Mammographic density (MD) is one of the strongest breast cancer risk factors. Its age-related characteristics have been studied in women in western countries, but whether these associations apply to women worldwide is not known.I2) was 16.5%. Among premenopausal women, the √PD difference per 10-year increase in age was −0.24 cm , reflecting a compositional change . In postmenopausal women, the corresponding difference in √PD  was additionally driven by increasing breast area. The study is limited by different mammography systems and its cross-sectional rather than longitudinal nature.We examined cross-sectional differences in MD by age and menopausal status in over 11,000 breast-cancer-free women aged 35–85 years, from 40 ethnicity- and location-specific population groups across 22 countries in the International Consortium on Mammographic Density (ICMD). MD was read centrally using a quantitative method (Cumulus) and its square-root metrics were analysed using meta-analysis of group-level estimates and linear regression models of pooled data, adjusted for body mass index, reproductive factors, mammogram view, image type, and reader. In all, 4,534 women were premenopausal, and 6,481 postmenopausal, at the time of mammography. A large age-adjusted difference in percent MD (PD) between post- and premenopausal women was apparent  and appeared greater in women with lower breast cancer risk profiles; variation across population groups due to heterogeneity (Declines in MD with increasing age are present premenopausally, continue postmenopausally, and are most pronounced over the menopausal transition. These effects were highly consistent across diverse groups of women worldwide, suggesting that they result from an intrinsic biological, likely hormonal, mechanism common to women. If cumulative breast density is a key determinant of breast cancer risk, younger ages may be the more critical periods for lifestyle modifications aimed at breast density and breast cancer risk reduction. Valerie McCormack and colleagues reveal reduced breast density with increased age in women from different ethnic groups; however increased breast density in young women is a cancer risk. Breast density, a measure of the amount of dense to fatty tissue in the breast, is a strong marker of breast cancer risk.Breast density determinants have been studied in high-income countries, but not in women worldwide.We studied how breast density differed by age and menopausal status in diverse groups of women from 22 countries worldwide.For over 11,000 women, mammograms were read centrally and risk factor data harmonised.We found that, regardless of the country and ethnic group of women, breast density was much lower in postmenopausal than in premenopausal women of the same age.Additionally, as a relative proportion of breast area, breast density was lower in older women both among premenopausal and postmenopausal women. Among premenopausal women, breast density changed with age without an increase in breast area, but among postmenopausal women, the latter also increased.That this change in breast density with age is seen internationally suggests that the change is due to a universal biological mechanism inherent to all women.If cumulative breast density is a key determinant of breast cancer risk, younger ages may be the more critical periods for lifestyle modifications aimed at breast density and breast cancer risk reduction. Mammographic density (MD), a measure of the amount of radiopaque fibroglandular as opposed to fat tissue in the breast, is amongst the strongest of breast cancer risk factors –3. ParalMD associations with ageing have been examined in longitudinal studies –12 and iThe International Consortium on Mammographic Density (ICMD) is an international pooling consortium of cross-sectional individual-level epidemiologic and MD data on over 11,000 breast-cancer-free women from 22 diverse countries. In this consortium, we examined differences in MD by menopausal status and age across 4 decades of life.Ethics approvals for ICMD were obtained from the International Agency for Research on Cancer (IEC 12–34). Each individual participating study had received local ethical approval at the time of the original conduct of the study and again to contribute to the consortium.n = 180). An additional 10% (rounded to n = 20) was added to account for potential later exclusions . Population groups were categorised into broad ethnic groups as follows: (i) East Asian , (ii) mestizo (Mexican and Chilean) and Hawaiian, (iii) South Asian , (iv) white (European and of European descent), (v) Eastern Mediterranean  and (vi) black . Mammograms were originally taken as part of organised screening (n = 13 studies), opportunistic or community-based screening (n = 8), mammography trials (n = 3), or research (n = 3). We also extracted the best estimate of the age-standardised incidence rate  for breast cancer from Cancer Incidence in Five Continents, GLOBOCAN, or used another estimate [The ICMD methodology and contributing studies are discussed in detail elsewhere . In brieestimate ,18 for e2), ideally obtained at the time of mammography. For menopausal status, study-specific definitions were used, as provided in n = 7 studies) or no periods for the past 6 or 12 months (n = 15), self-reported postmenopausal (n = 3), or a combination of age, menstruation, hormone replacement therapy (HRT), and hysterectomy/oophorectomy history (n = 2). Perimenopausal women were excluded from ICMD sample selection in 10 studies, were not defined separately in 13 studies, and were included and categorised separately in 4 studies . For consistency, the latter were reclassified as premenopausal for analyses. Menopausal variables were ascertained at or after mammography for 22 studies. For 4 of the remaining studies, menopausal status was assumed not to have changed as it was ascertained less than 1 year before mammography, on average. For 1 study, in which risk factors were ascertained via questionnaire an average of 2.8 years before mammography, a premenopausal woman at the time of the questionnaire was considered postmenopausal at the time of mammography if her age at mammography exceeded the study’s mean age at menopause.ICMD harmonised data from each study on sociodemographic and lifestyle factors, including height and weight to calculate body mass index , women with no BMI data (n = 2) or with extreme BMIs , 11,423 women were included, 11,232 of whom had PD data, 11,375 dense-area readings, and 11,184 non-dense-area and breast-area readings. Differences in the numbers of women with different MD metrics arose because, in some mammograms, dense area could be estimated but the breast edge was not visible , and, for 78 images from 1 study, PD could be estimated, but uncertainties in the original pixel size prevented the calculation of absolute areas.After excluding poor-quality images and suspected tumours , but the same change in √PD of 1 from 7 to 8 is, on the original scale, an increase from 72 to 82, or an absolute increase of 15 (from 49 to 64). To aid the interpretation on the square-root scale, √MD can be interpreted by considering areas as squares, thus regression model beta-coefficients represent differences in the width, in centimetres, of the side of the square. Similarly, as PD (percent) is the dense area per 100 cm2, √PD is the width of a dense square within a 10 cm × 10 cm square, and therefore beta-coefficients for √PD represent differences in the dense square width, within a 10 cm × 10 cm square.We analysed PD and dense, non-dense, and breast area after square-root transforming each measure to improve normality of residuals. The use of the square-root transformation of MD in regression models means that absolute differences in areas are smaller at the lower end of the PD range. For example, an increase in √PD from 4 to 5 (change in √PD of 1) is, on the original scale, an increase from 4I2 statistic [We examined cross-sectional differences in √MD measures by age and menopausal status using 2 approaches. First, we examined associations by population group and combined estimates using a random effects meta-analysis. Population group estimates were obtained from a multi-level linear regression model to account for repeat MD readings between readers and between batches for the same woman. The percentage of variation in regression estimates across population groups that was due to heterogeneity was examined using the tatistic , for whiInteractions of age and menopausal status with demographic and lifestyle factors were tested using likelihood ratio tests. We also examined effect modification by ‘breast area for BMI’, a proxy for a woman’s breast size independent of her BMI, which we generated as the residual of the regression of √breast area on BMI (linear and quadratic terms) and mammography view. Sensitivity analyses excluding women with very early or late menopause, those under 40 or over 70 years, and women with self-reported versus measured BMI were also conducted.The 11,423 ICMD women ranged in age from 35 to 85 years at mammography, with at least 500 women in each 5-year age category from 35 to 70 . Mean agI2 = 16.5%) and dense (I2 = 26.5%), non-dense (I2 = 0%), and breast area (I2 = 0%) . The findings from the pooled analyses closely matched the meta-analytic results, but confidence intervals (CIs) were narrower  Figs  and S6A.r Tables : the √PDr Tables .p = 0.11, 0.04, 0.08, 0.005, and 0.06, respectively; 2, whilst these women tended to have the smallest menopause-associated differences in PD . These associations reflect similar inverse √dense area–age associations . However, whereas in premenopausal women PD differences occurred without a difference in breast area, in postmenopausal women √breast area was 0.34 cm  larger per 10-year age increase (I2 ~ 30%) and across ASR categories; in postmenopausal women, all point estimates were negative.Meta-analyses  and poolincrease . PD–age p for interaction = 0.045; p = 0.007) and not with non-dense or breast area . Additionally, among premenopausal women, there was some evidence that the inverse √dense area–age association was stronger in nulliparous than parous women , and whilst there were no differences by ethnicity in premenopausal women, in postmenopausal women the PD–age slope was shallowest for black women (ck women .p = 0.42), dense area (p = 0.90), and breast area (p = 0.09) in premenopausal women and for all 4 MD measures in postmenopausal women , thus suggesting that there is no plateauing of MD within this age range. For non-dense area in premenopausal women, a fractional polynomial model had a better fit than a linear model (p = 0.008), as the positive association with age was not seen until around age 45 years. In sensitivity analyses, the PD–age association in premenopausal women was attenuated from −0.24 to −0.18 if older premenopausal women (>50 years) were excluded, and postmenopausal PD–age associations were stronger (increased from −0.38 to −0.47) when women over age 65 years were excluded (estimates are provided here and do not appear in tables).Further examination of MD–age associations using the best-fitting flexible fractional polynomials revealed that such non-linear models were not a better fit than the simplest linear models for PD  to analyse the impact of age-adjusted years since menopause, which was independently associated with √PD , an effect that was present up to 15 years after menopause . After a2, equivalent to 15 to 20 years of ageing. This difference in PD between post- and premenopausal women of the same age was present up to 15 years after the menopause and may be greater in women with lower breast cancer risk profiles . PD also decreased with increasing age both among premenopausal and postmenopausal women. In premenopausal women, these declines were entirely due to breast compositional changes, i.e., due to a decline in dense area and an equal but opposite increase in non-dense area. However, in postmenopausal women, PD reductions were also accompanied by increasing breast area and continued beyond 70 years of age.Across diverse populations of breast-cancer-free women worldwide, we assessed how MD is related to age and menopausal status. Overall, despite inevitable differences between contributing studies, we found consistency in the direction of associations of age and menopausal status with PD and its component tissues across ICMD women. Assuming that inferences from these cross-sectional data reflect within-woman changes, the greatest reduction in MD occurred upon menopausal transition, when dense area declined from a mean of 16.0 to 12.5 cmThe large decrease in MD at menopause after adjusting for age is largely consistent with previous observations in westernised countries, either from within-woman or between-woman comparisons –10,12,15Comparisons of age-related changes have been more variable. In ICMD, we found no strong evidence of different PD–age or dense area–age slopes in pre- and postmenopausal women, in agreement with the full longitudinal data from 1 of the ICMD studies, the Melbourne Collaborative Cohort Study/Australian Breast Cancer Family Registry , but difThe remarkable consistency of the age and menopausal effects on MD across diverse female populations spanning all continents suggests that these associations reflect a biological process common to all women. The extent of the decline in MD may be modified by ‘external’ factors, such as reproductive or other lifestyle or environmental factors. These observations lend credibility to the hypothesis that the sharp decline in MD over the menopause is a phenotypic marker of the decline in the rate of breast tissue ageing , which rr = 0.18).At a systemic level, a hormonal pathway is most certainly implicated in MD changes that occur during the menopausal transition. Several reproductive hormones decline at different stages of the transition , some ofThe present study is greatly enhanced by the heterogeneity of the study populations included in ICMD, in terms of a wide range of BMI values, reproductive characteristics, ages (40-year age range), and ethnicities and their associated range of breast sizes and composition, making this, to our knowledge, the largest multi-ethnic, multi-country study of MD to date. The consistent findings are likely to reflect intrinsic biological processes and should therefore apply to the general population of women worldwide. Our separate analyses of tissue components revealed important differences in the drivers of changes in breast tissue composition at different life stages. However, inherent to the consortial nature of ICMD is the fact that we relied on existing data; thus, some sample sizes were smaller, not all studies included women spanning the full age range, and there is variability in image types and exposure variable definitions. Menopause was included as binary variable due to the limitations of the data, but may occur over many months or years. The definition of menopausal status also varied, from simple self-reports to complex algorithms, measured at or some time before or after mammography. Potential misclassification bias might attenuate the estimate of the menopausal effect but is unlikely to affect within-population group estimates of the menopause difference. Additionally, including some perimenopausal women would also underestimate a menopausal effect. In the 31% of women with self-reported anthropometry, possible underreporting of weight and overestimation of height, particularly in older women, would lead to an underestimation of BMI [Women in ICMD were recruited from a range of settings, including some that were not population-based screening; thus, there is likely an overrepresentation of symptomatic or high-risk women. Nevertheless, the present findings rely on the representativeness of the associations and not of the sample populations; thus, any lack of representativeness of study populations would affect results only if there was an age-related pattern to representativeness. In a similar manner, cross-sectional associations may only partially reflect within-woman changes, as birth cohort effects on MD, through factors unadjusted for, may confound associations. These findings should be verified with longitudinal data in which within-woman changes can be examined.There are broader implications of the profile of MD with ageing. Similar to the reduced sensitivity of mammography in younger women than in older women in organised screening programs , becauseFinally, based on the current findings that MD is in general highest earlier in life, primary prevention efforts might best be targeted to younger ages, reducing breast density earlier in life, leading to a lower cumulative MD across life. Studies of breast density in girls or younger women that use MRI or dual-energy X-ray absorptiometry (DXA) imaging are fewer. They have found suggestions of increased breast density associated with greater birth size , duratioS1 Fig(DOCX)Click here for additional data file.S2 Fig(DOCX)Click here for additional data file.S3 FigCurves are crude associations (no adjustment for BMI or any other factors).(DOCX)Click here for additional data file.S4 FigAssociations of square-root dense area (cm), by population group, with (a) menopausal status, (b) age in premenopausal women, and (c) age in postmenopausal women, meta-combined overall and by low, medium, and high breast cancer incidence rate in the source population.(DOCX)Click here for additional data file.S5 FigAssociations of square-root breast area (cm), by population group, with (a) menopausal status, (b) age in premenopausal women, and (c) age in postmenopausal women, meta-combined overall and by low, medium, and high breast cancer incidence rate in the source population.(DOCX)Click here for additional data file.S6 FigAssociations of square-root non-dense area (cm), by population group, with (a) menopausal status, (b) age in premenopausal women, and (c) age in postmenopausal women, meta-combined overall and by low, medium, and high breast cancer incidence rate in the source population.(DOCX)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.S1 Text(DOCX)Click here for additional data file.S1 STROBE Checklist(DOC)Click here for additional data file.


Breast cancer patients are at an increased risk of venous thromboembolism (VTE). However, current evidence as to whether VTE increases the risk of mortality in breast cancer patients is conflicting. We present data from a large cohort of patients from the UK and pool these with previous data from a systematic review.Using the Clinical Practice Research Datalink (CPRD) dataset, we identified a cohort of 13,202 breast cancer patients, of whom 611 were diagnosed with VTE between 1997 and 2006 and 12,591 did not develop VTE. Hazard ratios (HR) were used to compare mortality between the two groups. These were then pooled with existing data on this topic identified via a search of the MEDLINE and EMBASE databases (until January 2015) using a random-effects meta-analysis.Within the CPRD, VTE was associated with increased mortality when treated as a time-varying covariate , however, when patients were permanently classed as having VTE based on presence of a VTE event within 6 months of cancer diagnosis, no increased risk was observed . The pooled HR from seven studies using the second approach was 1.69 (1.12–2.55), with no effect seen when restricted to studies which adjusted for key covariates.A large HR for VTE in the time-varying covariate analysis reflects the known short-term mortality following a VTE. When breast cancer patients are fortunate to survive the initial VTE, the influence on longer-term mortality is less certain.The online version of this article (10.1186/s12885-017-3719-1) contains supplementary material, which is available to authorized users. Breast cancer is the most common type of cancer amongst women worldwide accounting for approximately 1.67 million new cases and 522,000 deaths in 2012 .It is reported that breast cancer patients are 3–4 fold more likely to develop VTE compared with patients of equivalent age without cancer . Our recVTE associated with breast cancer is a devastating complication, which occurs among women with an otherwise good health prognosis. By establishing the extent to which a VTE influences prognosis, especially longer-term, the implications of both prophylactic and therapeutic anticoagulation on preventing mortality can be more fully understood. We therefore present new data from a UK based cohort study and pool this with existing published and unpublished data in a systematic review and meta-analysis to assess the risk of mortality in breast cancer patients with VTE compared to those without VTE.A summary of this was work previously published as a poster at the National Cancer Research Institute conference in 2015 , highlighting that the risk of mortality in breast cancers due to VTE was non-significant when adjusted for important covariates including age, stage and comorbidity (or performance status)  compared to the 2 studies which defined VTE before cancer diagnosis [HR 1.63 (95% CI 0.64–4.13)] , the pooled hazard ratio was 2.35 (2.17–2.55) for studies using a TVC analysis and 1.69 (1.12–2.55) for those using an nTVA, the latter of which contained substantial heterogeneity. The hazard ratio we report for TVC analysis is comparable to that reported by Posch et al. more recently of 2.98 (2.36–3.77) using a multi-state model applied to data from the Vienna Cancer and Thrombosis Study which considered all cancer types rather than breast cancer specifically . Sub-groTo our knowledge, this is the first attempt to systematically evaluate all available data exploring whether or not among women with breast cancer, the risk of mortality is raised following development of a VTE. Our systematic review was strengthened by inclusion of two established databases (MEDLINE and EMBASE) with carefully selected search terms. Furthermore, through obtaining additional data for studies originally published in the form of conference abstracts, we were able to include data which is currently unpublished in our synthesis of the evidence. Thirdly, by inclusion of our data from the CPRD we were able to include data in the overall synthesis which has the strength of utilizing recently linked primary, secondary and cancer registration data from a large representative sample of women from the UK. Our two distinct approaches to analysis, enabled us to assess the effect of a VTE on short-term and long-term mortality separately.Limitations of our work include the fact the methods of meta-analysis employed in our systematic review relied on survival data being presented both separately for breast cancer patients in studies where patients with a mixture of cancer types were reported, and also in an appropriate numerical form so that hazard ratios  from these could be obtained. As such there were several potentially relevant studies which have been conducted but which we were unable to include. Our systematic review also contained a high degree of heterogeneity, meaning that it was not possible for us to determine the “true” degree which developing a VTE has on subsequent mortality. Instead effect sizes would be influenced by characteristics of the study population , methods for establishing VTE (including whether methods such as a Doppler scan were used to confirm the diagnosis) and duration of follow-up. In part, we were successful in elucidating specific reasons for this heterogeneity, namely that our finding in the CPRD that effect sizes were attenuated considerably after adjustment for key covariates was also demonstrated within one of the papers included in our systematic review . HoweverDifferences in methodological quality of original studies represent another potential source of heterogeneity in reviews of observational studies as addressed by the sub-group analyses described above. Similarly, methodological deficiencies in some or all of the component studies could bias estimates of the pooled result. Many of the source studies relied on routinely collected administrative data for determining VTE status in study participants. Misclassification of VTE events could attenuate the magnitude of an association between VTE and survival. In the CPRD, our algorithm for defining VTE was previously shown to have positive predictive value of 84% when compared with more detailed investigations of patient records . HoweverThe potential for immortal time bias was avoided in both of the approaches to analysis we adopted for the CPRD data. The use of a time-varying covariate analysis incorporates changes in exposure status throughout the follow-up period and thus is sensitive to picking up changes in risk of outcome which occur shortly after a change in exposure status . This apFinally we were unable to clearly establish whether factors such as cancer stage and underlying health status may have influenced the extent to which a VTE is associated with the risk of mortality. Whilst HRs were larger for women with local disease at the time of diagnosis, given that the risk of mortality was considerably higher in women with metastatic disease (314 deaths in 1200 person-years of follow-up) than in women with local disease  this is likely to be due to the issue of scale dependence whereby there is the potential for VTE to have a greater impact on a measure of relative association (such as the hazard ratio) in subgroups where the underlying risk of an outcome event is lower .There are several mechanisms via which a VTE may exert a detrimental impact on cancer survival. There is an immediate impact due to the known high short-term fatality resulting from a thrombotic event which among all patients is estimated to be around 1% following a DVT and over 20% following a pulmonary embolism , 43. PooCancer patients are at increased risk of bleeding from anticoagulation, with an estimated 2-fold increased risk for major bleeding compared to non-cancer patients . UnsurprA further explanation for the detrimental impact of VTE on cancer survival relates to complex mechanisms underlying the symbiotic relationship between coagulation and tumour factors. Coagulation parameters are understood to play an important role in tumour progression and metastases, with changes in the haemostatic system evident in cancer patients even in the absence of a VTE . It is hWe report evidence that short-term mortality is raised in women with breast cancer following a VTE. However, when women are fortunate enough to survive their initial VTE event, the influence on mortality is far less certain due to considerable variability in results between individual studies. Future observational research on this topic should explore this heterogeneity by discovering whether there are specific groups of women with breast cancer for whom a VTE may exert a particularly poor prognostic effect, and for whom treatment strategies could therefore be influenced. Only with this knowledge along with more relevant data specific to women with breast cancer can we fully start to understand the true extent that deaths in breast cancer patients can be prevented by primary prophylaxis in those most at risk and whether presence of a VTE could influence cancer treatment strategies in these patients.Additional file 1:Medline and EMBASE search strategies. Search strategies employed for the systematic review presented in the second part of the Results section. (DOCX 13 kb)Additional file 2:Results from the CPRD  stratified by comorbidity score (Charlson). Additional results where key results from the paper, difference in mortality risk between women with and without a VTE, were stratified by underlying health status as defined by Charlson comorbidity score. Results are presented for the analysis where VTE was treated as a time-varying covariate. (DOCX 14 kb)Additional file 3:Influence of covariates on risk of mortality. Table showing the association with mortality for each of the covariates adjusted for in the CPRD analysis (non-time varying effect of VTE), with all other terms including VTE adjusted for. (DOCX 14 kb)Additional file 4:Characteristics of Included Studies. Detailed overview of all studies included in the systematic review. (DOCX 23 kb)


Older women have poorer survival from breast cancer, which may be at least partly due to poor breast cancer awareness leading to delayed presentation and more advanced stage at diagnosis. In a randomised trial, an intervention to promote early presentation of breast cancer in older women increased breast cancer awareness at 1 year compared with usual care (24 versus 4%). We examined its effectiveness in routine clinical practice.We piloted the intervention delivered by practising health professionals to women aged about 70 in four breast screening services. We measured the effect on breast cancer awareness at 1 year compared with comparison services, where women did not receive the intervention.p = 0.001). The components of breast cancer awareness were knowledge of breast cancer non-lump symptoms , knowledge of age related risk  and reported breast checking .At 1 year, 25% of women in pilot services were breast cancer aware compared with 4% in comparison services  on 3rd October 2007.The PEP trial was registered with the International Standard Registered Clinical/soCial sTudy Number (ISRCTN) as a clinical trial ( Women in the United Kingdom (UK) have poorer survival from breast cancer compared to other similar countries , 2. WhilThe Promoting Early Presentation (PEP) Intervention was developed to provide older women with the knowledge, motivation, confidence and skills to present promptly on discovering a breast symptom. It is a brief, scripted, one-to-one intervention delivered by a health professional in a positive, motivational and collaborative style and supported by a booklet , 7. In aWomen attending for their final invited screening appointment at four NHS breast screening services where the PEP Intervention was offered (pilot services) and at a comparison service where the PEP Intervention was not offered (comparison service) were invited to take part during May 2011 and April 2012. Recruitment is described in more detail elsewhere  and infoWomen completed a questionnaire before their mammogram. The questionnaire included a validated measure of breast cancer awareness . Women wWe excluded from the analysis women who reported being treated for breast cancer during that year. We included only women who had provided data at baseline and 1 year on all three relevant questions. We used women’s responses to the three breast cancer awareness questions to calculate a breast cancer awareness score (range 0-3). Women were considered breast cancer aware if they scored 3 out of 3, meaning that: they knew that risk of breast cancer increases with age (knowledge of age-related risk), could identify five or more non-lump symptoms of breast cancer (knowledge of non-lump symptoms) and reported checking their breasts at least once a month.To examine change in breast cancer awareness from baseline to 1 year, we used repeated measures logistic regression models. These logistic regression models  allow us to model the relationship between covariates of interest  and an outcome (breast cancer awareness) measured at multiple time points, accounting for the correlated nature of the data. These calculated odd ratios (ORs) with 95% confidence intervals (CI) for odds of being breast cancer aware (i.e. scoring 3 in the breast cancer awareness score) in women who received the PEP Intervention compared to those in the comparison service. We also carried our similar analyses for the three component questions of the breast cancer awareness score: for the odds of knowing the age-related risk of breast cancer and non-lump symptoms, and for breast checking at least once a month. We examined the effect on the odds ratios of controlling for differences in age, whether they had a husband/partner, age at leaving full-time education and Index of Multiple Deprivation (IMD), a score based on area of residence using data from a number of sources, which provides an estimate of socioeconomic deprivation.In the four pilot breast screening services, 356 women provided analysable breast cancer awareness data at 1 year, representing 72% of the 497 who completed the baseline questionnaire . Details of non-responders at 1 month are given in our previous paper . Those eIn the comparison services, 661 women provided analysable breast cancer awareness data, representing 75% of the 880 who completed the baseline questionnaire . We found no demographic differences between those included in the analysis and those not, although women who were excluded were less likely to be breast cancer aware at baseline.There were some demographic differences between women in the pilot and comparison services: women in the pilot services were slightly older, less likely to be living with a husband or partner, less socioeconomically deprived and more educated (described in more detail in our previous paper ).Women who received the PEP Intervention were significantly more likely to be breast cancer aware at 1 year than women in the comparison service (25 vs. 4%; Table An intervention to promote early presentation of breast cancer among older women delivered by NHS mammographers in routine clinical practice raises breast cancer awareness to a similar extent as in a research setting. All three components of breast cancer awareness were increased in women receiving the PEP Intervention when compared to the comparison service at 1 year. The most marked effect was seen in women’s knowledge of age-related risk, albeit knowledge was still much lower than for the other components of breast cancer awareness.The intervention was conducted at the final scheduled mammography appointment, so it is surprising that the level of awareness in women was in fact not higher than found. However, previous studies with older women have also found low levels of breast cancer awareness . An explSimilar increases in magnitude for women’s knowledge of age-related risk were found in the implementation of the PEP Intervention into routine clinical practice to those found in the RCT , which iThe high response rates and use of a validated measure of breast cancer awareness  are streThere were demographic differences between women in the pilot services and the comparison service. However, we think this is unlikely to explain our findings – controlling for this made little difference to the magnitude of the effect.We carried out the analysis only on those women with complete data at 1 year. The women who were excluded from this were less likely to have been breast cancer aware at baseline. This could have spuriously inflated differences in breast cancer awareness at 1 year between PEP Intervention and comparison services, but the differences are so striking that it is very unlikely to explain them fully.In a 2013 report, the All Party Parliamentary Group on Breast Cancer recommended that the PEP Intervention be more widely implemented so that the effect on breast cancer mortality can be evaluated  may ultiThe success of the intervention in a mammography setting has led to further adaptation of the intervention to enable it to be transferable to other settings such as general practice , to addiWomen who received the PEP intervention in routine clinical practice demonstrated similar levels of breast cancer awareness at 1 year as those women receiving the PEP intervention in a randomised controlled trial. Follow up showing the effect of this kind of intervention in routine clinical practice after 1 year is unprecedented. These findings can usefully inform future interventions aimed at promoting the early presentation of breast cancer in older women.


Background. Nearly 70% of women diagnosed with breast cancer in Ghana are in advanced stages of the disease due especially to low awareness, resulting in limited treatment success and high death rate. With limited epidemiological studies on breast cancer in Ghana, the aim of this study is to assess and understand the pattern of breast cancer distribution for enhancing early detection and treatment. Methods. We randomly selected and screened 3000 women for clinical palpable breast lumps and used univariate and bivariate analysis for description and exploration of variables, respectively, in relation to incidence of breast cancer. Results. We diagnosed 23 (0.76%) breast cancer cases out of 194 (6.46%) participants with clinically palpable breast lumps. Seventeen out of these 23 (0.56%) were premenopausal (<46.6 years) with 7 (0.23%) being below 35 years. With an overall breast cancer incidence of 0.76% in this study, our observation that about 30% of these cancer cases were below 35 years may indicate a relative possible shift of cancer burden to women in their early thirties in Ghana, compared to Western countries. Conclusion. These results suggest an age adjustment for breast cancer screening to early twenties for Ghanaian women and the need for a nationwide breast cancer screening to understand completely the pattern of breast cancer distribution in Ghana.  Cancer of the breast is the most common cancer in both developing and developed countries and is responsible for over one million in an estimated ten million neoplasms diagnosed in both sexes worldwide . Breast Despite these challenges, several general aspects of breast cancer burden in African women have been characterized including lower lifetime risk of developing breast cancer comparatively , 13 and In Ghana, breast cancer is a major public health problem and the most common type of cancer among women in terms of mortality and incidence . The incThis is a cross-sectional study in five regions of Ghana: Greater Accra, Volta, Ashanti, Western, and Brong Ahafo. The other five regions not included are Upper East, Upper West, Northern, Eastern, and Central. Region selection was based on (i) population density and accessibility, (ii) willingness of participants, (iii) limited resources, and especially (iv) proximity to treatment centres where suspicious cases could be referred to for further evaluation and treatment. Thus even though Upper East, Upper West, and Northern Regions occupy about 40.9% of the size of Ghana, the comparatively low population density scattered in clusters made accessibility and proximity to the few health facilities very difficult. Characteristics in Eastern and Central Regions are similar to those of Ashanti and Western Regions, respectively, so results in these two larger population dense regions can be extrapolated and representative.The study originated from the Ministry of Health and Ministry of Women and Children, Ghana, and had gone through and had been approved by the Ministries' Review Boards. Mammocare was granted authority to conduct the study and was required to organize an awareness talk, explain all procedures, and respond to participant's questions before the screening process. Discussions included the harmless procedural process, no coercion and ability to withdraw at one's own will, no invasion of privacy or involvement of deception, and absence of monetary rewards. After all these, only willing participants who picked and completed a consent form were included in the study. Members of the medical team that performed the clinical breast examination (screening) were in good standing with their respective boards at the time of the examination.Awareness creation and detailed explanation of procedures were launched and conducted in churches, mosques, schools, offices, and market places within the five selected regions between January 2007 and November 2008. Willing female participants ranging from 15 years to 74 years underwent clinical breast examination. As part of the screening, participants were guided to respond to questionnaires which captured information such as age, menarche, parity, family history of breast cancer, knowledge level, and perception of breast cancer and its symptoms. All participants with clinically palpable breast lumps were counselled by the medical team and then referred to the district or regional hospitals for confirmation and appropriate treatment. Even though the scope of this study was limited to patterns and incidence, follow-ups were made on the study participants with suspected cases. Applying the Raosoft sample size calculator approach using an incidence of 1% breast abnormality in the population and an absolute precision/confidence level of 0.5% with a design effect of 1.0 for random sample, a total sample size of 3000 women can be used as a true representation of the population in the five regions. In achieving our target number, we did our best to cover most districts in the regions in order to capture a wider distribution of the population.All cases of suspicious palpable lumps were referred to the Regional Health Facilities. Here procedures such as mammography or ultrasonography were applied depending on age. This was followed by fine needle aspiration cytology and tissue histopathology for confirmation of the palpable masses as benign or cancerous.P < 0.005. The results from Pearson's Chi-squared test were used for inferential analysis.Two levels of data analyses were conducted on the acceptable questionnaires. At the first level, univariate analysis was performed to provide a summary and description of the variables considered in the study. Then, descriptive bivariate associations were used in the second level of analyses to explore the relationship between each of the background characteristics of participants and the main outcome variable (results of screening). Here, Pearson's Chi-squared test was applied as the main test of statistical significance at This study involved 3000 randomly selected female participants and With 145 palpable masses, the remaining 1769 premenopausal participants group under Aberrations of Normal Development and Involution (ANDI): 455; Abscesses, Infections, and Mastitis (AIMS): 169; and No Abnormalities Detected (NAD): 1145 . SimilarWe next decided to ascertain the regional distribution of breast cancer and benign masses. In A common risk factor for breast cancer is age at first menstruation (menarche). The earlier you menstruate the higher the risk for breast cancer is. http://dx.doi.org/10.1155/2016/3645308). This result may support previous reports that early pregnancies reduce the risk of breast cancer, though the 0.03% observed for participants who had their first child between 30–34 years digresses from expectation. Results on whether multiparity offers protection were inconclusive (not shown) and it also did not matter whether you were married or single (not shown) even though some women in sub-Saharan Africa believe that marriage offers some protection.Other known protective factors such as the age at first pregnancy and the number of pregnancies were also examined. We report 0.07%, 0.23%, 0.43%, and 0.03% breast cancer for participants who had their first child at <19, 20–24, 25–29, and 30–34, respectively  team. Our aim was to accurately assess the incidence and pattern of breast cancer distribution in Ghana to enhance detection, diagnosis, and treatment. Breast cancer is complex and has been associated with ethnic origins, so it is important to ascertain any peculiar characteristics of the disease locally, to enable the recommendation of the most suitable control method to reduce mortality. The 2010 Ghana population census report  estimate2) due to its smaller size far exceeds the other four regions combined (457/Km2). Together, with accessibility to willing participants and proximity to treatment centres explains why most of the participants were from GAR  of the cases as invasive ductal carcinoma, four (4) as invasive lobular ductal carcinoma, and one (1) as in situ carcinoma. Our results are in conformity with other reports where 70–80% of all invasive lesions are invasive ductal carcinomas , 43 and The low incidence of breast cancer in sub-Saharan Africa has been attributed to factors such as late menarche, early child-bearing age, high parity with prolonged lactating, and irregular menses. As sub-Saharan countries shift from low to lower middle income, significant changes such as early menarche, early childbirth, reduced parity, and short lactating periods are on the increase and this may be the reason why we are seeing the increasing incidence in comparatively younger women, though other factors such as diet, socioeconomic status, and family history cannot be ruled out.Assessing the regional distribution, the 0.43% of breast cancer observed in the Volta Region  is on the high side and very puzzling considering that the population sampled in Volta Region is about a quarter of Greater Accra Region. Our questionnaire did not capture migration patterns, lifestyle choices, and type of stable food preparation and intake, so we cannot for now give any tangible reason for such incidence. Despite that, we find it to be way out of the norm and therefore recommend performing genomic surveillance and rescreening in the Volta Region with more participants using questionnaires that capture more information.Our results are in line with previous reports asserting early menarche as a risk factor for breast cancer , 40, 44.Our analysis of whether early childbirth offered protection showed positive correlation with known literature. However, a low percentage (0.03%) of breast cancer was observed for women who had their first child between 30 and 34 years. We are yet to find an explanation for this observation. Other results such as multiparity and long lactating times are not shown, but multivariate analysis carried out shows that neither long lactating times nor multiparity confirmed or refuted previous reports that they reduce the risk of breast cancer. Rosenberg et al. in 2002 reported that women in South Africa with childbirth at age 30 years or older had a twofold increase in breast cancer risk compared to women who had their first child at 16 years or younger . Coogan Both government and nongovernmental organizations in Ghana have been carrying out public education campaigns to create breast cancer awareness. To determine the impact of these campaigns, study participants were asked to perform self-breast examination (SBE) on their breasts and report suspicious lumps and/or any abnormalities detected. The team then conducted thorough clinical breast examination and the two results were compared . Though In conclusion, this project was conducted to answer three pertinent questions. (i) What is the pattern and incidence of breast cancer in Ghana? (ii) Will the result justify and recommend mass screening of Ghanaian women? And (iii) will the result require us to modify our approach to screening campaigns? Our results reveal a breast cancer incidence of 0.76% and an increasing incidence in women below 35 years. So, on the side of caution, we propose a review of the guidelines, such that breast cancer awareness campaigns should start in the senior high schools and breast screening for Ghanaian ladies should start from 21 years onwards. The result also justifies mass screening in Ghana and the establishment of a national breast cancer registry to formulate a control and treatment policy in Ghana. Since the number of breast cancer cases will increase in the coming years, such controlled policies will enable us to use our scarce resources to improve quality of service and fund interventions that provide value for money.2548 of the 3000 participants who partook in the screening exercise had been pregnant before. The questionnaire captured the age at first pregnancy and the results were then categorized under the following groupings: <19 years (284), 20–24 years (958), 25–29 years (849), 30–34 years (427), and >35 years (30). The ages were rounded up to the next highest whole number and the incidence of breast cancer and breast mass for each age group ascertained.


Although it has been well-documented that obesity is associated with decreased risk of premenopausal breast cancer and increased risk of postmenopausal breast cancer, it is unclear whether these associations differ among breast cancer subtypes defined by the tumor protein expression status of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2).We evaluated the associations of body mass index (BMI) at age 18 years and recent BMI in relation to risk of breast cancer overall and ER/PR/HER2-defined subtypes, in 6320 women  aged 35–64 years, who participated in one of three population-based case-control studies. We estimated multivariable-adjusted odd ratios (ORs) and corresponding 95% confidence intervals (CIs) using polychotomous unconditional logistic regression methods for case-control comparisons in premenopausal women and postmenopausal women.2, OR = 0.72, 95% CI = 0.53–0.96; per 5 kg/m2 increase, OR = 0.83, 95% CI = 0.73–0.95). This inverse association did not differ across ER/PR/HER2-defined subtypes or by race . Recent BMI was not associated with risk of premenopausal breast cancer after adjustment for BMI at age 18 years; nevertheless, the analysis for the joint effects of BMI at age 18 years and recent BMI showed that premenopausal women in the highest categories of the two BMI measures (≥ 25 kg/m2 at age 18 years and ≥ 30 kg/m2 for recent BMI) had 46% lower risk of breast cancer than premenopausal women in the lowest categories of the two BMI measures . Neither measure of BMI was statistically significantly associated with risk of postmenopausal breast cancer.BMI at age 18 years was inversely associated with risk of breast cancer, particularly among premenopausal women (≥ 25 vs. < 20 kg/mOur findings indicate that high BMI near the end of adolescence decreases risk of all ER/PR/HER2-defined subtypes of premenopausal breast cancer and also suggest that this benefit could be maximized among premenopausal women who consistently have high BMI during their premenopausal years. In the same study, obesity was not associated with the risk of ER-negative (ER–)/PR– breast cancer in either premenopausal women or postmenopausal women.Munsell et al.  conductePierobon et al.  used met2, ER+ OR = 0.65, 95% CI = 0.42–1.01; ER– OR = 1.00, 95% CI = 0.63–1.58; TNBC OR = 1.08, 95% CI = 0.59–1.98). However, among postmenopausal women, BMI at age 18 years was associated with decreased risk of all subtypes of breast cancer . They also found that high BMI immediately before diagnosis (cases) or an index date (controls) was not associated with the risk of ER–, ER+, or TNBC in premenopausal women, but was associated with 31% increased risk of ER+ breast cancer  and 40% decreased risk of TNBC in postmenopausal women .Bandera et al.  present Given the lack of consistency in results for analysis of BMI in relation to tumor marker subtypes of breast cancer, especially TNBC, additional research is needed to clarify whether obesity impacts all subtypes of breast cancer or only certain receptor-defined subtypes. Moreover, it remains unclear whether associations differ among racial/ethnic groups.Here we present results from a pooled analysis of data from three population-based breast cancer case-control studies conducted among white women and African-American women –8; we exEligible participants for this analysis were women who participated in one of the three population-based case-control studies – the Women’s Contraceptive and Reproductive Experiences (CARE) Study , the WomThe Women’s CARE Study was a population-based, multi-site, case-control study designed to examine risk factors for invasive breast cancer among US-born white women and African-American women . The ageThe Women’s CARE Study participants included in this pooled analysis are from Los Angeles and Detroit, the two study sites where tumor tissue samples were collected. Details of tissue collection for case-patient participants at the two sites have been described previously . The WomThe Women’s BCIS Study investigated risk factors for BCIS among US-born white women and African-American women who resided in Los Angeles County . Case-paThe Women’s LIFE Study investigated genetic and epidemiologic risk factors for invasive breast cancer in US-born white women and African-American women who resided in Los Angeles County , 11. CasFor all three studies, detailed information about body size measures and covariates prior to the reference date was collected by trained staff in standardized in-person interviews. The reference date for a case-patient participant was the date of her breast cancer diagnosis; the reference date for a control participant was the date she was identified by random digit dialing in the Women’s CARE Study, or the date of initial contact in the Women’s LIFE Study.2). Based on the World Health Organization’s guideline [2; overweight, 25.0–29.9 kg/m2; and obese, ≥30.0 kg/m2. Because only 1.6% of women at age 18 years had a BMI of 30 kg/m2 or higher and 47.8% had a BMI that was lower than 20.0 kg/m2, we used previously published categories for BMI at age 18 years  [Anthropometric variables involved in this analysis include: tallest height without shoes, usual weight  at age 18 years and 5 years before reference age (termed “recent weight”). BMI at each time point was calculated as the corresponding body weight in kilograms divided by height in meters squared  . None of0 kg/m2) .After pooling the data from the three source studies, 6723 women (4245 case-patient participants and 2478 control participants) were potentially eligible for this analysis. We excluded 160 case-patient participants and 64 control participants for whom information was missing on the following factors: age at menarche , parity , duration of oral contraceptive use , education , BMI at age 18 years , recent BMI , recreational physical activity , smoking status (8 cases), alcohol intake , and menopausal status . We were unable to determine menopausal status for 53 case patients and 30 control participants who had a hysterectomy with at least a portion of one ovary remaining , began menopausal hormone therapy (MHT) use within 12 months of their last menstrual period , or did not answer the questions regarding menopausal status and MHT use . We also excluded 179 participants  in the Women’s LIFE Study who were younger than 35 years at diagnosis or reference date, since the age range for the Women’s CARE and BCIS studies was 35 to 64 years.After these exclusions, 3934 case-patient participants  and 2386 control participants  remained and were included in the pooled analysis.As noted above, we determined ER/PR/HER2 receptor status of the breast cancers in case-patient participants in the Women’s CARE Study and Women’s BCIS Study in a centralized clinical laboratory improvement act (CLIA)-approved, College of American Pathologists (CAP)-certified pathology laboratory at USC using immunohistochemistry (IHC) methods , 16. Forn = 515), luminal-like breast cancer , HER2-enriched breast cancer , and an unclassified group (n = 1151) [n = 1175), luminal B-like-HER2– , or luminal B-like-HER2+ , based on the 13th St. Gallen International Breast Cancer Conference (2013) Expert Panel recommendation [Of 3934 case-patient participants, 2861 (72.7%) had ER status, 2740 (69.7%) had PR status, and 2560 (65.1%) had HER2 status. In our analysis, we classified case-patient participants into four subgroups: TNBC , had a surgical menopause , or had an induced menopause (periods stopped because of chemotherapy or radiation therapy at least 12 months before the reference date). Considering the possibility that associations with recent BMI among postmenopausal women might be modified by MHT use , we alsoFor premenopausal women, in which we observed an inverse association between BMI at age 18 years and breast cancer risk, we further conducted race-stratified analyses  for breast cancer overall and for two major subtypes . Finally, we assessed the joint effects of BMI at age 18 years and recent BMI (using a variable that combined these two variables) in premenopausal women for breast cancer overall and for the luminal-like subtype (the most common subtype). We did not do race-stratified analyses for the HER2-enriched subtype nor did we assess the joint effects of BMI at age 18 years and recent BMI for either the HER2-enriched subtype or TNBC, due to limited sample size. For postmenopausal women, we did not conduct race-stratified analyses or assess the joint effects of the two BMI measures due to the limited numbers of postmenopausal women in some subgroups.Our models assessing effects of BMI at age 18 years or recent BMI included both BMI variables . All models also included the following factors, selected a priori, as potential confounders in all multivariable models: source study , study site , race , education as a proxy for socioeconomic status , reference age , family history of breast cancer , no first-degree family history), age at menarche , number of completed (greater than 26-week gestation) pregnancies , lifetime recreational physical activity  hour/week), alcohol intake , cigarette smoking status , and oral contraceptive use . In the analyses of postmenopausal women overall, we additionally adjusted for MHT use .We repeated our analyses limiting data to the two source studies with ER/PR/HER2 status obtained by the centralized laboratory to assess whether using ER/PR/HER2 status from multiple laboratories in the LIFE Study (obtained from the LACSP) would influence our results. In another analysis, we restricted case-patient participant data to those obtained from women diagnosed with invasive breast cancer.2 increase in BMI (slope coefficient) differed from the null (test for trend) or whether slope coefficients differed across ER/PR/HER2-defined subtypes (test for homogeneity of trends) we considered a two-sided P value less than 0.05 as statistically significant. All analyses were performed using the SAS statistical package .In reporting the results of statistical tests determining whether the 5 kg/mOverall, mean age at reference date was 47.3 and 47.9 years for case-patient participants and control participants, respectively Table . By meno2, OR = 0.72, 95% CI = 0.53–0.96; per 5 kg/m2 increase, OR = 0.83, 95% CI = 0.73–0.95, Table 2 increase in BMI at age 18 years did not differ by subtype (P for homogeneity of slope coefficients per 5 kg/m2 increase = 0.15).In premenopausal women, BMI at age 18 years was inversely associated with risk of breast cancer overall .Recent BMI was not associated with risk of premenopausal breast cancer overall. However, our analyses of ER/PR/HER2-defined subtypes in premenopausal women showed some evidence that recent obesity affected ER/PR/HER2-defined subtypes differently, with no association for luminal-like subtype and potentially increased risks of TNBC and HER2-enriched subtypes ; no differences in risk across ER/PR/HER2-defined subtypes was observed . Furthermore, recent BMI was not associated with risk of breast cancer overall, TNBC, luminal-like subtype, or HER2-enriched subtype in postmenopausal women. Among postmenopausal women who had never used MHT, risk of the luminal-like subtype was 1.5-fold greater among women who were obese than among women who were normal weight or thin .In postmenopausal women, BMI at age 18 years was not associated with risk of breast cancer overall although the OR was reduced more than 20% when comparing overweight and obese women to thin women .2 increase, white women, OR = 0.86, 95% CI = 0.73–1.02; African-American women, OR = 0.79, 95% CI = 0.62–1.00, Table 2 increase, OR for TNBC = 0.61, 95% CI = 0.44–0.86; OR for luminal-like subtype = 0.87, 95% CI = 0.71–1.06) and premenopausal African-American women .A modest inverse association was observed between BMI at age 18 years and premenopausal breast cancer overall in both white women and African-American women . Recent BMI was not associated with risk of breast cancer overall or the two subtypes in premenopausal African-American women .In premenopausal white women, recent obesity was associated with a reduced risk for breast cancer overall and for luminal-like subtype, but was not associated with TNBC (≥ 30 vs. < 25 kg/m2 at age 18 years and ≥ 30 kg/m2 for recent BMI) had 46% lower risk of breast cancer overall .Premenopausal women in the highest categories of the two BMI measures . When the analyses were restricted to premenopausal invasive breast cancer case-patient participants (excluding the BCIS Study), results again remained similar .2 at age 18 years and ≥ 30 kg/m2 for recent BMI) with women in the lowest categories of the two BMI measures (< 20 kg/m2 at age 18 years and < 25 kg/m2 for recent BMI). No compelling evidence was observed among postmenopausal women for any associations between BMI at age 18 years or recent BMI and breast cancer overall or ER/PR/HER2-defined subtypes, except for a 1.5-fold increased risk of luminal-like subtype associated with recent BMI among postmenopausal women who had never used MHT.We pooled data from three population-based case-control studies that included white women and African-American women ages 35–64 years. The analyses of premenopausal women showed that BMI at age 18 years was inversely associated with breast cancer risk overall and with risk of each ER/PR/HER2-defined subtype of breast cancer. These inverse associations did not differ by race. We found no strong evidence of any inverse association between recent BMI and risk of premenopausal breast cancer except when we analyzed the joint effects of BMI at age 18 years and recent BMI, which showed marked inverse associations (range 46–54% decreases in risk) for breast cancer overall and for luminal-like subtype comparing premenopausal women in the highest categories of the two BMI measures  = 0.5, 95% CI = 0.4–0.8; luminal B subtype HR = 0.7, 95% CI = 0.3–1.4; HER2 HR = 0.6, 95% CI = 0.2–1.7; basal subtype HR = 0.4, 95% CI = 0.1–1.1). Our results also showed that BMI at age 18 years was inversely associated with all tumor marker subtypes and additionally suggested that the inverse association was stronger among premenopausal women than among postmenopausal women. The AMBER Consortium [2, ER+ OR = 0.65, 95% CI = 0.42–1.01; ER– OR = 1.00, 95% CI = 0.63–1.58; TNBC OR = 1.08, 95% CI = 0.59–1.98). However, among postmenopausal women in the AMBER Consortium Study, it was inversely associated with the risk of all subtypes of breast cancer . The Women’s Health Initiative Cohort Study [2, ER+ OR = 0.83, 95% CI = 0.69–0.98; TNBC OR = 0.94, 95% CI = 0.56–1.56). Based on our pooled results and those of earlier studies, no conclusion can be drawn as to whether the impact of BMI at age 18 years varies by tumor subtype, but at least, all studies support that BMI at age 18 years is inversely associated with risk of breast cancer.The Nurses’ Health Study , consistrt Study , which i2, luminal-like OR = 0.71, 95% CI = 0.55–0.91; TNBC OR = 0.96, 95% CI = 0.67–1.38; HER2-enriched OR =1.02, 95% CI = 0.60–1.73; per 5 kg/m2 increase, luminal-like OR = 0.90, 95% CI = 0.83–0.98; TNBC OR = 1.00, 95% CI = 0.89–1.12; HER2-enriched OR = 1.02, 95% CI = 0.86–1.20, P for homogeneity of slope coefficients per 5 kg/m2 increase = 0.12, results not shown). Comparing the models with adjustment to those without adjustment for BMI at age 18 years, we note that the magnitude of the protective effect of recent obesity on premenopausal luminal-like cancer was reduced from 29% to 20%. This could explain why we did not observe strong evidence of a negative association between recent BMI and luminal-like subtype of breast cancer in premenopausal women. Nevertheless, we observed clear inverse associations of all ER/PR/HER2-subtypes when assessing BMI at age 18 years after adjusting for recent BMI. Therefore, our data provide evidence suggesting that BMI in late adolescence plays a more important role than recent BMI in premenopausal breast cancer development.Many previous epidemiologic studies showed that recent BMI was inversely associated with premenopausal women’s risk of breast cancer overall and hormone receptor positive breast cancer, but not with hormone receptor negative breast cancer or TNBC , 5; howeAlthough our data did not show strong evidence of an inverse association between recent BMI and risk of premenopausal breast cancer, our analyses of the joint effects of BMI at age 18 years and recent BMI in premenopausal women showed the greatest risk reductions for breast cancer overall (46% reduction) and for luminal-like subtype (54% reduction) when contrasting the highest categories of the two variables with the lowest categories. These findings suggest that the reduced risk of premenopausal breast cancer is maximized in women who are consistently overweight or obese during the premenopausal period. Moreover, our results showing a greater reduction in risk for luminal-like subtype than for breast cancer overall associated with recent BMI and the lack of differences in risk reduction across tumor subtypes associated with BMI at age 18 years suggests that recent BMI is more important in determining risk of luminal-like subtype. Yet, results from the AMBER Consortium showing a lack of any impact of the joint effects of BMI at age 18 years and recent BMI on premenopausal ER+ breast cancer risk differ from our results [It has been well-documented that estrogen and progesterone play important roles in breast tumorigenesis –29. A po2 in a premenopausal woman  to become a risk factor (relative risk of 1.20 at age 62 years). MacInnis et al. [2 increase, HR = 0.98, 95% CI = 0.82–1.18), but was associated with a 26% increased risk  in women who were postmenopausal for 15 years or more, supporting the notion that prolonged exposure to the proliferative effects of elevated circulating estrogens from adipose tissue is needed. In our pooled data, the upper age limit of participants was 64 years, the average age at reference date for postmenopausal women was 54 years, and only 9% of the postmenopausal women were above age 62 years. Such under-representation of older women might, at least partly, explain why we did not observe consistent positive associations between recent BMI and breast cancer overall or the luminal-like subtype in postmenopausal women.As women pass through menopause, the beneficial effect of obesity on breast cancer risk is replaced by an adverse effect, possibly due to the fact that an important source of estrogen at this time comes from peripheral adipose tissue, where androstenedione is aromatized and converted to estrogen , 33. It s et al.  found thOur data did show that recent obesity was associated with a 1.5-fold increased risk of luminal-like subtype in postmenopausal women who had never used MHT, but not in those who had used MHT. This could be because the conversion of androstenedione to estrogen in peripheral adipose tissue is negligible when exogenous hormones artificially elevate the amount of circulating estrogens to a comparable level in both lean and obese women .Our pooled analysis has several strengths, including its size, especially the large number of case-patient participants with incident TNBC. Furthermore, the information on body size measures and covariates used in this analysis was collected by trained staff who administrated standardized, in-person interviews using structured questionnaires, which were nearly identical across the three source studies. To our knowledge, we are the first to report results on the associations of both early adulthood and recent BMI with ER/PR/HER2-defined subtypes of breast cancer according to both menopausal status and race.HER2 gene amplification in FISH analysis were false negative by 10H8-IHC (scored as 0 or 1+) and 9.7% of breast cancers without HER2 gene amplification in FISH analysis were false positive [Several limitations of the current study should be considered. First, our two BMI measures, BMI at age 18 years and recent BMI (representing BMI 5 years prior to reference date), are based on self-reported measures of weight and height. We cannot exclude the possibility that some women may have misreported their weight or height, which could result in the misclassification of BMI. This classification could differ between case-patient participants and control participants, but it is unlikely to differ across ER/PR/HER2-defined case-patient participants. Second, 29% of our case-patient participants had missing data on both ER and PR or on HER2. We compared the distribution of BMI at age 18 years and recent BMI between case-patient participants with known ER/PR/HER2-defined subtypes and those in the undefined group. No statistically significant differences in distribution were detected. Third, ER/PR/HER2 status in two of our source studies , 7 was dpositive , 39, we Our findings indicate that high BMI near the end of adolescence decreases risk of all ER/PR/HER2-defined subtypes of premenopausal breast cancer and also suggest that this benefit could be maximized among premenopausal women who consistently have high BMI during their premenopausal years.


CD44 encoded by a single gene is a cell surface transmembrane glycoprotein. Exon 2 is one of the important exons to bind CD44 protein to hyaluronan. Experimental evidences show that hyaluronan–CD44 interaction intensifies the proliferation, migration, and invasion of breast cancer cells. Therefore, the current study aimed at investigating the association between specific polymorphisms in exon 2 and its flanking region of CD44 with predisposition to breast cancer.In the current study, 175 Iranian female patients with breast cancer and 175 age-matched healthy controls were recruited in biobank, Breast Cancer Research Center, Tehran, Iran. Single nucleotide polymorphisms of CD44 exon 2 and its flanking were analyzed via polymerase chain reaction and gene sequencing techniques. Association between the observed variation with breast cancer risk and clinico-pathological characteristics were studied. Subsequently, bioinformatics analysis was conducted to predict potential exonic splicing enhancer (ESE) motifs changed as the result of a mutation.A unique polymorphism of the gene encoding CD44 was identified at position 14 nucleotide upstream of exon 2 (A37692→G) by the sequencing method. The A > G polymorphism exhibited a significant association with higher-grades of breast cancer, although no significant relation was found between this polymorphism and breast cancer risk. Finally, computational analysis revealed that the intronic mutation generated a new consensus-binding motif for the splicing factor, SC35, within intron 1.The current study results indicated that A > G polymorphism was associated with breast cancer development; in addition, in silico analysis with ESE finder prediction software showed that the change created a new SC35 binding site. BRCA1 and BRCA2, which are inherited with autosomal dominant pattern. The carriers of mutant genes have a significantly greater risk for developing breast and ovary cancers , indicating that A > G polymorphism increased approximately twice more the risk of higher grade of breast cancer  in only two patients with breast cancer. Both heterozygous and homozygous SNPs were identified in patients with breast cancer.Sequence analysis showed a unique polymorphism between n intron . The polThe disruption of cis-elements or the change in splice site strength are among the approaches in which mutations can affect splicing. These effects were investigated by Human Splicing Finder version 3.0 and ESE-finder, respectively , 28.ESE finder showed that mutation generated a new SC35 binding site within intron 1. This sequence is shown in boldface in Table CD44 gene is located on human chromosome 11p13 in which at least 10 internal exons can be alternatively spliced [CD44 polymorphisms and breast cancer risk [CD44 rs353639 variant may associate with breast cancer prognosis; however, both the rs13347 and rs353639 polymorphisms did not affect breast cancer risk in a North Indian population [CD44 exon 2 were significantly associated with breast cancer development; however, no significant difference was found between SNPs and breast cancer risk [The  spliced . The CD4 spliced . Experim spliced –33. Thercer risk , 34–37. cer risk . This poIn the current study, a significant association was found between A > G polymorphism and higher grades of breast cancer (grade 3), while no significant difference was observed between the said polymorphism and breast cancer risk. To the authors’ best knowledge, the association between A > G polymorphism and cancer grade was reported for the first time in the current study.CD44 polymorphism and breast cancer risk in the population, European descent and African–American. However, there were statistically significant differences in the distribution of allele frequency and breast cancer risk based on ethnic groups; the difference was especially great in the case of the European descent (P < 0.005). The difference in allele frequencies between above-mentioned study and our data may be due to the variations in sample selection criteria, geographical distribution, and different ethnic groups. It was reported that African–American have higher mortality rate due to breast cancer than the European descent; however, African–American females had a lower incidence of breast cancer compared with European females [CD44 intron 1 was higher both in African–American patients with breast cancer and normal donors than white population, while breast cancer was diagnosed at an earlier age in African–American females carrying the unique polymorphism in intron 1 than the European females. These results were consistent with those of the current study that showed the association of the unique SNP in intron 1 with breast cancer invasion and mortality [AA genotypes are directly proportional to low grade tumors (G 1/2), while this trend is reversed in patients carrying AG/GG genotypes as they showed a significantly higher incidence of grade 3. These data indicate that AG/GG genotypes may lead to higher grades of breast cancer. In another study, a significant association was observed between the same  females . Zhou etortality .CD44 and its flanking region [CD44 alternative splicing implicated in tumor progression [It is estimated that 15% of point mutations causing human genetic diseases disrupt splice sites or splicing control sequences . Most mug region . Remarkagression . In humagression . Based oThe current study had some limitations that should be acknowledged. Since the new alternative splicing site was found in this study, further experimental validation of this site and detecting probable protein varient producing from this site is recommended. In addition, independent studies in other ethnic populations are still needed to confirm our present findings.CD44 was associated with higher grades of breast cancer, and generated a new SC35 binding site as predicted by the ESE finder. Since CD44 alternative splicing and overexpression implicated in tumor progression, more experiments should be performed to determine the probable effects of A > G polymorphism on CD44 expression in patients with breast cancer.The current study found that A > G polymorphism in intron 1 of


Hormone replacement therapy (HRT) use increases breast cancer risk and mammographic density (MD). We examine whether MD mediates or modifies the association of HRT with the breast cancer.For the 4,501 participants in the Danish diet, cancer and health cohort (1993–1997) who attended mammographic screening in Copenhagen (1993–2001), MD (mixed/dense or fatty) was assessed at the first screening after cohort entry. HRT use was assessed by questionnaire and breast cancer diagnoses until 2012 obtained from the Danish cancer registry. The associations of HRT with MD and with breast cancer were analyzed separately using Cox’s regression. Mediation analyses were used to estimate proportion [with 95% confidence intervals (CI)] of an association between HRT and breast cancer mediated by MD.p value for interaction = 0.15).2,444 (54.3%) women had mixed/dense breasts, 229 (5.4%) developed breast cancer, and 35.9% were current HRT users at enrollment. Compared to never users, current HRT use was statistically significantly associated with having mixed/dense breasts , and higher risk of breast cancer . Association between current HRT use and breast cancer risk was partially mediated by MD . The current HRT use-related breast cancer risk was higher in women with mixed/dense  than fatty  breasts (MD partially mediates some of the association between HRT and breast cancer risk. The association between HRT and breast cancer seems to be stronger in women with dense breasts. Mammographic density (MD) is increasingly being used as a biomarker of breast cancer risk, as it is one of the strongest risk factors . MD refeCombined estrogen plus progestin hormone replacement therapy (HRT) is an established risk factor for breast cancer –5 althouA number of studies have shown that current use of HRT increases MD –14 and tFurthermore, it has been suggested that the impact of HRT use on breast cancer risk varies by MD. Hou et al. found that the HRT use was associated with the highest breast cancer risk in women with very dense breasts, while no excess risk was found with HRT use in women with fatty breasts . SimilarThe purpose of this study is to determine whether the effect of HRT on breast cancer risk is mediated or modified by its effect on MD, separately for different HRT regimens: estrogen (E), SEP, and CEP.Between 1993 and 1997, a total of 160,725 persons , 50–64 years of age, born in Denmark, living in Copenhagen or Aarhus (the two largest cities in Denmark), and with no record of cancer in the Danish Cancer Registry, were invited to participate in the Danish prospective diet, cancer and health (DCH) cohort. In total, 57,053 people, of whom 29,875 were women , accepted the invitation and participated in the study and answered a detailed questionnaire on diet, health, education, occupation, lifestyle, and reproductive characteristics. A detailed description of the DCH cohort has been published previously  to examine the association between HRT and MD. Since the log–glm model did not converge, we instead fitted the model using Cox proportional hazard procedure  with ageThe study was entirely based on register data and was approved by the Danish data inspection agency (2014-41-3168). Danish law regarding ethical approval of register-based research does not require informed consent from study participants, thus no contact was made with the participating women or their relatives and general practitioners.Table Ever users of HRT at enrollment had significantly higher risk of having mixed/dense breasts  than never users   and current users , as well as for SEP users  and CEP   and indirect effect, or effect mediated by MD , on breast cancer risk, with estimated mediation proportion of 11% (4–30%)  .The breast cancer risk related to HRT was highest in women with mixed/dense breasts, both in ever  and current  users at enrollment, compared to women with fatty breasts , although the differences were not statistically significant  than CEP (21%), while there was no statistically significant association with estrogen use, although positive association of 8% was detected. Number of the studies found that increase in MD is more pronounced in CEP than in SEP and estrogen users , 39–42. % than CEWe found a strong positive association between estrogen–progestin HRT regimen and breast cancer, in agreement with vast evidence –5.We detWe found that increase in breast cancer risk of 56 and 87% related to ever and current HRT use, respectively, attenuated slightly, by 14 and 13%, respectively, after adjustment for MD, by similar magnitude for SEP and CEP . The difference was even stronger in current HRT users, where women with fatty breasts had 37% and women with mixed/dense breasts had 94% increased risk of breast cancer (p = 0.15). This is in agreement with results by Hou et al., which directly assessed the effect modification of association between HRT and breast cancer by MD, though in American women with different racial composition from Danish women [p = 0.001) [Risk of breast cancer in HRT users differed according to MD and was generally higher in women with mixed/dense than with fatty MD Table . Ever us= 0.001) . Kerliko= 0.001) . Further= 0.001) , while w= 0.001) .Several biological mechanisms behind association of HRT use and MD have been suggested. Previous studies showed the association between serum estradiol level and MD changes in women who used HRT, which support proliferative effect of estrogen on breast epithelial cell , 47. SimThis study benefited from an ability, unique to Denmark, to link breast density data from Copenhagen mammography register to a large prospective Danish DCH cohort, with detailed information on HRT and breast cancer risk factors, and facilitate the data to study whether MD mediates the effect of HRT on breast cancer risk, explored in few other studies to date –17. DCH We found significantly positive associations between HRT use and MD, as well as between HRT and breast cancer risk, which seemed limited to estrogen + progestin HRT regimens. We found that the association between HRT use and breast cancer risk was in part, by around 10%, mediated by MD. This suggests that MD is a mediator of certain biological pathways on HRT-related breast cancer development, and also that other mechanisms are at play. Finally, the association between HRT and breast cancer risk seemed more pronounced in women with dense breasts.


Women with breast cancer who have multiple affected relatives are more likely to have inherited genetic risk factors for the disease. All the currently known genetic risk factors for breast cancer account for less than half of the average familial risk. Furthermore, the genetic factor(s) underlying an increased cancer risk for many women from multiple-case families remain unknown. Rare genomic duplications and deletions, known as copy number variants (CNVs), cover more than 10% of a human genome, are often not assessed in studies of genetic predisposition, and could account for some of the so-called “missing heritability”.We carried out a hypothesis-generating case-control study of breast cancer diagnosed before age 40 years  using population-based cases from the Australian Breast Cancer Family Study. Genome-wide scanning for CNVs was performed using the Human610-Quad BeadChip and fine-mapping was conducted using PennCNV.BRCA1 and BLM), and a duplication overlapping SMARCB1, associated with risk. The number of deletions across the genome was 1.5-fold higher for cases than controls (P = 10-16), and 2-fold higher when only rare deletions overlapping genes (frequency <1%) were assessed (P = 5 × 10-4). Association tests of CNVs, followed by experimental validation of CNV calls, found deletions overlapping the OR4C11 and OR4P4 genes were associated with breast cancer .We identified deletions overlapping two known cancer susceptibility genes,  contains supplementary material, which is available to authorized users. Breast cancer is the most common malignancy among women in the developed world, and is increasing rapidly in the developing world. A proportion of women with breast cancer have multiple affected relatives and are therefore more likely to have inherited genetic factors that increase their risk of developing the disease. All the currently known genetic risk factors for breast cancer currently only account for around 48% of average familial risk, and account for a lower proportion of the familial risk of disease at a young age, and the vast majority of women from multiple-case families do not have a known genetic explanation for their increased cancer risk , 2. ThusBRCA1, BRCA2, TP53 and CHEK2 [Copy number variants (CNVs) are estimated to cover 5–10% of the human genome  and, basnd CHEK2 , and cound CHEK2 . Howevernd CHEK2 . Evidencnd CHEK2 , 9, and nd CHEK2 . Thus, fAPOBEC3 gene cluster associated with up to 1.3-fold and up to 2.3-fold increase in risk of breast cancer associated with hemizygous and homozygous deletions, respectively [Only a few studies have examined the relationship between common germ-line CNVs and breast cancer risk. A large genome-wide association study (2000 breast cancer cases and 3000 controls) from the Wellcome Trust Case Control Consortium suggested that such CNVs were unlikely to have a major role in the genetic basis of breast cancer . Howeverectively , 12.To better understand the role of CNVs in breast cancer risk we have conducted a hypothesis-generating study of breast cancer at a young age (diagnosed before the age of 40 years). Our study aimed to assess whether CNVs across the genome are more frequent in such breast cancer cases when compared with unaffected controls, and whether cancer susceptibility genes are disrupted by rare CNVs.BRCA1, ATM, CHEK2, PALB2, TP53, BRCA2, CDH1, and FANCM [We conducted a hypothesis-generating study of 258 women who were diagnosed with breast cancer before the age of 40 years from the population-based Australian Breast Cancer Family Study –15. Thesnd FANCM , 16–25. nd FANCM . All stuAll DNA samples were genotyped with the Human610-Quad BeadChip  with approximately 610,000 markers  for single nucleotide polymorphism (SNP) and CNV analysis. Samples were processed using Illumina’s recommended protocol for Infinium HD assays. Data for each array were normalised using GenomeStudio 2011.1 software (Illumina). Probe information, including genomic location, signal intensity (Norm R), allele frequency (Norm theta), log R ratios (LRRs), and B allele frequencies (BAF), for each sample was calculated and exported from GenomeStudio. All samples had a call rate >95%. The CNV calls were generated using the PennCNV program (version 27 Aug. 2009), using the default program parameters, library files, and genomic wave adjustment.Quality control procedures were performed to remove poor-quality array data  transcripts using the SOURCE database  and defi8 transcrBecause putative CNV calls do not typically conform to discrete genomic regions in different women, we used the genome coordinates of 18,791 RefSeq gene (NCBI36/Hg18) boundaries to define a CNV region . Primer and probe sequences are presented in Additional file t test was conducted to establish the level of significance associated with the difference in CNV carrier frequencies between the cases and controls. This test is an adaptation of Student’s t test designed to cope with datasets that have unequal variances. The statistical package R version R 2.14.2 was used to perform statistical analyses. P values <0.05 were considered significant.Welch’s P values for the association between each CNV and cancer status. P values were adjusted for multiple testing with a false discover rate of 5%, using the method of Benjamini and Yekutieli (2001). Tests with a corrected P value <0.05 were considered statistically significant. The analysis was performed based on CNVs defined by their location within a gene region.Genes overlapping CNVs identified in cases or controls were assigned as having DNA loss (copy number states zero or one) or DNA gain (copy number states three or four). Perl 5.14.2  was used to produce counts of the CNVs based on copy number state and the gene region by which they were defined. The CNV state with the most CNVs for each region was identified. A corresponding table of incidence of the most numerous CNV state in that region was analysed between cases and controls using Fisher’s exact test. This was used to calculate odds ratios, 95% confidence intervals and P = 2 × 10-10) (Table P = 2 × 10-16), whereas the average number of copy number gains in cases was slightly lower than that of controls . These results suggest that women with early-onset breast cancer carried a greater CNV load across the genome compared with controls and that this feature was due to the inheritance or de novo formation of genomic deletions.A total of 58 cases and 55 controls were removed from the study after quality control criteria were applied, leaving 200 cases and 293 controls for downstream analyses . Concordantly, the average number of RefSeq genes predicted to be disrupted by genomic deletions was also 1.6-fold higher in cases compared with controls . By comparison, there was no significant difference observed between cases and controls when the number of copy number gains overlapping genes (P = 0.1), and the number of genes overlapping copy number gains (P = 0.5) were measured.To assess the potential disruption of CNVs to functional regions across the genome, CNVs overlapping 18,791 reference sequence (RefSeq) genes (NCBI36/Hg18) were identified in cases and controls. Thirty-four percent of CNVs were predicted to overlap genes in both study groups (Table P = 0.001); however, there was no statistically significant difference in the average size of the CNVs between the groups when considering copy number type (deletion or duplication)  Table . Thus, tP = 5 × 10-4), but there was no statistically significant difference in copy number gains between the two groups (P = 0.6) (Table P = 5 × 10-3). The ratio of genes disrupted per rare deletion event in each sample was 1.2 in cases and 1.4 in controls (data not shown). There was no significant difference in ratios between the two groups (P = 0.1). Together these results suggest that in most samples rare deletions are disrupting a single gene, and such events in cases of early-onset breast cancer were twice as common as in controls.To examine the prevalence of rare CNVs, RefSeq gene regions containing five or more CNVs (>1% frequency in the study cohort) were excluded from downstream analyses. By this process, all remaining rare CNVs assessed in this study overlapped RefSeq gene regions. The number of rare deletions in the cases were twofold greater than in controls  Table . The aveAPC (n = 2), BRCA1 (n = 1) and BLM (n = 1), and one case with a duplication overlapping SMARCB1 (n = 1). One control was also found to harbour a putative deletion overlapping APC   non-carrier of this deletion had had breast cancer diagnosed at age 42 years . qPCR did not confirm the small 646-base-pair deletion at the DOCK5 locus  breast cancer in a population-based study. Our results suggest that CNV frequency (or CNV load) may be associated with breast cancer risk, which is consistent with non-statistically significant data from a previous study of cases of familial and early-onset (<40 years of age) breast cancer . MoreoveConsistent with our data, a recent analysis of the Exome Aggregation Consortium (ExAC) database showed that the average human genome contains 2.1 rare <0.5%) CNVs  that intersect at least one protein-coding gene . These r% CNVs  at the age of 39 years, who did not have a family history of the disease and did not have any relatives participating in our study. A rare deletion overlapping the Bloom syndrome RecQ-like helicase gene, BLM, was also detected in a patient and some of her family members. Although data were limited for segregation analysis, our results are consistent with the previous finding that BLM mutations are associated with a perhaps more moderate increased risk of breast cancer [Our study identified a deletion overlapping the known breast cancer susceptibility gene, t cancer . These dDOCK5, 6.9-fold, P = 0.003; OR4C11, 2.6-fold, P = 0.02, and OR4P4, 2.4-fold, P = 0.03) that were associated with an increased risk of breast cancer after accounting for multiple testing  and The Cancer Genome Atlas (n = 960) showed that expression of OR4C11 and OR4P4 did not correlate with copy number loss (data not shown) [A genome-wide association study of the cases and controls identified deletions overlapping three gene regions  , 37, altCNVs overlapping more than 100 genes have been found exclusively or at a greater frequency in cases of familial and/or early-onset breast cancer; however, none of these loci have been identified in more than one study . Large-sOR4C11/OR4P4 locus that were also associated with breast cancer risk. Larger studies are required to further investigate these possible associations to understand the role of CNVs in the development of breast cancer.We report that the frequency of rare CNVs may be associated with breast cancer risk, and that compared with controls, patients with early-onset breast cancer carried one extra deletion within their genome that overlapped a coding gene. A genome-wide analysis of CNVs identified deletions at the