yasmeen, Shagufta; Sarto, Gloria; Rosenberg, Carol A.; Hubbell, F. Allan.

In: Journal of the National Cancer Institute, Vol. 99, No. 22, 11.2007, p. 1695-1705.

Research output: Contribution to journalArticle

Chlebowski, RT, Anderson, GL, Lane, DS, Aragaki, AK, Rohan, TE, Yasmeen, S, Sarto, G, Rosenberg, CA & Hubbell, FA 2007, 'Predicting risk of breast cancer in postmenopausal women by hormone receptor status', Journal of the National Cancer Institute, vol. 99, no. 22, pp. 1695-1705. https://doi.org/10.1093/jnci/djm224
Chlebowski, Rowan T. ; Anderson, Garnet L. ; Lane, Dorothy S. ; Aragaki, Aaron K. ; Rohan, Thomas E. ; Yasmeen, Shagufta ; Sarto, Gloria ; Rosenberg, Carol A. ; Hubbell, F. Allan. / Predicting risk of breast cancer in postmenopausal women by hormone receptor status. In: Journal of the National Cancer Institute. 2007 ; Vol. 99, No. 22. pp. 1695-1705.
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abstract = "Background: Strategies for estrogen receptor (ER)-positive breast cancer risk reduction in postmenopausal women require screening of large populations to identify those with potential benefit. We evaluated and attempted to improve the performance of the Breast Cancer Risk Assessment Tool (i.e., the Gail model) for estimating invasive breast cancer risk by receptor status in postmenopausal women. Methods: In The Women's Health Initiative cohort, breast cancer risk estimates from the Gail model and models incorporating additional or fewer risk factors and 5-year incidence of ER-positive and ER-negative invasive breast cancers were determined and compared by use of receiver operating characteristics and area under the curve (AUC) statistics. All statistical tests were two-sided. Results: Among 147 916 eligible women, 3236 were diagnosed with invasive breast cancer. The overall AUC for the Gail model was 0.58 (95{\%} confidence interval [CI]=0.56 to 0.60). The Gail model underestimated 5-year invasive breast cancer incidence by approximately 20{\%} (P<.001), mostly among those with a low estimated risk. Discriminatory performance was better for the risk of ER-positive cancer (AUC = 0.60, 95{\%} CI = 0.58 to 0.62) than for the risk of ER-negative cancer (AUC = 0.50, 95{\%} CI = 0.45 to 0.54). Age and age at menopause were statistically significantly associated with ER-positive but not ER-negative cancers (P=.05 and P=.04 for heterogeneity, respectively). For ER-positive cancers, no additional risk factors substantially improved the Gail model prediction. However, a simpler model that included only age, breast cancer in first-degree relatives, and previous breast biopsy examination performed similarly for ER-positive breast cancer prediction (AUC=0.58, 95{\%} CI= 0.56 to 0.60); postmenopausal women who were 55 years or older with either a previous breast biopsy examination or a family history of breast cancer had a 5-year breast cancer risk of 1.8{\%} or higher. Conclusions: In postmenopausal women, the Gail model identified populations at increased risk for ER-positive but not ER-negative breast cancers. A model with fewer variables appears to provide a simpler approach for screening for breast cancer risk.",
author = "Chlebowski, {Rowan T.} and Anderson, {Garnet L.} and Lane, {Dorothy S.} and Aragaki, {Aaron K.} and Rohan, {Thomas E.} and Shagufta Yasmeen and Gloria Sarto and Rosenberg, {Carol A.} and Hubbell, {F. Allan}",
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AU - Chlebowski, Rowan T.

AU - Anderson, Garnet L.

AU - Lane, Dorothy S.

AU - Aragaki, Aaron K.

AU - Rohan, Thomas E.

AU - Yasmeen, Shagufta

AU - Sarto, Gloria

AU - Rosenberg, Carol A.

AU - Hubbell, F. Allan

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N2 - Background: Strategies for estrogen receptor (ER)-positive breast cancer risk reduction in postmenopausal women require screening of large populations to identify those with potential benefit. We evaluated and attempted to improve the performance of the Breast Cancer Risk Assessment Tool (i.e., the Gail model) for estimating invasive breast cancer risk by receptor status in postmenopausal women. Methods: In The Women's Health Initiative cohort, breast cancer risk estimates from the Gail model and models incorporating additional or fewer risk factors and 5-year incidence of ER-positive and ER-negative invasive breast cancers were determined and compared by use of receiver operating characteristics and area under the curve (AUC) statistics. All statistical tests were two-sided. Results: Among 147 916 eligible women, 3236 were diagnosed with invasive breast cancer. The overall AUC for the Gail model was 0.58 (95% confidence interval [CI]=0.56 to 0.60). The Gail model underestimated 5-year invasive breast cancer incidence by approximately 20% (P<.001), mostly among those with a low estimated risk. Discriminatory performance was better for the risk of ER-positive cancer (AUC = 0.60, 95% CI = 0.58 to 0.62) than for the risk of ER-negative cancer (AUC = 0.50, 95% CI = 0.45 to 0.54). Age and age at menopause were statistically significantly associated with ER-positive but not ER-negative cancers (P=.05 and P=.04 for heterogeneity, respectively). For ER-positive cancers, no additional risk factors substantially improved the Gail model prediction. However, a simpler model that included only age, breast cancer in first-degree relatives, and previous breast biopsy examination performed similarly for ER-positive breast cancer prediction (AUC=0.58, 95% CI= 0.56 to 0.60); postmenopausal women who were 55 years or older with either a previous breast biopsy examination or a family history of breast cancer had a 5-year breast cancer risk of 1.8% or higher. Conclusions: In postmenopausal women, the Gail model identified populations at increased risk for ER-positive but not ER-negative breast cancers. A model with fewer variables appears to provide a simpler approach for screening for breast cancer risk.

AB - Background: Strategies for estrogen receptor (ER)-positive breast cancer risk reduction in postmenopausal women require screening of large populations to identify those with potential benefit. We evaluated and attempted to improve the performance of the Breast Cancer Risk Assessment Tool (i.e., the Gail model) for estimating invasive breast cancer risk by receptor status in postmenopausal women. Methods: In The Women's Health Initiative cohort, breast cancer risk estimates from the Gail model and models incorporating additional or fewer risk factors and 5-year incidence of ER-positive and ER-negative invasive breast cancers were determined and compared by use of receiver operating characteristics and area under the curve (AUC) statistics. All statistical tests were two-sided. Results: Among 147 916 eligible women, 3236 were diagnosed with invasive breast cancer. The overall AUC for the Gail model was 0.58 (95% confidence interval [CI]=0.56 to 0.60). The Gail model underestimated 5-year invasive breast cancer incidence by approximately 20% (P<.001), mostly among those with a low estimated risk. Discriminatory performance was better for the risk of ER-positive cancer (AUC = 0.60, 95% CI = 0.58 to 0.62) than for the risk of ER-negative cancer (AUC = 0.50, 95% CI = 0.45 to 0.54). Age and age at menopause were statistically significantly associated with ER-positive but not ER-negative cancers (P=.05 and P=.04 for heterogeneity, respectively). For ER-positive cancers, no additional risk factors substantially improved the Gail model prediction. However, a simpler model that included only age, breast cancer in first-degree relatives, and previous breast biopsy examination performed similarly for ER-positive breast cancer prediction (AUC=0.58, 95% CI= 0.56 to 0.60); postmenopausal women who were 55 years or older with either a previous breast biopsy examination or a family history of breast cancer had a 5-year breast cancer risk of 1.8% or higher. Conclusions: In postmenopausal women, the Gail model identified populations at increased risk for ER-positive but not ER-negative breast cancers. A model with fewer variables appears to provide a simpler approach for screening for breast cancer risk.

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