Association between Breast Density and Subsequent Breast Cancer Following Treatment for Ductal Carcinoma In situ

Biomarkers for Breast Adenocarcinoma Using In Silico Approaches

This work elucidates the idea of finding probable critical genes linked to breast adenocarcinoma. In this study, the GEO database gene expression profile data set (GSE70951) was retrieved to look for genes that were expressed variably across breast adenocarcinoma samples and healthy tissue samples. The genes were confirmed to be part of the PPI network for breast cancer pathogenesis and prognosis. In Cytoscape, the CytoHubba module was used to discover the hub genes. For correlation analysis, the predictive biomarker of these hub genes, as well as GEPIA, was used. A total of 155 (85 upregulated genes and 70 downregulated genes) were identified. By integrating the PPI and CytoHubba data, the major key/hub genes were selected from the results. The KM plotter is employed to find the prognosis of those major pivot genes, and the outcome shows worse prognosis in breast adenocarcinoma patients. Further experimental validation will show the predicted expression levels of those hub genes. The overall result of our study gives the consequences for the identification of a critical gene to ease the molecular targeting therapy for breast adenocarcinoma. It could be used as a prognostic biomarker and could lead to therapy options for breast adenocarcinoma.

Preoperative MRI in breast cancer: effect of breast density on biopsy rate and yield

PURPOSE

Preoperative breast MRI is used to evaluate for additional cancer and extent of disease for newly diagnosed breast cancer, yet benefits and harms of preoperative MRI are not well-documented. We examined whether preoperative MRI yields additional biopsy and cancer detection by extent of breast density.

METHODS

We followed women in the Breast Cancer Surveillance Consortium with an incident breast cancer diagnosed from 2005 to 2017. We quantified breast biopsies and cancers detected within 6 months of diagnosis by preoperative breast MRI receipt, overall and by breast density, accounting for MRI selection bias using inverse probability weighted logistic regression.

RESULTS

Among 19,324 women with newly diagnosed breast cancer, 28% had preoperative MRI, 11% additional biopsy, and 5% additional cancer detected. Four times as many women with preoperative MRI underwent additional biopsy compared to women without MRI (22.6% v. 5.1%). Additional biopsy rates with preoperative MRI increased with increasing breast density (27.4% for extremely dense compared to 16.2% for almost entirely fatty breasts). Rates of additional cancer detection were almost four times higher for women with v. without MRI (9.9% v. 2.6%). Conditional on additional biopsy, age-adjusted rates of additional cancer detection were lowest among women with extremely dense breasts, regardless of imaging modality (with MRI: 35.0%; 95% CI 27.0-43.0%; without MRI: 45.1%; 95% CI 32.6-57.5%).

CONCLUSION

For women with dense breasts, preoperative MRI was associated with much higher biopsy rates, without concomitant higher cancer detection. Preoperative MRI may be considered for some women, but selecting women based on breast density is not supported by evidence.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT02980848; registered 2017.

Breast adipocyte size associates with ipsilateral invasive breast cancer risk after ductal carcinoma in situ

Although ductal carcinoma in situ (DCIS) is a non-obligate precursor to ipsilateral invasive breast cancer (iIBC), most DCIS lesions remain indolent. Hence, overdiagnosis and overtreatment of DCIS is a major concern. There is an urgent need for prognostic markers that can distinguish harmless from potentially hazardous DCIS. We hypothesised that features of the breast adipose tissue may be associated with risk of subsequent iIBC. We performed a case-control study nested in a population-based DCIS cohort, consisting of 2658 women diagnosed with primary DCIS between 1989 and 2005, uniformly treated with breast conserving surgery (BCS) alone. We assessed breast adipose features with digital pathology (HALO®, Indica Labs) and related these to iIBC risk in 108 women that developed subsequent iIBC (cases) and 168 women who did not (controls) by conditional logistic regression, accounting for clinicopathological and immunohistochemistry variables. Large breast adipocyte size was significantly associated with iIBC risk (odds ratio (OR) 2.75, 95% confidence interval (95% CI) = 1.25-6.05). High cyclooxygenase (COX)-2 protein expression in the DCIS cells was also associated with subsequent iIBC (OR 3.70 (95% CI = 1.59-8.64). DCIS with both high COX-2 expression and large breast adipocytes was associated with a 12-fold higher risk (OR 12.0, 95% CI = 3.10-46.3, P < 0.001) for subsequent iIBC compared with women with smaller adipocyte size and low COX-2 expression. Large breast adipocytes combined with high COX-2 expression in DCIS is associated with a high risk of subsequent iIBC. Besides COX-2, adipocyte size has the potential to improve clinical management in patients diagnosed with primary DCIS.

Heparanase Promotes Syndecan-1 Expression to Mediate Fibrillar Collagen and Mammographic Density in Human Breast Tissue Cultured ex vivo

Mammographic density (MD) is a strong and independent factor for breast cancer (BC) risk and is increasingly associated with BC progression. We have previously shown in mice that high MD, which is characterized by the preponderance of a fibrous stroma, facilitates BC xenograft growth and metastasis. This stroma is rich in extracellular matrix (ECM) factors, including heparan sulfate proteoglycans (HSPGs), such as the BC-associated syndecan-1 (SDC1). These proteoglycans tether growth factors, which are released by heparanase (HPSE). MD is positively associated with estrogen exposure and, in cell models, estrogen has been implicated in the upregulation of HPSE, the activity of which promotes SDC expression. Herein we describe a novel measurement approach (single-sided NMR) using a patient-derived explant (PDE) model of normal human (female) mammary tissue cultured ex vivo to investigate the role(s) of HPSE and SDC1 on MD. Relative HSPG gene and protein analyses determined in patient-paired high vs. low MD tissues identified SDC1 and SDC4 as potential mediators of MD. Using the PDE model we demonstrate that HPSE promotes SDC1 rather than SDC4 expression and cleavage, leading to increased MD. In this model system, synstatin (SSTN), an SDC1 inhibitory peptide designed to decouple SDC1-ITGαvβ3 parallel collagen alignment, reduced the abundance of fibrillar collagen as assessed by picrosirius red viewed under polarized light, and reduced MD. Our results reveal a potential role for HPSE in maintaining MD via its direct regulation of SDC1, which in turn physically tethers collagen into aligned fibers characteristic of MD. We propose that inhibitors of HPSE and/or SDC1 may afford an opportunity to reduce MD in high BC risk individuals and reduce MD-associated BC progression in conjunction with established BC therapies.

Quantitative stain-free imaging and digital profiling of collagen structure reveal diverse survival of triple negative breast cancer patients

Background

Stromal and collagen biology has a significant impact on tumorigenesis and metastasis. Collagen is a major structural extracellular matrix component in breast cancer, but its role in cancer progression is the subject of historical debate. Collagen may represent a protective layer that prevents cancer cell migration, while increased stromal collagen has been demonstrated to facilitate breast cancer metastasis.

Methods

Stromal remodeling is characterized by collagen fiber restructuring and realignment in stromal and tumoral areas. The patients in our study were diagnosed with triple-negative breast cancer in Singapore General Hospital from 2003 to 2015. We designed novel image processing and quantification pipelines to profile collagen structures using numerical imaging parameters. Our solution differentiated the collagen into two distinct modes: aggregated thick collagen (ATC) and dispersed thin collagen (DTC).

Results

Extracted parameters were significantly associated with bigger tumor size and DCIS association. Of numerical parameters, ATC collagen fiber density (CFD) and DTC collagen fiber length (CFL) were of significant prognostic value for disease-free survival and overall survival for the TNBC patient cohort. Using these two parameters, we built a predictive model to stratify the patients into four groups.

Conclusions

Our study provides a novel insight for the quantitation of collagen in the tumor microenvironment and will help predict clinical outcomes for TNBC patients. The identified collagen parameters, ATC CFD and DTC CFL, represent a new direction for clinical prognosis and precision medicine. We also compared our result with benign samples and DICS samples to get novel insight about the TNBC heterogeneity. The improved understanding of collagen compartment of TNBC may provide insights into novel targets for better patient stratification and treatment.

Does Breast Density Increase the Risk of Re-excision for Women with Breast Cancer Having Breast-Conservation Therapy?

BACKGROUND

Women with dense breasts may have less-accurate preoperative evaluation of extent of disease, potentially affecting the achievement of negative margins. The goal of this study is to examine the association between breast density and re-excision rates in women having breast-conserving surgery for invasive breast cancer.

PATIENTS AND METHODS

Women with stage I/II invasive breast cancer treated with breast-conserving surgery between 1/1/2014 and 10/31/2014 were included. Breast density was assessed by two radiologists. The association between breast density and re-excision was examined using logistic regression.

RESULTS

Seven hundred and one women were included. Overall, 106 (15.1%) women had at least one re-excision. Younger age at diagnosis was associated with increased breast density (p < 0.001). On univariable analysis, increased breast density was associated with significantly increased odds of re-excision (odds ratio [OR] 1.38, 95% confidence interval [CI] 1.04-1.83), as was multifocal disease, human epidermal growth factor receptor 2 (HER2) positive status, and extensive intraductal component (EIC) (all p < 0.05). On multivariable analysis, breast density remained significantly associated with increased odds of re-excision (OR 1.37, 95% CI 1.00-1.86), as did multifocality and EIC. HER2 positive status was not significantly associated with re-excision on multivariable analysis.

CONCLUSIONS

Women with dense breasts are more likely to need additional surgery (re-excision after breast-conserving surgery), but increased breast density did not adversely affect disease-free survival in our study. Our findings support the need for further study in developing techniques that can help decrease re-excisions for women with dense breasts who undergo breast-conserving surgery.

Are mammographic density phenotypes associated with breast cancer treatment response and clinical outcomes? A systematic review and meta-analysis

Mammographic density (MD) increases breast cancer (BC) risk, however, its association with patient outcomes is unclear. We examined the association of baseline MD (BMD), and MD reduction (MDR) following BC treatment with patient outcomes. Six databases (CINAHL, Scopus, PubMed, Web of Science, MEDLINE, and Embase) were used to identify relevant articles. The PRISMA strategy was used to extract relevant details. Study quality and risk of bias were assessed using the "Quality In Prognosis Studies" (QUIPS) tool. A Meta-analysis and pooled risk estimates were performed. Results showed that BMD is associated with contralateral breast cancer (CBC) risk (HR = 1.9; 95%CI: 1.3-3.0, p = 0.0007), recurrence (HR = 2.0; 95%CI: 1.0-4.0, p = 0.04), and mortality (HR = 1.4; 95%CI: 1.1-1.9, p = 0.003). No association was found between BMD and prognosis (HR = 3.2; 95%CI: 0.9-11.2, p = 0.06). Data on risk estimates (95%CI) from BMD for survival [RR: 1.75; 0.99-3.1 to 2.4; 1.4-4.1], ipsilateral BC [HR: 1; 0.6-1.6 to 3; 1.2-7.5], and treatment response (OR, 1.8; 0.98-3.3) are limited. MDR showed no association with mortality (HR = 0.5; 95%CI: 0.2-1.2, p = 0.13). MDR is associated with a reduced risk of recurrence [HR/RR: 0.35; 0.17-0.68 to 1.33; 0.67-2.65)], however data on MDR and outcomes such as mortality [HR/RR: 0.5; 0.27-0.93 to 0.59; 0.22-0.88], and CBC risk [RR/HR: 0.53; 0.24-0.84 to 1.3; 0.6-2.7] are limited. Evidence, although sparse, demonstrates that high BMD is associated with an increased risk of recurrence, CBC, and mortality. Conversely, MDR is associated with a reduced risk of BC recurrence, CBC, and BC-related mortality.

A review of the influence of mammographic density on breast cancer clinical and pathological phenotype

PURPOSE

It is well established that high mammographic density (MD), when adjusted for age and body mass index, is one of the strongest known risk factors for breast cancer (BC), and also associates with higher incidence of interval cancers in screening due to the masking of early mammographic abnormalities. Increasing research is being undertaken to determine the underlying histological and biochemical determinants of MD and their consequences for BC pathogenesis, anticipating that improved mechanistic insights may lead to novel preventative or treatment interventions. At the same time, technological advances in digital and contrast mammography are such that the validity of well-established relationships needs to be re-examined in this context.

METHODS

With attention to old versus new technologies, we conducted a literature review to summarise the relationships between clinicopathologic features of BC and the density of the surrounding breast tissue on mammography, including the associations with BC biological features inclusive of subtype, and implications for the clinical disease course encompassing relapse, progression, treatment response and survival.

RESULTS AND CONCLUSIONS

There is reasonable evidence to support positive relationships between high MD (HMD) and tumour size, lymph node positivity and local relapse in the absence of radiotherapy, but not between HMD and LVI, regional relapse or distant metastasis. Conflicting data exist for associations of HMD with tumour location, grade, intrinsic subtype, receptor status, second primary incidence and survival, which need further confirmatory studies. We did not identify any relationships that did not hold up when data involving newer imaging techniques were employed in analysis.

Predictors of an Invasive Breast Cancer Recurrence after DCIS: A Systematic Review and Meta-analyses

We performed a systematic review with meta-analyses to summarize current knowledge on prognostic factors for invasive disease after a diagnosis of ductal carcinoma in situ (DCIS). Eligible studies assessed risk of invasive recurrence in women primarily diagnosed and treated for DCIS and included at least 10 ipsilateral-invasive breast cancer events and 1 year of follow-up. Quality in Prognosis Studies tool was used for risk of bias assessment. Meta-analyses were performed to estimate the average effect size of the prognostic factors. Of 1,781 articles reviewed, 40 articles met the inclusion criteria. Highest risk of bias was attributable to insufficient handling of confounders and poorly described study groups. Six prognostic factors were statistically significant in the meta-analyses: African-American race [pooled estimate (ES), 1.43; 95% confidence interval (CI), 1.15-1.79], premenopausal status (ES, 1.59; 95% CI, 1.20-2.11), detection by palpation (ES, 1.84; 95% CI, 1.47-2.29), involved margins (ES, 1.63; 95% CI, 1.14-2.32), high histologic grade (ES, 1.36; 95% CI, 1.04-1.77), and high p16 expression (ES, 1.51; 95% CI, 1.04-2.19). Six prognostic factors associated with invasive recurrence were identified, whereas many other factors need confirmation in well-designed studies on large patient numbers. Furthermore, we identified frequently occurring biases in studies on invasive recurrence after DCIS. Avoiding these common methodological pitfalls can improve future study designs.

Dose-dependent effect of mammographic breast density on the risk of contralateral breast cancer

PURPOSE

Increased mammographic breast density is a significant risk factor for breast cancer. It is not clear if it is also a risk factor for the development of contralateral breast cancer.

METHODS

The data were obtained from Breast Cancer Surveillance Consortium and included women diagnosed with invasive breast cancer or ductal carcinoma in situ between ages 18 and 88 and years 1995 and 2009. Each case of contralateral breast cancer was matched with three controls based on year of first breast cancer diagnosis, race, and length of follow-up. A total of 847 cases and 2541 controls were included. The risk factors included in the study were mammographic breast density, age of first breast cancer diagnosis, family history of breast cancer, anti-estrogen treatment, hormone replacement therapy, menopausal status, and estrogen receptor status, all from the time of first breast cancer diagnosis. Both univariate analysis and multivariate conditional logistic regression analysis were performed.

RESULTS

In the final multivariate model, breast density, family history of breast cancer, and anti-estrogen treatment remained significant with p values less than 0.01. Increasing breast density had a dose-dependent effect on the risk of contralateral breast cancer. Relative to 'almost entirely fat' category of breast density, the adjusted odds ratios (and p values) in the multivariate analysis for 'scattered density,' 'heterogeneously dense,' and 'extremely dense' categories were 1.65 (0.036), 2.10 (0.002), and 2.32 (0.001), respectively.

CONCLUSION

Breast density is an independent and significant risk factor for development of contralateral breast cancer. This risk factor should contribute to clinical decision making.

The association of mammographic density with risk of contralateral breast cancer and change in density with treatment in the WECARE study

Background

Mammographic density (MD) is an established predictor of risk of a first breast cancer, but the relationship of MD to contralateral breast cancer (CBC) risk is not clear, including the roles of age, mammogram timing, and change with treatment. Multivariable prediction models for CBC risk are needed and MD could contribute to these.

Methods

We conducted a case-control study of MD and CBC risk in phase II of the WECARE study where cases had a CBC diagnosed ≥ 2 years after first diagnosis at age <55 years and controls had unilateral breast cancer (UBC) with similar follow-up time. We retrieved film mammograms of the unaffected breast from two time points, prior to/at the time of the first diagnosis (253 CBC cases, 269 UBC controls) and ≥ 6 months up to 48 months following the first diagnosis (333 CBC cases, 377 UBC controls). Mammograms were digitized and percent MD (%MD) was measured using the thresholding program Cumulus. Odds ratios (OR) and 95% confidence intervals (CI) for association between %MD and CBC, adjusted for age, treatment, and other factors related to CBC, were estimated using logistic regression. Linear regression was used to estimate the association between treatment modality and change in %MD in 467 women with mammograms at both time points.

Results

For %MD assessed following diagnosis, there was a statistically significant trend of increasing CBC with increasing %MD (p = 0.03). Lower density (<25%) was associated with reduced risk of CBC compared to 25 to < 50% density (OR 0.69, 95% CI 0.49, 0.98). Similar, but weaker, associations were noted for %MD measurements prior to/at diagnosis. The relationship appeared strongest in women aged < 45 years and non-existent in women aged 50 to 54 years. A decrease of ≥ 10% in %MD between first and second mammogram was associated marginally with reduced risk of CBC (OR 0.63, 95% CI 0.40, 1.01) compared to change of <10%. Both tamoxifen and chemotherapy were associated with statistically significant 3% decreases in %MD (p < 0.01).

Conclusions

Post-diagnosis measures of %MD may be useful to include in CBC risk prediction models with consideration of age at diagnosis. Chemotherapy is associated with reductions in %MD, similar to tamoxifen.

Electronic supplementary material

The online version of this article (10.1186/s13058-018-0948-4) contains supplementary material, which is available to authorized users.

Automatic outer and inner breast tissue segmentation using multi-parametric MRI images of breast tumor patients

The objectives of the study were to develop a framework for automatic outer and inner breast tissue segmentation using multi-parametric MRI images of the breast tumor patients; and to perform breast density and tumor tissue analysis. MRI of the breast was performed on 30 patients at 3T-MRI. T₁, T₂ and PD-weighted(W) images, with and without fat saturation(WWFS), and dynamic-contrast-enhanced(DCE)-MRI data were acquired. The proposed automatic segmentation approach was performed in two steps. In step-1, outer segmentation of breast tissue from rest of body parts was performed on structural images (T₂-W/T₁-W/PD-W without fat saturation images) using automatic landmarks detection technique based on operations like profile screening, Otsu thresholding, morphological operations and empirical observation. In step-2, inner segmentation of breast tissue into fibro-glandular(FG), fatty and tumor tissue was performed. For validation of breast tissue segmentation, manual segmentation was carried out by two radiologists and similarity coefficients(Dice and Jaccard) were computed for outer as well as inner tissues. FG density and tumor volume were also computed and analyzed. The proposed outer and inner segmentation approach worked well for all the subjects and was validated by two radiologists. The average Dice and Jaccard coefficients value for outer segmentation using T₂-W images, obtained by two radiologists, were 0.977 and 0.951 respectively. These coefficient values for FG tissue were 0.915 and 0.875 respectively whereas for tumor tissue, values were 0.968 and 0.95 respectively. The volume of segmented tumor ranged over 2.1 cm3–7.08 cm³. The proposed approach provided automatic outer and inner breast tissue segmentation, which enables automatic calculations of breast tissue density and tumor volume. This is a complete framework for outer and inner breast segmentation method for all structural images.

Identifying progression predictors of breast ductal carcinoma in situ

Ductal carcinoma in situ (DCIS) refers to neoplastic epithelial cells proliferating within the mammary ducts of the breast, which have not breached the basement membrane nor invaded surrounding tissues. Traditional thinking holds that DCIS represents an early step in a linear progression towards invasive ductal carcinoma (IDC). However, as only approximately half of DCIS cases progress to IDC, important questions around the key determinants of malignant progression need to be answered. Recent studies have revealed that molecular differences between DCIS and IDC cells are not found at the genomic level; instead, altered patterns of gene expression and post-translational regulation lead to distinct transcriptomic and proteomic profiles. Therefore, understanding malignant progression will require a different approach that takes into account the diverse tumour cell extrinsic factors driving changes in tumour cell gene expression necessary for the invasive phenotype. Here, we review the roles of the tumour stroma (including mesenchymal cells, immune cells and the extracellular matrix) and myoepithelial cells in malignant progression and make a case for a more integrated approach to the study and assessment of DCIS and its progression, or lack thereof, to invasive disease.

The hallmarks of premalignant conditions: a molecular basis for cancer prevention

The hallmarks of premalignant lesions were first described in the 1970s, a time when relatively little was known about the molecular underpinnings of cancer. Yet it was clear there must be opportunities to intervene early in carcinogenesis. A vast array of molecular information has since been uncovered, with much of this stemming from studies of existing cancer or cancer models. Here, examples of how an understanding of cancer biology has informed cancer prevention studies are highlighted and emerging areas that may have implications for the field of cancer prevention research are described. A note of caution accompanies these examples, in that while there are similarities, there are also fundamental differences between the biology of premalignant lesions or premalignant conditions and invasive cancer. These differences must be kept in mind, and indeed leveraged, when exploring potential cancer prevention measures.

Cancer statistics: Breast cancer in situ

An estimated 60,290 new cases of breast carcinoma in situ are expected to be diagnosed in 2015, and approximately 1 in 33 women is likely to receive an in situ breast cancer diagnosis in her lifetime. Although in situ breast cancers are relatively common, their clinical significance and optimal treatment are topics of uncertainty and concern for both patients and clinicians. In this article, the American Cancer Society provides information about occurrence and treatment patterns for the 2 major subtypes of in situ breast cancer in the United States-ductal carcinoma in situ and lobular carcinoma in situ-using data from the North American Association of Central Cancer Registries and the 13 oldest Surveillance, Epidemiology, and End Results registries. The authors also present an overview of in situ breast cancer detection, treatment, risk factors, and prevention and discuss research needs and initiatives.

Breast cancer screening in an era of personalized regimens: a conceptual model and National Cancer Institute initiative for risk-based and preference-based approaches at a population level

Breast cancer screening holds a prominent place in public health, health care delivery, policy, and women's health care decisions. Several factors are driving shifts in how population-based breast cancer screening is approached, including advanced imaging technologies, health system performance measures, health care reform, concern for "overdiagnosis," and improved understanding of risk. Maximizing benefits while minimizing the harms of screening requires moving from a "1-size-fits-all" guideline paradigm to more personalized strategies. A refined conceptual model for breast cancer screening is needed to align women's risks and preferences with screening regimens. A conceptual model of personalized breast cancer screening is presented herein that emphasizes key domains and transitions throughout the screening process, as well as multilevel perspectives. The key domains of screening awareness, detection, diagnosis, and treatment and survivorship are conceptualized to function at the level of the patient, provider, facility, health care system, and population/policy arena. Personalized breast cancer screening can be assessed across these domains with both process and outcome measures. Identifying, evaluating, and monitoring process measures in screening is a focus of a National Cancer Institute initiative entitled PROSPR (Population-based Research Optimizing Screening through Personalized Regimens), which will provide generalizable evidence for a risk-based model of breast cancer screening, The model presented builds on prior breast cancer screening models and may serve to identify new measures to optimize benefits-to-harms tradeoffs in population-based screening, which is a timely goal in the era of health care reform.

Mammographic density-a review on the current understanding of its association with breast cancer

There has been considerable recent interest in the genetic, biological and epidemiological basis of mammographic density (MD), and the search for causative links between MD and breast cancer (BC) risk. This report will critically review the current literature on MD and summarize the current evidence for its association with BC. Keywords 'mammographic dens*', 'dense mammary tissue' or 'percent dens*' were used to search the existing literature in English on PubMed and Medline. All reports were critically analyzed. The data were assigned to one of the following aspects of MD: general association with BC, its relationship with the breast hormonal milieu, the cellular basis of MD, the generic variations of MD, and its significance in the clinical setting. MD adjusted for age, and BMI is associated with increased risk of BC diagnosis, advanced tumour stage at diagnosis and increased risk of both local recurrence and second primary cancers. The MD measures that predict BC risk have high heritability, and to date several genetic markers associated with BC risk have been found to also be associated with these MD risk predictors. Change in MD could be a predictor of the extent of chemoprevention with tamoxifen. Although the biological and genetic pathways that determine and perhaps modulate MD remain largely unresolved, significant inroads are being made into the understanding of MD, which may lead to benefits in clinical screening, assessment and treatment strategies. This review provides a timely update on the current understanding of MD's association with BC risk.

Role of dual-energy contrast-enhanced digital mammography as a problem-solving tool in dense breasts: A case report

Breast density is strongly and independently related to the risk of breast cancer. Women with very dense breasts may have up to five times higher chances of developing malignancy as compared to those with less breast density. Detecting lesions in extremely dense or heterogeneous breasts on screening mammogram can be difficult. We report a case of incidental bilateral breast malignancy in an asymptomatic patient in whom mammogram and screening ultrasound were equivocal.

Risk factors for second screen-detected or interval breast cancers in women with a personal history of breast cancer participating in mammography screening

BACKGROUND

Women with a personal history of breast cancer (PHBC) have increased risk of an interval cancer. We aimed to identify risk factors for second (ipsilateral or contralateral) screen-detected or interval breast cancer within 1 year of screening in PHBC women.

METHODS

Screening mammograms from women with history of early-stage breast cancer at Breast Cancer Surveillance Consortium-affiliated facilities (1996-2008) were examined. Associations between woman-level, screen-level, and first cancer variables and the probability of a second breast cancer were modeled using multinomial logistic regression for three outcomes [screen-detected invasive breast cancer, interval invasive breast cancer, or ductal carcinoma in situ (DCIS)] relative to no second breast cancer.

RESULTS

There were 697 second breast cancers, of these 240 were interval cancers, among 67,819 screens in 20,941 women. In separate models for women with DCIS or invasive first cancer, first breast cancer surgery predicted all three second breast cancer outcomes (P < 0.001), and high ORs for second breast cancers (between 1.95 and 4.82) were estimated for breast conservation without radiation (relative to mastectomy). In women with invasive first breast cancer, additional variables predicted risk (P < 0.05) for at least one of the three outcomes: first-degree family history, dense breasts, longer time between mammograms, young age at first breast cancer, first breast cancer stage, and adjuvant systemic therapy for first breast cancer; and risk of interval invasive breast cancer was highest in women <40 years at first breast cancer (OR, 3.41; 1.34-8.70), those with extremely dense breasts (OR, 2.55; 1.4-4.67), and those treated with breast conservation without radiation (OR, 2.67; 1.53-4.65).

CONCLUSION

Although the risk of a second breast cancer is modest, our models identify risk factors for interval second breast cancer in PHBC women.

IMPACT

Our findings may guide discussion and evaluations of tailored breast screening in PHBC women, and incorporating this information into clinical decision-making warrants further research.

Mammographic density and breast cancer risk: current understanding and future prospects

Variations in percent mammographic density (PMD) reflect variations in the amounts of collagen and number of epithelial and non-epithelial cells in the breast. Extensive PMD is associated with a markedly increased risk of invasive breast cancer. The PMD phenotype is important in the context of breast cancer prevention because extensive PMD is common in the population, is strongly associated with risk of the disease, and, unlike most breast cancer risk factors, can be changed. Work now in progress makes it likely that measurement of PMD will be improved in the near future and that understanding of the genetics and biological basis of the association of PMD with breast cancer risk will also improve. Future prospects for the application of PMD include mammographic screening, risk prediction in individuals, breast cancer prevention research, and clinical decision making.

Mammographic density and risk of second breast cancer after ductal carcinoma in situ

BACKGROUND

We examined whether mammographic density predicts risk of second breast cancers among patients with ductal carcinoma in situ (DCIS).

METHODS

The study included DCIS patients diagnosed during 1990 to 1997 and treated with breast-conserving surgery at Kaiser Permanente Northern California. Medical records were reviewed for clinical factors and subsequent breast cancers (DCIS and invasive). Ipsilateral mammograms from the index DCIS were assessed for density without knowledge of subsequent cancer status. Cox regression modeling was used to examine the association between mammographic density and risk of breast cancer events.

RESULTS

Of the 935 eligible DCIS patients, 164 (18%) had a subsequent ipsilateral breast cancer, and 59 (6%) had a new primary cancer in the contralateral breast during follow-up (median, 103 mo). Those with the greatest total area of density (upper 20% of values) were at increased risk for invasive disease in either breast [hazard ratio (HR), 2.1; 95% confidence interval (95% CI), 1.2-3.8] or any cancer (DCIS or invasive) in the ipsilateral (HR, 1.7; 95% CI, 1.0-2.9) or contralateral (HR, 3.0; 95% CI, 1.3-6.9) breast compared with those with the smallest area of density (bottom 20%). HRs for these same end points comparing those in the highest with those in the lowest American College of Radiology Breast Imaging Reporting and Data System category were 1.6 (95% CI, 0.7-3.6), 1.3 (95% CI, 0.7-2.6), and 5.0 (95% CI, 1.4-17.9), respectively. There was a suggestion of increasing risk of contralateral, but not ipsilateral, cancer with increasing percent density.

CONCLUSIONS

Women with mammographically dense breasts may be at higher risk of subsequent breast cancer, especially in the contralateral breast.

IMPACT

Information about mammographic density may help with DCIS treatment decisions.

Association between patient and tumor characteristics with clinical outcomes in women with ductal carcinoma in situ

We synthesized the evidence of the association between patient and tumor characteristics with clinical outcomes in women with ductal carcinoma in situ of the breast. We identified five randomized controlled clinical trials and 64 observational studies that were published in English from January 1970 to January 2009. Younger women with clinically presented ductal carcinoma in situ had higher risk of ipsilateral recurrent cancer. African Americans had higher mortality and greater rates of advanced recurrent cancer. Women with larger tumor size, comedo necrosis, worse pathological grading, positive surgical margins, and at a higher risk category, using a composite prognostic index, had worse outcomes. Inconsistent evidence suggested that positive HER2 receptor and negative estrogen receptor status were associated with worse outcomes. Synthesis of evidence was hampered by low statistical power to detect significant differences in predictor categories and inconsistent adjustment practices across the studies. Future research should address composite prediction indices among race groups for all outcomes.

Prevention of breast cancer in postmenopausal women: approaches to estimating and reducing risk

BACKGROUND

It is uncertain whether evidence supports routinely estimating a postmenopausal woman's risk of breast cancer and intervening to reduce risk.

METHODS

We systematically reviewed prospective studies about models and sex hormone levels to assess breast cancer risk and used meta-analysis with random effects models to summarize the predictive accuracy of breast density. We also reviewed prospective studies of the effects of exercise, weight management, healthy diet, moderate alcohol consumption, and fruit and vegetable intake on breast cancer risk, and used random effects models for a meta-analyses of tamoxifen and raloxifene for primary prevention of breast cancer. All studies reviewed were published before June 2008, and all statistical tests were two-sided.

RESULTS

Risk models that are based on demographic characteristics and medical history had modest discriminatory accuracy for estimating breast cancer risk (c-statistics range = 0.58-0.63). Breast density was strongly associated with breast cancer (relative risk [RR] = 4.03, 95% confidence interval [CI] = 3.10 to 5.26, for Breast Imaging Reporting and Data System category IV vs category I; RR = 4.20, 95% CI = 3.61 to 4.89, for >75% vs <5% of dense area), and adding breast density to models improved discriminatory accuracy (c-statistics range = 0.63-0.66). Estradiol was also associated with breast cancer (RR range = 2.0-2.9, comparing the highest vs lowest quintile of estradiol, P < .01). Most studies found that exercise, weight reduction, low-fat diet, and reduced alcohol intake were associated with a decreased risk of breast cancer. Tamoxifen and raloxifene reduced the risk of estrogen receptor-positive invasive breast cancer and invasive breast cancer overall.

CONCLUSIONS

Evidence from this study supports screening for breast cancer risk in all postmenopausal women by use of risk factors and breast density and considering chemoprevention for those found to be at high risk. Several lifestyle changes with the potential to prevent breast cancer should be recommended regardless of risk.

Mammographic density and breast cancer after ductal carcinoma in situ

Women with ductal carcinoma in situ (DCIS) are at substantially increased risk for a second breast cancer, but few strong predictors for these subsequent tumors have been identified. We used Cox regression modeling to examine the association between mammographic density at diagnosis of DCIS of 504 women from the National Surgical Adjuvant Breast and Bowel Project B-17 trial and risk of subsequent breast cancer events. In this group of patients, mostly 50 years old or older, approximately 6.6% had breasts categorized as highly dense (i.e., > or =75% of the breast occupied by dense tissue). After adjusting for treatment with radiotherapy, age, and body mass index, women with highly dense breasts had 2.8 (95% confidence interval [CI] = 1.3 to 6.1) times the risk of subsequent breast cancer (DCIS or invasive), 3.2 (95% CI = 1.2 to 8.5) times the risk of invasive breast cancer, and 3.0 (95% CI = 1.2 to 7.5) times the risk of any ipsilateral breast cancer, compared with women with less than 25% of the breast occupied by dense tissue. Our results provide initial evidence that the risk of second breast cancers may be increased among DCIS patients with highly dense breasts.