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Fulltext Incidence of breast cancer attributable to breast density, modifiable and non-modifiable breast cancer risk factors in Singapore

Ho PJ, Lau HSH, Ho WK, Wong FY, Yang Q, Tan KW, et al.

Sci Rep, 2020 01 16;10(1):503.
PMID: 31949192 DOI: 10.1038/s41598-019-57341-7

Incidence of breast cancer is rising rapidly in Asia. Some breast cancer risk factors are modifiable. We examined the impact of known breast cancer risk factors, including body mass index (BMI), reproductive and hormonal risk factors, and breast density on the incidence of breast cancer, in Singapore. The study population was a population-based prospective trial of screening mammography - Singapore Breast Cancer Screening Project. Population attributable risk and absolute risks of breast cancer due to various risk factors were calculated. Among 28,130 women, 474 women (1.7%) developed breast cancer. The population attributable risk was highest for ethnicity (49.4%) and lowest for family history of breast cancer (3.8%). The proportion of breast cancers that is attributable to modifiable risk factor BMI was 16.2%. The proportion of breast cancers that is attributable to reproductive risk factors were low; 9.2% for age at menarche and 4.2% for number of live births. Up to 45.9% of all breast cancers could be avoided if all women had breast density <12% and BMI <25 kg/m2. Notably, sixty percent of women with the lowest risk based on non-modifiable risk factors will never reach the risk level recommended for mammography screening. A combination of easily assessable breast cancer risk factors can help to identify women at high risk of developing breast cancer for targeted screening. A large number of high-risk women could benefit from risk-reduction and risk stratification strategies.

Matched MeSH terms: Breast Density
Fulltext Mammographic compression in Asian women

Lau S, Abdul Aziz YF, Ng KH

PLoS One, 2017;12(4):e0175781.
PMID: 28419125 DOI: 10.1371/journal.pone.0175781

OBJECTIVES: To investigate: (1) the variability of mammographic compression parameters amongst Asian women; and (2) the effects of reducing compression force on image quality and mean glandular dose (MGD) in Asian women based on phantom study.
METHODS: We retrospectively collected 15818 raw digital mammograms from 3772 Asian women aged 35-80 years who underwent screening or diagnostic mammography between Jan 2012 and Dec 2014 at our center. The mammograms were processed using a volumetric breast density (VBD) measurement software (Volpara) to assess compression force, compression pressure, compressed breast thickness (CBT), breast volume, VBD and MGD against breast contact area. The effects of reducing compression force on image quality and MGD were also evaluated based on measurement obtained from 105 Asian women, as well as using the RMI156 Mammographic Accreditation Phantom and polymethyl methacrylate (PMMA) slabs.
RESULTS: Compression force, compression pressure, CBT, breast volume, VBD and MGD correlated significantly with breast contact area (p<0.0001). Compression parameters including compression force, compression pressure, CBT and breast contact area were widely variable between [relative standard deviation (RSD)≥21.0%] and within (p<0.0001) Asian women. The median compression force should be about 8.1 daN compared to the current 12.0 daN. Decreasing compression force from 12.0 daN to 9.0 daN increased CBT by 3.3±1.4 mm, MGD by 6.2-11.0%, and caused no significant effects on image quality (p>0.05).
CONCLUSIONS: Force-standardized protocol led to widely variable compression parameters in Asian women. Based on phantom study, it is feasible to reduce compression force up to 32.5% with minimal effects on image quality and MGD.

Matched MeSH terms: Breast Density
Fulltext Association of bone mineral density to dietary intake and predictors of breast cancer in premenopausal and postmenopausal Malaysian women

Norhayati Mohd Zain, Kanaga, Kumari Chelliah, Vengkatha, Priya Seriramulu, Shantini Arasaratnam, Poh, Bee Koon

Jurnal Sains Kesihatan Malaysia, 2017;15(22):137-144.
MyJurnal

Daily food intake of women may affect their bone health by altering their bone mineral density (BMD) as the lack of certain
nutrients may affect bone integrity whilst, BMD also can be a predictor of breast cancer. To date, many studies have been
conducted to discuss on association of BMD and mammographic breast density (MBD) and how both are related to breast
cancer risks but no consideration has been made on dietary intake. Therefore, this study was designed to determine
the association of dietary intake with BMD and other breast cancer risk factors. A cross-sectional study on 76 pre- and
postmenopausal women above 40 years underwent mammogram screening and Dual Energy X-ray Absorptiometry (DEXA)
was conducted in Hospital Kuala Lumpur (HKL) for the duration of 1 year. Purposive sampling method was used to choose
the respondents. Women who are diagnosed with breast cancer and underwent cancer treatment were excluded from this
study. DEXA unit (Hologic Discovery W, Hologic, Inc) were used to measure BMD at the femoral neck and lumbar spine in
grams per centimetre squared (g/cm2
) and they were classified into normal and abnormal group based on the T-scores.
The subjects were asked about their daily dietary pattern for a duration of three days using Diet History Questionnaire
(DHQ). The mean of selected characteristics were compared between groups. Additionally, binary logistic regression was
used to determine the association between diet intake with BMD and other risk factors of breast cancer. The total number
of pre- and postmenopausal women who consented to participate in this study are equal. The mean age was 47.1 years
and 54.9 years for premenopausal and postmenopausal women respectively. The results indicate only menopausal age of
the women was statistically significant (p < 0.05). A number of 17% premenopausal and 9% of postmenopausal women
showed to have family history of breast cancer, however, it was not statistically significant (p = 0.12). There was no
significant difference in daily energy intake of food in both groups (p = 0.22). None of the nutrients in daily food intake
showed to be statistically significant. Menstrual status showed an association with BMD with p < 0.05 and the remaining
risk factors did not show any association. Logistic regression revealed that only menstrual status had correlation with
BMD in both groups. This study provided the dietary pattern and the effects on bone health. The association of other risk
factors of breast cancer with BMD were also analysed and most of it showed a negative association.

Matched MeSH terms: Breast Density
Fulltext Developing a new case based computer-aided detection scheme and an adaptive cueing method to improve performance in detecting mammographic lesions

Tan M, Aghaei F, Wang Y, Zheng B

Phys Med Biol, 2017 01 21;62(2):358-376.
PMID: 27997380 DOI: 10.1088/1361-6560/aa5081

The purpose of this study is to evaluate a new method to improve performance of computer-aided detection (CAD) schemes of screening mammograms with two approaches. In the first approach, we developed a new case based CAD scheme using a set of optimally selected global mammographic density, texture, spiculation, and structural similarity features computed from all four full-field digital mammography images of the craniocaudal (CC) and mediolateral oblique (MLO) views by using a modified fast and accurate sequential floating forward selection feature selection algorithm. Selected features were then applied to a 'scoring fusion' artificial neural network classification scheme to produce a final case based risk score. In the second approach, we combined the case based risk score with the conventional lesion based scores of a conventional lesion based CAD scheme using a new adaptive cueing method that is integrated with the case based risk scores. We evaluated our methods using a ten-fold cross-validation scheme on 924 cases (476 cancer and 448 recalled or negative), whereby each case had all four images from the CC and MLO views. The area under the receiver operating characteristic curve was AUC = 0.793 ± 0.015 and the odds ratio monotonically increased from 1 to 37.21 as CAD-generated case based detection scores increased. Using the new adaptive cueing method, the region based and case based sensitivities of the conventional CAD scheme at a false positive rate of 0.71 per image increased by 2.4% and 0.8%, respectively. The study demonstrated that supplementary information can be derived by computing global mammographic density image features to improve CAD-cueing performance on the suspicious mammographic lesions.

Matched MeSH terms: Breast Density
Fulltext International Consortium on Mammographic Density: Methodology and population diversity captured across 22 countries

McCormack VA, Burton A, dos-Santos-Silva I, Hipwell JH, Dickens C, Salem D, et al.

Cancer Epidemiol, 2016 Feb;40:141-51.
PMID: 26724463 DOI: 10.1016/j.canep.2015.11.015

Mammographic density (MD) is a quantitative trait, measurable in all women, and is among the strongest markers of breast cancer risk. The population-based epidemiology of MD has revealed genetic, lifestyle and societal/environmental determinants, but studies have largely been conducted in women with similar westernized lifestyles living in countries with high breast cancer incidence rates. To benefit from the heterogeneity in risk factors and their combinations worldwide, we created an International Consortium on Mammographic Density (ICMD) to pool individual-level epidemiological and MD data from general population studies worldwide. ICMD aims to characterize determinants of MD more precisely, and to evaluate whether they are consistent across populations worldwide. We included 11755 women, from 27 studies in 22 countries, on whom individual-level risk factor data were pooled and original mammographic images were re-read for ICMD to obtain standardized comparable MD data. In the present article, we present (i) the rationale for this consortium; (ii) characteristics of the studies and women included; and (iii) study methodology to obtain comparable MD data from original re-read films. We also highlight the risk factor heterogeneity captured by such an effort and, thus, the unique insight the pooled study promises to offer through wider exposure ranges, different confounding structures and enhanced power for sub-group analyses.

Matched MeSH terms: Breast Density
Fulltext Long-term exposure to insulin and volumetric mammographic density: observational and genetic associations in the Karma study

Borgquist S, Rosendahl AH, Czene K, Bhoo-Pathy N, Dorkhan M, Hall P, et al.

Breast Cancer Res, 2018 08 09;20(1):93.
PMID: 30092829 DOI: 10.1186/s13058-018-1026-7

BACKGROUND: Long-term insulin exposure has been implicated in breast cancer etiology, but epidemiological evidence remains inconclusive. The aims of this study were to investigate the association of insulin therapy with mammographic density (MD) as an intermediate phenotype for breast cancer and to assess associations with long-term elevated circulating insulin levels using a genetic score comprising 18 insulin-associated variants.
METHODS: We used data from the KARolinska MAmmography (Karma) project, a Swedish mammography screening cohort. Insulin-treated patients with type 1 (T1D, n = 122) and type 2 (T2D, n = 237) diabetes were identified through linkage with the Prescribed Drug Register and age-matched to 1771 women without diabetes. We assessed associations with treatment duration and insulin glargine use, and we further examined MD differences using non-insulin-treated T2D patients as an active comparator. MD was measured using a fully automated volumetric method, and analyses were adjusted for multiple potential confounders. Associations with the insulin genetic score were assessed in 9437 study participants without diabetes.
RESULTS: Compared with age-matched women without diabetes, insulin-treated T1D patients had greater percent dense (8.7% vs. 11.4%) and absolute dense volumes (59.7 vs. 64.7 cm3), and a smaller absolute nondense volume (615 vs. 491 cm3). Similar associations were observed for insulin-treated T2D, and estimates were not materially different in analyses comparing insulin-treated T2D patients with T2D patients receiving noninsulin glucose-lowering medication. In both T1D and T2D, the magnitude of the association with the absolute dense volume was highest for long-term insulin therapy (≥ 5 years) and the long-acting insulin analog glargine. No consistent evidence of differential associations by insulin treatment duration or type was found for percent dense and absolute nondense volumes. Genetically predicted insulin levels were positively associated with percent dense and absolute dense volumes, but not with the absolute nondense volume (percentage difference [95% CI] per 1-SD increase in insulin genetic score = 0.8 [0.0; 1.6], 0.9 [0.1; 1.8], and 0.1 [- 0.8; 0.9], respectively).
CONCLUSIONS: The consistency in direction of association for insulin treatment and the insulin genetic score with the absolute dense volume suggest a causal influence of long-term increased insulin exposure on mammographic dense breast tissue.

Matched MeSH terms: Breast Density/drug effects*
A novel method of determining breast cancer risk using parenchymal textural analysis of mammography images on an Asian cohort

Tan M, Mariapun S, Yip CH, Ng KH, Teo SH

Phys Med Biol, 2019 01 31;64(3):035016.
PMID: 30577031 DOI: 10.1088/1361-6560/aafabd

Historically, breast cancer risk prediction models are based on mammographic density measures, which are dichotomous in nature and generally categorize each voxel or area of the breast parenchyma as 'dense' or 'not dense'. Using these conventional methods, the structural patterns or textural components of the breast tissue elements are not considered or ignored entirely. This study presents a novel method to predict breast cancer risk that combines new texture and mammographic density based image features. We performed a comprehensive study of the correlation of 944 new and conventional texture and mammographic density features with breast cancer risk on a cohort of Asian women. We studied 250 breast cancer cases and 250 controls matched at full-field digital mammography (FFDM) status for age, BMI and ethnicity. Stepwise regression analysis identified relevant features to be included in a linear discriminant analysis (LDA) classifier model, trained and tested using a leave-one-out based cross-validation method. The area under the receiver operating characteristic (AUC) and adjusted odds ratios (ORs) were used as the two performance assessment indices in our study. For the LDA trained classifier, the adjusted OR was 6.15 (95% confidence interval: 3.55-10.64) and for Volpara volumetric breast density, 1.10 (0.67-1.81). The AUC for the LDA trained classifier was 0.68 (0.64-0.73), compared to 0.52 (0.47-0.57) for Volpara volumetric breast density (p breast cancer risk assessment based models. Parenchymal texture analysis has an important role for stratifying breast cancer risk in women, which can be implemented to routine breast cancer screening strategies.

Matched MeSH terms: Breast Density
Fulltext Differential Burden of Rare and Common Variants on Tumor Characteristics, Survival, and Mode of Detection in Breast Cancer

Li J, Ugalde-Morales E, Wen WX, Decker B, Eriksson M, Torstensson A, et al.

Cancer Res, 2018 11 01;78(21):6329-6338.
PMID: 30385609 DOI: 10.1158/0008-5472.CAN-18-1018

Genetic variants that increase breast cancer risk can be rare or common. This study tests whether the genetic risk stratification of breast cancer by rare and common variants in established loci can discriminate tumors with different biology, patient survival, and mode of detection. Multinomial logistic regression tested associations between genetic risk load [protein-truncating variant (PTV) carriership in 31 breast cancer predisposition genes-or polygenic risk score (PRS) using 162 single-nucleotide polymorphisms], tumor characteristics, and mode of detection (OR). Ten-year breast cancer-specific survival (HR) was estimated using Cox regression models. In this unselected cohort of 5,099 patients with breast cancer diagnosed in Sweden between 2001 and 2008, PTV carriers (n = 597) were younger and associated with more aggressive tumor phenotypes (ER-negative, large size, high grade, high proliferation, luminal B, and basal-like subtype) and worse outcome (HR, 1.65; 1.16-2.36) than noncarriers. After excluding 92 BRCA1/2 carriers, PTV carriership remained associated with high grade and worse survival (HR, 1.76; 1.21-2.56). In 5,007 BRCA1/2 noncarriers, higher PRS was associated with less aggressive tumor characteristics (ER-positive, PR-positive, small size, low grade, low proliferation, and luminal A subtype). Among patients with low mammographic density (<25%), non-BRCA1/2 PTV carriers were more often interval than screen-detected breast cancer (OR, 1.89; 1.12-3.21) than noncarriers. In contrast, higher PRS was associated with lower risk of interval compared with screen-detected cancer (OR, 0.77; 0.64-0.93) in women with low mammographic density. These findings suggest that rare and common breast cancer susceptibility loci are differentially associated with tumor characteristics, survival, and mode of detection.Significance: These findings offer the potential to improve screening practices for breast cancer by providing a deeper understanding of how risk variants affect disease progression and mode of detection. Cancer Res; 78(21); 6329-38. ©2018 AACR.

Matched MeSH terms: Breast Density