Of ten other risk factors that we studied, life time breastfeeding duration had the strongest evidence of association with the presence of microcalcifications . Developing algorithms, such as ours, which can be applied on both digitised and digital mammograms (in particular for presentation images), is important because large epidemiological studies, for deriving markers of  risk prediction of breast cancer and prognosis, can be based on images from these different formats.Using for-presentation and for-processing digital mammograms, the presence of microcalcifications has been shown to be associated with short-term risk of breast cancer. In a previous article we developed an algorithm for microcalcification cluster detection from for-presentation digital mammograms. Here, we focus on digitised mammograms and use a three-step algorithm. In total, 253 incident invasive breast cancer cases  and 728 controls  were included in a short-term risk study. After adjusting for potential confounding variables, we found evidence of an association between the number of microcalcification clusters and short-term (within 3–24 months) invasive breast cancer risk ). Using the 728 postmenopausal healthy controls, we also examined association of microcalcification clusters with reproductive factors and other established breast cancer risk factors. Age was positively associated with the presence of microcalcification clusters (p = 4 × 10 Calcification deposits are found within the ductal system, the breast acini, stroma and vessels2. Microcalcifications are present in approximately 55% of nonpalpable breast malignancies and are responsible for the detection of 85–95% of cases of ductal carcinoma in situ (DCIS) by screening mammography3, and they can also be present in invasive cancers4. The role of microcalcifications in the detection of breast cancer has been widely studied and some research groups have even investigated the role of microcalcifications in terms of risk and progression of breast cancer.Microcalcifications are deposits of calcium oxalate and calcium phosphate within the breast tissue that appear as white specks on a mammogram. The mechanisms by which microcalcifications occur are not clearly understood, although many factors are suspected to play a role, such as age, hormonal unbalance, pregnancy, breastfeeding and diet change. Active cellular processes, or effects of cellular degeneration may be involved7, in particular, when the false positive results are due to microcalcifications at mammography8. Detected abnormalities, although noncancerous, may therefore be useful as imaging features for breast cancer risk prediction. Microcalcifications represent a challenge in both perception and interpretation; between 12.7% and 41.2% of women are recalled with calcifications as the main mammographic feature/finding in screening programs. Although the value of using the computer aided detection (CAD) in breast screening is questioned9, in a study in the U.S., where CAD is used routinely in screening, it has been shown that false positive recall is associated with short-term risk of breast cancer10. It has also been demonstrated that CAD generated false positive detection, which includes the assessment of the presence of suspicious microcalcifications, can be used as a quantitative imaging marker of short-term breast cancer risk11. Further, it has been shown in a population where CAD is not routinely used, that the presence of clustered microcalcifications detected by a CAD algorithm, is important for short-term risk prediction12, even of invasive breast cancer.Previous studies have shown that women with false-positive results at screening have, on average, higher risks of breast cancer being detected at subsequent mammographic examinations than women with negative screening results13, for use on digitised images. Developing such algorithms as ours, which can be applied on both digitised and for-presentation digital mammograms, is important because large epidemiological studies, for deriving markers of  risk prediction of breast cancer and for studying prognosis, may have to be based on banks of images from different formats. We evaluate our algorithm in an epidemiological study of the short term risk of breast cancer using a case-control study design.Although almost all mammograms, nowadays, are acquired with full-field digital mammography systems , some valuable databases contain predominantly traditional screen-film mammographic images. In the current paper, we adapt a method that we recently developed for detecting microcalcification clusters in for-presentation digital imageset al.14 for a deep learning approach to microcalcification detection, trained against radiologists annotations, in for-processing digital images, and see Wang & Yang15 for a deep learning approach to distinguish between benign and malignant calcifications), but they may not be optimal for our purpose. CAD algorithms are designed specifically for cancer detection and are focused on malignant calcifications. However, even non-malignant calcifications may be indicative of a future risk.Our algorithms are specifically intended to be used in studies aimed at improving understanding of the importance/potential of microcalcifications for short-term risk prediction. Unlike in the development of CAD algorithms for suspicious microcalcification detection, in our context there is no gold-standard that can be derived and trained against. The underlying logic of our approach is that even if no detectable tumor is currently present, there may be characteristics in a woman’s mammographic image, picked up by our algorithm, that are indicative of an increased risk of breast cancer in the near future (the coming few years). It would of course be possible to use existing CAD algorithms, e.g. based on deep learning in short-term risk prediction models  to describe the adaptation of our algorithm  for potential microcalcification cluster assessment on digitised mammograms and to investigate the association of these clusters with the short-term risk of developing invasive breast cancer, and (2) to investigate the associations of established breast cancer (mainly reproductive history) risk factors with the presence of microcalcification clusters on mammograms.16. All cases had primary invasive breast cancer. CAHRES was able to collect (via screening and radiology units) mammograms for approximately 75% of its cases17. After making a number of exclusions  e.g. for having implants in the breast, a measure of percent density was able to be calculated for 1747 cancer patients, on mammograms close to diagnosis (the median time before diagnosis for these mammograms was 50 days). Area-based percent density (PD) has been measured for these women using Cumulus18, a computer-assisted thresholding technique, using the mammogram contralateral to the tumor. We were able to trace negative screens prior to diagnosis for 1338 of these cancer patients, but only 662 had a negative screening within 3−24 months before diagnosis. Of these, 325 had mediolateral oblique (MLO) mammograms from both left and right breasts. In the current study we used mammograms from 253 of these cases for which complete data on age, BMI, hormone replacement therapy (HRT) status, parity, smoking status, diabetes status, and age at menopause were available. We used a similar procedure, to that used for the cancer patients (cases), for selecting controls from the original CAHRES study base, by searching for images within 3−24 months before questionnaire date, and found 728 women that had both left and right mammograms as well as complete data for the covariates. In controls, PD had been measured from a single mammogram, with side chosen at random. We note that we could use fewer cases (253) than controls (728) because we needed the exact diagnostic date for cases, which was sometimes missing.Our analysis is based on CAHRES (Cancer and Hormone Replacement Study), a population-based post-menopausal breast cancer case-control study of Swedish residents born in Sweden and aged 50 to 74 years, between October 1993 and 31 March 1995. The CAHRES study base, from which we selected a subset of cases and controls, includes approximately 6000 women (approximately 3000 cases and 3000 age group matched controls). Details on data collection in CAHRES have been described elsewhereFor both cases and controls, body mass index (BMI) was recorded at entrance to the study, whereas age, in this study, was defined as age at mammography. Mammograms were digitised with an Array 2905 HD Laser Film Digitizer , which cover a range of 0−4.7 optical density. The size of the images was 4770 × 3580 pixels with 0.05 mm per pixel. Informed consent was obtained from all individual participants included in the study, and the study had the approval of the ethics review board at Karolinska Institutet, Stockholm, Sweden.Additional information  on breast feeding, life time breast feeding duration, and age at first birth for parous women was included in an additional analysis of association with case-control status and also in our analysis of association of microcalcifications with breast cancer risk factors.13, can be divided into the following steps: (a) image preprocessing, consisting mainly of denoising, quality improvement and enhancement of small objects, (b) identification of microcalcifications, (c) filtering out noise and grouping microcalcifications into clusters; see Fig. 13 that needs to be adapted for use on screen-film mammograms.Our proposed approach for microcalcification cluster detection, which is described in details in our earlier paperThe main aim of the preprocessing step is to separate the breast from other objects in the mammogram  by applying intensity transformations using the cosine function. We finally applied the Difference of Gaussian filter (DoG), a band-pass filter in which both cut-off frequencies were parametrised to be associated with microcalcification candidate sizes.20, that can enhance the brightness of microcalcifications and, at the same time, give more homogeneous linear structures. After applying thresholding operations to obtain the microcalcification candidate, all objects with shapes, sizes and appearances similar to microcalcifications were then filtered to reduce the noise. The last step involved microcalcification grouping using a Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm21. The same parameters that were defined for for-presentation images13 were used here.The segmentation of microcalcifications in mammographic images is challenging due to several reasons. Due to their physical properties, they are arbitrarily shaped spots of a limited range of sizes and there are often strong variations in the background, which can introduce structures which are similar to those of microcalcifications. Also, a noisy background in an image can sometimes exceed the signal of interest. We tackled these problems by applying a selective detector (Hessian of Gaussian (HOG)), targeting both blob-like and line-like structureset al.22. We note that the AUCs will be partially age-adjusted23 (i.e. will partly remove the effect of age), due to the fact that the study base, CAHRES, matched cases and controls within five year age groups.We evaluated the association between the presence of microcalcification clusters and case-control status by fitting a logistic regression model treating case-control status as the dependent variable. We treated the total number of microcalcification clusters in the left and right breasts as an independent variable. The variable used in our study of for-presentation images was defined in the same way. We first fitted logistic regression using all cases (253) and controls (728) by including the covariates age (continuous), BMI (continuous), PD (continuous), HRT , parity (continuous), smoking status , diabetes status  and age at menopause (continuous), as adjustment variables. In an additional logistic regression analysis we also added breastfeeding and age at first birth as adjustment variables. Because these variables are defined only for non-parous women, we combined the variables parity, breastfeeding and age at first birth into a single categorical variable with 9 categories. We also calculated and compared AUCs for two models, with and without the total number of microcalcification clusters variable entered as a covariate. In both cases all other covariates, except breastfeeding and age at first birth were included (i.e. we used the first model). To avoid over-fitting, we calculated “honest” values (of the AUCs) using the bootstrap procedure described by Harrell 24. The risk factors were age, BMI, PD, parity, age at first birth, breastfeeding duration, breastfeeding, HRT use, smoking status, diabetes status and age at menopause, and these were treated in the same way as in the risk analysis. In the results section we report parameter estimates from the models as odds ratios (OR) ). All analyses were performed in accordance with relevant institutional and national guidelines and regulations.To assess, at a population level, the association between a selection of established breast cancer risk factors (one at a time) with the presence of microcalcification clusters, using only breast cancer-free controls, we fitted a number of age-adjusted logistic regression models. We chose to study microcalcification clusters as a binary variable here . The data was too sparse to use multinomial logistic regression. Use of logistic regression is also consistent with a previous study of factors of vascular calcificationsAll authors approved the manuscript and consented for publication.We illustrate the results of applying our algorithm for detecting microcalcifications, for an example of digitised image; see Fig. Key characteristics of cases and controls included in our association analyses are described in Table −03), see Table −04; this corresponds, for example, to an OR of 5.1 when comparing women with a difference in PD of 75%. In a second logistic regression where we adjusted for all potential confounding variables (210 cases and 605 controls), we found similar evidence of association with the number of microcalcification clusters , p = 7 × 10−03). In this model the OR for PD was 1.025, 95% CI = (1.012–1.038), p = 1 × 10−04). Using a bootstrapping procedure (based on 1000 bootstrap samples), we obtained honest estimates of 0.656 and 0.645 for the AUCs for the full model, with and without the total number of potential microcalcification clusters, respectively (the corresponding apparent AUCs were 0.680 and 0.667).After adjusting for potential confounding variables , we found evidence of an association between the total number of microcalcification clusters and short-term invasive breast cancer risk , p = 1 × 10–1.534, pAmong the 728 postmenopausal healthy women, 27% had microcalcification clusters at mammography. Age was positively associated with the presence of microcalcification clusters Table . ResultsWe have adapted an algorithm for detecting microcalcifications which was originally developed for for-presentation digital images, for use on digitised film mammograms and, in a case-control study of postmenopausal invasive breast cancer, using negative screening images taken prior to diagnosis, have shown that our measure of microcalcification clusters is significantly associated with short-term risk of invasive breast cancer. In this study, we provide further evidence that microcalcifications can predict the future risk of invasive breast cancer.25. Whilst factors such as those listed above may be useful for long-term individualised screening26, there is also a need to find factors associated with short-term breast cancer risk, for which there would be an immediate clinical relevance . As we, and others, have shown, incorporating potential microcalcification clusters on mammography can be helpful for short-term breast cancer risk prediction.Many factors that increase the long-term risk of breast cancer are now known, such as a high percent density, a family history of breast cancer, a late age of first birth, an early onset of first menstruation, a late age at menopause. A large number of genetic markers of susceptibility to the disease, both rare and common have also been identified27 or to noncancerous lumps shrinking and calcifying with menopause and aging. To our knowledge, ours is the first study to describe an association between breast feeding and the presence of microcalcification clusters. Several cases of postlactational microcalcifications have been reported in the literature29. This might be a result of a combination of programmed cell death (apoptosis) and stasis of secretions29, since upon cessation of lactation the breast decreases in size as the glandular elements regress and atrophy.The association of the presence of microcalcification clusters and age can be due to involutionThe mechanisms by which these factors are associated with microcalcifications is still not clear and it is possible that these factors are associated differently across subtypes of microcalcification clusters.30, whereas smoking is associated with lower BAC prevalence30.In the current study, we considered all type of microcalcifications. For example, the output of our algorithm will include breast arterial calcifications (BAC), which are small calcium deposits in the vessel walls of the arteries; see Fig. 13 ), which was based on for-presentation mammograms, largely overlap. We suspect, however, that the “true” effect size based on digitised images may be smaller due to the quality of the images, since digital mammograms offer improved image contrast, and no digitisation noise, as well as access to information about the exact pixel resolution of the images. We would also point out that the women considered in this study are older than in our previous study, which means that there is a higher rate of detected microcalcification clusters due to age. There are limitations to any detection process, regardless of image format; it is not possible to account for random artifacts and noise that occur during the acquisition/digitisation step. In addition, studies have shown that microcalcification detection is sensitive to image quality and the radiation doses that are used32.The confidence intervals for the effect size of microcalcification clusters in this study ) and in our previous studyWe reiterate that it is important to develop algorithms for novel image-based markers that can be derived from both digital and digitised mammograms in order to open the door for research based on large collections of mammograms. We are, for example, currently working on a study of mammographic features for the early prediction of invasive breast cancer subtypes which is based on combining digital and digitised mammograms. Another interesting line of research would be to investigate the association of features describing microcalcification clusters, such as cluster locations in the breast, morphology and density, with cancer risk. It would even be interesting to study the relationships of these features with cancer risk factors. In a future study, we would like to test for association between microcalcification clusters and breastfeeding duration based on digital images.We have presented a method for microcalcification detection using digitised images. Our results confirm the association between the number of microcalcification clusters and the short-term risk of being diagnosed with invasive breast cancer. We have also reported associations between the presence of microcalcification clusters and a selection of breast cancer risk factors. Lifetime breast feeding duration was found to be positively associated with the presence of microcalcifications.


Comparison of risk factor associations between DCIS and invasive disease may elucidate which factors influence early versus late stages of carcinogenesis. Therefore, we determined whether there were differences in risk factor profiles for screen-detected DCIS and invasive breast cancer among Luminal A lesions.Invasive breast cancers are thought to arise from We conducted a case-control analysis using data from the Carolina Breast Cancer Study (1993–2001). Analyses were restricted to Luminal A tumors and screen-detected tumors among mammography-eligible women, to limit confounding by mode of detection . Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for associations between risk factors and lesion type.In stratified analyses, we observed qualitative differences in the direction of association for ever smoking, obese BMI, high waist-to-hip-ratio (WHR), and ≥10 years of oral contraceptive use between DCIS and invasive disease. Breastfeeding was inversely associated with invasive disease and was not associated with DCIS. Interaction tests for risk factor associations between Luminal A DCIS and invasive breast cancer were not statistically significant (p>0.05).Among Luminal A tumors, established breast cancer risk factors may exert stronger effects on progression of early lesions to invasive disease, with lesser effects on risk of DCIS. Higher WHR (≥0.84 versus <0.77) displayed an inverse association with DCIS , but was positively associated with invasive breast cancer . Likewise, being obese (BMI≥30 vs <25) was inversely associated with DCIS  and positively associated with invasive breast cancer . Oral contraceptive (OC) use for more than 10 years was differentially associated with DCIS and invasive breast cancer, with a weakly protective association for DCIS and strongly associated with invasive disease . Physical activity was inversely associated with invasive disease and was not associated with DCIS.Smoking and alcohol drinking showed stronger associations with DCIS than invasive disease. Ever drinking alcohol was positively associated with DCIS [OR: 1.63 95% CI (0.96–2.79)], but the association was attenuated for invasive breast cancer [OR: 1.17 95% CI ]. Ever smoking was inversely associated with DCIS but not invasive disease .Additional analyses, including all cases of Luminal A DCIS and Luminal A invasive breast cancer, regardless of age at diagnosis or mode of detection, are presented in Using data from the population-based Carolina Breast Cancer Study Phases 1–2, we found limited evidence that risk factor profiles may differ for screen-detected Luminal A DCIS compared to screen-detected Luminal A invasive breast cancer. Although no statistically significant interactions were detected, differences in the direction of association were observed for measures of adiposity (BMI and WHR) and oral contraceptive use for DCIS and invasive disease. Ever smoking was inversely associated with DCIS, but not invasive disease. We also observed that ever breastfeeding and physical activity were inversely associated with risk of invasive disease, but not DCIS. Risk factor profiles were similar between the two groups for family history of breast cancer, number of full-term pregnancies, and age at first full term pregnancy.et al. (2010) and Trentham-Dietz et al. (2007), we observed an inverse relationship between ever smoking and risk of Luminal A DCIS.[et al. (2009) and Furberg et al. (2002)[Many of the associations we observed track with published literature reports. As reported previously in the literature by Kabat l A DCIS., 25 Thisl. (2002), 27 and l. (2002) and the l. (2002) Adipositl. (2002)–32 and il. (2002), 34 We sl. (2002) Differenl. (2002), 36–43 AA previous CBCS analysis investigated differences between DCIS and invasive breast cancer wherein all DCIS were stratified by pathological subtype (comedo vs. non-comedo) and found comedo DCIS to have similar risk factor profiles to invasive breast cancer, whereas non-comedo DCIS may represent a distinct etiology. In more Our study has some limitations. First, we had limited sample size to investigate the interactions between DCIS and invasive disease and most of our interaction tests were not statistically significant. Second, we used IHC markers to act as a surrogate for Luminal A subtype. Although progesterone receptor (PR) was assessed for invasive and not DCIS cases, it was uncommon for invasive breast cancer in the CBCS to be PR positive and ER negative and therefore differentiation between subgroups of hormone receptor positive cancers was not possible. However, sensitivity analyses showed that exclusion of invasive breast cancers that were only PR positive did not substantially alter associations. Third, we acknowledge potential misclassification of the self-reported mode of detection, because this data was not confirmed by medical records or mammography history. Additionally, we do not expect any recall bias for lifestyle factors to differentially influence DCIS or invasive cases. We do not expect differential misclassification of mode of detection by DCIS or invasive breast cancer. By restricting our analysis to screen-detected invasive breast cancer and screening-eligible controls we have focused on a smaller subset of tumors, and our findings may not generalizable to other subtypes  and ages (e.g. breast cancer before age 40 years). However, our analysis has maximized internal validity to compare DCIS and invasive disease. Finally, analyses such as ours are helpful in identifying etiologic differences between diseases but are not well-suited to identify biologic mechanisms.The widespread use of mammography has increased detection of both DCIS lesions and invasive breast cancers over the past decades., 2 IdentS1 Table(DOCX)Click here for additional data file.


Personal cancer risk assessments enable stratified care, for example, offering preventive surgical measures such as risk-reducing mastectomy (RRM) to women at high risk for breast cancer. In scenario-based experiments, we investigated whether different benefit–harm ratios of RRM influence women’s consideration of this, whether this consideration is influenced by women’s perception of and desire to know their personal cancer risk, or by their intention to take a novel cancer risk-predictive test, and whether consideration varies across different countries.In January 2017, 1,675 women 40 to 75 years of age from five European countries—Czech Republic, Germany, UK, Italy, and Sweden—took part in an online scenario-based experiment. Six different scenarios of hypothetical benefit–harm ratios of RRM were presented in accessible fact box formats: Baseline risk/risk reduction pairings were 20/16, 20/4, 10/8, 10/2, 5/4, and 5/1 out of 1,000 women dying from breast cancer.Varying the baseline risk of dying from breast cancer and the extent of risk reduction influenced the decision to consider RRM for 23% of women. Decisions varied by country, risk perception, and the intention to take a cancer risk-predictive test. Women who expressed a stronger intention to take such a test were more likely to consider having RRM. The desire to know one’s risk of developing any female cancer in general moderated women’s decisions, whereas the specific desire to know the risk of breast cancer did not.In this hypothetical scenario-based study, only for a minority of women did the change in benefit–harm ratio inform their consideration of RRM. Because this consideration is influenced by risk perception and the intention to learn one’s cancer risks via a cancer risk-predictive test, careful disclosure of different potential preventive measures and their benefit–harm ratios is necessary before testing for individual risk. Furthermore, information on risk testing should acknowledge country-specific sensitivities for benefit–harm ratios. Genetic, epigenetic, lifestyle, and reproductive factors alone or combined can be used to predict a woman’s risk for developing breast cancer.–3 Althouhttps://forecee.eu) aims to develop a risk-predictive test—for breast, cervical, endometrial, and ovarian cancer—in cervical epithelial cells, based on epigenetic markers.[BRCA1 or BRCA2 mutations.[The FORECEE Consortium  varying baseline risks of breast cancer-specific mortality and varying extents of reduction in breast cancer-specific mortality following mastectomy would affect women’s consideration of RRM. In order to control whether aspects other than risk information would moderate their decisions, we further investigate if potential differences in women’s considerations are associated with (2) their perception of the individual female cancer risk, (3) their desire to know their female cancer risks, and (4) their intention to take a novel risk-predictive test if available. Finally, we investigated (5) whether the proportion of women considering RRM varied across European countries.We developed an online survey questionnaire, which was translated into five languages. FORECEE Consortium members The study was approved by the Institutional Ethics Board of the Max Planck Institute for Human Development, Berlin (Germany). It was carried out in accordance with the guidelines and regulations of the Max Planck Society for the Advancement of Science in Germany. Written informed consent was required to participate in this particular study.In January 2017, Harris Interactive drew national samples of women in the core age group of screening programs and around that core age (aged 40 to 75 years) from five European countries that represent Northern (Sweden), Eastern (Czech Republic), Southern , Western (United Kingdom), and Central Europe (Germany): Of the 3,629 women invited (inclusion criteria: aged 40 to 75 years), 2,092 responded and 1,675 completed the survey (response rate: 61.4%). The questionnaire did not allow for item nonresponse. Sample selection and sample population are detailed elsewhere.[The survey consisted of three sections eliciting women’s disease risk perception, their attitude toward cancer risk-predictive testing based on epigenetic markers, and their considerations to undertake RRM. Participants were presented with a leaflet containing baseline risk information about developing breast, cervical, endometrial, or ovarian cancer within 10 years and a novel risk-predictive test  before tWithin the fact box, in a frequency format, informatThe fact box was presented together with the question “Would you consider having prophylactic removal of your breasts?”. At the end of the survey, participants were debriefed that the figures in the scenarios were hypothetical and how they were varied across the scenarios.Within-subjects and between-subjects analyses were performed using variance analyses, with samples approximating normal distributions. Linear regressions with the dependent variable average level of mastectomy consideration across the six scenarios and logistic regressions with the dependent variable scenario-specific mastectomy consideration were conducted to investigate the influences of disease risk perception, a general desire to know one’s female cancer risk, and the intention to have a risk-predictive test for female cancer. Different response patterns of consideration were identified and the association with the study variables was assessed using the Chi-squared test.Among the 1,675 women in the study (the participants characteristics are described in χ2(4) = 23.11, p < .001): Women with low levels of the International Standard Classification of Education (ISCED) were more likely to consider mastectomy in every scenario, those with medium levels were more likely to never consider mastectomy, and those with high levels were more likely to consider mastectomy in dependence of the risk information provided in the scenarios. Response patterns varied by country (χ2(8) = 124.07, p < .001): 75.5% of women in Germany but only 42.1% of women in the United Kingdom and 43.0% in Sweden never considered mastectomy in the scenarios. Conversely, 24.8% of women in the United Kingdom and 27.6% in Sweden, but only 9.3% of women in Germany, considered mastectomy in each scenario  = 43.67, p < .001, ηp2 = 0.03) and larger mortality risk reduction with RRM  = 62.86, p < .001, ηp2 = 0.04) were associated with a larger average consideration of RRM in our sample (n = 104), breast cancer diagnosis, or ductal carcinoma in situ (n = 59). Including age group as a between-subject factor revealed neither a main effect on consideration  = 0.25, p = .862) nor interactions with baseline risk  = 1.81, p = .095) or risk reduction  = 2.19, p = .087). Factors associated with scenario-dependent responses are presented in Higher baseline risk of breast cancer mortality  = 34.22, p < .001, R2 = 0.10)  explained the increased consideration of mastectomy across countries. However, women from Italy , Germany , and the Czech Republic  with a general desire to know their female cancer risks were less likely to consider mastectomy than those from the United Kingdom. Moreover, German women  were less likely to consider mastectomy in general  . The gen general .M = 0.38, SD = 0.44). In comparison, the average consideration of those who did not perceive themselves to be at higher risk was M = 0.28 (SD = 0.40). This association holds after controlling for several factors, including the desire to know one’s risk level and the intention to take a novel risk-predictive test under development.During the study, the women were given a leaflet containing the age-specific risks of developing breast cancer. After reThe stepwise regression showed that the women were more likely to decide to consider mastectomy when they intended to take the predictive test for four different types of cancer and when they had a general desire to know their cancer risk, averaged across the four types of cancer. At the same time, when controlled for the general desire to know, the desire to know one’s breast cancer risk did not make it more likely to consider mastectomy . As womeTo summarise and structure all described relationships, BRCA mutation carriers identified up to 2015 underwent RRM[BRCA mutation carriers chose to undergo RRM within five years after disclosure of the test result.[Only 23% of the participants varied their decisions on RRM according to a given baseline risk of breast cancer mortality and the expected risk reduction due to the mastectomy. In contrast, most of the women always applied the same response strategy, that is, always responded “yes” or “no” regardless of information provided. Although this phenomenon may hint to the fact that the presented scenarios did not translate well to the women in our study, it is worth noting that the consistent response patterns systematically varied across the five European countries. For instance, we saw the largest proportion of women who would not consider undergoing RRM in Germany and the largest proportion who would always consider it in the United Kingdom and Sweden. Thus, the proportion of consistent response patterns observed in our survey might be less an artefact of women not understanding the information provided than a general national attitude toward having preventive surgeries to reduce cancer risk. The observed variations in our study are indeed quite in line with real uptake rates in different countries. In Walesrwent RRM, and 40%rwent RRM US data rwent RRM A study t result.A history of large-scale prevention campaigning in the United Kingdom and Sweden  were associated with considering. Many preventive considerations regarding breast cancer are not necessarily based on disease-related interest. Instead, it cannot be excluded that offering the test could nudge some part of the general population toward surgery by advancing cancer risk-testing opportunities in the first place.The hypothetical scenario-based approach does not allow for a direct transfer of our findings to real-world health considerations. For instance, there is a gap between considering and having prophylactic mastectomy. FurthermParticipants could only marginally experience the decision faced by a high-risk woman. However, we chose to use very high risks so that participants would not underestimate the impact of potential real-world risks. A limitation of the study is that only breast cancer mortality risk is considered and not the risk of developing breast cancer. Another limitation is that the presentation of the scenarios was in random sequence and non-adaptive, which can produce errors if participants are forced to make repeated judgments. This may have led the 112 participants (6.7%) to produce intransitive considerations. This is not surprising because low-numerate people have difficulties in understanding numerical risk information, but this could be overcome with the help of icon arrays in future studies.With a 61% response rate, there is a potential participation bias and nonresponse bias. However, there is unlikely to be bias by disease experience. For example, 3.5% of participants from Germany with a median age of 56 years reported a breast cancer diagnosis in the past. The cumulative risks of developing breast cancer in Germany for women aged 54 and 59 years are 2.9% and 4.1%, respectively. FurthermHow information is provided to the public is crucial. Obviously, many women in our study did not take the presented cancer mortality baseline risk into account and the extent of mortality reduction, but were influenced by other factors. It follows that, if risk-predictive tests for female cancers enter the healthcare system providing women with consistent evidence-based health information at all different stages of their care, this will be particularly important in order to ensure informed decisions. Furthermore, communication regarding cancer risk-predictive tests needs to promote reflection on potential benefits and harms of testing and non-testing as well as on risk management in the first place. Finally, communication strategies should also acknowledge country-specific health values.S1 Table(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.S3 Table(PDF)Click here for additional data file.S1 Fig(PDF)Click here for additional data file.S2 Fig(PDF)Click here for additional data file.S3 Fig(PDF)Click here for additional data file.S4 Fig(PDF)Click here for additional data file.S5 Fig(PDF)Click here for additional data file.S6 Fig(PDF)Click here for additional data file.S7 Fig(PDF)Click here for additional data file.S1 Text(PDF)Click here for additional data file.


Earlier age at onset of pubertal events and longer intervals between them (tempo) have been associated with increased breast cancer risk. It is unknown whether the timing and tempo of puberty are associated with adult breast density, which could mediate the increased risk.From 1988 to 1997, girls participating in the Dietary Intervention Study in Children (DISC) were clinically assessed annually between ages 8 and 17 years for Tanner stages of breast development (thelarche) and pubic hair (pubarche), and onset of menses (menarche) was self-reported. In 2006–2008, 182 participants then aged 25–29 years had their percent dense breast volume (%DBV) measured by magnetic resonance imaging. Multivariable, linear mixed-effects regression models adjusted for reproductive factors, demographics, and body size were used to evaluate associations of age and tempo of puberty events with %DBV.p trend = 0.04), while pubertal tempo between thelarche and menarche was positively associated with %DBV (p trend = 0.007). %DBV was 40% higher in women whose thelarche-to-menarche tempo was 2.9 years or longer (geometric mean (95%CI) = 21.8% (18.2–26.2%)) compared to women whose thelarche-to-menarche tempo was less than 1.6 years (geometric mean (95%CI) = 15.6% (13.9–17.5%)).The mean (standard deviation) and range of %DBV were 27.6 (20.5) and 0.2–86.1. Age at thelarche was negatively associated with %DBV (Our results suggest that a slower pubertal tempo, i.e., greater number of months between thelarche and menarche, is associated with higher percent breast density in young women. Future research should examine whether breast density mediates the association between slower tempo and increased breast cancer risk. An earlier age at menarche is an established risk factor for breast cancer –3. HowevCharacterizing the relationship between pubertal development and breast density may help clarify if breast cancer risk is influenced by factors during breast development, when breast tissue might be particularly susceptible to proliferative and carcinogenic stimuli. Given that earlier ages at thelarche and menarche are associated with increased breast cancer risk  and thatBetween 1988 and 1997, DISC, a multicenter randomized controlled clinical trial sponsored by the National Heart, Lung, and Blood Institute (NHLBI), was conducted to test the safety and efficacy of a dietary intervention to reduce serum low-density lipoprotein cholesterol (LDL-C) in children with elevated LDL-C –12. At bn = 30) and those who had breast implants or breast reduction surgery (n = 16) were not eligible for the current analysis. An additional 32 women were excluded because they had technically unacceptable or missing breast magnetic resonance imaging (MRI) leaving a total of 182 participants for inclusion in analyses.All female DISC participants were invited to participate in the DISC06 Follow-Up Study, and 260 (86.4%) of the 301 females originally randomized took part. Women who were pregnant or breastfeeding at or within 12 weeks before the study visit (Trained and certified clinicians assessed girls for breast and pubic hair Tanner stage (T1–5) at annual visits between the ages of 8 and 17 years until T5 was reached . Ages atr = .87) based on mammography [%DBV was measured using noncontrast MRI on a whole-body 1.5-Tesla or higher field-strength MRI scanner with a dedicated breast-imaging radiofrequency coil as previously described , 14. Onemography , which imography . ADBV anAt DISC06 follow-up visits, participants completed several questionnaires on demographic characteristics; medical, reproductive, and menstrual histories; medication use; and health habits. Height, weight, and waist circumference were measured, and body composition was assessed by whole-body dual-energy X-ray absorptiometry (DXA) as previously described .z-score relative to CDC 2000 Growth Charts [N = 6), age at thelarche (n = 12), and age at pubarche (n = 9) were imputed using values from a prediction model that included adult BMI as an independent variable as well as covariates in model 3; this process was repeated 25 times to create 25 multiply-imputed datasets. Results from each imputed dataset were pooled using Rubin’s rule [z-score was < 1.5. All tests were two-sided and considered to be significant if p value < 0.05. All analyses were conducted using STATA 13.0 .We initially explored distributions of breast density measures graphically and by using nonparametric statistics, and prior to modeling, log-transformed measures to improve normality. We calculated geometric means and 95% confidence intervals of %DBV, ADBV, and ANDBV across quartiles of ages at thelarche, pubarche, menarche, and pubertal tempo variables by exponentiating the least square means from multivariable linear mixed-effects regression models with clinic as a random effect and robust standard errors. Model 1 is the crude, unadjusted model. Model 2 adjusted for adult covariates, including parity (nulliparous vs parous), duration of hormone use (continuous), education , race (white vs. non-white), smoking status (never vs ever), whole-body percent fat measured by DXA (continuous), and height (continuous). Because childhood BMI is a strong predictor of pubertal timing and was also previously associated with %DBV in DISC06 , model 3h Charts . Missingn’s rule . Using m2. The mean (standard deviation) of %DBV was 27.6 (20.5). Covariates across tempo categories were generally similar .At baseline, all girls were pre-pubertal, and during the DISC trial, the majority reached thelarche before pubarche. The mean age of 182 women included in the present study was 27.2 years at the DISC06 follow-up visit , %DBV increased with increasing duration from thelarche- to- menarche tempo (p trend = 0.007). %DBV was 40% higher in women whose thelarche-to-menarche tempo was 2.9 years or longer (geometric mean (95%CI) = 21.8% (18.2–26.2)) compared to women whose thelarche-to-menarche tempo was less than 1.6 years (geometric mean (95%CI) = 15.6% (14.2–20.7)). Girls who were oldest at thelarche (≥ 11.1 years) had an 18% lower %DBV compared to girls who were youngest .Table p for interaction < 0.001).We, therefore, explored the combined effects of pubertal timing (age at thelarche and menarche) and thelarche-menarche tempo in cross-classified models and present the %DBV geometric means and 95% confidence intervals from these models in Table p ≤ 0.01).There was a positive multiplicative interaction between thelarche and menarche in association with %DBV .There was no interaction between thelarche-to-menarche tempo and diet intervention assignment. In sensitivity analyses, restricting to white women, nulliparous women, women not using hormonal contraceptives, or women with baseline BMI Associations of pubertal timing and tempo with ADBV and ANDBV are shown in Additional file In this prospective study with over 20 years of follow-up, girls with a thelarche-to-menarche tempo of approximately 3 years or more have significantly higher %DBV in their mid-to-late twenties compared to girls with a tempo of ~1.5 years or less. Age at thelarche, but not menarche, also was associated with %DBV in our fully adjusted models.This prospective study demonstrates an association between clinically assessed pubertal timing and tempo with %DBV in young women. One previous study by Schoemaker et al. evaluated recalled pubertal timing in relation to adult breast density . In thatn = 24) of healthy premenopausal Asian women by Chen et al. that found the mean %DBV to be 21.4 (8.4) [The mean (SD) of %DBV in our study was 27.6 (20.5), which is slightly higher than that in another small study (.4 (8.4) . In cont.4 (8.4) , the medEarlier age at menarche is a long established risk factor for breast cancer . Even thz-scores (> 1.5), the pattern of associations between tempo and adult %DBV remained, suggesting that the finding is robust to any misclassification of lipomastia for breast development. Our findings suggest associations between age at thelarche and thelarche-to-menarche tempo and %DBV but cannot prove causation or rule out a common cause.Our study has limitations. To be eligible for the original DISC trial, children had to have high LDL-C defined as greater than or equal to the 80th and less than the 98th age- and sex-specific percentiles of the Lipid Research Clinics population, which for girls translates to 117.5–164.5 mg/dL . AdditioDespite these limitations, our study has several strengths. In particular, we were able to leverage prospectively collected data on pubertal development and breast density measured from the DISC study. Trained and certified personnel following standard protocols collected all data. Clinicians assessed sexual maturation and participants reported onset of menses annually. Finally, breast density was measured at age 25–29 years by MRI, which gives accurate and precise measurement of %DBV.Our finding that a longer pubertal tempo is associated with increased %DBV may help to explain the current increasing rates of early-onset breast cancer incidence . In the Additional file 1 : Table S1. Characteristics of DISC participants in childhood and as young adults by quartiles of thelarche to menarche tempo duration. Table S2. Geometric mean (95%CI) from mixed-effects regression models for each pubertal factor in relation to Absolute Dense Breast Volume (ADBV). Table S3. Geometric mean (95%CI) from mixed-effects regression models for each pubertal factor in relation to absolute non-dense volume (ANDBV).


Tamoxifen treatment greatly reduces a woman’s risk of developing a second primary breast cancer. There is, however, substantial variability in treatment response, some of which may be attributed to germline genetic variation. CYP2D6 is a key enzyme in the metabolism of tamoxifen to its active metabolites, and variants in this gene have been associated with reduced tamoxifen metabolism. The impact of variation on risk of contralateral breast cancer (CBC) is unknown.Germline DNA from 1514 CBC cases and 2203 unilateral breast cancer controls was genotyped for seven single nucleotide polymorphisms, one three-nucleotide insertion-deletion, and a full gene deletion. Each variant has an expected impact on enzyme activity, which in combination allows for the classification of women as extensive, intermediate, and poor metabolizers . Each woman was assigned one of six possible diplotypes and a corresponding CYP2D6 activity score (AS): EM/EM (AS = 2), EM/IM (AS = 1.5), EM/PM (AS = 1), IM/IM (AS = 0.75), IM/PM (AS = 0.5), and PM/PM (AS = 0). We also collapsed categories of the AS to generate an overall phenotype . Rate ratios (RRs) and 95% confidence intervals (CIs) for the association between tamoxifen treatment and risk of CBC in our study population were estimated using conditional logistic regression, stratified by AS.p for homogeneity = – 0.02).Among women with AS ≥ 1 , tamoxifen treatment was associated with a 20–55% reduced RR of CBC . Among women with no EM alleles and at least one PM allele , tamoxifen did not appear to impact the RR of CBC in this population  (This study suggests that the CYP2D6 phenotype may contribute to some of the observed variability in the impact of tamoxifen treatment for a first breast cancer on risk of developing CBC.The online version of this article (10.1186/s13058-018-1083-y) contains supplementary material, which is available to authorized users. The high incidence of breast cancer in the United States, coupled with a high rate of survival, places an increasing number of women at risk of contralateral breast cancer (CBC) . CBC is CYP2D6 have been shown to have reduced enzyme activity and lower circulating levels of active metabolites [CYP2D6 is a key enzyme in tamoxifen metabolism and has been central to the pharmacogenetic investigation of tamoxifen treatment response. Focus has been placed on CYP2D6 because it is responsible for the metabolism of tamoxifen to its two primary active metabolites, 4-hydroxytamoxifen and endoxifen. Compared to tamoxifen, these metabolites have over 100-fold higher affinity for the estrogen receptor (ER), and 30-fold to 100-fold greater potency in suppressing estrogen-dependent tumor cell growth , 8. Carrabolites .CYP2D6 on breast cancer recurrence and mortality, with mixed results [CYP2D6 on risk of CBC. It is currently unknown whether germline variation in CYP2D6 modifies the association between tamoxifen treatment and risk of CBC. Given the relationship between tamoxifen and risk of CBC, this is potentially a critical clinical issue. The objective of this study was to examine the impact of genetically inferred CYP2D6 phenotype on the association between tamoxifen treatment for a first breast cancer and the risk of CBC in a large population-based case–control study.Given these effects on tamoxifen metabolism, studies have examined the impact of variation in  results –27. ThesThe Women’s Environmental Cancer and Radiation Epidemiology (WECARE) Study is a multicenter, population- based case–control study where cases are women with asynchronous CBC and controls are women with unilateral breast cancer (UBC). Case–control recruitment for the WECARE Study was conducted in two phases: WECARE I (2001–2004) and WECARE II (2009–2012). 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 Registries . These cancer registries all contribute to the National Cancer Institute (NCI) Surveillance, Epidemiology and End Results (SEER) program in the United States. Patients were also recruited from the Ontario (Canada) Cancer Registry and the Danish Breast Cancer Cooperative Group Registry, supplemented by data from the Danish Cancer Registry. All study participants provided written informed consent, and the study protocol was reviewed and approved by the Institutional Review Board at each recruitment site and the ethical committee systems in Denmark and Ontario. Across the eight cancer registries a total of 2354 CBC cases and 3599 UBC controls were identified as being eligible and were approached for the study. The final number of participants who completed the interview and provided a biospecimen for DNA analysis was 1518 (64%) cases and 2208 (61%) controls. Reasons for nonparticipation have been described in detail . An addiDetails of recruitment procedures, eligibility, and the study questionnaire have been described previously, and were nearly identical for the two study phases . BrieflyWECARE Study participants were interviewed by telephone using a structured questionnaire that 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. The at-risk period was defined as beginning at least 1 year after diagnosis with a first breast cancer and ending at the second diagnosis in CBC cases, or the corresponding reference date for UBC controls. The study questionnaire included questions 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, any recurrences experienced prior to the reference date, and tumor characteristics of the first primary tumor .CYP2D6 [Germline DNA was isolated from blood using standard phenol–chloroform extraction methods or from saliva using the manufacturer’s recommendations . Samples were genotyped for seven single nucleotide polymorphisms (SNPs), one three-nucleotide insertion-deletion (indel), and a full gene deletion Table , accountCYP2D6 . Genotyphttps://agenacx.com), and a method similar to that reported by Falzoi et al. [CYP2D6 in a long-range PCR. The PCR products were verified on a 1% agarose gel. One microliter of the amplified product was used for genotyping using specific primers and cycling conditions , with assays designed using the Agena Cx online tools  analysis was conducted with a modified three-primer-based, long-range PCR using primers described by Okubo et al. [2+ , 0.5 mM dNTPs , 0.5 μM of each primer, and 0.4 units of Takara LA Taq DNA Polymerase (Clontech), in a total volume of 8 μl. Cycling included denaturation at 94 °C for 1 min, 25 cycles of 98 °C for 20 s and 70 °C for 6 min, annealing at 70 °C for 6 min, and a final hold at 4 °C. PCR products were run on 1% e-gels , and band sizes were determined against molecular weight markers to evaluate CYP2D6 presence (4.7 kb band) or deletion . QC procedures included use of control samples from the Coriell Institute, 5% intraplate and 0.5% interplate duplicates, as well as negative (sterile distilled water) controls.Full o et al.  to ensurwww.Pharmvar.org/gene/CYP2D6  [CYP2D6 nomenclature came from the American College of Medical Genetics and Genomes (ACMG) Standards and Guidelines  and PharD6 Table . AllelesYP2D6*6) . In thisYP2D6*6) , 36, 37.YP2D6*6) .N = 1335 CBC cases and N = 1980 UBC controls) to address the issue of ancestral differences in genotype frequencies. All statistical analyses were conducted using SAS 9.4 .Rate ratios (RRs) and 95% confidence intervals (CIs) for the association between tamoxifen treatment and risk of CBC in our study population were estimated fitting conditional logistic regression models, stratified by CYP2D6 AS. Rate ratios can be interpreted as a relative risk  of CBC in tamoxifen-treated versus untreated women in our study population. Models were adjusted for: age at first diagnosis, histology, stage, and ER status of first diagnosis, first-degree family history of breast cancer, chemotherapy for first breast cancer, radiation treatment for first breast cancer, hormonal therapy other than tamoxifen for a first breast cancer, number of full-term pregnancies before first diagnosis, and age at menarche. Because treatment for a first breast cancer could induce menopause, menopausal status and age at menopause 2 years prior to first diagnosis were used. To account for the counter-matching in WECARE I, we included a log-weight covariate offset term. For WECARE II participants who were matched in pairs (without counter-matching on radiation treatment), we assigned the value of 1 to be the offset term. We used the likelihood ratio test to test for homogeneity of treatment effect across AS/phenotypes. A sensitivity analysis was conducted restricting model fitting to Caucasian women  were comparable to the expected frequencies in a predominantly Caucasian study population . When AS categories were grouped to classify individuals based on overall phenotype , women with at least one fully functional (EM) allele  treated with tamoxifen had nearly a 40% lower risk of CBC relative to those not treated with tamoxifen . Conversely, women classified as IM or PM  treated with tamoxifen were not at a lower risk of CBC . However, these results (by AS phenotype) were not statistically significantly different (p for homogeneity of 0.09). Restricting the analyses to women with an ER-positive first primary breast cancer, to women who were premenopausal at first diagnosis, or to Caucasian women did not alter the results  relative to those not treated with tamoxifen  , althougor small . Indeed,ecisions . The curp for homogeneity = 0.09), the overall trend appeared to be consistent. The exception is the finding for EM/EM (AS = 2), where RR = 0.81  who were treated with tamoxifen had a lower risk of CBC relative to those not treated with tamoxifen , women classified as having AS < 1  who were treated with tamoxifen were not at lower risk of CBC . Although these results are not statistically significantly different  [In our study, a relatively large proportion 41%) of women with ER-positive first breast cancers did not receive hormonal therapy of any kind, while some women with ER-negative breast cancer did (18%). This may have happened because approximately 20% of women included in this study were diagnosed with a first primary breast cancer prior to 1989 (Table % of womearriers) , tamoxifCYP2D6 copy number variation and therefore were not able to identify ultra-rapid metabolizers within our study population. In addition, the WECARE Study predominantly consists of Caucasian women, limiting the generalizability of our results somewhat. However, although the CYP2D6 variant frequency and corresponding inferred phenotypes have been shown to vary by race/ethnicity [A major and unique strength of this study is our ability to investigate the impact of the CYP2D6 phenotype specifically on the risk of CBC. This was made possible given our use of a retrospective, multicenter, population-based design, which allowed for the inclusion of a large number of women diagnosed with CBC. Another key strength was the availability of detailed treatment histories from medical records, including both tamoxifen treatment as well as other treatments that were included as covariates in the analysis. This study also has some limitations. Information regarding use of other medications (beyond those used for treatment of a first breast cancer) was not collected. Consequently, we were not able to account for drugs that have been observed to inhibit CYP2D6 , although evidence to date suggests that any possible effects are likely quite modest . We alsothnicity , their ithnicity .Aromatase inhibitors are now the first-line hormonal treatment for postmenopausal women with ER-positive breast cancer , while tWomen frequently overestimate their risk of CBC, leading to increasing rates of contralateral prophylactic mastectomy. Overall, this study provides early evidence that the CYP2D6 phenotype may contribute to some of the observed variability in the impact of tamoxifen treatment for a first breast cancer on the risk of developing CBC. Identifying factors that can influence a woman’s risk of developing CBC will inform discussions between patient and physician, help guide treatment decisions, and strengthen evidence-based risk communication.Additional file 1: CYP2D6 polymorphisms tested, primer sequences, and PCR conditions for genotyping. (XLSX 10 kb)Additional file 2:CYP2D6 variant details by case–control status. (DOCX 27 kb)Additional file 3:Association between tamoxifen treatment and risk of CBC stratified by CYP2D6 activity score in women with ER-positive first breast cancer in the WECARE Study population. (DOCX 16 kb)Additional file 4:Association between tamoxifen treatment and risk of CBC stratified by CYP2D6 activity score in women who are premenopausal at first diagnosis in the WECARE Study population. (DOCX 17 kb)Additional file 5:Association between tamoxifen treatment and risk of CBC stratified by CYP2D6 activity score in Caucasian women in the WECARE Study population (DOCX 16 kb)


Background/Objective: Data suggest that modifiable risk factors such as alcohol and tobacco use may increase the risk of breast cancer (BC) recurrence and reduce survival. Female BC mortality in South Carolina is 40% higher among African Americans (AAs) than European Americans (EAs). Given this substantial racial disparity, using a cross-sectional survey design we examined alcohol and tobacco use in an ethnically diverse statewide study of women with recently diagnosed invasive breast cancer. This included a unique South Carolina AA subpopulation, the Sea Islanders (SI), culturally isolated and with the lowest European American genetic admixture of any AA group.Methods: Participants , diagnosed between August 2011 and December 2012, were identified through the South Carolina Central Cancer Registry and interviewed by telephone within 21 months of diagnosis. Self-reported educational status, alcohol consumption and tobacco use were obtained using elements of the Behavior and Risk Factor Surveillance System questionnaire.Results:Alcohol: EAs were approximately twice as likely to consume alcohol (40%) and to be moderate drinkers (29%) than either AA group . Users tended to be younger, significantly among EAs and non-SI AAs, but not SIs, and to have attained more education. Heavy drinking was rare (≤1%) and binge drinking uncommon (≤10%) with no differences by race/ethnicity. Among both AA subgroups but not EAs, alcohol users were six to nine times more likely to have late stage disease , statistically significant but with wide confidence intervals. Tobacco: Current cigarette smoking  was reported by 14% of EAs, 14% of non-SI AAs and 7% of SIs. Smoking was inversely associated with educational attainment. Use of both alcohol and cigarettes was reported by 3–6% of cases.Conclusions: Prevalences of alcohol and cigarette use were similar to those in the general population, with alcohol consumption more common among EAs. Up to half of cases used alcohol and/or tobacco. Given the risks from alcohol for disease recurrence, and implications of smoking for various health outcomes, these utilization rates are of concern. With the advent of better detection methods and more effective adjuvant therapies, cancer survivorship has steadily increased, with an estimated 3.3 million female breast cancer survivors in the United States as of 2014 , descending from West Africans who, skilled in rice farming, were enslaved to work the South Carolina rice plantations in the 1700–1800's . The SIsThis analysis is part of a feasibility study of breast cancer among women in South Carolina, the first to compare three ethnically different groups: two AA ethnic groups, those without known SI ancestry (non-SIs) and those considered SIs; and EAs. For simplicity and to recognize the importance of investigating breast cancer disparities between AAs and EAs, we use the term “race/ethnicity” as we explore the differences and similarities among these three groups.Recognizing the implications for alcohol and tobacco use on survivorship, the primary purpose of this analysis was to characterize alcohol and tobacco use among women recently diagnosed with breast cancer across these three South Carolina racial/ethnic groups. Secondarily, we investigated whether patterns of use correlated with age or education (socioeconomic status and income were not available) and whether use within 6–21 months after diagnosis, as a surrogate for the years prior to diagnosis, correlated with cancer stage or tumor markers. We also compared alcohol consumption and cigarette smoking among our study sample with use in the general female population of South Carolina, of the same races (EA and AA) and age range as the study sample.This study was carried out in accordance with the US Department of Health and Human Subjects Policy for the Protection of Human Research Subjects. The protocol was approved by the IRBs of the Medical University of South Carolina (MUSC), and the South Carolina Department of Health and Environmental Control. All subjects gave verbal consent as allowed under the policies of the above IRBs, as the research presented no more than minimal risk of harm to subjects and involved no procedures for which written consent is normally required outside of the research context.Case ascertainment and data collection steps in this cross-sectional study are illustrated in the CONSORT diagram Figure . PotentiSCCCR study staff contacted each identified potentially eligible case by telephone after receiving passive physician approval [treating physician was asked to respond to investigators only to forbid contact with a potential subject ]. Women Race/ethnicity of each participant was categorized based on that of parents and grandparents as reported in the MUSC interview: EA if the candidate considered all four grandparents to be of European origin, or AA if all four grandparents were AA. Among AAs, the study candidate was sub-classified as Sea Islander (SI) if (a) she considered herself to be a SI, coming from the SI geographic region of South Carolina , and (b) either all four AA grandparents were born in this region or, in cases where the birthplace of all four grandparents was not known, at least both AA parents were born in this region. Women who did not meet these definitions, for example women of mixed race or unknown ancestry, or who reported Asian or Hispanic ancestry, were excluded from the study. Thus, this study included only Non-Hispanic EA and AA women.The geographic definition of the SI region was established by researchers of the Sea Islander/Gullah people , 39, andThe SCCCR provided data on age at diagnosis, race and breast cancer characteristics . Trained MUSC interviewers administered a short telephone interview with each participant to verify date of birth and obtain self-reported race, ethnicity, education, height and weight, plus alcohol consumption and cigarette smoking during the past 30 days.Breast cancer estrogen receptor (ER) and progesterone receptor (PR) expression were categorized as “negative” if reported in the SCCCR data as “negative” or “borderline.” HER-2 expression was categorized as negative if reported as “negative,” “borderline,” or “within normal limits.” Tumors negative for all three markers were labeled triple-negative.Alcohol consumption and cigarette smoking during the past 30 days were ascertained using questions selected from the Centers for Disease Control and Prevention (CDC) 2010 Behavioral Risk Factor Surveillance Survey (BRFSS) Figure . The BRFPublished CDC guidelines were used to characterize alcohol and tobacco use , 46, wheTobacco use (cigarettes) was defined as “yes” if the participant reported having smoked at least 100 cigarettes during her lifetime . SmokersTo assess how representative our study population was of incident breast cancer cases statewide, age at diagnosis and disease stage were compared to SCCCR data for all invasive cases (of known stage) diagnosed during 2011–2012 among non-Hispanic EA and AA women of the same age range as study participants. In addition, educational attainment, alcohol and tobacco use among study participants were compared with 2012–2013 South Carolina BRFSS data for women of the same age range as the study participants . These data represent the entire female population, and are not restricted to women with breast cancer. Note that AA ethnicity is not available in BRFSS data.t-tests, Wilcoxon rank sum and Kruskal-Wallis H non-parametric analysis for continuous data as appropriate, and chi-square or Fisher exact tests for categorical data. Simple linear and logistic regression modeling techniques were used to investigate associations between alcohol consumption, tobacco use, age, and cancer characteristics. Age at interview was used in analyses of self-reported data. For comparison of breast cancer characteristics with population-based state-level data, age at diagnosis was used. Statistical analyses were conducted using STATA 10.1 , and 86 and 81% respectively of these completed the MUSC interview (p = 0.36).The analytic study sample was derived from 365 potential candidates identified from the SCCCR by registry staff  exceeding our target. One SI was later determined to be ineligible, resulting in 29 SIs in the final analytic sample. EA telephone interviews were continued until SI recruitment was complete (n = 42).Ascertainment of SIs presented specific challenges, as AA ethnicity is not recorded in the SCCCR. We therefore oversampled AAs, focusing on the coastal region, until reaching the target sample size of 30 participants per racial/ethnic group. This resulted in the non-SI AA sample , significantly different from EAs and SIs; and least likely to have estrogen receptor expression (ER) positive cancer, significantly different from EAs only. Among SIs, cancer stage, ER, PR and triple-negative status  were more similar to EAs than non-SI AAs, an unexpected finding Table .p-values each 0.038). About 9% (non-SIs) to 12% (EAs) consumed more than one glass per day when drinking, not different among or between racial/ethnic groups. Heavy drinking (more than one drink per day on average during the past 30 days) was rare, reported by only two of the 137 study participants. Binge drinking (consuming four or more drinks on any given day) was reported by 10% of both EAs and SIs, and 3% of non-SI AAs. Neither heavy nor binge drinking differed significantly among or between ethnic or racial groups.A minority of participants self-identified as consuming alcohol Table , a practp < 0.001), 11 years younger among non-SI AAs (p = 0.010), and 5 years younger among SIs (p = 0.283). Alcohol use was two to three times more prevalent among women with a college degree, a non-significant trend seen in EAs and non-SI AAs but not among SIs  or non-SI . However 95% confidence intervals were very wide even with all AAs combined, reflecting small cells, and so these findings should be interpreted with caution. Alcohol consumption was not consistently or significantly associated with tumor ER, PR, or triple-negative status in any racial/ethnic group (data not shown).Late stage disease  was significantly associated with consuming alcohol Table , specifip = 0.026 and 24% of SIs, p = 0.047). In contrast, only 12% of participants reported current use of cigarettes , with no significant differences by racial/ethnic group. As with alcohol consumption, current smoking was less common among older women of each race/ethnicity although not statistically significant (Table p = 0.010), a trend observed but not significant within each racial/ethnic group. No significant or consistent associations were observed between current smoking and cancer stage, or ER status.Ever smoking Table  was repont Table . Women wp = 0.070) or SIs , reflecting the higher use of alcohol than cigarettes. One third to one half of current smokers  also consumed alcohol, but very few participants reported this double exposure .Consuming alcohol and/or currently smoking cigarettes was more prevalent among EAs (50%) than non-SI AAs , regardless of SI ancestry, to report consuming alcohol in the past 30 days: 40% of EAs, 24% of non-SIs and 21% of SIs. Moderate consumption  was also significantly higher among EAs than AAs, comprising one-half to one-third of drinkers respectively, while about 10% of each group consumed more than one drink per day on such days. Similar racial differences have also been found in other work, including the Carolina Breast Cancer Study of breast cancer survivors in North Carolina  among AAs only, regardless of SI ethnicity. While these associations have wide confidence intervals, this observation suggests that alcohol consumption may bear further investigation as a contributor to racial disparities in breast cancer risk.Smoking is associated with a 2-fold higher rate of dying from breast cancer compared to never smoking , as wellIn our study, 14% of EAs, 14% of non-SIs and 7% of SIs (no significant differences) reported current smoking . This is somewhat lower than reported for women in North Carolina with recently diagnosed breast cancer (22% of EAs and AAs), but consistent with their finding of no racial difference in current smoking . In our In the last few years through large studies and meta-analyses, cigarette smoking, whether active or passive, has emerged as conferring moderate risk for breast cancer , 69, theOur study is the first to use a statewide sampling approach to investigate alcohol use and cigarette smoking among women of South Carolina with recently diagnosed breast cancer, and to specifically include Sea Islanders. Based upon comparison with all SCCCR breast cancer cases, our EA study sample included fewer cases with late stage disease than expected, suggesting a possible EA recruitment bias toward early stage disease; this pattern was not seen among AAs combined as a single group. However, with no similar studies of SIs for comparison and SI ethnicity not recorded in the SCCCR, we cannot know whether our study sample reflects age and disease characteristic typical of this AA subgroup.As with any study relying on self-reported behavioral data, there are some limitations. There is potential for recall bias if respondents found it difficult to remember and estimate the number of alcoholic drinks consumed in the past 30 days, and number of days involved. Some women may also have under-reported their consumption . Our data for alcohol and tobacco use were obtained at between 6 and 21 months of diagnosis. We do not know whether or how these behaviors may have changed since diagnosis or may change again while women continue treatment and enter the “survivor” phase. To the extent that alcohol use may impact breast cancer stage at diagnosis and/or subsequent recurrence and survival, if prevalence and level of consumption were under-reported our data under-estimate the seriousness of our findings.This is the first study to investigate breast cancer among the Sea Islanders, a unique African American ethnic group, estimating differences in alcohol and tobacco utilization among three racial/ethnic groups in South Carolina. It is an exploratory feasibility study, obtaining cases from the SCCCR, rather than a hospital-based design, in order to obtain a state-wide representative sample of patients including SI patients. It provides a basis for further investigations among AA ethnic groups, toward better understanding of racial and ethnic disparities in breast cancer (and possibly other) outcomes. Differences and similarities between and across racial/ethnic groups are presented as a first estimate, not as a definitive statement, and confidence intervals reflect sample sizes. We acknowledge that sample sizes of EAs, and particularly SIs, were relatively small in comparison to the number of non-SI AAs. However, that statistically significant differences were found even with these relatively small sample sizes suggests that differences in breast cancer characteristics and patterns of alcohol and cigarette use between AA subgroups do bear additional scrutiny.We have described patterns of alcohol and cigarette use among recently diagnosed invasive breast cancer cases belonging to the three major racial/ethnic groups of South Carolina: EAs, and AAs with and without Sea Island ancestry.In our statewide sample we found that race-specific patterns of alcohol consumption and cigarette use were similar to or perhaps lower than those in the general South Carolina population, with EAs more likely to consume alcohol than AAs. However, the association between tumor stage and alcohol use, among AAs, is suggestive and differential effects of these exposures on breast cancer risk as well as survival among the racial/ethnic groups cannot be ruled out.Although moderate alcohol use and frequency of consumption were greater among EAs than AAs, heavier consumption and binge drinking were similar among all groups. In general, alcohol consumption was more common among younger women, in whom breast cancer is often of poorer prognosis. Cigarette smoking was infrequent in every group, but 50% of EAs, 32% of non-SI AAs, and 24% of SIs used one or both products. Given the carcinogenic effects of alcohol, the deleterious health impacts of frequent moderate (or greater) alcohol consumption and of smoking, the known and potential impacts on cancer outcomes and survival, and the potential for differences in alcohol effects on either incidence or survival according to genetic heritage, we recommend that women (and men) with breast cancer be educated and actively assisted in reducing or eliminating these exposures.AA and RK: co-primary investigator, study development and management; CB and HV: participant interviews; CM: case identification and recruitment; DB, KK and TH: study and data management; DH: case identification and recruitment, cancer data; JC: study development, data analysis and interpretation, manuscript preparation; MF: primary investigator, study development and management, manuscript preparation; SB: cancer registry interface, case identification and recruitment, cancer data; VB: hypothesis development, participant interviews, manuscript preparation.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer DD and the handling Editor declared their shared affiliation.


Breast cancer ranks first in women, and is the second cause of death in this gender. In addition to genetics, the environment contributes to the development of the disease, although the factors involved are not well known. Among the latter is the influence of microorganisms and, therefore, attention is recently being paid to the mammary microbiota. We hypothesize that the risk of breast cancer could be associated with the composition and functionality of the mammary/gut microbiota, and that exposure to environmental contaminants  might contribute to alter these microbiota.We describe a case-control clinical study that will be performed in women between 25 and 70 years of age. Cases will be women diagnosed and surgically intervened of breast cancer (stages I and II). Women with antecedents of cancer or advanced tumor stage (metastasis), or who have received antibiotic treatment within a period of 3 months prior to recruitment, or any neoadjuvant therapy, will be excluded. Controls will be women surgically intervened of breast augmentation or reduction. Women with oncological, gynecological or endocrine history, and those who have received antibiotic treatment within a period of 3 months prior to recruitment will also be excluded. Blood, urine, breast tissue and stool samples will be collected. Data regarding anthropometric, sociodemographic, reproductive history, tumor features and dietary habits will be gathered.Metabolomic studies will be carried out in stool and breast tissue samples. Metagenomic studies will also be performed in stool and breast tissue samples to ascertain the viral, fungal, bacterial and archaea populations of the microbiota. Quantitation of estrogens, estrogen metabolites and EDCs in samples of serum, urine and breast tissue will also be performed.This is the first time that the contribution of bacteria, archaea, viruses and fungi together with their alteration by environmental contaminants to the risk of breast cancer will be evaluated in the same study. Results obtained could contribute to elucidate risk factors, improve the prognosis, as well as to propose novel intervention studies in this disease.NCT03885648, 03/25/2019. Retrospectively registered.ClinicalTrials.gov  The trial is currently in progress. Enrolment of patients and analysis of data continues.14 bacteria and several archaea, eukaryotes and virus , parabens , benzophenones  will be determined. Final concentrations will be adjusted for urinary creatinine levels (mg/dl), to account for both urine dilution and body composition, as previously reported , 32.Concentrations of estrone, estradiol and 13 estrogen metabolites  will be determined in fasting spot urine samples, adjusting for urinary creatinine levels (mg/dL). The quantitation of urinary estrogens will be assessed by gas chromatography tandem mass spectrometry using a triple quadrupole analyzer as previously described with minor modifications , 34. BriParticipants’ anthropometric, sociodemographic and reproductive features will be recorded. They will also grant permission to access their clinical history.Age, race, weight, height, residence area , marital status, education, current working activity, social class, smoking habits , and alcohol consumption , will be recorded.Age of menarche and menopause status , number of pregnancies, number of sons, age at the first and last pregnancy, total duration of breast feeding, use of hormonal contraceptives and/or substitute hormonal therapy (age at beginning and duration).Type and hystological grade according to the International Classification of Oncological Diseases (CIE-0-2); tumor stage: clinical and anatomopathogical TNM ; hormone receptors (estrogens and progesterone); HER2, and tumor markers .Participants will answer two questionnaires: adherence to the Mediterranean diet and frequency of food consumption.U-Mann de Whitney. Intestinal and mammary microbiota clusters will be calculated by an analysis of principal components made with the bioinformatic data. Those data will be normalized between 0 and 1, and the Euclidean distance will be evaluated. A permutation ANOVA (PERMANOVA) will be carried out with the PRIMER 7 software. Finally, a tree diagram will be built for each evaluated group based on the different taxonomic scales.Relative abundance of the microbes will be expressed as median ± range. Differences among microbes will be calculated by the p-value 0.05 will be considered statistically significant. A one-way ANOVA, assuming homogeneity of variance, will be used to determine whether at least two unknown means are all equal or at least one pair of means is different. In case that the variances were unequal, a Welch-ANOVA will be performed. The false discovery rate  will be calculated to take into account the multiple comparisons that normally occur in metabolomics-based studies, thus estimating the reliability of the results. A q-value 0.1 will be considered statistically significant.For metabolomic statistical analysis and data display purposes, any missing values will be assumed to be below the limits of detection, and these values will be imputed with the compound minimum . The data will be tested for variance homogeneity, and if there were unequal variances, the data will be log-transformed. The statistical analysis of the data will be performed using Array Studio  and proprietary software from Metabolon. A t-test for equality of the means will be carried out between the intestinal and mammary microbiota and for each metabolite to determine differences. A Random forest (RF) is a supervised classification technique based on an ensemble of decision trees  with sevParticipants will be grouped into tertiles of urinary EDC levels based on their distributions among the controls. Odds ratios and 95% confidence intervals (CIs) for breast cancer comparing the second and third tertiles with the first tertile will be estimated using logistic regression models. Further, associations of participant characteristics with urinary EDC levels, estrogens and estrogen metabolites and fecal microbiome measures will be evaluated by using general linear models and testing either for differences across categories or for trends across categories. Linear regression models will also be used to evaluate associations of each steroid measure with measures of the diversity of the fecal microbiome, abundance and with taxonomic groups at phylum and family levels, adjusting by covariates.ClinicalTrials.gov dealing with breast cancer and microbiota, 2 already completed and 4 currently ongoing. Of the 2 completed studies, one investigated the antibiotic profilaxis in oncological surgery of the breast, and the other investigated the relationship between intestinal bacteria and breast cancer risk. As for the studies in progress, these are trials investigating various intervention strategies , the effects of gut microbiome on the neoadjuvant chemotherapy-induced immunosurveillance in triple negative breast cancer, or the effects of chemotherapy on gut bacteria in newly diagnosed breast cancer. Our study is a case-control clinical trial that aims at ascertaining the connection relating i) the composition of both gut and breast microbiota, ii) the functionality of both gut and breast microbiota, and iii) the exposure to environmental contaminants with the risk of developing breast cancer. To the best of our knowledge, it is the first study undertaking the simultaneous analysis of the microbiota of the mammary tissue and the intestine, and also the first attempt to link the microbiome with the EDC load and the risk of this disease.There are 7 studies registered in The microbiota is affected by either modifiable and unmodifiable factors such as genetics, stress, diet, physical activity, lactation, delivery mode, antibiotic treatment, smoking, age, and alcohol consumption, among others . For thiThe hypothesis of this study is that the risk of breast cancer could be associated with the composition and functionality of the mammary and/or intestinal microbiota. The hypothesis is supported by preliminary studies which suggest that the microbial pattern of women with breast cancer is different than that of healthy women, not only with regards to bacterial types and relative abundance, but also with their functionality  , 37–39. Validation of the hypothesis could translate into new recommendations and guidelines of clinical practice to improve prevention and prognosis of breast cancer, alleviating the burden of this disease. Likewise, a better identification of those patients most likely to efficiently respond to treatment could derive, given the fact that efficacy of immunotherapy against cancer depends on patients’ intestinal microbiota , 43. Fin