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El-Bastawissi, Amira Y.; White, Emily; Mandelson, Margaret T.; Taplin, Stephen H.

doi:10.1023/a:1026514032085

Cited by 97 publications

(27 citation statements)

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“…A positive association between age at menarche and density was reported to be stronger in premenopausal women (El-Bastawissi et al , 2000; Vachon et al , 2000); in some studies (Vachon et al , 2000) these associations were attenuated in multivariate analyses. Hormone replacement therapy (HRT), older age at first child's birth, nulliparity, a family history of breast cancer, and alcohol consumption have been reported to be associated with increased breast density (Gram et al , 1995; El-Bastawissi et al , 2000; Vachon et al , 2000, 2002, 2005; Colacurci et al , 2001; Erel et al , 2001; Rutter et al , 2001; Gapstur et al , 2003; Ziv et al , 2003; Conner et al , 2004; Harvey et al , 2005; Boyd et al , 2006; Maskarinec et al , 2006; Titus-Ernstoff et al , 2006). Inconsistent relations with breast density have been reported for smoking, circulating hormone levels (blood estrogen, estrone levels, total estradiol levels, sex hormone-binding globulin), race/ethnicity, and a few polymorphisms in the estrogen metabolism pathway genes (Boyd et al , 2002; Haiman et al , 2002; Gapstur et al , 2003; Warwick et al , 2003; Conner et al , 2004; Aiello et al , 2005; Noh et al , 2006; Warren et al , 2006; Bremnes et al , 2007; Maskarinec et al , 2007; Tamimi et al , 2007; Verheus et al , 2007).…”

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confidence: 93%

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confidence: 99%

“…Inverse associations with breast density were reported for older age, parity, postmenopausal status, and high body mass index (BMI) (El-Bastawissi et al , 2000; Lam et al , 2000; Vachon et al , 2000; Colacurci et al , 2001; Erel et al , 2001; Vachon et al , 2002; Gapstur et al , 2003; Warwick et al , 2003; Conner et al , 2004; Vachon et al , 2005; Maskarinec et al , 2006; Modugno et al , 2006; Titus-Ernstoff et al , 2006; Ginsburg et al , 2008; Johansson et al , 2008; Kelemen et al , 2008). A positive association between age at menarche and density was reported to be stronger in premenopausal women (El-Bastawissi et al , 2000; Vachon et al , 2000); in some studies (Vachon et al , 2000) these associations were attenuated in multivariate analyses. Hormone replacement therapy (HRT), older age at first child's birth, nulliparity, a family history of breast cancer, and alcohol consumption have been reported to be associated with increased breast density (Gram et al , 1995; El-Bastawissi et al , 2000; Vachon et al , 2000, 2002, 2005; Colacurci et al , 2001; Erel et al , 2001; Rutter et al , 2001; Gapstur et al , 2003; Ziv et al , 2003; Conner et al , 2004; Harvey et al , 2005; Boyd et al , 2006; Maskarinec et al , 2006; Titus-Ernstoff et al , 2006).…”

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Relationship between breast cancer risk factors and mammographic breast density in the Fernald Community Cohort

et al. 2012

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Background:We investigated associations of known breast cancer risk factors with breast density, a well-established and very strong predictor of breast cancer risk.Methods:This nested case–control study included breast cancer-free women, 265 with high and 860 with low breast density. Women were required to be 40–80 years old and should have a body mass index (BMI) <35 at the time of the index mammogram. Information on covariates was obtained from annual questionnaires.Results:In the overall analysis, breast density was inversely associated with BMI at mammogram (P for trend<0.001), and parity (P for trend=0.02) and positively associated with alcohol consumption (ever vs never: odds ratio 2.0, 95% confidence interval 1.4–2.8). Alcohol consumption was positively associated with density, and the association was stronger in women with a family history of breast cancer (P<0.001) and in women with hormone replacement therapy (HRT) history (P<0.001). Parity was inversely associated with density in all subsets, except premenopausal women and women without a family history. The association of parity with density was stronger in women with HRT history (P<0.001).Conclusion:The associations of alcohol and parity with breast density appear to be in reverse direction, but stronger in women with a family history of breast cancer and women who ever used HRT.

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Relationship between breast cancer risk factors and mammographic breast density in the Fernald Community Cohort

et al. 2012

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“…While research has consistently shown a negative association between increasing parity and breast density (e.g., [10, 11]), findings have been less consistent for an association between breast density and older age at first birth (as reviewed in [12]). A few studies have demonstrated that some of the same birth characteristics shown to be associated with increased breast cancer risk were associated with high breast density, specifically, preterm birth, nulliparity/low parity, older age at first birth, and high birth weight [10, 11, 13, 14]. Lope et al [14] found that duration of breastfeeding was positively associated with breast density, while Butler et al [10] found no significant association between breast-feeding and breast density.…”

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First pregnancy events and future breast density: modification by age at first pregnancy and specific VEGF and IGF1R gene variants

Prebil

Ereman

Powell

et al. 2014

Cancer Causes Control

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Purpose Pregnancy characteristics have been associated with breast cancer risk, but information is limited on their relationship with breast density. Our objective was to examine the relationship between first pregnancy characteristics and later life breast density, and whether the association is modified by genotype.Methods The Marin Women’s Study was initiated to examine breast cancer in a high-incidence mammography population (Marin County, CA). Reproductive characteristics and pregnancy information including pregnancy-induced hypertension (PIH) were self-reported at the time of mammography. Forty-seven candidate single nucleotide polymorphisms were obtained from saliva samples; seven were assessed in relation to PIH and percent fibroglandular volume (%FGV). Breast density assessed as %FGV was measured on full-field digital mammograms by the San Francisco Mammography Registry.ResultsA multivariable regression model including 2,440 parous women showed that PIH during first pregnancy was associated with a statistically significant decrease in %FGV (b = −0.31, 95 % CI −0.52, −0.11), while each month of breast-feeding after first birth was associated with a statistically significant increase in %FGV (b = 0.01, 95 % CI 0.003, 0.02). PIH and breast-feeding associations with %FGV were modified by age at first birth. In a subsample of 1,240 women, there was evidence of modification in the association between PIH and %FGV by specific vascular endothelial growth factor (VEGF) (rs3025039) and insulin growth factor receptor-1 (IGFR1) (rs2016347) gene variants.ConclusionThese findings suggest that first pregnancy characteristics may exert an influence on extent of breast density later in life and that this influence may vary depending on inherited IGFR1 and VEGF genotypes.Electronic supplementary materialThe online version of this article (doi:10.1007/s10552-014-0386-2) contains supplementary material, which is available to authorized users.

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“…Nevertheless, it has been reported that age at first birth, family history of BC, mammographic density or genetic factors are also associated with greater risk [4,5]. Having a reliable individual BC risk estimate based on known factors makes it possible to develop personalized screening programs and optimize the use of resources in a population.…”

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An assessment of existing models for individualized breast cancer risk estimation in a screening program in Spain

et al. 2013

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BackgroundThe aim of this study was to evaluate the calibration and discriminatory power of three predictive models of breast cancer risk.MethodsWe included 13,760 women who were first-time participants in the Sabadell-Cerdanyola Breast Cancer Screening Program, in Catalonia, Spain. Projections of risk were obtained at three and five years for invasive cancer using the Gail, Chen and Barlow models. Incidence and mortality data were obtained from the Catalan registries. The calibration and discrimination of the models were assessed using the Hosmer-Lemeshow C statistic, the area under the receiver operating characteristic curve (AUC) and the Harrell’s C statistic.ResultsThe Gail and Chen models showed good calibration while the Barlow model overestimated the number of cases: the ratio between estimated and observed values at 5 years ranged from 0.86 to 1.55 for the first two models and from 1.82 to 3.44 for the Barlow model. The 5-year projection for the Chen and Barlow models had the highest discrimination, with an AUC around 0.58. The Harrell’s C statistic showed very similar values in the 5-year projection for each of the models. Although they passed the calibration test, the Gail and Chen models overestimated the number of cases in some breast density categories.ConclusionsThese models cannot be used as a measure of individual risk in early detection programs to customize screening strategies. The inclusion of longitudinal measures of breast density or other risk factors in joint models of survival and longitudinal data may be a step towards personalized early detection of BC.

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Abstract: Results suggest that pregnancy at an early age has a permanent beneficial association with density, while HRT has a transitory adverse association.

Cited by 97 publications

References 50 publications

Relationship between breast cancer risk factors and mammographic breast density in the Fernald Community Cohort

Relationship between breast cancer risk factors and mammographic breast density in the Fernald Community Cohort

First pregnancy events and future breast density: modification by age at first pregnancy and specific VEGF and IGF1R gene variants

An assessment of existing models for individualized breast cancer risk estimation in a screening program in Spain

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