Mammographic density and breast cancer risk in breast screening assessment cases and women with a family history of breast cancer.
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ABSTRACT: Background
Mammographic density has been shown to be a strong independent predictor of breast cancer and a causative factor in reducing the sensitivity of mammography. There remain questions as to the use of mammographic density information in the context of screening and risk management, and of the association with cancer in populations known to be at increased risk of breast cancer.Aim
To assess the association of breast density with presence of cancer by measuring mammographic density visually as a percentage, and with two automated volumetric methods, Quantra™ and VolparaDensity™.Methods
The TOMosynthesis with digital MammographY (TOMMY) study of digital breast tomosynthesis in the Breast Screening Programme of the National Health Service (NHS) of the United Kingdom (UK) included 6020 breast screening assessment cases (of whom 1158 had breast cancer) and 1040 screened women with a family history of breast cancer (of whom two had breast cancer). We assessed the association of each measure with breast cancer risk in these populations at enhanced risk, using logistic regression adjusted for age and total breast volume as a surrogate for body mass index (BMI).Results
All density measures showed a positive association with presence of cancer and all declined with age. The strongest effect was seen with Volpara absolute density, with a significant 3% (95% CI 1-5%) increase in risk per 10 cm3 of dense tissue. The effect of Volpara volumetric density on risk was stronger for large and grade 3 tumours.Conclusions
Automated absolute breast density is a predictor of breast cancer risk in populations at enhanced risk due to either positive mammographic findings or family history. In the screening context, density could be a trigger for more intensive imaging.
SUBMITTER: Duffy SW
PROVIDER: S-EPMC5768323 | biostudies-literature | 2018 Jan
REPOSITORIES: biostudies-literature
Publications
Mammographic density and breast cancer risk in breast screening assessment cases and women with a family history of breast cancer.
Duffy Stephen W SW Morrish Oliver W E OWE Allgood Prue C PC Black Richard R Gillan Maureen G C MGC Willsher Paula P Cooke Julie J Duncan Karen A KA Michell Michael J MJ Dobson Hilary M HM Maroni Roberta R Lim Yit Y YY Purushothaman Hema N HN Suaris Tamara T Astley Susan M SM Young Kenneth C KC Tucker Lorraine L Gilbert Fiona J FJ
European journal of cancer (Oxford, England : 1990) 20171127
<h4>Background</h4>Mammographic density has been shown to be a strong independent predictor of breast cancer and a causative factor in reducing the sensitivity of mammography. There remain questions as to the use of mammographic density information in the context of screening and risk management, and of the association with cancer in populations known to be at increased risk of breast cancer.<h4>Aim</h4>To assess the association of breast density with presence of cancer by measuring mammographic ...[more]
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Project description:ImportanceFamily history of breast cancer (FHBC) and mammographic breast density are independent risk factors for breast cancer, but the association of FHBC and mammographic breast density in premenopausal women is not well understood.ObjectivesTo investigate the association of FHBC and mammographic breast density in premenopausal women using both quantitative and qualitative measurements.Design, setting, and participantsThis single-center cohort study examined 2 retrospective cohorts: a discovery set of 375 premenopausal women and a validation set of 14 040 premenopausal women. Data from women in the discovery set was collected between December 2015 and October 2016, whereas data from women in the validation set was collected between June 2010 and December 2015. Data analysis was performed between June 2018 and June 2020.ExposuresFamily history of breast cancer (FHBC).Main outcomes and measuresThe primary outcomes were mammographic breast density measured quantitatively as volumetric percent density using Volpara (discovery set) and qualitatively using BI-RADS (Breast Imaging Reporting and Data System) breast density (validation set). Multivariable regressions were performed using a log-transformed normal distribution for the discovery set and a logistic distribution for the validation set.ResultsOf 14 415 premenopausal women included in the study, the discovery set and validation set had similar characteristics (discovery set with FHBC: mean [SD] age, 47.1 [5.6] years; 15 [17.2%] were Black or African American women and 64 [73.6%] were non-Hispanic White women; discovery set with no FHBC: mean [SD] age, 47.7 [4.5] years; 87 [31.6%] were Black or African American women and 178 [64.7%] were non-Hispanic White women; validation set with FHBC: mean [SD] age, 46.8 [7.3] years; 720 [33.4%] were Black or African American women and 1378 [64.0%] were non-Hispanic White women]; validation set with no FHBC: mean [SD] age, 47.5 [6.1] years; 4572 [38.5%] were Black or African American women and 6632 [55.8%] were non-Hispanic White women]). In the discovery set, participants who had FHBC were more likely to have a higher mean volumetric percent density compared with participants with no FHBC (11.1% vs 9.0%). In the multivariable-adjusted model, volumetric percent density was 25% higher (odds ratio [OR], 1.25 ;95% CI, 1.12-1.41) in women with FHBC compared with women without FHBC; and 24% higher (OR, 1.24; 95% CI, 1.10-1.40) in women who had 1 affected relative, but not significantly higher in women who had at least 2 affected relatives (OR, 1.40; 95% CI, 0.95-2.07) compared with women with no relatives affected. In the validation set, women with a positive FHBC were more likely to have dense breasts (BI-RADS 3-4) compared with women with no FHBC (BI-RADS 3: 41.1% vs 38.8%; BI-RADS 4: 10.5% vs 7.7%). In the multivariable-adjusted model, the odds of having dense breasts (BI-RADS 3-4) were 30% higher (OR, 1.30; 95% CI, 1.17-1.45) in women with FHBC compared with women without FHBC; and 29% higher (OR, 1.29; 95% CI, 1.14-1.45) in women who had 1 affected relative, but not significantly higher in women who had at least 2 affected relatives (OR, 1.38; 95% CI, 0.85-2.23) compared with women with no relatives affected.Conclusions and relevanceIn this cohort study, having an FHBC was positively associated with mammographic breast density in premenopausal women. Our findings highlight the heritable component of mammographic breast density and underscore the need to begin annual screening early in premenopausal women with a family history of breast cancer.
| S-EPMC8855232 | biostudies-literature
Project description:BackgroundMammographic density is one of the strongest risk factors for breast cancer. In the general population, mammographic density can be modified by various exposures; whether this is true for women a strong family history is not known. Thus, we evaluated the association between reproductive, hormonal, and lifestyle risk factors and mammographic density among women with a strong family history of breast cancer but no BRCA1 or BRCA2 mutation.MethodsWe included 97 premenopausal and 59 postmenopausal women (age range: 27-68 years). Risk factor data was extracted from the research questionnaire closest in time to the mammogram performed nearest to enrollment. The Cumulus software was used to measure percent density, dense area, and non-dense area for each mammogram. Multivariate generalized linear models were used to evaluate the relationships between breast cancer risk factors and measures of mammographic density, adjusting for relevant covariates.ResultsAmong premenopausal women, those who had two live births had a mean percent density of 28.8% vs. 41.6% among women who had one live birth (P=0.04). Women with a high body weight had a lower mean percent density compared to women with a low body weight among premenopausal (17.6% vs. 33.2%; P=0.0006) and postmenopausal women (8.7% vs. 14.7%; P=0.04). Among premenopausal women, those who smoked for 14 years or longer had a lower mean dense area compared to women who smoked for a shorter duration (25.3cm2 vs. 53.1cm2; P=0.002). Among postmenopausal women, former smokers had a higher mean percent density (19.5% vs. 10.8%; P=0.003) and dense area (26.9% vs. 16.4%; P=0.01) compared to never smokers. After applying the Bonferroni correction, the association between body weight and percent density among premenopausal women remained statistically significant.ConclusionsIn this cohort of women with a strong family history of breast cancer, body weight was associated with mammographic density. These findings suggest that mammographic density may explain the underlying relationship between some of these risk factors and breast cancer risk, and lend support for the inclusion of mammographic density into risk prediction models.
| S-EPMC6595553 | biostudies-literature
Project description:BackgroundThis study investigated whether the association between family history of breast cancer in first-degree relatives and breast cancer risk varies by breast density.MethodsWomen aged 40 years and older who underwent screening between 2009 and 2010 were followed up until 2020. Family history was assessed using a self-reported questionnaire. Using Breast Imaging Reporting and Data System (BI-RADS), breast density was categorized into dense breast (heterogeneously or extremely dense) and non-dense breast (almost entirely fatty or scattered areas of fibro-glandular). Cox regression model was used to assess the association between family history and breast cancer risk.ResultsOf the 4,835,507 women, 79,153 (1.6%) reported having a family history of breast cancer and 77,238 women developed breast cancer. Family history led to an increase in the 5-year cumulative incidence in women with dense- and non-dense breasts. Results from the regression model with and without adjustment for breast density yielded similar HRs in all age groups, suggesting that breast density did not modify the association between family history and breast cancer. After adjusting for breast density and other factors, family history of breast cancer was associated with an increased risk of breast cancer in all three age groups (age 40-49 years: aHR 1.96, 95% confidence interval [CI] 1.85-2.08; age 50-64 years: aHR 1.70, 95% CI 1.58-1.82, and age ≥65 years: aHR 1.95, 95% CI 1.78-2.14).ConclusionFamily history of breast cancer and breast density are independently associated with breast cancer. Both factors should be carefully considered in future risk prediction models of breast cancer.
| S-EPMC9441334 | biostudies-literature
Project description:Background: The utility of incorporating detailed family history into breast cancer risk prediction hinges on its independent contribution to breast cancer risk. We evaluated associations between detailed family history and breast cancer risk while accounting for breast density.Methods: We followed 222,019 participants ages 35 to 74 in the Breast Cancer Surveillance Consortium, of whom 2,456 developed invasive breast cancer. We calculated standardized breast cancer risks within joint strata of breast density and simple (1st-degree female relative) or detailed (first-degree, second-degree, or first- and second-degree female relative) breast cancer family history. We fit log-binomial models to estimate age-specific breast cancer associations for simple and detailed family history, accounting for breast density.Results: Simple first-degree family history was associated with increased breast cancer risk compared with no first-degree history [Risk ratio (RR), 1.5; 95% confidence interval (CI), 1.0-2.1 at age 40; RR, 1.5; 95% CI, 1.3-1.7 at age 50; RR, 1.4; 95% CI, 1.2-1.6 at age 60; RR, 1.3; 95% CI, 1.1-1.5 at age 70). Breast cancer associations with detailed family history were strongest for women with first- and second-degree family history compared with no history (RR, 1.9; 95% CI, 1.1-3.2 at age 40); this association weakened in higher age groups (RR, 1.2; 95% CI, 0.88-1.5 at age 70). Associations did not change substantially when adjusted for breast density.Conclusions: Even with adjustment for breast density, a history of breast cancer in both first- and second-degree relatives is more strongly associated with breast cancer than simple first-degree family history.Impact: Future efforts to improve breast cancer risk prediction models should evaluate detailed family history as a risk factor. Cancer Epidemiol Biomarkers Prev; 26(6); 938-44. ©2017 AACR.
| S-EPMC5457358 | biostudies-literature
Project description:Background Breast Imaging Reporting and Data System (BI-RADS) breast density categories assigned by interpreting radiologists often influence decisions surrounding supplemental breast cancer screening and risk assessment. The landscape of mammographic screening continuously evolves, and different mammographic screening modalities may result in different perception of density, reflected in different assignment of BI-RADS density categories. Purpose To investigate the effect of screening mammography modality on BI-RADS breast density assessments. Materials and Methods Data were retrospectively analyzed from 24 736 individual women (42.3% [10 455 of 24 736] white women, 57.7% [14 281 of 24 736] black women; mean age, 56.3 years; age range, 40.0-74.9 years) who underwent from one to seven mammographic screening examinations from September 2010 through February 2017 (60 766 examinations). Three screening modalities were used: digital mammography alone (8935 examinations); digital mammography with digital breast tomosynthesis (DBT; 30 779 examinations); and synthetic mammography with DBT (21 052 examinations). Random-effects logistic regression analysis was performed to estimate the likelihood of assignment to high versus low BI-RADS density category according to each modality, adjusted for ethnicity, age, body mass index (BMI), and radiologist. The interactions of modality with ethnicity and BMI on density categorization were also tested with the model. Results Women screened with DBT versus digital mammography alone had lower likelihood regarding categorization of high density breasts (digital mammography and DBT vs digital mammography: odds ratio, 0.69 [95% confidence interval: 0.61, 0.80], P < .001; synthetic mammography and DBT vs digital mammography: odds ratio, 0.43 [95% confidence interval: 0.37, 0.50], P < .001). Lower likelihood of high density was also observed at synthetic mammography and DBT compared with digital mammography and DBT (odds ratio, 0.62; 95% confidence interval: 0.56, 0.69; P < .001). There were interactions of modality with ethnicity (P = .007) and BMI (P = .003) on breast density assessment, with greater differences in density categorization according to modality observed for black women than for white women and groups with higher BMI. Conclusion Breast density categorization may vary by screening mammographic modality, and this effect appears to vary by ethnicity and body mass index. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Philpotts in this issue.
| S-EPMC6493215 | biostudies-literature
Project description:BackgroundAttention in the 2000s on the importance of mammographic density led us to study screening sensitivity, breast cancer incidence, and associations with risk factors by mammographic density in Danish breast cancer screening programs. Here, we summarise our approaches and findings.MethodsDichotomized density codes: fatty, equal to BI-RADS density code 1 and part of 2, and other mixed/dense data from the 1990s-were available from two counties, and BI-RADS density codes from one region were available from 2012/13. Density data were linked with data on vital status, incident breast cancer, and potential risk factors. We calculated screening sensitivity by combining data on screen-detected and interval cancers. We used cohorts to study high density as a predictor of breast cancer risk; cross-sectional data to study the association between life style factors and density, adjusting for age and body mass index (BMI); and time trends to study the prevalence of high density across birth cohorts.ResultsSensitivity decreased with increasing density from 78% in women with BI-RADS 1 to 47% in those with BI-RADS 4. For women with mixed/dense compared with those with fatty breasts, the rate ratio of incident breast cancer was 2.45 (95% CI 2.14-2.81). The percentage of women with mixed/dense breasts decreased with age, but at a higher rate the later the women were born. Among users of postmenopausal hormone therapy, the percentage of women with mixed/dense breasts was higher than in non-users, but the patterns across birth cohorts were similar. The occurrence of mixed/dense breast at screening age decreased by a z-score unit of BMI at age 13-odds ratio (OR) 0.56 (95% CI 0.53-0.58)-and so did breast cancer risk and hazard ratio (HR) 0.92 (95% CI 0.84-1.00), but it changed to HR 1.01 (95% CI 0.93-1.11) when controlled for density. Age and BMI adjusted associations between life style factors and density were largely close to unity; physical activity OR 1.06 (95% CI 0.93-1.21); alcohol consumption OR 1.01 (95% CI 0.81-1.27); air pollution OR 0.96 (95% 0.93-1.01) per 20 ?g/m3; and traffic noise OR 0.94 (95% CI 0.86-1.03) per 10 dB. Weak negative associations were seen for diabetes OR 0.61 (95% CI 0.40-0.92) and cigarette smoking OR 0.86 (95% CI 0.75-0.99), and a positive association was found with hormone therapy OR 1.24 (95% 1.14-1.35).ConclusionOur data indicate that breast tissue in middle-aged women is highly dependent on childhood body constitution while adult life-style plays a modest role, underlying the need for a long-term perspective in primary prevention of breast cancer.
| S-EPMC6912479 | biostudies-literature
Project description:BackgroundTamoxifen decreases mammographic density. Whether compliance affects this relationship is unclear as is the relationship between other types of adjuvant treatment and changes in mammographic density.MethodsThis prospective cohort study included 2490 women diagnosed with breast cancer during 2001-2015 in Sweden. Mammographic density was assessed within 3 months of diagnosis and 6-36 months post diagnosis. Logistic regression was performed to study the association between each respective adjuvant treatment and mammographic density reduction (annual dense area decrease >15%).ResultsIntention-to-treat analyses using treatment information from the regional cancer registries showed that tamoxifen-treated patients more frequently experienced mammographic density reductions compared with nontreated patients (odds ratio [OR] = 1.58, 95% confidence interval [CI] = 1.25 to 1.99), as did chemotherapy-treated patients (OR = 1.28, 95% CI = 1.06 to 1.54). For chemotherapy, the association was mainly seen in premenopausal women. Neither aromatase inhibitors nor radiotherapy was associated with density change. Tamoxifen use based on prescription and dispensation data from the Swedish Prescribed Drug Register showed that users were more likely to have density reductions compared with nonusers (adjusted OR = 2.24, 95% CI = 1.40 to 3.59). Moreover, among tamoxifen users, tamoxifen continuers were more likely than discontinuers to experience density reductions (adjusted OR = 1.50, 95% CI = 1.04 to 2.17).ConclusionsOur results indicate that adherence influences the association between tamoxifen and mammographic density reduction. We further found that chemotherapy was associated with density reductions and propose that this is largely secondary to chemotherapy-induced ovarian failure.
| S-EPMC6649795 | biostudies-literature
Project description:Mammographic breast density (MBD) is a strong independent risk factor for breast cancer (BC). We designed a matched case-case study in the EPIC Florence cohort, to evaluate possible associations between the pre-diagnostic metabolomic profile and the risk of BC in high- versus low-MBD women who developed BC during the follow-up. A case-case design with 100 low-MBD (MBD ≤ 25%) and 100 high-MDB BC cases (MBD > 50%) was performed. Matching variables included age, year and type of mammographic examination. 1H NMR metabolomic spectra were available for 87 complete case-case sets. The conditional logistic analyses showed an inverse association between serum levels of alanine, leucine, tyrosine, valine, lactic acid, pyruvic acid, triglycerides lipid main fraction and 11 VLDL lipid subfractions and high-MBD cases. Acetic acid was directly associated with high-MBD cases. In models adjusted for confounding variables, tyrosine remained inversely associated with high-MBD cases while 3 VLDL subfractions of free cholesterol emerged as directly associated with high-MBD cases. A pathway analysis showed that the "phenylalanine, tyrosine and tryptophan pathway" emerged and persisted after applying the FDR procedure. The supervised OPLS-DA analysis revealed a slight but significant separation between high- and low-MBD cases. This case-case study suggested a possible role for pre-diagnostic levels of tyrosine in modulating the risk of BC in high- versus low-MBD women. Moreover, some differences emerged in the pre-diagnostic concentration of other metabolites as well in the metabolomic fingerprints among the two groups of patients.
| S-EPMC8219761 | biostudies-literature
Project description:BackgroundHigh mammographic breast density (MBD) is a strong risk factor for breast cancer development, but the biological mechanisms underlying MBD are unclear. Lipids play important roles in cell differentiation, and perturbations in lipid metabolism are implicated in cancer development. Nevertheless, no study has applied untargeted lipidomics to profile the lipidome of MBD. Through this study, our goal is to characterize the lipidome of MBD in premenopausal women.MethodsPremenopausal women were recruited during their annual screening mammogram at the Washington University School of Medicine in St. Louis, MO. Untargeted lipidomic profiling for 982 lipid species was performed at Metabolon (Durham, NC®), and volumetric measures of MBD (volumetric percent density (VPD), dense volume (DV), and non-dense volume (NDV)) was assessed using Volpara 1.5 (Volpara Health®). We performed multivariable linear regression models to investigate the associations of lipid species with MBD and calculated the covariate-adjusted least square mean of MBD by quartiles of lipid species. MBD measures were log10 transformed, and lipid species were standardized. Linear coefficients of MBD were back-transformed and considered significant if the Bonferroni corrected p-value was < 0.05.ResultsOf the 705 premenopausal women, 72% were non-Hispanic white, and 23% were non-Hispanic black. Mean age, and BMI were 46 years and 30 kg/m2, respectively. Fifty-six lipid species were significantly associated with VPD (52 inversely and 4 positively). The lipid species with positive associations were phosphatidylcholine (PC)(18:1/18:1), lysophosphatidylcholine (LPC)(18:1), lactosylceramide (LCER)(14:0), and phosphatidylinositol (PI)(18:1/18:1). VPD increased across quartiles of PI(18:1/18:1): (Q1 = 7.5%, Q2 = 7.7%, Q3 = 8.4%, Q4 = 9.4%, Bonferroni p-trend = 0.02). The lipid species that were inversely associated with VPD were mostly from the triacylglycerol (N = 43) and diacylglycerol (N = 7) sub-pathways. Lipid species explained some of the variation in VPD. The inclusion of lipid species increased the adjusted R2 from 0.45, for a model that includes known determinants of VPD, to 0.59.ConclusionsWe report novel lipid species that are associated with MBD in premenopausal women. Studies are needed to validate our results and the translational potential.
| S-EPMC10561435 | biostudies-literature
Project description:Mammographic density is a strong risk factor for breast cancer, but limited data are available in African American (AA) women. We examined the association between mammographic density and breast cancer risk in AA and white women. Cases (n = 491) and controls (n = 528) were from the Carolina Breast Cancer Study (CBCS) who also had mammograms recorded in the Carolina Mammography Registry (CMR). Mammographic density was reported to CMR using Breast Imaging Reporting and Data System (BI-RADS) categories. Increasing mammographic density was associated with increased breast cancer risk among all women. After adjusting for potential confounders, a monotonically increasing risk of breast cancer was observed between the highest versus the lowest BI-RADS density categories [OR = 2.45, (95 % confidence interval: 0.99, 6.09)]. The association was stronger in whites, with ~40 % higher risk among those with extremely dense breasts compared to those with scattered fibroglandular densities [1.39, (0.75, 2.55)]. In AA women, the same comparison suggested lower risk [0.75, (0.30, 1.91)]. Because age, obesity, and exogenous hormones have strong associations with breast cancer risk, mammographic density, and race in the CBCS, effect measure modification by these factors was considered. Consistent with previous literature, density-associated risk was greatest among those with BMI > 30 and current hormone users (P value = 0.02 and 0.01, respectively). In the CBCS, mammographic density is associated with increased breast cancer risk, with some suggestion of effect measure modification by race, although results were not statistically significant. However, exposures such as BMI and hormone therapy may be important modifiers of this association and merit further investigation.
| S-EPMC3734952 | biostudies-literature