BMI) and risk of contralateral breast cancer (CBC) have reported mixed findings. We previously showed that obese postmenopausal women with estrogen receptor (ER)‐negative breast cancer have a fivefold higher risk of CBC compared with normal weight women. In the current analysis, we reexamined this relationship in the expanded Women's Environmental Cancer and Radiation Epidemiology (WECARE) Study, focusing on the impact of menopausal status and ER status of the first breast cancer. The WECARE Study is a population‐based case–control study of young women with CBC  and with unilateral breast cancer . Rate ratios (RR) and 95% confidence intervals (CI) were calculated to assess the relationship between BMI and risk of CBC stratified by menopausal and ER status. Positive associations with obesity and weight gain were limited to women who became postmenopausal following their first primary breast cancer. Among those with an ER‐negative first breast cancer, obesity  at first diagnosis was associated with an increased risk of CBC . Also, weight gain of ≥10 kg after first diagnosis was associated with an almost twofold increased risk of CBC . These results suggest that women with an ER‐negative first primary cancer who are obese at first primary diagnosis or who experience a large weight gain afterward may benefit from heightened surveillance. Future studies are needed to address the impact of weight loss interventions on risk of CBC.Studies examining the relationship between body mass index ( Body mass index (BMI) is positively associated with risk of first primary breast cancer in postmenopausal women BRCA1 or BRCA2 mutation Approximately 5–10% of breast cancer survivors will go on to develop a second primary tumor in the contralateral breast The Women's Environmental Cancer and Radiation Epidemiology (WECARE) Study is a population‐based case–control study of young women with CBC (cases) and women with unilateral breast cancer . Patient recruitment for the WECARE Study took place in two phases (termed WECARE I and WECARE II). In WECARE I, we previously reported that BMI at first diagnosis was not associated with risk of CBC, except among obese postmenopausal women with a first primary ER‐negative breast cancer whose CBC risk was fivefold greater than that of normal weight women The WECARE Study is a multicenter, population‐based case–control study of young women where cases are women with asynchronous CBC and controls are women with UBC. Participants were identified through eight population‐based cancer registries: Los Angeles County Cancer Surveillance Program; Cancer Surveillance System of the Fred Hutchinson Cancer Research Center ; State Health Registry of Iowa; The Cancer Surveillance Program of Orange County/San Diego‐Imperial Organization for Cancer Control ; the Greater Bay Area Cancer Registry ; and the Sacramento and Sierra Center Registry . All these cancer registries contribute to the National Cancer Institute (NCI) Surveillance, Epidemiology and End Results (SEER) program in the United States. Patients were also recruited from two other sources, the Ontario Cancer Registry and the Danish Breast Cancer Cooperative Group Registry, supplemented by data from the Danish Cancer Registry. The institutional review board at each recruitment site and the ethical committee system in Denmark and Ontario approved the study. Details of eligibility, recruitment, and study questionnaire have been described previously for WECARE I Briefly, WECARE Study participants were diagnosed prior to age 55 years, between 1985 and 2008 with a first primary invasive breast cancer (stage I–III). Cases were also diagnosed with a second primary CBC (in situ or invasive) at least 1 year later and controls had no history of any other second cancer diagnosis up to their reference date (the date of their matched case's second breast cancer diagnosis). Cases must also have been living in the same study reporting area for both diagnoses, while controls were required to be living in the same cancer reporting area on their reference date as they did for their first breast cancer diagnosis. Additionally, controls must not have undergone prophylactic mastectomy of the contralateral breast. All women had to be alive at the time of contact, able to provide informed consent, complete a telephone interview, and donate a blood or saliva sample for DNA extraction. Controls were matched to cases (1:2 for WECARE I and 1:1 for WECARE II) on year of birth (in 5‐year strata), year of diagnosis (in 4‐year strata), cancer registry region, and race/ethnicity. In WECARE I, cases and controls were further counter‐matched based on the cancer registry reported radiation treatment such that two members of each case–control trio had received radiation treatment for their first breast cancer. Counter‐matching was not used in WECARE II; this was taken into account in all statistical analyses (see below).Across the eight cancer registries, a total of 2354 CBC cases (998 from WECARE I and 1356 from WECARE II) and 3599 UBC controls (2122 from WECARE I and 1487 from WECARE II) were identified as being eligible and were approached for the study. Of these women, 1521 (65%) CBC cases (708 from WECARE I and 813 from WECARE II) and 2212 (61%) UBC controls (1399 from WECARE I and 813 from WECARE II) completed the phone interview and provided a DNA sample. Reasons for nonparticipation of eligible women included physician refusal (14 cases and 36 controls), interview refusal (768 cases and 1350 controls), and biospecimen refusal (32 cases and 47 controls).WECARE Study participants were interviewed by telephone using a structured questionnaire which was designed to obtain information about events occurring before the diagnosis of the first primary breast cancer, as well as events that occurred during the at‐risk period  for UBC controls). During the structured interview, participants were asked about personal demographics, medical history, family and reproductive history, hormone use, body size, smoking status, and alcohol intake. Additionally, medical records, pathology reports, and hospital charts were used to collect detailed treatment information  for the first primary breast cancer and any recurrences experienced prior to reference date, and tumor characteristics of the first primary tumor  status, histology).2; three controls at first diagnosis and three cases at reference date) or low BMI  were excluded. A further four cases/12 controls and seven cases/11 controls were excluded for having weight values that were outliers (<36.3 kg or >136 kg) at first diagnosis and reference date, respectively (note that there is some overlap between the missing and outlier categories listed above). Women who had reported use of MHT at first diagnosis and/or during the at‐risk period (103 cases and 130 controls) or had unknown menopausal status at first diagnosis or reference date (seven cases and 13 controls) were excluded. After these exclusions, the final analytic dataset included 1386 CBC cases and 2045 UBC controls.Body size measures were based on self‐report and supplemented as needed with medical record data. These included height and weight at age 18 years, weight at first breast cancer diagnosis, and weight at second diagnosis/reference date. Data at first diagnosis were available from both sources  for 72% of cases and 78% of controls. Results did not differ when one source was taken first over the other (data not shown). Fifteen women (six cases and nine controls) with missing information from both sources for height and/or weight at first diagnosis, and 22 (nine cases and 13 controls) at reference date were therefore excluded from the analysis. Additionally, women with an implausibly high BMI  and 95% CI to assess the relationship between BMI and risk of CBC. Models were adjusted for known risk factors for CBC, including age at diagnosis (continuous), age at menarche , number of full‐term pregnancies , first‐degree family history of breast cancer , histology , stage , chemotherapy treatment for a first breast cancer , hormonal treatment for a first breast cancer , and radiation therapy for a first breast cancer . A log‐weight covariate was included in the model to account for the sampling probability of the counter‐matching for radiation treatment status used in WECARE I. WECARE II participants (who were not counter‐matched) were assigned an offset term of 1.2), overweight (from 25 to <30 kg/m2), and obese (≥30 kg/m2). Weight change between first diagnosis and reference date was calculated and classified as >3 kg loss, 3 kg loss to <3 kg gain, 3 to <10 kg gain, and ≥10 kg gain. Average weight change (kg) per year (during the at‐risk period) was also calculated. Menopausal status at first diagnosis was estimated by comparing the date or age a woman last reported menstruating with the date of her first diagnosis of breast cancer. If a woman reported that she was still menstruating within 2 years before first diagnosis, or was pregnant, she was classified as premenopausal at that time point. A lag of 2 years was used to ensure minimal misclassification caused by rounding errors in the self‐report of age at menopause. Analyses were stratified by menopausal status during the at‐risk period . Women who were classified as pre‐ to postmenopausal are those who were premenopausal at the time of first breast cancer diagnosis, and became postmenopausal during the at‐risk period such that they were postmenopausal at reference date. Analyses were also stratified by the ER status of the first primary breast cancer.Body mass index was categorized as normal weight (<25 kg/mTable P = 0.04). When compared with normal weight women (BMI < 25 kg/m2), this association only reached statistical significance in overweight women , the association between weight gain and risk of CBC was limited to women with a BMI < 25 kg/m2 at first diagnosis . Average weight change per year was also modestly associated with risk of CBC, such that a 5% increase in CBC risk was seen per kg gained per year  in women who became postmenopausal during the at‐risk period (results no shown).Among women who were premenopausal throughout the at‐risk period, there was a modest inverse association between BMI at first diagnosis and risk of CBC . No association between average weight change per year and risk of CBC was seen in analyses stratified by ER status .A modest inverse association between BMI at first diagnosis and risk of CBC was observed among women diagnosed with an ER‐positive first primary breast cancer who became postmenopausal during the at‐risk period. The reduced CBC risk associated with obesity was of borderline statistical significance  will mitigate the potential for selection bias somewhat. Further, because cases and controls were both diagnosed with cancer, participation is less likely to differ by BMI status. Additionally, the proportion of eligible cases and controls who participated in the study was similar suggesting that any potential bias would be nondifferential. Other limitations include the predominantly Caucasian study population, limiting generalizability to other racial/ethnic groups, the lack of data on physical activity, and incomplete data on ER status of the second primary breast cancer, which precluded us from taking these variables into account in the analysis. Further, the majority of women maintained a stable weight, or gained weight, between first diagnosis and reference date with a relatively small proportion of women losing weight between these two time points. We were therefore limited in our ability to assess with confidence the impact of weight loss on the risk of CBC following a first breast cancer diagnosis.Of particular interest for the current analysis was the examination of the impact of ER status of the first primary breast cancer on the relationship between BMI at first diagnosis and weight change and risk of CBC. Having an ER‐negative first primary breast cancer is itself associated with increased risk of CBC None delcared.


Mammographic breast density (MBD) has been proven to be an important risk factor for breast cancer and an important determinant of mammographic screening performance. The measurement of density has changed dramatically since its inception. Initial qualitative measurement methods have been found to have limited consistency between readers, and in regards to breast cancer risk. Following the introduction of full-field digital mammography, more sophisticated measurement methodology is now possible. Automated computer-based density measurements can provide consistent, reproducible, and objective results. In this review paper, we describe various methods currently available to assess MBD, and provide a discussion on the clinical utility of such methods for breast cancer screening. Mammographic breast density (MBD) describes the proportion of radiologically dense fibroglandular tissue in the breast. Dense tissue comprises the functional glandular tissue  and the fibrous stromal tissue  of the breast . Due to MBD is an important consideration for both breast cancer screening and prevention. Due to their similar X-ray attenuation properties, dense tissue and tumors both appear white on a mammogram and numerous studies have shown the potential masking risk of MBD for cancer detection and negative association of increasing MBD with mammographic sensitivity ,9,10,11.Given that a mammographic image is a 2-dimensional (area-based) representation of a 3-dimensional (volumetric) physiological phenomenon, numerous density assessment methods have been proposed and developed over the past 4 decades that measure various aspects of fibroglandular tissue ,15,16,17The concept of MBD as a risk factor for breast cancer was first proposed by John Wolfe in 1976 ,19. WolfAn alternate pattern-based qualitative description system of breast density was developed by Lázló Tabár in 1997 . This moPattern-based assessment has suffered from a lack of reproducibility ,25,26,27Another semi-quantitative approach involves a visual estimation of the breast density using a Visual Analogue Scale (VAS). Readers mark along a continuous scale that represents 0–100% density, and these score sheets can then be scanned through software to obtain the percent breast density.VAS has been used in large clinical studies ,32,33,34Another visual method is the Breast Imaging-Reporting and Data System (BI-RADS) developed by the American College of Radiology (ACR), which is intended to provide a standardized method for reporting and streamlining imaging interpretations. This method also sought to help indicate the potential masking effect of dense breast tissue. Although a qualitative system to start with, the 4th edition of BI-RADS incorporated a quantitative component to the category definitions . More reConsidering the limitations of visual density assessment, less subjective and more quantitative measures have been sought. Martin Yaffe and researchers from the University of Toronto developed Cumulus as a semi-automated computerized measure of dense area . CumulusSeveral fully-automated breast density methods have been developed to provide objective measures of MBD that can be more easily integrated into clinical practice. However, as noted below, these methods vary widely in their approaches and which parameters of fibroglandular tissue are being measured.Many groups have developed automated area-based methods of MBD assessment, effectively removing the human interactive component of the Cumulus and Madena methods. Several of the research-only tools include: (1) an ImageJ based method developed at Karolinska Institute ; (2) Aut® [iReveal®   assessment tool produced by Hologic  and wasVolpara also outputs Volpara Density Grades (VDG) based on preset VBD thresholds, which are analogous to the BI-RADS visual density categories. Based on validation work compared to a panel of Mammography Quality Standards Act (MQSA) radiologists, the software can be configured to provide VDG scores that align with either the 4th or 5th edition BI-RADS definitions. Quantra 3 version 2.2.1 also outputs a BI-RADS-like score, analogous to the BI-RADS 5th edition density categories, by mapping an estimate of area-based density to BI-RADS. Several studies have compared the agreement between radiologists’ density assessments and the BI-RADS-like categories output from these software methods. Gweon et al. of South Korea compared Volpara (version 1.5.1) to BI-RADS categories as determined by radiologists utilizing FFDM images, and revealed a positive correlation between BI-RADS categories and the automated density assessment . The stuSXA, Volpara (version 1.4.3) and Quantra (version 3.2) to breast magnetic resonance imaging (MRI), which is considered the “ground truth” for measuring the accuracy of VBD estimates [SXA showed the highest correlation for VBD, though it is important to note that the slopes were substantially different from the identity line (1.0) for percent fibroglandular volume to MRI. Gubern-Merida similarly evaluated VDG assessment on FFDM mammograms by comparing results to volume estimates obtained from MRI data. Utilizing Volpara (version 1.4.3), high correlation to MRI was found for volumetric measurements from FFDM [A 2013 paper compared BDstimates . Volpararom FFDM .Philips Spectral Density Measurement Tool is another volumetric assessment method, but one that is based on spectral breast density as opposed to X-ray contrast . It is aDue to their 2-dimensional nature, area-based methods of MBD measurement inherently suffer from a set of biases. Firstly, they cannot determine the depth of the dense tissue or overlapping regions of dense tissue in the breast A. They aAs described in later sections, there is a growing demand for a reliable and consistent method of assessing density. Breast imagers have been using visual assessment for over a decade. While the visual method of density assessment is well-established, both in widescale acceptance and the relation of risk of interval cancer, as discussed in a later section, they do have limitations. This assessment method relies on human judgement and is thus inherently subjective. Individual radiologists can show high consistency, as determined by intra-reader agreement on density reading studies in both the US and abroad ,70,71,72The 5th edition BI-RADS criteria are more subjective and the new classification may see greater variation being introduced into density assessment. The new BI-RADS notes that even in breasts where <50% of the volume of the breast is dense, if the fibroglandular tissue is “sufficiently dense to obscure small masses” then the breast should be classified as “Heterogeneously Dense”; however, the visual interpretation of what is considered to be “sufficiently dense” can be subjective. Other MBD measures that report a BI-RADS analogous category, whether they be area-based or volumetric, will also need to address how exactly they will determine what “sufficiently dense” is from a quantitative stand-point. When comparing automated methods against each other, as was done in a 2015 study by Brandt et al. , variatip < 0.0001); with Quantra assigning lower density categories more frequently than by use of the visual assessment, or Volpara. Conversely, Volpara assigned the extremely dense category more frequently than visual assessment or Quantra. There were statistically significant differences found between Volpara and Quantra when assessing all volumetric data, though they were well correlated (y = 0.79–0.99).A recent study out of South Korea evaluated automated volumetric measurements with Volpara (version 1.5.1) and Quantra (version 2.0), in comparison to visual assessment utilizing the BI-RADS 5th edition . FFDM maWhile more repeatable than visual assessments, user-assisted methods are dependent on the experience and training of the reader. A study looking at the inter-reader and intra-reader variability using Cumulus software found higher inter-reader agreements for clinically-trained  versus non-clinically trained  readers . Fully aThe advent of FFDM provided numerous possibilities for quantitative MBD assessment that were not feasible with film screen mammography. However, variability in MBD assessment can be introduced by the different manufacturer post-processing algorithms applied to digital images to enhance their appearance for radiologist interpretation . Since sAnother source of variation in MBD assessment is the synthetic 2D mammogram, which is constructed from multiple projections of digital breast tomosynthesis . C-View Increased MBD affects various aspects of mammography screening performance. One driver of this is the aforementioned reason of both dense tissue and tumors attenuating X-rays in a similar manner. This contributes to higher rates of interval cancers  in women with higher MBD . Such inResults from large scale studies and screening populations have suggested that for women in the highest density categories, up to 50% of cancers are not detected by mammography  and are Other methods of evaluating the masking risk aspect of mammographic sensitivity have been investigated. An automated, quantitative algorithm was developed that estimates the likelihood of masking of simulated masses by dense tissue . HollandEven though breast density has been acknowledged in the medical community since the 1970s, it has not been widely applied to medical practice until the 2000s. While radiologists have long acknowledged the reduced sensitivity of mammography for women with increased MBD, this information was not, until recently, passed onto the women themselves. Because of being told her cancer may have been missed as a result of high MBD, a grassroots campaign called “Are You Dense?” was initiated, which aimed to spread information to the public about the risks and challenges associated with increased MBD . In 2009Twenty-four of the states require the use of specific language. Twenty-one states notify women with dense breasts; ten of the states choose to notify everyone, while Oregon only notifies women with “extreme density” (BI-RADS d). Most states (27) inform a woman if she has dense breasts, although in a majority of cases her personal density category is not specified. Twenty-four states mention the masking effect of density and a majority specify it is a risk factor for breast cancer. Unfortunately, less than half (15) mention supplemental screening. Of the 31 states with notification legislation, only 5 states  have enacted legislation mandating some form of insurance coverage for supplemental screening for women with dense breasts. In cases where “dense breasts” has been defined in the legislation, it is the BI-RADS density categories that have been cited. Therefore, to comply, visual BI-RADS or commercial software that provides density categories must be used i.e., Volpara, Quantra, Philips Spectral Density or iReveal. Providing accurate MBD assessments for communicating masking risk to lay women is becoming increasingly important as more and more states implement density notification laws and the use of objective methods have been shown to improve consistency across radiologist visual readings .Identifying women with dense breasts is paramount for providing them optimal screening outcomes. As it has been established that these women suffer from poor sensitivity on mammographic screening , they arCurrently in the US, even in states with density notification legislation in place, uptake of supplemental screening is fairly low. A previous study in our clinic found a 2% uptake of supplemental screening ultrasound for women notified of their dense breast tissue in an initial period after implementation of the law in our state (NY) . FurtherOne hindrance to more widespread use of supplemental screening is the large financial cost associated. For example, the 2017 reimbursement (based on Medicare average) for screening bilateral breast ultrasound is $156.98; which does not fully cover the cost a facility incurs to offer this service. Screening bilateral breast MRI reimbursement is approximately $518.68 (based on Medicare), similarly not covering the costs associated with a facility offering the service.The American College of Radiology (ACR) Appropriateness Criteria  warns thA review of the literature shows that supplemental screening does, in general, consistently detect additional breast cancers, most of which are invasive , though BRCA1 or BRCA2 mutation. The QALY saved varied by age, and was more favorable to those with a BRCA1 mutation. Interestingly, the study did find that cost-effectiveness increased when mammography sensitivity was lower, particularly in women with very dense tissue. According to the ACR Appropriateness Criteria, screening those at high risk with MRI is cost-effective, and this increases with increasing breast cancer risk. However, women with dense breast tissue are not considered in this.The cost-effectiveness of screening breast MRI is limited, and has largely been evaluated in high risk populations. A notable study  evaluateA link between MBD and breast cancer risk was first proposed in 1976 by the radiologist John Wolfe; however, several studies ,24,25,26It should be noted that different methods of MBD measurement bear different levels of association with breast cancer . SeveralIt is difficult to make conclusions about how mammography type (film versus FFDM) affects the association between density and breast cancer risk, and how this differs between measurement methods. Risk associations for many of the more recent methods have only been published for a single mammography type—either because the methods obligately require raw images, or simply due to lack of studies available. BI-RADS and Cumulus are some of the few methods that have more than one study for each mammography type. For these two methods, it is notable that film screen mammography appears to produce higher maximum risk associations than seen on FFDM . Both BIA number of studies have applied multiple MBD measurement methods on the same cohort of women, allowing for direct comparisons to be made. Some studies have concluded that visual assessment methods are most indicative of breast cancer risk. Researchers involved in the Predicting Risk of Cancer at Screening (PROCAS) study have found VAS to have a greater association with cancer risk, both for screen-detected as well as future cancers ,122. SimDespite being one of the strongest risk factors for breast cancer, MBD is not routinely used for breast cancer risk assessment. Incorporation of BI-RADS categories or an area-based continuous measure of MBD into current risk prediction models, such as the Gail and Tyrer-Cuzick models, have only showed minimal to modest improvements in terms of discriminatory ability ,146,147.Not only does dense tissue influence the risk of developing cancer, some studies have found increased density is related to poorer prognostic features, recurrence and survival, though results are variable. One study found a higher risk of subsequent breast cancer among patients with ductal carcinoma in situ (DCIS) with highly dense breasts , and higConversely, interval breast cancers in non-dense breasts were associated with lymph node involvement (OR 3.55), as well as estrogen receptor negative status (OR 4.05), human epidermal growth factor receptor 2 positive (OR 5.17), progesterone receptor negative (OR 2.63), triple negative (OR 5.33), grade 3 disease (OR 3.43), and tumor size >40 mm (OR 4.90) . In compBreast cancer specific survival, when taking mammographic density into consideration, was explored comparing interval cancers and screen-detected cancers . Utilizip = 0.0006). Percent density was associated with reduced risk of dying from the disease in those who received radiation, but with an elevated risk in those who did not . This work suggests additional value of assessing breast density, as it may aid in identifying women with a poorer prognosis and allow for recommendation of radiotherapy to improve outcomes. Similarly, review of data from the US BCSC did not find an association between high mammographic density and risk of death from breast cancer [Mammographic density was not found to be associated with breast cancer-specific survival  0.95) in a review of 607 breast cancer cases . Howevert cancer . An impoWhile density is not currently considered in determining breast cancer prognosis, the improvement in the accuracy and reliability of MBD assessment methods could see MBD incorporated into prognostic determinations in the future.MBD does not remain steady during a woman’s lifetime. Breasts undergo age-related involution which has an inverse association with density . MenopauWhen MBD assessments are made in normal clinical practice, the density scores of the prior exams are generally available. This could influence the final density score, as it is more likely that changes in density scores will only occur if significant changes are observed visually. Objective and automated methods  may be able to better show changes in breast density following interventions, and thus may be more appropriate for monitoring the efficacy of such interventions in reducing risk through breast density. Furthermore, depending on the method, small changes in density may go undetected. For instance, Cuzick et al. noted that a 10% change in density as measured by VAS was the smallest change that could be detected reproducibly . This isA recent study compared BI-RADS to an automated volumetric density measure in the Dutch breast screening program to determine which is more appropriate for temporal measurements . Five huCYP2D6) before it can take effect [CYP2D6 results in some women being poor tamoxifen metabolizers, and failing to attain clinical benefit due to a lack of active drug forms. Thus, a biomarker such as MBD reduction is valuable in order to identify women who are likely to benefit from treatment.Tamoxifen treatment reduces breast density; reportedly in 30–60% of breast cancer cases ,174. An e effect . The conMore recently, reductions in breast density with tamoxifen and aromatase inhibitors (AI) as a marker of treatment response was investigated in women with breast cancer, by comparing to a control group of untreated women without breast cancer; the first study of its kind to validate automated measures of breast density . DeclineChange in density has been discussed as a biomarker for assessing risk . Breast It should be noted that both tamoxifen and aromatase inhibitors act through the estrogenic pathway to inhibit cell proliferation . Thus, tA recent large-scale study evaluated population-attributable risk proportion for breast cancer associated with clinical breast cancer risk factors in premenopausal and postmenopausal women . Over 50MBD has come to be well-established as an important risk factor for breast cancer and an important consideration for breast cancer screening. Reliable assessment is also important for temporal assessment of breast density, in order to accurately characterize a woman’s breast cancer risk throughout her lifetime. Having clinically proven methods for breast density assessment are essential for providing women with optimal health care. The earlier qualitative measurement methods have limited consistency between readers and in relation to breast cancer risk. However, certain studies have demonstrated that the visual assessment of MBD may be detecting aspects of fibroglandular tissue that the computer-based methods do not. The development of automated computer-based density methods are advantageous in that they have been shown to provide consistent, reproducible and objective results, and can be implemented in large-scale clinical settings, such as breast screening programs. Moving towards a standardized assessment of MBD for clinical applications, while desirable, is a hugely complex feat. One must consider not only whether one method is better able to predict breast cancer risk or mammographic performance, but how consistent the method is across X-ray system vendors, modalities and over time, as well as how feasible the method is in terms of integration into health information technology (IT) systems and clinical practice. Although the MBD landscape has evolved rapidly since its inception in 1976, there is currently no consensus as to which methods are most appropriate for tailoring interventions to improve the early detection of breast cancer or reduce breast cancer risk. As demonstrated by the increasing interest in the development of MBD assessment methods, this is a highly active area of research. This research activity is expected to provide continuing improvement in MBD measurement, which will in turn translate to better risk assessment for women, high quality decision making when offering supplemental screening and improved monitoring of density over time.


The Ontario Breast Screening Program (OBSP) expanded in July 2011 to screen high‐risk women aged 30–69 with annual MRI and mammography. This study evaluated wait time (WT) indicators along the genetic assessment (GA) pathway for women referred to the High Risk OBSP.Information was collected for 27,170 women referred to the High Risk OBSP from July 2011 to June 2015 and followed for GA until June 2016. Median duration (days), interquartile range (IQR) were measured for each WT indicator by program year, age, prior breast cancer, and risk criteria.p < .0001). Among women having counseling and testing, WT from physician visit to counseling was shortest for mutation carriers . Median WT from testing to laboratory report issue was 41 days (IQR = 22–70) and 17 days to disclosure of test results (IQR = 7–33). Both WTs decreased with year and were shorter for mutation carriers .Among 24,811 women who completed GA, 16,367 (66.0%) had genetic counseling only, 8,444 (34.0%) had counseling and testing and 8,027 (32.4%) met the high risk criteria. Median WT from physician visit to first screen was longer for women having genetic counseling only compared to those having counseling and testing (244 vs. 197 days). Women having counseling only also experienced the longest WT from physician visit to genetic counseling , which increased by year from 71 to 100 days (After implementation of the High Risk OBSP, women received timely genetic counseling, in particular those having counseling and testing. Effective triage models for physicians could reduce WT to GA after physician referral. Although the estimated prevalence in the general population is low   in addition to mammography  is a province‐wide organized breast cancer screening program offering women aged 50–74 biennial mammograms. Based on recommendations from the Ontario Program in Evidence‐Based Care  predisposing to a markedly elevated breast cancer risk; untested first‐degree relatives of a gene mutation carrier; women with a family history consistent with hereditary breast cancer syndrome and estimated personal lifetime breast cancer risk ≥25%; and women who had radiation therapy to the chest (before age 30 and at least 8 years previously). Although the original Ontario guideline on breast MRI for high risk screening  Figures  or BOADI2.2The cohort was identified from women referred by their physician  to the High Risk OBSP between July 1, 2011 and June 30, 2015 and followed for genetic assessment (genetic counseling with or without testing) to determine eligibility until June 30, 2016. Women who were still in the process of genetic assessment at the time of data extraction, who declined services and for whom results were unknown were excluded.2.3Requisition for High Risk Screening Form, completed by the referring physician, includes data on date of physician visit, method of referral into the program (direct entry or genetic assessment required), high risk criteria, suggestive history of hereditary breast cancer, and medical history. For women referred for genetic assessment, the Breast Cancer Genetic Assessment Results Form, completed by a genetic counselor, collects data on high risk criteria, whether women declined genetic testing, date of genetic counseling and/or testing, date the laboratory report was issued, date the woman was informed of her genetic test results and eligibility for screening. Research ethics approval was not required for this study, because it fell into the category of quality assurance as specified by the University of Toronto Research Ethics Office.The data used for this study are routine information collected for all women screened within the High Risk OBSP from CCO's Integrated Client Management System database. The 2.4To evaluate the physician referral criteria we determined the proportion of women who met one of the four high risk eligibility criteria among women who completed genetic assessment and had a known final outcome. Wait time indicators were developed by the OBSP Expert Panel to ensure timeliness of genetic assessment within an organized setting. Dates of procedures are collected at specific points throughout phases of the program pathway. Wait time indicators examined include: days from initial physician visit to genetic counseling; days from genetic counseling to genetic testing; days from genetic testing to laboratory report issued; days from laboratory report issued to date the woman was informed of her genetic test result; and days from high risk confirmation to first high risk screen (MRI or ultrasound if MRI contraindicated) date.2.5Women having genetic assessment were excluded from this analysis if their genetic counseling date was prior to their physician visit date; their laboratory report result was entered prior to their genetic test date; date they were informed of their genetic test result was entered prior to the laboratory report issued date; or if the wait time exceeded 365 days. Median duration (in days), 90th percentile and interquartile range (IQR) were measured for each wait time indicator. Durations were stratified by program year (2011–2015), age group (30–49 or 50–69 years), prior breast cancer (yes or no) and risk criteria . Nonparametric Wilcoxon rank‐sum tests Haynes,  were per3Of the 29,602 women aged 30–69 years referred by their physician to the High Risk OBSP, 27,170 (91.8%) underwent genetic assessment to determine their eligibility   (Table p = .13), but significantly shorter among women with a prior breast cancer compared to those without . Among risk criteria after genetic counseling, women with a family history and ≥25% lifetime risk waited longer to see a genetic counselor compared to women who were untested first‐degree relative(s) of a mutation carrier .The majority of women (64%) who had genetic counseling only were 30–49 years of age and few (3%) had a prior breast cancer Table . Among tp = .002 and p = .0009, respectively). It was also shorter for women without a prior breast cancer compared to those with a prior history . Median wait times did not differ between women aged 30–49 and 50–69 years . Among risk criteria, the longest wait time to see a counselor was observed for women with a family history and ≥25% lifetime risk compared to gene mutation carriers ; wait times were similar between women who were untested first‐degree relatives and mutation carriers (p = .11).Women who had both genetic counseling and testing, were more likely to be 50–69 years of age (55%) and 19% had a prior breast cancer Table . Among tp < .0001 and p = .0008, respectively) (Table p < .0001), those with a prior breast cancer compared to those without , and those with a family history and ≥25% lifetime risk  compared to mutation carriers .Median wait time from genetic testing to laboratory report issued date decreased in the third  and fourth program years  compared to the first year  (Table p < .0001) and for women with a prior breast cancer  compared to those without . Women with a family history and ≥25% lifetime risk had similar wait times to known carriers .There was a significant decrease in median wait time from laboratory report issued date to when women were informed of their result in program years 2013–14  and 2014–15  compared to the first year  compared to those who had counseling and testing (197 days). The wait time from initial physician visit to genetic counseling was also longer for women referred for counseling only, and this wait time increased with program year. Conversely, wait times from genetic testing to laboratory reporting and disclosure of test results decreased over time. Among high risk criteria, women with a family history and ≥25% lifetime risk who had counseling only experienced the longest wait to see a genetic counselor. Among women having counseling and testing, mutation carriers experienced the shortest wait times along each phase of the genetic assessment pathway.In the High Risk OBSP 32.4% of women who completed genetic assessment met the high risk criteria. Another study conducted in the United Kingdom (UK) among 22 Regional Genetics Centres assessing familial cancer risk, also found that a low proportion (25%) of referred cases were in the highest risk category  would be predicted to be at greatest risk. Developing effective triage models that referring physicians could use to quickly identify patients who are ineligible for the program may help to reduce this wait time. Conversely, decreases in wait times by year from genetic testing to laboratory reporting and to subsequent disclosure of test results, suggests that the current number of laboratories is sufficient to manage the increased volume of women referred each year.While the wait time to see a genetic counselor after initial physician referral was lengthy in the High Risk OBSP, particularly among women who had counseling only, it is shorter than that reported by others. An earlier study conducted in the UK found that the median wait time from physician referral to counseling among genetic centers assessing familial cancer risk was 19 weeks, ranging from 4–53 weeks across centers due to variation in resources and access inequity  about genetic and other risk factors may also influence the initial referral process.BRCA1/2 mutation testing exist (Del Turco et al., Although standards for genetic assessment and The authors declare that they have no conflicts of interest.


Johns et al. have investigated the relationship between exposure to light at night (LAN) and breast cancer risk. Using questionnaires, these authors have collected data on the bedroom light levels and sleeping patterns of 105 866 participants who had no prior history of breast cancer. Their follow-up showed 1775 cases of breast cancer. In this prospective cohort analysis, Johns et al. concluded that there was no evidence of an association between LAN exposure and increased risk of breast cancer in their large UK-based cohort study. Despite its strengths, the paper authored by Johns et al. has at least two major shortcomings. Over the past decade, my colleagues and I have studied the adverse health effects of exposure to radiofrequency electromagnetic fields (RF-EMFs). Moreover, we have studied the biological effects of exposure to blue light emitted from digital screens3. The first shortcoming of the paper authored by Johns et al. concerns the authors ignoring the key factor of melatonin suppression, caused by exposure to artificial short-wavelength blue light emitted from the very widely used digital screens 4. It is worth noting that the study performed by the Pew research centre shows that about 95% of Americans own a cellphone5. It has recently been shown that blue light emitted from smartphones’ screens can be linked to decreased melatonin secretion (the mechanism behind the negative impact of smartphone use at night on sleep)6. We have previously shown that in people who use their smartphones at night, not only the RF-EMFs generated by smartphones but also the blue light emitted from the screens of these wireless devices can be associated with disrupted circadian rhythm3. Moreover, a recent study showed that the viewing distance of smartphones was negatively associated with subjective sleep status6. Therefore, it has been hypothesised that if women with hereditary breast cancer predispositions, such as women who carry mutated BRCA1 or BRCA2 or women with a family history of breast cancer, use their smartphones, tablets, and laptops at night, the disrupted circadian rhythms can amplify the risk of breast cancer7.This comment is regarding the article by Johns et al. entitled “Domestic light at night and breast cancer risk: a prospective analysis of 105 000 UK women in the Generations Study” published in the British Journal of Cancerto report their level of exposure to LAN over the year prior to recruitment and at age 20 years, in the room in which they slept, in the categories; ‘light enough to read’; ‘light enough to see across the room, but not read’; ‘light enough to see your hand in front of you, but not to see across the room’; and ‘too dark to see your hand, or you wear a mask’”. This study design shows that the authors have only focused on the intensity of light, while substantial data indicate that the spectral characteristics of light (wavelength) also significantly affect the melatonin level, sleep pattern, and circadian rhythms13. In summary, ignoring some key factors in the study conducted by Johns et al. has possibly affected the validity of their findings.Another shortcoming of this study comes from its poor design. The authors asked women “


P<0.05). Due to the easy availability of data on non-cancer patients referred to the cancer registry center, researchers may be encouraged to use them as a control group, but we must bear in mind that, this Group may be different in terms of some variables, and this difference leads to bias in the estimation of considered exposure effects.The aim of this study is evaluation of breast cancer risk factors distribution in two groups of healthy people referral to cancer registry and Shahid Mottahari center in Iran. This study is cross-sectional study which is part of the study to estimate Gene-Environment Interaction in women with breast cancer with case-control studies in Shiraz. In this study, two control groups have been used. The sample size of 300 was specified for each group. Selection sources of groups include Cancer Registry Center and referred people to surgical and internal ward of Shahid Mottahari Clinic. Information collect tools have included Form No. 1 in Cancer Registry Center which includes information of age, use of oral contraceptives history, breastfeeding history, number of live births, age at menarche, age at first childbirth, etc. Considering the results obtained, it was showed that the highest frequency (144) in the group of Cancer Registry Center belongs to high school education, but the highest frequency of Shahid Mottahari Clinic is related to primary education (176).There is statistically significant difference between the two groups in terms of education, history of breast cancer in first-degree relatives and age at first birth, ( Specifications TableValue of the data•Breast cancer is one of the most commonly diagnosed cancer and a leading cause of cancer death in women in the world •In some parts of Iran, the incidence of breast cancer is higher than in other places •In this study, two control groups have been used. Therefore, it can be said that the data obtained from this study is valuable.•The data of this study show that there is statistically significant difference between the two groups (case and control) in terms of education, history of breast cancer in first-degree relatives and age at first birth.1P=0.001). But in terms of history of live births and breastfeeding, there is no significant statistical difference between the two groups. But in terms of family history of breast cancer in first-degree relatives they had a significant difference that, the highest frequency of this variable (49) was in the group of breast registry center s and 17 cases were in the control group of Shahid Mottahari clinics. There was a statistically significant difference (p=0.001) between the two groups in terms of age at first birth that, the highest frequency (256) was associated with Shahid Mottahari clinic group with age at first birth 25–34 years. No significant difference was observed in terms of duration of contraceptive pills (ocp). And the statistical test can not be performed with the variable age at first menstrual, because the changes within both groups is constant. The above results are shown in Considering the results obtained, it was showed that the highest frequency (144) in the group of Cancer Registry Center belongs to high school education, and the lowest frequency associated with illiterate group. But the highest frequency of Shahid Mottahari Clinic is related to primary education (176) and the lowest one is related to cases with academic education 2α=0.05 and power of 80% and calculated sample size of 293. In this study, 300 controls of surgical and internal wards of ShahidMottahari clinic and 300 controls from the cancer registry were used. Sampling was such that 300 cases were selected from the list of breast cancer patients in the cancer registry with a simple random sampling and their ages were specified. And among patients referred to the center that their breast cancer has not been confirmed, 300 subjects were selected by sampling with the age ±3 years for each case as an age-matched control. In addition, 300 persons of internal and surgical wards of ShahidMottahari clinic were selected with available (easy) sampling method by interview after the consent to participate in the study as a second control group matched for age ± 3 years.The research is part of the study to estimate Gene-Environment Interaction in women with breast cancer with case-control studies, and the only one in Shiraz. In this study, two control groups were used: 1. Women without breast cancer selected among women referred to Cancer Registry Center for reasons other than breast cancer (such as obtaining the necessary training in the field of prevention). Mammography diagnostic test had been done to these people. The center׳s clients include families of patients, people referred from private clinics or health centers in which educational and screening services are provided to referring patients. Most of these people have been settled in Shiraz and questionnaire was completed for them. In this study, available information were used as a control group for patients with breast cancer that is readily available. 2. Women referred to medical and surgical wards of Shahid Mottahari clinic were interviewed after consent to participate in the study. The questionnaire was completed for this group, like the first group, the control group of Cancer Registry Center was selected among cases referred to the Cancer Registry Center (Breast Clinic). Measured independent variables include the use of oral contraceptives, breastfeeding history, number of pregnancies, age at menarche, age at first childbirth.Sample size is determined using Quanto1.2 application (January 2007) Samples included people living in Shiraz city more than five years.Information collection tool included Form No. 1 in Cancer Registry Center which includes information of age, use of oral contraceptives history, breastfeeding history, number of live births, age at menarche, age at first childbirth, etc. Statistical analysis has been performed using STATA 8.0 statistical software.


The aim of this study was to evaluate the effects of an educational intervention on breast self-examination, cancer prevention-related knowledge, practices, and behavior change in scholars from a low-income area in Bogota, Colombia. Uncontrolled trial was conducted in 155 scholars. Two educational sessions, 90 min each, were carried out in March 2015 according to the Colombian guidelines for educational communication in the framework of cancer control. All participants completed a self-reported questionnaire at pre- and post-intervention, as well as 1, 3, and 6 months after the intervention. Breast self-examination was practiced by 78.1% of the scholars, and the overall knowledge of breast cancer risk factors was poor. The educational intervention resulted in significant improvements on breast self-examination practice, the knowledge of the technique, and the knowledge of the main risk factors for breast cancer as well as the practice of physical activity and vegetable intake at 6 months follow-up. An educational intervention according to the Colombian guidelines for educational communication in the framework of cancer control improved the practice of breast self-examination, cancer prevention-related knowledge, as well as the practice of physical activity and vegetable consumption in scholars from a low-income area in Bogota, Colombia. Further randomized controlled studies are warranted. Breast cancer is a serious public health problem, which has been recognized as the most common cancer in women worldwide . In ColoThere is strong evidence that healthy lifestyles prevent breast cancer, as well as other type of cancers . PhysicaIn light of this, educational interventions have been recommended as effective public actions in the integral control of breast cancer, especially among youth . There iIn the Colombian context, there are scarce evidences about educational interventions for breast cancer prevention, whereas the benefits of the national guidelines for educational communication in the framework of cancer control reaming is unknown . The curThe study design was uncontrolled trial with repeated measurements at 1, 3, and 6 months post-intervention.We selected a convenience sample of 155 female adolescents (10–20 years old), students of a public school in a low-income area in Bogota, Colombia. The purpose of study, interventions, and dates were explained in the classroom to the eligible students. Those who referred pregnancy, breastfeeding, or previous participation in a similar educational intervention were excluded.Ethical approval to conduct this study was obtained from the ethics committee of the Our Lady of the Rosary University (Reference N. 306), after approval of the research protocol. Written informed consent was taken for each participant. Parents provided signed consent for each minor.We used the breast section of the Cancer Awareness Measure (CAM) , 25, whiBSE practice and knowledge of the technique were measured using a validated questionnaire provided by the German multicentre DACH in the University of Düsseldorf, Germany . For BSEWe adapted the Spanish version of the Behavioral Risk Factor Surveillance System published by the Centers for Disease Control and Prevention (CDC) . The folAll modules were translated into Spanish by one researcher, and back translation was conducted and checked by one independent bilingual translator to ensure equivalence. The final version of the questionnaire was then piloted in a subgroup of 50 scholars who completed the tool and provided feedback regarding feasibility, clarity, and understanding. No lingual difficulties were identified.The questionnaire was completed by all participants under supervision of the sports teacher, as suggested by the Cancer Research UK . CronbacThe educational intervention was developed in accordance with the national guidelines for educational communication in the framework of cancer control in Colombia , incorpop < 0.05 were considered as significant. The data were analyzed using the Stata version 22.0.The outcome of interest was the BSE practice, knowledge of breast cancer risk factors, and healthy lifestyles. The socio-demographic characteristics of scholars were described by using frequency, percentage, mean, and standard deviation. A multilevel regression model was used to estimate the change coefficients in the different scores with respect to pre-intervention measurements; each measurement was then assumed as a hierarchical source of variability. Alpha levels of p < 0.05) over a 7-day interval.Cronbach’s alpha provided scores over 0.7 for all items in the questionnaire, which suggested a strong level of internal consistency. Similarly, Pearson’s correlation test showed strong test-retest reliability (over 0.72) for all items  (range 10–20). All scholars are residents in a low-income area in south Bogota, Colombia. Only half of the participants live with both parents, and less than half of the parents have completed academic studies (Table p < 0.0001). Eighty percent of the scholars had never examined their breasts, and this rate showed a significant decrease of 67.8% (from 80.7 to 12.9%) at 6 months (p < 0.0001). Similar increases were also found for the frequency of BSE in all the categories evaluated. See Table Baseline scores showed poor levels for these outcomes. Knowledge of the BSE technique showed a significant exponential increase across all measurements . See Table The educational intervention decreased weekly alcohol consumption at 6 months after the intervention (11% decrease). Significant improvements were observed on the practice of physical activity and vegetable consumption p < 0.0. See TabOur findings demonstrated an educational intervention improve the knowledge of BSE, its practice, the knowledge of the main risk factors for breast cancer, and healthy lifestyles in a group of female scholars up to 6 months follow-up.We observed large improvements on BSE knowledge, practice, and frequency at 6 months follow-up. These findings are in line with those of recent studies carried out in Malaysia , Turkey The knowledge of the Colombian female scholars was poor for most of the breast cancer risk factors and showed significant improvements after the educational intervention, which is similar to those reported in females from Malaysia , Iran 3, Egypt , and IndIn spite of a lack of statistical significance on some domains, we can state that this educational intervention improved healthy lifestyles in the scholars.Alcohol consumption exhibited a small reduction at 6 months follow-up. Similar promising findings have been reported by the Project Toward No Drug Abuse  and the Scholars referred an unexpected small increase (1%) in smoking at 6 months after the intervention. The Cochrane Tobacco Addiction Group has discussed similar results from 49 randomized controlled trials  and concluded that prevention studies did not provide overall effect at 1 year or less, and multimodal interventions and those with an information-only approach were similarly ineffective . HoweverWe found exponential significant improvements in the practice of physical activity (>150 min/week) in the scholars. Similar findings have been communicated in a Cochrane review  which concluded that educational interventions combining printed educational materials and changes to the school curriculum that promote physical activity during school hours can lead to positive effects in increasing duration of physical activity from 5 to 45 min more per day and other outcomes such as the time spent watching television from 5 to 60 min less per day, and physical fitness . ConsideOur improvements in fruit and vegetable intake are similar to those published by Evans and colleagues  in 2012 This study is the first evidence in evaluating the Colombian guidelines for educational communication in the framework of cancer control. It is important to highlight the relevance of involving low-income groups in educational interventions since these individuals have limited access to most of the massive educational campaigns that take place in the country . HoweverFurther well-conducted randomized controlled trials can provide more rigorous evidence about the effects of educational interventions in improving female potential for breast cancer early detection and its prevention through healthy lifestyles. Further RCTs must incorporate strong sample sizes and adequate methods for allocation concealment, sequences generation, and outcome measurement. The use of objective measurements for lifestyle-related outcomes is also warranted.The results from this study are articulated with the priorities of the cancer risk control and prevention strategies of the Colombian Ministry of Health  and thosAn educational intervention based on the Colombian guidelines for educational communication in the framework of cancer control improves BSE practice, breast cancer prevention-related knowledge, as well as the practice of physical activity and vegetable consumption in scholars from a low-income area in Bogota, Colombia. Further randomized controlled studies are warranted.


ER) and progesterone receptor (PR) status or included racial/ethnic minority populations who vary in their fiber intake. We analyzed food frequency data from a population‐based case–control study, including 2135 breast cancer cases ) and 2571 controls . Odds ratios (OR) and 95% confidence intervals (CI) for breast cancer associated with fiber intake were calculated using unconditional logistic regression. Breast cancer risk associated with high intake (high vs. low quartile) of bean fiber (p‐trend = 0.01), total beans (p‐trend = 0.03), or total grains (p‐trend = 0.05) was reduced by 20%. Inverse associations were strongest for ER‐PR‐ breast cancer, with risk reductions associated with high intake ranging from 28 to 36%. For bean fiber, risk was reduced among foreign‐born Hispanics only, who had the highest fiber intake, whereas for grain intake, inverse associations were found among NHWs only. There was no evidence of association with fiber intake from vegetables and fruits or total intake of vegetables and fruits. A high dietary intake of bean fiber and fiber‐rich foods such as beans and grains may lower the risk of ER‐PR‐ breast cancer, an aggressive breast cancer subtype for which few risk factors have been identified.High dietary fiber intake has been associated with reduced breast cancer risk, but few studies considered tumor subtypes defined by estrogen receptor ( The role of dietary fiber in breast cancer etiology remains uncertain To date, most studies on fiber intake and breast cancer risk have been conducted in non‐Hispanic White (NHW) women. Data on Hispanic and African American women are sparse, although fiber intake and fiber sources have been shown to vary substantially across racial/ethnic populations in the United States (U.S.) We examined the relation between intake of fiber and fiber‐rich foods and breast cancer risk in a population‐based case–control study conducted in a multiethnic population with a wide range of dietary fiber intake from diverse sources.n = 2571). Of those selected, 2258 (88%) completed an in‐person interview, including 1119 (89%) Hispanic, 543 (87%) African American, and 596 (86%) NHW cases.Women included in this study were participants in the San Francisco Bay Area Breast Cancer Study, a population‐based case–control study conducted from 1995 to 2004 Controls were identified through random‐digit dialing The study was approved by the Institutional Review Board of the Cancer Prevention Institute of California .fruits , vegetables , beans , and grains . The same FFQ was administered to women of all races/ethnicities. Daily intake of specific nutrients was estimated using the DIETSYS software that linked the FFQ data to a nutrient database, which was adapted from nutrient databases developed for the Block 1995 FFQ, and the FFQ used for the Study of Women's Health Across the Nation A structured questionnaire in English or Spanish was administered by trained bilingual and bicultural interviewers at the participants’ home, collecting information on demographic background, lifestyle factors, menstrual and reproductive history, hormone use, and medical history up to the reference year . Measurements of weight and height were taken during the interview. Usual dietary intake (frequency of consumption and portion size) in the reference year was assessed using a food frequency questionnaire (FFQ) adapted from the 1995 106‐item Block Health History and Habits Questionnaire, with the addition of food items commonly consumed by Hispanic and African‐American women in California, including a variety of beans 2) was calculated as self‐reported weight (kg) in the reference year divided by measured squared height (m). For the small number of participants who did not report their weight in the reference year (1% of cases and 2% of controls), we used measured weight, and for those who declined the height measurement (7% of cases and 7% of controls), we used self‐reported height for the BMI calculation. We used self‐reported instead of measured weight because of concern about treatment‐related and disease‐related weight gain after diagnosis. Average lifetime physical activity (hours/week) between menarche and the reference year was estimated from self‐reported histories of exercise, walking and bicycling, strenuous indoor and outdoor chores, and occupational activity We examined intake (g/day) of total fiber; fiber from specific foods ; and fiber‐rich foods . Body mass index  and 54 cases and 72 controls with missing covariate data, leaving 2135 cases and 2571 controls for the analysis. Using multivariable unconditional logistic regression, we estimated odds ratios (OR) and 95% confidence intervals (CI) for breast cancer risk associated with intake of total fiber, intake of fiber from specific foods , and intake of fiber‐rich foods . Models were adjusted for total energy intake using the residual method (with logarithm transformation of nutrients and energy intake) 2), daily alcohol consumption , daily energy intake (continuous), and daily fat intake . We stratified the analyses by race/ethnicity and birthplace and by hormone receptor status. Polytomous logistic regression was used to estimate the associations between the dietary variables and risk of hormone receptor‐positive (ER+ and/or PR+) and ER‐PR‐ breast cancer. Analyses for ER+ and/or PR+ breast cancer were adjusted for the same variables as for overall breast cancer. Analyses for ER‐PR‐ breast cancer were adjusted for age, race/ethnicity and birthplace, age at menarche, menopausal status and HT use, breastfeeding, physical activity, and energy and fat intake. All tests of significance were two‐sided with P < 0.05 as the significant cutoff point. Analyses were performed using SAS Version 9.4 .The multivariable models were adjusted for age (continuous), race/ethnicity and birthplace , and variables associated with breast cancer risk Table , includiCompared with controls, cases had higher education, earlier menarche, older age at first full‐term pregnancy, shorter duration of breastfeeding, lower physical activity, lower BMI, higher alcohol consumption, and higher caloric and fat intake; higher proportions of cases than controls had a family history of breast cancer or a personal history of benign breast disease and were nulliparous or current HT users Table .Control women had a higher fiber intake and consumed a higher percentage of fiber from beans than cases Table . ForeignAssociations between breast cancer risk and intake of fiber, different sources of fiber, and fiber‐rich foods are shown in Table For hormone receptor‐positive breast cancer Table , there wIn this population‐based case–control study, fiber intake was most strongly associated with risk of ER‐PR‐ breast cancer. Inverse trends were associated with intake of bean fiber (p‐trend = 0.02), total beans (p‐trend = 0.04), and total grains (p‐trend = 0.01), with risk reductions associated with high intake ranging from 28 to 36%. For hormone receptor‐positive breast cancer, inverse trends for total fiber and bean fiber were of borderline significance.We found a 25% reduction in breast cancer risk associated with high versus low total fiber intake and no association with fiber from vegetables and fruits combined or total intake of vegetables and/or fruits. A recent meta‐analysis of 16 prospective studies reported that high intake of total fiber In our study, the strongest inverse associations were found for bean fiber and total bean intake, but limited to ER‐PR‐ breast cancer and foreign‐born Hispanic women. Few studies have assessed the relation between breast cancer and intake of bean fiber or total beans, possibly due to its minor role as a source of fiber in most NHW populations. Of the four studies that reported on the association with fiber from beans or legumes, only the Nurses’ Health Study II found an association, albeit marginally significant, with breast cancer risk overall P = 0.08) for total fiber intake in premenopausal women Data on fiber intake and breast cancer risk in Hispanic populations are very limited. A small study from Mexico  reported a marginal inverse trend  Phytoestrogens are unlikely to account for the associations observed for bean fiber, as the types of beans commonly consumed by our study participants  are generally not rich sources of lignans or isoflavones Some limitations need to be considered when interpreting our results. The FFQ was not validated in different racial/ethnic groups. Therefore, it is not known whether there are differences in validity between racial/ethnic groups and whether this explains why we observed different associations by race/ethnicity. The dietary assessment was based on self‐report, and inaccurate recall of past dietary intake might have introduced some exposure misclassification. Although we cannot rule out the possibility of differential recall of dietary intake by case–control status, it is unlikely that such recall bias would differ by ER/PR status among cases. The FFQ did not consider fiber intake from supplements. Fiber supplements, however, contribute little to total fiber intake This study has several strengths, including the large sample size and racially/ethnically diverse population. The large number of Hispanic participants allowed us to assess a wider range of fiber intake than if the study had included NHW women only. The FFQ assessed both frequency of consumption and usual portion size to estimate usual intake. To facilitate recall of portion size, food models and utensils were used. We were able to adjust the analyses for many known risk factors for breast cancer, which was found to be important as the inverse associations were somewhat attenuated after multivariate adjustment. Lastly, information on ER and PR status was available for most cases (90%). Prior studies that did not consider tumor hormone receptor status may have failed to detect inverse associations with intake of fiber or fiber‐rich foods.The finding of inverse associations of ER‐PR‐ breast cancer with intake of bean fiber, beans, and grains, if confirmed, has important public health implications. Few risk factors have been identified for ER‐PR‐ breast cancer which is more common in African American and Hispanic women and has worse prognosis. The identification of modifiable lifestyle factors is therefore particularly important for the prevention of this aggressive breast cancer subtype. The role of diet, including fiber, in the etiology of specific breast cancer subtypes, warrants further investigation.There is increasing evidence that higher levels of acculturation into mainstream American culture by Hispanic women are often accompanied by health behaviors that may increase their risk of cancer, including the adoption of U.S. diets higher in fat and lower in fruits and vegetables Given that for a large proportion of women in our study, daily total fiber intakes fell short of daily recommended values, educational programs aimed at increasing intake of fiber or fiber‐rich foods such as beans and grains may be effective in reducing the risk of not only ER‐PR‐ breast cancer, but also other cancers, such as colon, rectal, and esophageal cancer The authors declare that they have no conflict of interest.


ATM, H2AFX and MRE11 genes in determining breast cancer (BC) susceptibility.DNA damage repair is a complex process, which can trigger the development of cancer if disturbed. In this study, we hypothesize a role of variants in the ATM gene  and single nucleotide polymorphisms (SNPs) in H2AFX  and MRE11 (rs1061956 and rs2155209) among 315 breast cancer patients and 515 controls. The analysis was performed using high-resolution melting for new variants and the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method for recurrent ATM mutations. H2AFX and MRE11 polymorphisms were analyzed using TaqMan assays. The cumulative genetic risk scores (CGRS) were calculated using unweighted and weighted approaches.We examined the whole sequence of the ATM kinase domain and estimated the frequency of founder mutations in the ATM gene in three BC cases and two control subjects. We observed a statistically significant association of H2AFX variants with BC. Risk alleles (the G of rs7759 and the T of rs8551 and rs2509049) were observed more frequently in BC cases compared to the control group, with P values, odds ratios (OR) and 95% confidence intervals (CIs) of 0.0018, 1.47 (1.19 to 1.82); 0.018, 1.33 (1.09 to 1.64); and 0.024, 1.3 (1.06 to 1.59), respectively. Haplotype-based tests identified a significant association of the H2AFX CACT haplotype with BC . The risk of BC increased with the growing number of risk alleles. The OR (95% CI) for carriers of ≥ four risk alleles was 1.71 (1.11 to 2.62) for the CGRS.We identified four mutations  in the H2AFX variants are associated with an increased risk of BC. The above-reported sequence variants of MRE11 genes may not constitute a risk factor of breast cancer in the Polish population. The contribution of mutations detected in the ATM gene to the development of breast cancer needs further detailed study.This study confirms that  Cell-cycle checkpoints and DNA damage repair prevent genetic instability and mutagenesis. In response to DNA double-strand breaks, a signaling cascade is initiated: first, the M/R/N complex, consisting of three proteins, MRE11, RAD50 and NBN, acts as a sensor for DNA damage. M/R/N proteins recruit the key signal transducer of DNA damage response: ataxia-telangiectasia mutated (ATM) kinase ) of the cumulative risk scores among the two groups studied were similar (for BC 2.37 ± 2.06 and for the control group 2.01 ± 1.88), although mode values were different for the BC and control groups, at 3 and 0 respectively. Individuals were stratified into three groups according to the number of risk alleles: carrying ≤ two (reference group), three, and ≥ four alleles. The risk of BC increased with the number of alleles and was statistically significant for three alleles (P = 0.019) and ≥ four alleles (P = 0.014) compared to ≤ two risk alleles. ORs (95% CI) for carriers of three and ≥ four risk alleles were 1.46 (1.06 to 2.01) and 1.71 (1.11 to 2.62), respectively  between BC patients and controls ranged between 71 and 94%. This means that the study had enough power to detect an association of the H2AFX gene in BC group, in the case-control analysis.The post-hoc analysis revealed that the statistical power of our study for analyses of the differences in distribution of alleles at loci rs7759, rs8551 and rs2509049  [NBN c.657del5 mutation have an increased risk of malignant tumor development, especially of breast, prostate, colon and rectal cancers [RAD50 gene mutations are not a risk factor of familial and sporadic breast cancer in the Polish population [Our previous studies focused on the hypothesis that M/R/N gene polymorphisms are associated with the risk of different cancers. We showed that the germline p.Ile171Val mutation in ia (ALL) –17. Hete cancers . We alsopulation .ATM, H2AFX and MRE11 genes and risk of breast cancer.In this case-control study, we investigated the relationships between other variants in ATM mutations cause increased risk of malignancy. Female relatives of ataxia-telangiectasia cases have increased risk of breast cancer [ATM variants to breast cancer [ATM gene have been detected in Polish ataxia-telangiectasia patients. Three of the mutations, c.6095G > A, c.7630-2A > C and c.5932G > T, were the most frequent [ATM gene in a series of women with breast cancer.It has been shown that heterozygous t cancer , 21. Mort cancer –26. A fefrequent , 28. A mATM gene mutation in the Polish population. Bogdanova et al. showed that the c.5932G > T mutation is a predisposing breast cancer susceptibility variant in populations in Belarus, Russia, Ukraine and Poland [ATM gene were found in two Polish probands with breast cancer without founder mutations in BRCA1, CHEK2 or NBS1. In that study, both patients with ATM mutations also had another truncating mutation, in the PALB2 and XRCC2 genes, respectively [There are a few studies regarding associations between breast cancer development and the d Poland . In anotectively .ATM kinase domain in our study, we detected five mutations in the 830 samples in both the BC and control groups. One of the mutations, which presented in two BC patients, is the founder mutation (c.6095G > A) observed in Polish ataxia-telangiectasia patients. The rest of the detected variants were single nucleotide changes: c.6067G > A, p.Gly2023Arg; c.8314G > A, p.Gly2772Arg; c.8187A > T, p.Gln2729His; c.8787-55C > T and c.6083A > G; Q2028R. Using SIFT and PolyPhen and Mutation taster Phylop algorithms to predict the possible impact of the amino acid changes on ATM function, we confirmed that three of the missense variants  were classified as probably being damaging mutations/ disease causing. All these algorithms estimate a functional effect of SNPs in different ways. Accordingly, the pathogenic effects of ATM gene variants were confirmed if more than two analyses indicated demanding consequences.In the coding sequence of the NBN p.Ile171Val mutation. It is difficult to conclude which changes are pathogenic because the p.Ile171Val variant has been connected with ALL, breast, larynx and colorectal cancer, and multiple primary tumors of the head and neck [However, one functional study indicated that c.8314G > A, p.Gly2772Arg is only a missense variant, which does not interfere with ATM kinase activity and radiosensitivity . In our and neck –37. On tand neck .ATM variants also had other changes in different genes involved in DNA damage repair [In the above-mentioned results and in data previously presented by Cybulski et al., it was observed that some of the BC patients with detected e repair . This evIn addition, we found two polymorphic variants: c.6083A > G, Gln2028Arg and the intronic variant, c.8787-55C > T, which was found in a homozygous state. These two variants do not play a role in the development of breast cancer.H2AFX and MRE11, connected with the DNA damage response signaling cascade. We selected SNPs in H2AFX and MRE11 genes based on observations from previous reports [H2AFX gene -1654C > T, -1420C > T, −1187A > G, and -417C > T, respectively. Two of SNPs, rs8551 and rs7759, are also located in the 3′UTR of other gene, DPAGT1. While, the rs643788 causes an amino acid change in DPAGT1 protein. This substitution converts isoleucine into valine (I393V). The I393V variant was predicted as tolerated by SIFT and benign by PolyPhen2. DPAGT1 gene encodes an enzyme that catalyzes the first step in the dolichol-linked oligosaccharide pathway for glycoprotein biosynthesis. However, we did not find any evidences that I393V variant has pathogenic effect on DPAGT1 protein or is associated with an increased risk of cancer.In the second part of our case-control study, six potentially functional SNPs were genotyped in two other genes,  reports –42. FourMRE11 variants, rs1061956 (*442A > G) and rs2155209 (*2501A > G), are located in non-coding DNA sequences: the three prime untranslated region (3’UTR) of the gene. A functional study of polymorphisms in the H2AFX distal promoter showed a possible regulatory impact of two SNPs. Studies, based on gel shift assays, revealed that the rs643788 C allele disrupts a consensus sequence for a Yin Yang 1 transcription factor binding site. Moreover, the probe with rs2509049 C allele binds more strongly to an undefined protein complex than the rs2509049 T allele. On the other hand, it has been shown no differential binding by gel shift assay for rs8551 and rs7759 probes. It is not excluded that these SNPs may have an impact on binding only under specific conditions [H2AFX are associated with cancer risk. Lu et al. found significant associations between minor variant genotypes of four SNPs  and haplotypes with minor alleles in the promoter region of H2AFX and risk of breast cancer. Age at onset of breast cancer significantly decreased as the number of variant alleles in the H2AFX promoter region increased [The 1061956 *2A > G anncreased .H2AFX SNPs: rs8551 and rs7759. Likewise, comparing the allele frequency of rs7759, rs8551 and rs2509049 SNPs, we observed a statistically significant higher prevalence of the minor alleles in BC cases in comparison with the control group. However, the haplotype analysis of all the H2AFX polymorphisms studied showed no association of haplotypes with minor/major alleles with increased risk of breast cancer. We only observed significant differences in the distributions of haplotype consisting of CACT alleles between the BC cases and controls.Our findings suggest that there is a potential link between an increased risk of breast cancer and two H2AFX promoter locus. The risk of breast cancer escalated with an increased number of risk alleles. The comparison of clinical data between two groups, BC patients with high cumulative genetic risk score  and BC patients with < 4 risk alleles, showed that high CGRS is not correlated with age of diagnosis (53 vs 54 yrs.), T stage and histological subtype of breast cancer. We observed differences in tumor grade among two groups. In patients with high cumulative genetic risk score, grades of tumor were shifted towards moderate and poor differentiation . We found increased numbers of patients with high cumulative genetic risk score with negative ER status (59.2% vs 24.6%) and PgR status (54.9% vs 25.4%), in comparison to all BC cases.We also identified a cumulative effect of three SNPs in the MRE11 gene, were investigated. Choudhury et al. demonstrated the MRE11 3’UTR SNP to be associated with bladder cancer risk. However, the authors noticed a marginal increase in risk of bladder cancer for rs2155209  in individuals homozygous for the C allele compared to those carrying the common TT or TC genotype [MRE11 was significantly associated with worse cancer-specific survival among patients with muscle-invasive bladder cancer [MRE11 polymorphisms with breast cancer patients from Poland. Neither the rs2155209 nor the rs1061956 SNP showed statistically significant differences in the frequencies of genotypes.In this paper, two other SNPs from a subsequent gene involved in the DNA repair process, the genotype . The carr cancer . In thisH2AFX variants are significantly associated with BC. The risk of BC increased with the number of the risk alleles  carried. The above-reported sequence variants of the MRE11 gene may not constitute a risk factor of breast cancer in the Polish population. The contribution of mutations detected in the ATM gene to the development of breast cancer needs further detailed study.The current data suggest that


This review will inform radiologists about the evidence base regarding radiographic imaging for transgender individuals and considerations for providing culturally sensitive care for this population.Transgender individuals are increasingly referred for both screening and diagnostic breast imaging. It is important that the clinic environment is welcoming, the medical staff utilize accepted terminology and patients are able to designate their gender and personal history to ensure appropriate care. Hormone and surgical treatments used for transition by many transgender women and men may change the approach to imaging.Although not yet evidence-based, screening mammography is currently suggested for transgender women with risk factors, including those receiving hormone treatment over 5 years. The risk for breast cancer in transgender individuals is still being defined. It is estimated that from 8 to 25 million individuals worldwide now identify as transgender ••. The iIn this paper, we will present indications for diagnostic breast imaging in the transgender population, show expected radiographic findings, and provide an evidence-based review of the current recommendations for breast cancer screening in transgender individuals based on relative risks for cancer derived from both retrospective and cohort studies. We will also outline practical changes that should be considered to provide culturally sensitive health care to this population. A conclusion that will emerge from this review is that there remains a need for prospective longitudinal follow-up of transgender individuals electing breast cancer surveillance; a description of and a means to refer patients to one such registry will be presented.Transgender is an adjective used to describe an individual whose gender does not correspond to the one assigned to them at birth. It is independent of genotype, sexual orientation, and behavior. While gender assigned at birth is assessed by inspection of genitalia, gender identity arises from an individual’s internal sense of being male or female or something else. Individuals assigned male sex at birth who desire to live as female  or assigned female sex at birth who desire to live as male  may take steps to alter their outward appearance to align with their gender identity. Transition refers to the process of changing gender expression or physical appearance to align with gender identity. Gender reassignment refers to steps taken to permanently alter one’s phenotype and can be achieved by hormone treatment and surgery. Cisgender and non-transgender refer to people whose gender and gender expression aligns with that assigned to them at birth . Table 1Due to stigma and discrimination, transgender individuals have suffered from lack of access to competent medical care , 4. GiveAn essential element of transition for transgender women is breast development. Transgender women may be treated with estrogen for feminization. In addition to estrogen, agents with antiandrogen activity such as spironolactone may be used to suppress testosterone , 7•.Breast development secondary to a physiologic estrogen surge in natal girls has been categorized into five Tanner stages of pubertal development . TransgeTransgender men may be treated with testosterone for masculinization and elect surgery to create a male chest contour.Testosterone is delivered by intramuscular injection or by transdermal patch, gel, or implant , 7•. ProTransgender men who elect surgical breast removal, referred to as “top surgery”, may have residual breast tissue if the surgical procedure consists of contouring of the chest and nipple sparing. It is generally agreed that transgender male patients who undergo breast removal are at very low risk of developing breast cancer. Models for breast cancer risk reduction following simple mastectomy are derived from high-risk cisgender women. It has been observed that there is less than 2% risk for breast cancer in cisgender women at increased hereditary risk who have prophylactic mastectomy .A mildly elevated ratio of estrogen to progesterone may normally occur in cisgender males during infancy, adolescence and advanced age . This caHistologic changes due to progesterone or androgen given in the setting of female to male transition have been inconsistent between studies. Slagter’s group looked at histology from 23 trans men treated with injectable testosterone and observed reduced glandular tissue and increased fibrous connective tissue similar to involutional changes observed in post-menopausal women . HoweverFinally, the largest study of mastectomy specimens from 100 transgender males—who were of average age 28 and received androgens for 2–9 years prior to surgery—showed markedly reduced glandular tissue and proliferation of fibrous stroma in 93% of cases . These iCross-sex hormone treatment for transgender women causes development of ductal epithelium and lobules which vary in distribution and density between individuals. The same breast pathology that occurs in natal women should be expected in transgender women. There are reports of benign entities such as fibroadenomas , 23, lipA Belgian series assessed 50 transgender women who were at least 6 months post-sex reassignment surgery with screening mammography and ultrasound . In thisDiagnostic imaging using mammography, ultrasound or MRI is the same in transgender and non-transgender women. Palpable abnormalities, in the absence of free injected silicone, can be evaluated with mammography and ultrasound. Figure In our experience, immature lobules similar to those found in adolescent breast tissue were noted in a transgender women at age 65 who had been taking estrogen for 13 years . TherefoAs with cisgender patients, breast implants are imaged with standard oblique and craniocaudal views and Eklund displaced views. Breast augmentation by direct injection of particles such as silicone, mineral oil, liquid paraffin, or petrolatum jelly presents a special challenge for imaging. This material migrates in the fat and muscle resulting in masses termed sclerosing lipogranulomas –32. BreaFree oil injections may be detected on cross-sectional imaging. Diffuse circumscribed fat density masses in the chest wall in Fig. The relationship of altered androgen and estrogen on breast cancer risk is poorly understood. The risk for breast cancer due to exogenous hormones prescribed for transgender individuals is informed by studies of estrogen and androgens in the general population. Use of relatively short-term combined exogenous estrogen and progesterone in post-menopausal cisgender women was associated with increased breast cancer incidence; however, exogenous estrogen alone was not associated with increased risk, according to data from the Women’s Health Initiative . AccordiConversely, though there are abundant androgen receptors in normal breast tissue and androgen receptors are also frequently expressed in breast cancers, there is no evidence for increased breast cancer incidence in women with hyperandrogenism such as polycystic ovary syndrome, or in transgender men receiving testosterone treatment . This isIt is not possible to derive cancer incidence in transgender individuals from existing U.S. cancer registries because transgender status is not documented. Misclassification of sex/gender assignment in U.S. cancer registries is a well-known phenomenon which may also result in under reporting of breast cancers in cisgender males . AlthougA descriptive study performed in the U.S. published in 2015 measured breast cancer incidence in a cohort of 5,135 transgender veterans . Chart rApart from the prospective and retrospective cohorts from the Netherlands and U.S. referred to above, there are a small number of case reports of breast cancers in transgender women. As of 2014, there were ten reported cases of breast cancer in transgender women on hormone treatment. Among those ten cases we observed that age at diagnosis tended to be younger than in cisgender populations, with a median age 48 compared to age 61 in cisgender females. In addition, five out of eight cases had ER negative cancer, and lobular development was similar to that of an adolescent girl . Our serIt appears that risk for breast cancer in trans men on testosterone treatment is low and it has been hypothesized that testosterone treatment reduces risk •. There It is generally recommended that transgender men who have not had mastectomy or who have only undergone breast reduction should follow the same guidelines for screening mammography as cisgender women irrespective of hormone treatment .While not supported by data, transgender men who have had mastectomy with chest contouring should consider clinical chest exams because, as noted above, cancers have been reported in this setting. Mammography may not be feasible in this group.There is a lack of consensus among the many organizations that provide recommendations for screening mammography for transgender women who are on hormone treatment. Screening mammography recommendations range from annual or biennial generally starting at age 50 for transgender women who have received estrogen treatment for at least 5 years , 48. OthThere are limited conflicting observations of utilization of mammography by transgender individuals. Using phone surveys conducted in 2014 by the Center for Disease Control’s Behavioral Risk Factor Surveillance System including 220 respondents, 54.5% of transgender females and 64.3% of transgender male respondents had undergone mammography within the past year . This stWhile any patient with breast tissue may develop breast cancer, risks vary according to genotype, phenotype, and acquired risk factors due to certain exposures. Table Because there is no evidence base for screening recommendations, any recommended screening should be done as part of an ongoing prospective study. We have initiated one such effort in New York, which is open to any individual seeking more information . AdditioRadiologists need to be knowledgeable about hormone and surgical treatments for transgender individuals that influence imaging appearance and risk for breast diseases. Imaging should be performed in a culturally sensitive environment. The current recommendations for mammography screening are based on data from cisgender women. Additional data, specifically from prospective longitudinal follow-up of transgender individuals electing breast cancer radiologic surveillance is needed to understand breast cancer risk in this population and to develop appropriate risk-adapted screening protocols. We have initiated one such effort in New York.