scholarly journals Adjuvant Therapy and Mammographic Density Changes in Women With Breast Cancer

2018 ◽  
Vol 2 (4) ◽  
Author(s):  
Louise Eriksson ◽  
Wei He ◽  
Mikael Eriksson ◽  
Keith Humphreys ◽  
Jonas Bergh ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Mammographic Density ◽  
Adjuvant Treatment ◽  
Premenopausal Women ◽  
Cancer Registries ◽  
Dense Area ◽  
Intention To Treat ◽  
Density Reduction ◽  
Treatment Information ◽  
Drug Register

Abstract Background Tamoxifen 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. Methods This 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%). Results Intention-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). Conclusions Our 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.

scholarly journals Predictors of mammographic density among women with a strong family history of breast cancer

BMC Cancer ◽  
2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Olivia Moran ◽  
Andrea Eisen ◽  
Rochelle Demsky ◽  
Kristina Blackmore ◽  
Julia A. Knight ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Body Weight ◽  
Family History ◽  
Mammographic Density ◽  
Premenopausal Women ◽  
Percent Density ◽  
Strong Family History ◽  
Dense Area ◽  
History Of

Abstract Background Mammographic 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. Methods We 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. Results Among 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. Conclusions In 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.

scholarly journals Low-Dose Tamoxifen for Mammographic Density Reduction: A Randomized Controlled Trial

2021 ◽  
pp. JCO.20.02598 ◽  
Author(s):  
Mikael Eriksson ◽  
Martin Eklund ◽  
Signe Borgquist ◽  
Roxanna Hellgren ◽  
Sara Margolin ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Mammographic Density ◽  
Screening Program ◽  
Standard Dose ◽  
Controlled Trial ◽  
Menopausal Status ◽  
Premenopausal Women ◽  
Secondary Outcome ◽  
Double Blind ◽  
Density Reduction

PURPOSE Tamoxifen prevents breast cancer in high-risk women and reduces mortality in the adjuvant setting. Mammographic density change is a proxy for tamoxifen therapy response. We tested whether lower doses of tamoxifen were noninferior to reduce mammographic density and associated with fewer symptoms. PATIENTS AND METHODS Women, 40-74 years of age, participating in the Swedish mammography screening program were invited to the 6-month double-blind six-arm randomized placebo-controlled noninferiority dose-determination KARISMA phase II trial stratified by menopausal status (EudraCT 2016-000882-22). In all, 1,439 women were accrued with 1,230 participants accessible for intention-to-treat analysis. The primary outcome was proportion of women treated with placebo, 1, 2.5, 5, and 10 mg whose mammographic density decreased at least as much as the median reduction in the 20 mg arm. The noninferior margin was 17%. Secondary outcome was reduction of symptoms. Post hoc analyses were performed by menopausal status. Per-protocol population and full population were analyzed in sensitivity analysis. RESULTS The 1,439 participants, 566 and 873 pre- and postmenopausal women, respectively, were recruited between October 1, 2016, and September 30, 2019. The participants had noninferior mammographic density reduction following 2.5, 5, and 10 mg tamoxifen compared with the median 10.1% decrease observed in the 20 mg group, a reduction confined to premenopausal women. Severe vasomotor symptoms (hot flashes, cold sweats, and night sweats) were reduced by approximately 50% in the 2.5, 5, and 10 mg groups compared with the 20 mg group. CONCLUSION Premenopausal women showed noninferior magnitude of breast density decrease at 2.5 mg of tamoxifen, but fewer side effects compared with the standard dose of 20 mg. Future studies should test whether 2.5 mg of tamoxifen reduces the risk of primary breast cancer.

Mammographic Density, Response to Hormones, and Breast Cancer Risk

2011 ◽  
Vol 29 (22) ◽  
pp. 2985-2992 ◽  
Author(s):  
Norman F. Boyd ◽  
Olga Melnichouk ◽  
Lisa J. Martin ◽  
Greg Hislop ◽  
Anna M. Chiarelli ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Postmenopausal Women ◽  
Mammographic Density ◽  
Premenopausal Women ◽  
Case Control Studies ◽  
Dense Area ◽  
Hormone Exposure ◽  
The Difference

Background Percent mammographic density (PMD) is a strong risk factor for breast cancer that changes in response to changes in hormone exposure. We have examined the magnitude of the association of hormone exposure with PMD according to subsequent breast cancer risk. Methods In three case-control studies, with 1,164 patient cases and 1,155 controls nested in cohorts of women screened with mammography, we examined the association of PMD measured in the baseline mammogram with risk of breast cancer in the following 1 to 8 years (mean, 3 years), according to use of oral contraceptives (OCs) in premenopausal women, menopause, and hormone therapy (HT) in postmenopausal women. All statistical comparisons are adjusted for age and other risk factors. Results In premenopausal women who later developed breast cancer (patient cases), PMD was 5.3% greater in past users of OCs than in nonusers (P = .06). In controls, OC users had 2% less density than nonusers (P = .44; test for interaction P = .06). The difference in PMD between premenopausal and postmenopausal women for patient cases was 8.5% (P < .001) and for controls, 3.9% (P = .01; test for interaction P = .03). In postmenopausal women, PMD was 6% greater in patients who used HT than in never users (P < .001). Controls who used HT had 1.6% greater PMD (P = .26) than never users (test for interaction P = .001). Differences in PMD resulted mainly from differences in the dense area of the mammogram. Conclusion Differences in PMD associated with differences in hormone exposure were greater in women who later developed breast cancer than in controls in each of the hormone exposures examined.

No association between night shiftwork and mammographic density

2020 ◽  
Vol 77 (8) ◽  
pp. 564-567
Author(s):  
Sonia El-Zaemey ◽  
Lin Fritschi ◽  
Jane Heyworth ◽  
Terry Boyle ◽  
Christobel Saunders ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Phase Shift ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Mammographic Density ◽  
Large Population ◽  
Cancer Case ◽  
Light At Night ◽  
Related Factors ◽  
Dense Area

BackgroundIncreased mammographic density is one of the strongest risk factors for breast cancer. Night shiftwork and its related factors, which include light at night, phase shift and sleep disruption, are believed to increase breast cancer risk however, their effects on mammographic density have barely been studied.MethodsThis study included 1821 women enrolled in the Breast Cancer Environment and Employment Study between 2009 and 2011. Mammographic density was measured using the Cumulus software program. The association of night shiftwork factors with square root transformed absolute dense area (DA) and percentage dense area (PDA) were modelled using linear regression adjusted for confounders.ResultsEver doing graveyard shiftwork (between 24:00 and 05:00 hours) was not associated with PDA (β=−0.10; 95% CI −0.27 to 0.08)) and DA (β=−0.12; 95% CI −0.33 to 0.09)). No association was found between night shiftwork related factors (light at night, phase shift and sleep disturbance) with PDA or DA.ConclusionsShiftwork and its related factors are not associated with mammographic density. Using high-quality, comprehensive shiftwork data from a large population-based breast cancer case–control study, this study suggests that mammographic density does not play a role in the relationship between shiftwork and breast cancer risk.

scholarly journals Inclusion of Plasma Prolactin Levels in Current Risk Prediction Models of Premenopausal and Postmenopausal Breast Cancer

2018 ◽  
Vol 2 (4) ◽  
Author(s):  
Marike Gabrielson ◽  
Kumari Ubhayasekera ◽  
Bo Ek ◽  
Mikael Andersson Franko ◽  
Mikael Eriksson ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Risk Prediction ◽  
Mammographic Density ◽  
Postmenopausal Breast Cancer ◽  
Premenopausal Women ◽  
Plasma Prolactin ◽  
Risk Models ◽  
Current Risk

Abstract Background Circulating plasma prolactin is associated with breast cancer risk and may improve our ability to identify high-risk women. Mammographic density is a strong risk factor for breast cancer, but the association with prolactin is unclear. We studied the association between breast cancer, established breast cancer risk factors and plasma prolactin, and improvement of risk prediction by adding prolactin. Methods We conducted a nested case-control study including 721 breast cancer patients and 1400 age-matched controls. Plasma prolactin levels were assayed using immunoassay and mammographic density measured by STRATUS. Odds ratios (ORs) were calculated by multivariable adjusted logistic regression, and improvement in the area under the curve for the risk of breast cancer by adding prolactin to established risk models. Statistical tests were two-sided. Results In multivariable adjusted analyses, prolactin was associated with risk of premenopausal (OR, top vs bottom quintile = 1.9; 1.88 (95% confidence interval [CI] = 1.08 to 3.26) but not with postmenopausal breast cancer. In postmenopausal cases prolactin increased by 10.6% per cBIRADS category (Ptrend = .03). In combined analyses of prolactin and mammographic density, ORs for women in the highest vs lowest tertile of both was 3.2 (95% CI = 1.3 to 7.7) for premenopausal women and 2.44 (95% CI = 1.44 to 4.14) for postmenopausal women. Adding prolactin to current risk models improved the area under the curve of the Gail model (+2.4 units, P = .02), Tyrer-Cuzick model (+3.8, P = .02), and the CAD2Y model (+1.7, P = .008) in premenopausal women. Conclusion Circulating plasma prolactin and mammographic density appear independently associated with breast cancer risk among premenopausal women, and prolactin may improve risk prediction by current risk models.

The effect of raloxifene on breast MRI volume in premenopausal women at increased risk for invasive breast cancer

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 1518-1518
Author(s):  
J. Eng-Wong ◽  
C. K. Chow ◽  
J. Orzano ◽  
D. Venzon ◽  
J. Zujewski ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Mammographic Density ◽  
Ductal Carcinoma ◽  
Premenopausal Women ◽  
Breast Mri ◽  
Rank Test ◽  
Increased Risk ◽  
Significant Change ◽  
One Year ◽  
Relative Change

1518 Background: Breast MRI volume (MRIV) and mammographic density (MD) assess the amount of fibroglandular tissue in the breast. While increased MD is associated with a 4 to 6 fold increase in breast cancer risk, the association between MRIV and breast cancer is unknown. Previous studies have shown that MRIV and MD can be modulated with hormonal interventions. We evaluated the effect of raloxifene on MRIV in premenopausal women at increased risk for breast cancer. We have previously reported that raloxifene did not change MD in this cohort. Raloxifene is indicated for the prevention and treatment of osteoporosis but not for prevention of breast cancer or for use in premenopausal women. Methods: Premenopausal women at increased risk by virtue of: Gail model risk > 1.7% over 5 years; lobular neoplasia, ductal carcinoma in situ, BRCA1/2 mutation positive, or a very strong family history were eligible for this phase II chemoprevention study. MRIs obtained at baseline and after two years on raloxifene 60 mg daily, and one year after discontinuing the drug were evaluated.T1 weighted spoiled gradient-echo MRI with fat suppression was used to determine volume using a semiautomatic method, after visual verification. Median relative change in MRIV was assessed by the Wilcoxon signed rank test. Results: 19 of 30 subjects who started study drug had breast MRI at baseline and after 2 years on raloxifene; median relative change was -16% (range -57 to +25%) (p=0.0004). 17 subjects had MRI at year 2 and one year after stopping drug. No significant change in MRIV was observed after stopping raloxifene, median relative change -9% (p=0.64). Conclusions: MRIV significantly declined while on raloxifene. In contrast no significant change in percent mammographic density in this same cohort was seen. Our findings suggest that MRIV may be a better surrogate biomarker than MD in premenopausal women at risk for breast cancer because of less variation in its measurement. MRIV should be further evaluated as a potential surrogate biomarker in prevention studies. No significant financial relationships to disclose.

scholarly journals Mammographic density as an image-based biomarker of therapy response in neoadjuvant-treated breast cancer patients

2020 ◽  
Author(s):  
Ida Skarping ◽  
Daniel Förnvik ◽  
Uffe Heide-Jørgensen ◽  
Hanna Sartor ◽  
Per Hall ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Mammographic Density ◽  
Breast Imaging ◽  
Menopausal Status ◽  
Therapy Response ◽  
Predictive Biomarkers ◽  
Premenopausal Women ◽  
Complete Response ◽  
Breast Cancer Patients ◽  
Multicenter Studies

Abstract Purpose Personalized cancer treatment requires predictive biomarkers, including image-based biomarkers. Breast cancer (BC) patients receiving neoadjuvant chemotherapy (NACT) are in a clinically vulnerable situation with the tumor present. This study investigated whether mammographic density (MD), assessed pre-NACT, is predictive of pathological complete response (pCR). Methods A total of 495 BC patients receiving NACT in Sweden 2005–2019 were included, merged from two different cohorts. Cohort 1 was retrospectively collected (n = 295) and cohort 2 was prospectively collected (n = 200). Mammograms were scored for MD pre-NACT according to the Breast Imaging-Reporting and Data System (BI-RADS), 5th Edition. The association between MD and accomplishing pCR post-NACT was analyzed using logistic regression models—for the whole cohort, stratified by menopausal status, and in different St. Gallen surrogate subtypes. Results In comparison to patients with low MD (BI-RADS a), the multivariable-adjusted odds ratio (OR) of accomplishing pCR following NACT was on a descending scale: 0.62 (95% confidence interval (CI) 0.24–1.57), 0.38 (95% CI 0.14–1.02), and 0.32 (95% CI 0.09–1.08) for BI-RADS b, c, and d, respectively. For premenopausal patients selectively, the corresponding point estimates were lower, although wider CIs: 0.31 (95% CI 0.06–1.62), 0.24 (95% CI 0.04–1.27), and 0.13 (95% CI 0.02–0.88). Subgroup analyses based on BC subtypes resulted in imprecise estimates, i.e., wide CIs. Conclusions It seemed as though patients with higher MD at baseline were less likely to reach pCR after NACT—a finding more pronounced in premenopausal women. Larger multicenter studies are needed to enable analyses and interpretation for different BC subtypes.

Sign in / Sign up

Export Citation Format

Share Document