LSP1-rs3817198 and parity (Pinteraction = 2.4×10−6) and between CASP8-rs17468277 and alcohol consumption (Pinteraction = 3.1×10−4). Overall, the per-allele odds ratio  for LSP1-rs3817198 was 1.08 (1.01–1.16) in nulliparous women and ranged from 1.03 (0.96–1.10) in parous women with one birth to 1.26 (1.16–1.37) in women with at least four births. For CASP8-rs17468277, the per-allele OR was 0.91 (0.85–0.98) in those with an alcohol intake of <20 g/day and 1.45 (1.14–1.85) in those who drank ≥20 g/day. Additionally, interaction was found between 1p11.2-rs11249433 and ever being parous (Pinteraction = 5.3×10−5), with a per-allele OR of 1.14 (1.11–1.17) in parous women and 0.98 (0.92–1.05) in nulliparous women. These data provide first strong evidence that the risk of breast cancer associated with some common genetic variants may vary with environmental risk factors.Various common genetic susceptibility loci have been identified for breast cancer; however, it is unclear how they combine with lifestyle/environmental risk factors to influence risk. We undertook an international collaborative study to assess gene-environment interaction for risk of breast cancer. Data from 24 studies of the Breast Cancer Association Consortium were pooled. Using up to 34,793 invasive breast cancers and 41,099 controls, we examined whether the relative risks associated with 23 single nucleotide polymorphisms were modified by 10 established environmental risk factors  in women of European ancestry. We used logistic regression models stratified by study and adjusted for age and performed likelihood ratio tests to assess gene–environment interactions. All statistical tests were two-sided. We replicated previously reported potential interactions between  BRCA1 and BRCA2, account for only a small proportion of disease occurrence. Recent genome-wide research has identified more than 20 common genetic variants, which individually alter breast cancer risk very moderately. We undertook an international collaborative study to determine whether the effect of these genetic variants vary with environmental factors, such as parity, body mass index (BMI), height, oral contraceptive use, menopausal hormone therapy use, alcohol consumption, cigarette smoking, and physical activity, which are known to affect risk of developing breast cancer. Using pooled data from 24 studies of the Breast Cancer Association Consortium (BCAC), we provide first convincing evidence that the breast cancer risk associated with a genetic variant in LSP1 differs with the number of births and that the risk associated with a CASP8 variant is altered by high alcohol consumption. The effect of an additional genetic variant might also be modified by reproductive factors. This knowledge will stimulate new research towards a better understanding of breast cancer development.Breast cancer involves combined effects of numerous genetic, environmental, and behavioral risk factors that are unique to each individual. High risk genes, such as  BRCA1 and BRCA2, more moderate susceptibility variants in genes such as PALB2, CHEK2 and ATM, and more than 20 common genetic susceptibility variants conferring modest increased risks, principally identified through genome-wide association studies. Taken together, the known susceptibility variants have been estimated to explain about 20–25% of the observed familial breast cancer risk FGFR2 and use of menopausal hormone therapy (MHT) were not confirmed LSP1-rs3817198 and number of births , between CASP8-rs104585 and alcohol consumption , and between 5p12-rs10941679 and use of estrogen-only MHT  Both genetic and non-genetic factors are involved in the etiology of breast cancer. Known susceptibility variants include rare high-risk mutations, principally in Up to 34,793 invasive cases and 41,099 controls of self-reported European ancestry were included in these analyses . Based oTGFB1-rs1982073, all SNPs showed highly significant associations with breast cancer overall  (interaction = 1.6×10−3), thus independently replicating the previous finding. The results were consistent across studies (Pheterogeneity = 0.37) (The strongest evidence was found for modification of the association with  = 0.37) . In the  = 0.37)  and in c = 0.37) .interaction = 5.3×10−5). The interaction was non-significantly stronger for risk of ER-positive than ER-negative tumours   but not nulliparous women  (P.6×10−5) . There w.6×10−5) .CASP8-rs1045485 (in complete LD with rs17468277) and alcohol consumption (<1 versus ≥1 drink/day) interaction per 10 g/day = 3.0×10−3) (CASP8-rs17468277 was 0.91 (0.84–0.98) in those who drank <20 g/day and 1.45 (1.14–1.85) in those who drank ≥20 g/day (Pinteraction = 3.1×10−4)  . However.1×10−4) .interaction = 2.4×10−3), rs2823093 and current use of estrogen only MHT (yes/no) (Pinteraction = 6.6×10−3), rs999737 and duration of estrogen only MHT among current users (Pinteraction = 4.0×10−3), and rs614367 and age at first birth among parous women (Pinteraction = 9.1×10−3) (We observed weaker evidence of differences in the associations with breast cancer for three further SNPs according to use of MHT and for one SNP according to age at first birth. These included rs13387042 and current use of combined estrogen/progestagen MHT (yes/no) (P.1×10−3) .The observed SNP-environmental interaction ORs were not altered substantially (less than 8% change in the interaction ORs) when adjusting for additional covariates. These additional covariates included  ever parous (yes/no), number of births, BMI, age surrogate for postmenopausal status (≥54 years), interaction of BMI and postmenopausal status (≥54 years), current use of MHT, past use of MHT, duration of oral contraceptives (OC) use, lifetime alcohol intake, smoking (pack-years) . SubjectLSP1-rs3817198 by number of births and 1p11.2-rs11249433 and being ever parous. For the effect modification of CASP8-rs17468277 by alcohol intake ≥20 g/day, the FPRP was below 0.2 at a prior probability greater than 0.01. For the four potential interactions reported above, the FPRP was only below 0.2 at a prior probability greater than 0.05.  was below 0.2 at a prior probability greater than 0.001 for the replicated effect modification of an 0.05. .We carried out a comprehensive evaluation of potential gene-environment interactions between 23 established common susceptibility variants for breast cancer and 10 established environmental risk factors, using 18 variables. Compared to the previous analysis, the present dataset from BCAC included 5 new population-based studies as well as additional study participants from some studies LSP1-rs3817198 by number of births LSP1-rs3817198 and ever being parous. The rs3817198 SNP is located on the short arm of chromosome 11 and lies within LSP1, encoding lymphocyte-specific protein 1, an intracellular F-actin binding protein, although the gene underlying the association has not been definitively identified. The SNP lies close to the H19/IGF2 imprinted region, and the association of breast cancer with rs3817198 has been reported to be restricted to the paternally inherited allele LSP1-rs3817198 by number of births appears to be partly due to a significant negative correlation between number of rs3817198 C alleles and number of births in parous women , which was found both in the data of our previous report as well as the additional data for the present analysis. Although not statistically significant, the mean number of children was also reported to be lower in women carrying the CC genotype in the Million Women Study LSP1-rs3817198 has been associated with mammographic density, consistent with the direction of the breast cancer association In our previous report, the strongest evidence of effect modification  was observed for CASP8-rs1045485 (or rs17468277 in our dataset) was 0.99 (0.92–1.07) in those who reported <1 drink/day and 1.23 (1.09–1.38) in those who reported ≥1 drink/day . Our observation of an increased per-allele OR of 1.45 (1.14–1.85) for those who reported high alcohol intake ≥20 g/day and 0.91 (0.84–0.98) for those who consume less provides independent replication of this SNP-environmental interaction. Although one drink corresponds to an intake of approximately 10 g alcohol, the Million Women study reported the strongest risk increase in breast cancer for women consuming at least 15 drinks per week (RR 1.29 (1.23–1.35)) CASP8-rs1045485, however, it is associated with a risk haplotype in CASP8, which is more strongly associated with breast cancer risk We also replicated the strongest finding reported in the Million Women Study based on 7,610 cases and 10,196 controls FCGR1B (low-affinity Fc gamma receptor family) and NOTCH2 (coding a transmembrane receptor protein). Recently, a study reported a positive association of NOTCH2 mRNA expression with the breast cancer risk allele of rs11249433 NOTCH2 expression Ever being parous, but not number of births, was found to modify the effect of a different SNP, 1p11.2-rs11249433, in particular for ER-positive breast cancer. This SNP shows significantly stronger association with risk of ER-positive tumors than of ER-negative tumors RAD51L1-rs999737 by duration of estrogen only MHT in current users is particularly interesting because this polymorphism has been associated with mammographic density in the same direction as the breast cancer association The evidence for the other four potential interactions mentioned in the results was considerably weaker and confirmation of these findings in further studies is therefore required. Three of these involved effect modification by use of MHT. The effect modification of RAD51L1 is a member of the Rad51-like proteins that play a crucial role in homologous recombinational repair BRCA1 and BRCA2, confer a high risk of breast cancer BRCA1 mutation carriers although the evidence is still limited RAD51L1 on breast cancer risk.NRIP1 (nuclear receptor–interacting protein 1), also called RIP140 (receptor-interacting protein 140), is known to interact with ERα, repress ER signaling and inhibit its mitogenic effects NRIP1 rs2823093 with breast cancer.TNP1 (transition protein 1), IGFBP5 (insulin-like growth factor binding protein 5), IGFBP2 (insulin-like growth factor binding protein 2) and TNS1 (tensin 1/matrix-remodelling-associated protein 6) It is less clear how 2q35-rs13387042 might be modified by current combined estrogen/progestagen MHT use since the gene involved at this locus is still unknown. The SNP is located on the short arm of chromosome 2 and lies in a linkage disequilibrium (LD) block containing no known gene(s) or non-coding RNAs. The closest known genes are RAD51L1-rs999737 with MHT and breast cancer risk. However, neither study considered current use of MHT even though elevated risks for breast cancer have been clearly established for current use and not for past use FGFR2 variants with MHT and other factors Both Campa et al. and the Million Women Study investigated potential interactions with MHT  One of the strengths of our study is the large sample size, required for assessing weak to moderate gene-environment interactions, particularly when marker SNPs instead of causal variants are used The effect modifications identified in our study are relatively weak and should result in small differences in risk estimates of joint effects compared to those based on models assuming multiplicative effects. However, most of the SNPs investigated are only markers of the underlying causal variants and underestimate the effects of the causal variants if linkage disequilibrium is incomplete LSP1-rs3817198 by number of births and of CASP8-rs1045485 by alcohol consumption. For some additional common genetic variants, the associations with breast cancer risk may vary with environmental factors. However, there is little evidence for multiplicative gene-environment interactions for most susceptibility loci and environmental risk factors. Understanding the biological implications of the observed interactions could provide further insight into the etiology of breast cancer. The potential impact of these results on risk prediction for breast cancer needs to be considered in future studies.In summary, we provide strong evidence of effect modification of We used primary data from the studies in BCAC. All studies had approval from the relevant ethics committees and all participants gave informed consent. A centralized BCAC database of information about common risk factors and tumor characteristics was constructed to facilitate studies of potential modifications of SNP associations by other risk factors. A multi-step data harmonization procedure was used to reconcile differences in individual study questionnaires. The reference age for cohort studies was calculated at time of enrollment and for case-control studies at date of diagnosis for cases and at date of interview for controls. All time-dependent variables were assessed at reference age. This analysis included only subjects of European ancestry that had genotype data for at least 3 SNPs and provided information on at least one of the established risk factors. Relevant data were available from 24 studies, including 16 population-based studies (14 case-control and 2 prospective cohort studies) and 8 non-population-based studies . Subsets−7) TGFB1 and CASP8 from candidate gene studies RAD51L1, 12p11, CASP8, a surrogate SNP in high linkage disequilibrium (LD) (2r = 1 in HapMap CEU) was genotyped in a subset  and their 95% confidence intervals (CI) were calculated for the SNP associations assuming a log-additive model and tested for association with a one degree of freedom trend test. All statistical tests were two-sided.The assessment of associations with the environmental risk factors was based on data only from the 16 population-based studies to ensure unbiased estimates for comparison with established effect sizes. The variables considered were analyzed as continuous , or as dichotomous  . AnalyseTo test for interactions between SNPs and environmental risk factors, we fitted for each SNP two logistic models, a model with terms for the SNP and the risk factor of interest and another model with additionally an interaction term for the product between the SNP  and the risk factor variable. We modeled the interaction based on the risk factor variable definitions employed for the main effects. All analyses were stratified by study and adjusted for age as a continuous variable. The likelihood ratio test was used to compare the difference between the two models and departure from independent multiplicative effects of the SNP and the risk factor. BMI was the only variable found to show differential effects by menopausal status, which is consistent with the literature −3, we also compared results after adjusting for additional covariates. We performed a total of 414 (23 SNPs x 18 risk variables) tests. To account for chance findings due to multiple comparisons, we calculated the false positive report probability (FPRP) for SNP-environment interactions with associated P-value<10−3For SNP-environment interactions with associated P-value<10In secondary analyses, we examined associations and effect modifications separately for women with ER-positive tumors and ER-negative tumors, each compared to all controls. Effect heterogeneity by ER status was tested using case-case analysis.Data harmonization was performed using an ACCESS database and transformation of the data elements was performed using SAS (Release 9.2). All other data analyses were conducted using SAS (Release 9.2) and the R programming language Table S1Description of BCAC studies included in the analysis of gene–environment interaction.(PDF)Click here for additional data file.Table S2Description of environmental risk factors by study.(PDF)Click here for additional data file.Table S3SNPs previously reported to be associated with breast cancer risk.(PDF)Click here for additional data file.Table S4Per-allele odds ratios (OR) and 95% confidence intervals (CI) for SNPs by environmental risk factors of breast cancer, overall.(PDF)Click here for additional data file.Table S5Per-allele odds ratios (OR) and 95% confidence intervals (CI) for SNPs by environmental risk factors of breast cancer, estrogen receptor positive.(PDF)Click here for additional data file.Table S6Per-allele odds ratios (OR) and 95% confidence intervals (CI) for SNPs by environmental risk factors of breast cancer, estrogen receptor negative.(PDF)Click here for additional data file.Table S7−4, overall and by ER status, adjusted for additional covariates.Gene-environment interactions between SNPs and breast cancer risk factors in Caucasians with interaction p-value<10(PDF)Click here for additional data file.Table S8−4, overall and by ER status, restricted to population-based studies.Gene-environment interactions between SNPs and breast cancer risk factors in Caucasians with interaction p-value<10(PDF)Click here for additional data file.Table S9−2.False-positive reporting probability (FPRP) for interactions of SNPs and environmental risk factors of breast cancer showing interaction p-value<10(PDF)Click here for additional data file.


Women who are at high risk of breast cancer can be offered chemoprevention. Chemoprevention strategies have expanded over the past decade and include selective receptor modulator inhibitors and aromatase inhibitors. Physicians are expected to provide individualized risk assessments to identify high risk women who may be eligible for chemoprevention. It is prudent that physicians utilize a shared decision approach when counseling high risk women about their preventive options. Barriers and misperceptions however exist with patient and physician acceptance of chemoprevention and continue to impede uptake of chemoprevention as a strategy to reduce breast cancer risk. Programs to increase awareness and elucidate the barriers are critical for women to engage in cancer prevention and promote chemoprevention adherence. The incidence of breast cancer among high risk women is 43.4 per 1,000 at five years. This rate decreased to 22 per 1,000 high risk women who received tamoxifen in the NSABP-P1 trial , U.S. PrDespite endorsement by several societies and organizations, use of hormonal intervention for primary prevention of breast cancer is limited even in women whose risk/benefit ratio is in favor of preventive therapies ,10,11,12The early evidence linking endocrine manipulation to breast cancer was regression of metastatic breast cancer resulting from estrogen suppression by way of oophorectomy over a century ago . This leIn view of its proven effectiveness against metastatic, recurrent and contralateral breast cancers, reasonable toxicity profile and positive long-term follow up, tamoxifen was the obvious first choice for assessment as a preventive therapy candidate. The earliest and most extensive studies on breast cancer chemoprevention focused on tamoxifen  15,16,1,18. An oversus raloxifene was the Study of Tamoxifen and Raloxifene (STAR) trial and this study demonstrated that both drugs are efficacious against breast carcinogenesis, albeit raloxifene is only 78% as effective as tamoxifen. The important finding of STAR trial is the lack of proliferative effect of raloxifene on the endometrium and lower incidence of thromboembolic events compared to tamoxifen; making it an ideal strategy for postmenopausal women with a uterus.Although tamoxifen is the revolutionary SERM in breast cancer prevention, raloxifene is the first drug to be used as preventive therapy studied in the context of osteoporosis prevention . It is iversus placebo. This trial showed a 79% risk-reduction in breast cancer, 42% reduction in vertebral fracture, 24% reduction in non-vertebral fracture 32% reduction in coronary events and 36% reduction in stroke. Lasofoxifene is currently under evaluation in the United States. The GENERATIONS trial randomized postmenopausal women to arzoxifene versus placebo and demonstrated a significant 70% reduction in estrogen positive breast cancer. However, there was a higher incidence of thromboembolic events and gynecologic side-effects .,28.27,28Like the SERMs, the evidence supporting the effectiveness of aromatase inhibitors as preventive candidates stemmed from the studies on AIs as adjuvant therapy and the observed rates of decline in contralateral cancers ,30. Thesin situ. The concern is reduced bone mineral density associated with anastrozole; therefore a substudy arm of 1,000 women has been designed to assess the impact on bone mineral density.The IBIS-II is a randomized placebo controlled trial that began in 2003  32]; re; re32]; in situ, lobular carcinoma in situ, atypical ductal and lobular hyperplasia, hip and vertebral fracture risk, cardiac end points and quality of life measures. Exemestane reduced the relative incidence of invasive breast cancer by 65% . Se. Se33]. r by 65% . In addiThere is currently a placebo controlled trial underway assessing breast cancer preventive capability of letrozole in BRCA mutation carriers . A phaseNone of the agents described above prevent estrogen negative breast cancer. Evidence is emerging that some agents used clinically to address other diseases are effective in reducing estrogen positive and negative breast cancers  37,38,3,45,46,47Bisphosphonates inhibit osteoclastic activity and have been used to prevent bone resorption in metastatic disease. They have also been found to reduce bone loss induced by aromatase inhibitors . BeneficMetformin is the most commonly used AMPK activator in the management of type II diabetes and polycystic ovarian syndrome. Laboratory data demonstrates that this drug can also inhibit growth of breast cancer tumor cells . RetrospInhibitors of HMG-CoA reductase have been in clinical use as lipid lowering drugs for a long time. Observational studies suggest that they may have a role in prevention of breast cancer, but four meta-analyses have found inconsistent trends with no such results ,44,45,46in situ and invasive breast cancer cells [Aspirin is an inhibitor of COX-1 and COX-2. These enzymes are expressed er cells . Epidemier cells .A synthetic steroid, tibolone, showed a 68% risk reduction in breast cancer and beneficial effects on bone mineral density and cardiovascular disease postmenopausal women in the LIFT trial . This fiA vitamin-A derivative, fenretinide, has been studied in the context of breast cancer prevention. Some trend was seen in premenopausal women without overall convincing evidence . A studyin vivo demonstration of inhibition of progression of atypia to in situ cancer and in situ to invasive cancer by lapatinib [New research interest is developing in evaluating and targeting the HER2 neu family for breast cancer prevention based on apatinib .3 have been shown to down regulate growth pathways of breast cancer cells and are therefore promising for future investigation of their cytostatic effect in terms of prevention [In addition, melatonin and vitamin Devention .et al. demonstrated that almost two-thirds of women who are at high risk of developing breast cancer, actually are interested in chemoprevention, but require more information, mainly from their primary care physicians [versus benefit associated with the use of chemoprevention; and (ii) lack of biomarkers to assess response to preventive treatment as a surrogate for actual deterrence of cancer. First, in the past few years researchers have attempted to develop tools to aid physicians with risk-benefit analysis; Gail et al. published an exhaustive risk-benefit analysis in 1999 [et al. have published tables assessing benefit/risk of tamoxifen versus raloxifene in women 50 year of age and older and in those with and without a hysterectomy [Several decades of invested time, resources and research efforts has led to major advances in chemoprevention strategies to reduce breast cancer risk specifically in high risk women. Despite this major investment, the acceptance of breast cancer chemoprevention by physicians and patients is dismal ,10,11,12ysicians . This siysicians . There a in 1999 . This st in 1999 . Freedmaerectomy . Second,erectomy . Researcerectomy .et al. is a step in the right direction, where the term “chemoprevention” is deemed inappropriate and to be replaced by “preventive therapy” [The Paradox between Evidence and Advocacy Inaction: The discussion of factors contributing to our lack of appreciation of the evidence based trials in breast cancer prevention is not complete without the mention of “advocacy inaction.” In retrospect, when the P-1 study was reported, many physicians received free Gail Model risk calculators from the pharmaceutical companies that held patents for tamoxifen. In 2000, it was estimated that 120,000 women were receiving tamoxifen as preventive treatment! This number decreased to 60,000 in 2005 . Now thatherapy” . This mitherapy” , to guidEvidence-based research both at the clinical and laboratory level have resulted in significant strides in the availability of new and effective chemoprevention options to reduce breast cancer risk. Overall both SERMs and AI’s have demonstrated favorable benefit-risk balance and most likely to benefit high risk women yet these medications are underutilized by primary care providers and patients. Several significant barriers to uptake of chemoprevention have been described including inability to accurate calculate individual risk, perceived risk of serious adverse events and lack of biomarkers to determine response to medication. Given the magnitude and burden of breast cancer there is no doubt that greater emphasis needs to be made on implementation of chemoprevention medications into clinical practice. National societies with a mission to improve quality of care in breast disease must prudently assist physicians caring for high risk women by providing tools for shared decision models that encourage counseling and education about the available chemoprevention options and take into account the patient’s personal values and interest in reducing breast cancer risk.


Metabolic Syndrome (MS) has been correlated to breast carcinogenesis. MS is common in the general population (34%) and increases with age and body mass index. Although the link between obesity, MS and hormone related cancer incidence is now widely recognized, the molecular mechanisms at the basis of such increase are still poorly characterized. A crucial role is supposed to be played by the altered insulin signalling, occurring in obese patients, which fuels cancer cell growth, proliferation and survival. Therefore we focused specifically on insulin resistance to investigate clinically the potential role of insulin in breast carcinogenesis.975 patients were enrolled and the association between MS, insulin resistance, and breast cancer was evaluated. Women were stratified by age and menopausal status. Insulin resistance was measured through the Homeostasis Model Assessment score (HOMA-IR). The cut off value to define insulin resistance was HOMA-IR ≥ 2.50.2 was calculated. Both cases and controls were characterized by BMI ≥ 25 Kg/m2 (58% of cases compared to 61% of controls). Waist circumference >88 cm was measured in 53% of cases - OR 1.58- (95% CI 0.8-2.8) and in 46% of controls. Hyperinsulinemia was detected in 7% of cases – OR 2.14 (95% CI 1.78-2.99) and only in 3% of controls. HOMA-IR score was elevated in 49% of cases compared to 34% of controls [OR 1.86], suggesting that insulin resistance can nearly double the risk of breast cancer development. Interestingly 61% of women operated for breast cancer (cases) with HOMA-IR ≥ 2.5 presented subclinical insulin resistance with fasting plasma glucose levels and fasting plasma insulin levels in the normal range. Both android fat distribution and insulin resistance correlated to MS in the subgroup of postmenopausal women affected by breast cancer.Higher prevalence of MS (35%) was found among postmenopausal women with breast cancer compared to postmenopausal healthy women (19%) [OR 2.16]. A broad range of BMI spanning 19–48 Kg/mOur results further support the hypothesis that MS, in particular insulin resistance and abdominal fat, can be considered as risk factors for developing breast cancer after menopause. We suggest that HOMA-IR, rather than fasting plasma glucose and fasting plasma insulin levels alone, could be a valuable tool to identify patients with subclinical insulin resistance, which could be relevant for primary prevention and for high risk patient screening. Metabolic syndrome (MS), characterized by central adiposity, insulin resistance, low serum high density lipoprotein cholesterol (HDL-C), high serum triglycerides, and high blood pressure, seems to be in strict correlation to breast carcinogenesis ,2. MS, a2) was calculated from weight and height values and evaluated according to the World Health Organization classification . The waist and hip ratio (WHR) was obtained from waist and hip circumference, measuring the smallest circumference of both to discriminate between android and gynoid fat distribution. Fasting plasma glucose, insulin levels, HDL-C, triglycerides, were assessed from blood samples. In particular, fasting plasma glucose, HDL-C and triglycerides were measured according to the NCEP ATP III criteria. Blood samples were locally assessed at the central laboratory of the National Cancer Institute. Sample collection was standardized by time at blood withdrawing. Samples were taken in the early morning hours (between 8.00 and 10.00 A.M.). Fasting plasma glucose assessment was measured by the COBAS INTEGRA Glucose HK cassette (GLUC2). It contains an in vitro diagnostic reagent system intended for use on COBAS INTEGRA systems for the quantitative determination of the glucose concentration in hemolysate. Electrochemiluminescence immunoassay (ECLIA) applied on Cobas 6000 was used for insulin concentration measurement. Enzymatic colorimetric test CHOD – POD was employed for cholesterol dosage. The GPO - POD method based on the enzymatic determination of glycerol using the enzyme glycerol phosphate oxidase (GPO) was used for triglycerides determination. Fresh, clear, unhemolyzed serum was the specimen of choice. The specimen was collected following the guidelines of NCCLS document H4-A3. Diabetes was considered an exclusion criterion. Diabetes was diagnosed on laboratory determinations with fasting plasma glucose assessment ≥ 126 mg/dl according to American Diabetes Association guidelines [975 women spanning 35–75 years in age have been enrolled in our nested case–control observational retrospective study between 2008 and 2011 . Waist circumference >88 cm was measured in 53% of cases - OR 1.58- (95% CI 0.8-2.8) and in 46% of controls. Hypertriglyceridemia was found in 14% of cases respect to 9% of controls [OR 1.4]. 27% of cases presented HDL-C <50 mg/dl compared to 24% of controls [OR 1.09]. High blood pressure was detected in 40% of cases – OR 1.58 (95% CI 0.37-0.47) respect to 30% of controls. Hyperinsulinemia was detected in 7% of cases – OR 2.14 (95% CI 1.78-2.99) and only in 3% of controls  with Odds Ratio of postmenopausal breast cancer of 1.63 (95% CI 1.09- 1.79). Overall, considering the 975 women included in the study (age range = 35–75 years) MS prevalence was higher among cases (27%) than in controls (14%). We did not find significant differences in MS prevalence between cases and controls among premenopausal patients, whereas the prevalence of MS in postmenopausal was 35% for cases OR 2.16 (95% CI = 0.31 to 0.39) and 19% for controls (95% CI = 0.16 to 0.23). MS was detected in one third of post-menopausal cases. A broad range of BMI spanning 19–48 Kg/mHOMA-IR was ≥ 2.50 in 49% of cases – OR 1.86 (C.I.95% =0.42 to 0.52) respect to 34% of controls (C.I.95% =0.03 to 0.38), showing a positive trend for breast cancer patients. Interestingly, 80% of insulin resistant cases were postmenopausal, whereas premenopausal were only 20% (C.I.95% =0.85 to 0.74 vs 0.33 to 0.7)  with waist circumference > 88 cm  with HOMA-IR ≥ 2.5 presented fasting plasma glucose levels and fasting plasma insulin levels in the normal range (group 1). Only 5% of cases showed high levels of both fasting plasma glucose and fasting plasma insulin (group 2). 7% were euglycemic, but plasmatic insulin levels were high (group 3). 27% of patients presented as hyperglycaemic, but insulin levels were in the normal range (group 4).Our data still confirm the existing linkage between metabolic alterations and breast cancer. Higher prevalence of MS 35%) among postmenopausal women with breast cancer compared to healthy women 19%) OR 2.16] was found. No statistical significant difference in premenopausal women was found. Probably, alterations in metabolic signalling that activate pro-mitotic and anti-apoptotic pathways are more likely to occur in postmenopausal women. Moreover all MS features were positively, but weakly associated to breast cancer risk. As expected from the recent literature, android fat distribution-consisting in WC >88 cm- was positively associated to MS and breast cancer more than BMI. Waist circumference >88 cm was measured in 53% of cases - OR 1.58 (95% CI 0.8-2.8) and in 46% of controls, whereas no differences in BMI were found between cases and controls. A majority of prospective studies show breast cancer risk to be higher in obese postmenopausal women with upper abdominal adiposity than in those with overall adiposity. The evidence is more limited and inconsistent in the case of premenopausal women. Overall adiposity in women adversely affects breast cancer risk mainly by greater exposure of mammary epithelial tissue to endogenous oestrogen and to pro-inflammatory cytokines. Upper abdominal adiposity appears to involve an additional effect related to the presence of insulin resistance . Waist c9% [OR 2.5% among  was founOur data, consistently with our previous study, further support the hypothesis that MS can be considered as a risk factor for developing breast cancer in postmenopause . We specHOMA-IR: Homeostasis model assessment – insulin resistance; NCEP: National cholesterol program; ATP III: Adult treatment panel III; IGF1: Insulin-like growth factor 1; IGF2: Insulin-like growth factor 2; MS: Metabolic syndrome; BMI: Body mass index; WC: Waist circumference; WHR: Waist hip ratio; LDL cholesterol: Low density lipoprotein - cholesterol; HDL cholesterol: High densityThe authors declare that they have no competing interests.IC realized the protocol design, EE wrote the draft and edited the manuscript. FP revised critically the manuscript. AG has given final approval of the version to be published. MM, AC and MG contributed to the statistical design. NM recruited metabolic syndrome affected women. GDA and GC conceived the study idea, supervised the study design. SL and TP supervised the protocol development. MDA and AF recruited patients for the study and selected patients at risk of breast cancer. EC and GE took blood samples and analyzed them in the lab. GB has contributed in data managing and preparing informed consent. All authors read and approved the final manuscript.


BRCA1 or BRCA2 gene mutation. Such women have an increased risk of developing a new primary breast and/or ovarian tumor, and may therefore opt for preventive surgery . It is common practice to offer high-risk patients genetic counseling and DNA testing after their primary treatment, with genetic test results being available within 4-6 months. However, some non-commercial laboratories can currently generate test results within 3 to 6 weeks, and thus make it possible to provide rapid genetic counseling and testing (RGCT) prior to primary treatment. The aim of this study is to determine the effect of RGCT on treatment decisions and on psychosocial health.It has been estimated that between 5% and 10% of women diagnosed with breast cancer have a hereditary form of the disease, primarily caused by a BRCA gene mutation are being recruited from 12 hospitals in the Netherlands. Participants are randomized in a 2:1 ratio to either a RGCT intervention group  or to a usual care control group. The primary behavioral outcome is the uptake of direct bilateral mastectomy or delayed prophylactic contralateral mastectomy. Psychosocial outcomes include cancer risk perception, cancer-related worry and distress, health-related quality of life, decisional satisfaction and the perceived need for and use of additional decisional counseling and psychosocial support. Data are collected via medical chart audits and self-report questionnaires administered prior to randomization, and at 6 month and at 12 month follow-up.In this randomized controlled trial, 255 newly diagnosed breast cancer patients with at least a 10% risk of carrying a This trial will provide essential information on the impact of RGCT on the choice of primary surgical treatment among women with breast cancer with an increased risk of hereditary cancer. This study will also provide data on the psychosocial consequences of RGCT and of risk-reducing behavior.The study is registered at the Netherlands Trial Register (NTR1493) and ClinicalTrials.gov (NCT00783822). BRCA1 or BRCA2 gene [BRCA1 or BRCA2 genes have up to an 85% lifetime risk of developing breast cancer, and can also have up to a 60% lifetime risk of developing ovarian cancer [BRCA1/2 mutation have a 3% annual risk of developing contralateral breast cancer, with the overall risk being as high as 52% by the age of 70 [BRCA1/2 carriers who were diagnosed with breast cancer before the age of 40 years, the cumulative risk of developing contralateral breast cancer after a follow up of 25 years is even higher, i.e. 63% [Breast cancer is the most frequently occurring malignancy in women in the Netherlands. Approximately 1 in 8 women will develop the disease during their lifetime, resulting in approximately 12,000 new cases annually. A positive family history of breast cancer is the single strongest risk factor for developing the disease. In 5%-10% of the cases, breast cancer has a hereditary basis. In 15%-30% of patients from high-risk families, breast cancer is caused by a germline mutation in the CA2 gene . A similn cancer . Breast i.e. 63% . Given tBRCA1 or BRCA2 gene mutation, and are thus, in general, considered as candidates for DNA testing. Genetic counseling and DNA testing for breast cancer usually takes approximately 4-6 months to complete. However, some hospitals and non-commercial laboratories are now able to generate test results within 3 to 6 weeks. This technology of rapid genetic testing creates new opportunities for providing both women and their treating surgeons with information potentially relevant for deciding between available treatment options, including type of surgery and adjuvant therapy [The objectives of cancer genetic counseling, in general, are to improve knowledge and understanding of the possible genetic basis of the disease, of personal risks of developing cancer, and of the possible consequences of undergoing genetic testing ,11. In t therapy -19.BRCA1/2 mutation carriers will accept the invitation to undergo RGCT, and that the DNA test results can have a substantial impact on the choice of surgery [BRCA1 or BRCA2 mutation opted for a bilateral mastectomy, with some opting for a delayed CPM instead of direct BLM. Additionally, between 16% and 24% of high-risk patients who test negative for a BRCA1/2 mutation opted for BLM [Newly diagnosed patients who learn that they are gene mutation carriers may decide to undergo a mastectomy rather than a lumpectomy, or bilateral mastectomy (BLM) rather than unilateral mastectomy. Recent studies have shown that BLM and delayed contralateral prophylactic mastectomy (CPM) substantially reduce the risk of contralateral breast cancer, while studies on survival have yielded mixed results -23. Addi surgery ,25. In tThe psychosocial impact of genetic testing in recently diagnosed breast cancer patients has been the subject of only limited study . AlthougTo summarize, recent advances in the technology of genetic testing for breast cancer open the possibility of offering women with a suspected hereditary form of the disease the opportunity to undergo RGCT in the period of time between receiving the diagnosis and undergoing primary treatment. For those high-risk women who opt for direct BLM or delayed CPM, there are clear advantages in terms of reduction in the risk of contralateral disease, although an improvement in survival has not yet been convincingly demonstrated ,22. WomeBRCA1 or BRCA2 gene mutation. RGCT is being offered to women shortly after diagnosis, prior to surgery. The comparison group is composed of women who receive usual care (UC), in which RGCT is available but is rarely recommended or requested.This study is evaluating the behavioral and psychosocial effects of the routine offer of RGCT to newly diagnosed primary breast cancer patients who meet criteria for being at-risk of having a The specific research hypotheses are:1. A significantly greater percentage of women in the RGCT group as compared to the UC group will undergo a direct bilateral mastectomy (BLM).2. A significantly greater percentage of women in the RGCT group as compared to the UC group will undergo a delayed prophylactic contralateral mastectomy (CPM).3. Women in the RGCT group will report significantly lower levels of perceived cancer risk, cancer worries, and cancer-related distress at 12 month follow-up than women in the UC group.4. Women in the RGCT will have significantly higher levels of knowledge of genetic issues in breast cancer, and higher levels of decisional satisfaction than women in the UC group.5. Following from hypotheses 1 and 2, women in the RGCT group will report significantly more problems with body image and sexuality than those in the UC group. No significant differences will be observed between the RGCT and the UC groups on other HRQL outcomes.This is a multicenter, randomized, controlled trial in which patients are randomized to RGCT or to UC on a 2:1 basis. The primary clinical outcomes include: the uptake of direct BLM or of delayed CPM. Data on surgical outcomes will be abstracted from the medical records. This protocol follows the CONSORT guidelines .Psychosocial outcomes include: perceived risk for ipsilateral and contralateral breast cancer and for ovarian cancer, cancer-related worry and distress; knowledge of genetic aspects of breast cancer; decisional satisfaction; and HRQL. The study also is evaluating women's experience of and satisfaction with RGCT , and the surgeons' experience with RGCT. Standardized questionnaires are administered at study entry (prior to randomization), and at 6 month and 12 month follow-up  who meet at least one of the criteria for referral for genetic counseling and DNA analysis according to the Dutch Institute for Healthcare Improvement (CBO). These criteria are: (1) age at time of breast cancer diagnosis less than 35 years; (2) previous history of cancer in the contralateral breast, with the first breast cancer diagnosis at less than 50 years of age; (3) previous personal history of ovarian cancer; (4) a family history of ovarian cancer; (5) a first degree male relative with breast cancer; (6) breast cancer diagnosed under the age of 50 years, with a first degree relative diagnosed with breast cancer under the age of 50 years; (7) breast cancer diagnosed under the age of 50 years, with a relative with prostate cancer diagnosed under the age of 60 years; (8) breast cancer, with two or more relatives from the same side of the family diagnosed with breast cancer, where at least one family member (either the patient or a relative) was diagnosed under the age of 50 years; or (9) a proven mutation . Women aPatient recruitment began in November 2008, following approval by the ethical review committees of the participating hospitals. Participating surgeons make use of an 11-item checklist to determine patient eligibility. All patients who meet the study inclusion criteria are informed by the surgeon or nurse practitioner about the study, and are given an envelope containing an information letter, a consent form and the baseline questionnaire. Eligible patients receive a phone call by a member of the research team within a few days, in order to carry out the informed consent procedures and to administer the baseline questionnaire to consenting patients. Patients are then randomized to the RGCT or the UC group in a 2:1 ratio. The computerized randomization is stratified per hospital and blocked per 9 cases . These 1Women in the RGCT group receive an appointment with a clinical geneticist or genetic counselor within one week following randomization, either at the Family Cancer Clinic of the Netherlands Cancer Institute/Antoni van Leeuwenhoek Hospital or at the Department of Medical Genetics of the University Medical Centre Utrecht. Those patients who decline to undergo RGCT are given the opportunity to receive genetic counseling and testing at a later time.BRCA1 and BRCA2 genes can be taken on the same day. For women whose test result will not be of immediate consequence for their choice of treatment, the timing of the DNA testing does not need to be accelerated . Examples are women who, from a medical point of view, cannot opt for breast conserving therapy and have already had a contralateral mastectomy, women who do not wish to take immediate secondary preventive measures, or women whose family history provides them with sufficient reasons to undergo bilateral treatment regardless of whether a mutation can be found.While the standard steps involved in genetic counseling are followed, the process is accelerated when necessary. All patients are asked to complete a standard, detailed family history form in order to draw a three-generation pedigree. Where possible, confirmation of the (age at) diagnosis of the affected family members is confirmed via medical record audits following required informed consent procedures. At the time of the first consultation with the clinical geneticist, the urgency of the steps to be taken are discussed and a decision about DNA testing is made. If the patient agrees, a blood sample for testing for mutations in the Where it is anticipated that the DNA test results could influence treatment decisions, a fast-track procedure is used and the results are made available within 3 to 6 weeks. From a medical point of view, this timeframe is sufficiently short to inform patients and clinicians about the results before definite treatment decisions have to be made.The number of contacts between the patient and the clinical geneticist prior to surgery depends on the complexity of each individual case. For women who choose not to undergo DNA testing, this may be limited to a single session. For women who undergo DNA testing, at least one additional session is held in order to discuss the DNA test results. All results of the RGCT are forwarded to the treating surgeon, and consultation between the clinical geneticist and surgeon takes place prior to and following the patient's first appointment with the clinical geneticist.BRCA1/2 carriers and to all women who are considering undergoing BLM regardless of whether they have undergone DNA testing. Where appropriate, referrals are made to mental health caregivers in the hospital. The need for and uptake of more intensive psychosocial care during subsequent treatment are being assessed as part of the study.Psychosocial support is offered routinely to all women who opt for rapid DNA testing, Women in the UC condition receive standard advice and care from their treating surgeon. In relation to the possible hereditary nature of their disease, this typically involves discussion of the family history and of appropriate surgical options. In some cases, patients may be referred for genetic counseling or may self-refer. However, in current practice, this occurs rarely during the pre-surgery period ,39.The patients' age, education, marital status, ethnic background, work status and general health status are obtained via the baseline questionnaire. Data on family pedigree and genetic risk status are obtained via a questionnaire. Clinical data, including diagnosis, tumor characteristics and treatment history  are obtained via both questionnaire and medical record audit. Results of the genetic counseling and testing, including genetic test results, are obtained from the records of the participating departments of clinical genetics.The patients' definitive surgical treatment decision is determined via medical record audit. Via questionnaires women are asked to report the factors motivating their choice of treatment.Risk perception is assessed with 4 items adapted from previous studies [ studies -42 that Cancer worries are assessed with 8 items, 6 of which are adapted from previous work by Watson [y Watson ,43, thatpsychological distress. The HADS contains 14 items. Both a total score and separate scores for anxiety and depression can be calculated. The HADS has been validated for use in the Dutch population, showing good psychometric properties, with Cronbach's alphas for both the anxiety and depression scales >0.70 [The Hospital Anxiety and Depression Scale (HADS)  is used es >0.70 -47.Cancer-specific distress is assessed with the Impact of Events Scale (IES), a 15-item Likert-scale organized into 2 subscales: intrusive thoughts and feelings, and avoidance of thoughts and feelings related to the stressful situation. In this case, the stressful situation is the diagnosis of breast cancer [t cancer . The IESt cancer .Satisfaction with decision-making is assessed with the Satisfaction with Decision Scale (SWD) [le (SWD)  and the le (SWD) ,52. The le (SWD) . The 16-Knowledge of breast cancer and its genetic aspects is assessed with a 7-item, true-false-don't know questionnaire adapted from Claes et al. [s et al. ,53.Health-related quality of life is assessed with the EORTC QLQ-C30 [ QLQ-C30  and the  QLQ-C30 . The QLQPerceived influence of the surgeon on treatment choice is assessed with a series of questions adapted from Schwartz et al. . Women iBRCA1/2 carriers, and to allow for secondary analyses . The percentages indicated above are based on the following assumptions: (1) based on the participating hospitals' experiences in the previous three years, 5% of the women in the UC arm are expected to choose bilateral mastectomy; (2) in the RGCT arm, it is expected that 20% will test positive for a BRCA1 or BRCA2 mutation, of whom, on average, 50% will opt for a bilateral mastectomy. Of the remaining 80% of women in the RGCT arm, we expect a 10% uptake of bilateral mastectomy. For the remaining, primarily self-report outcomes , the sample of 255 participants is more than sufficient to detect a 0.5 standard deviation between-group difference in mean scores. Based on data obtained from the cancer registries of the Integral Cancer Centers of Amsterdam and Middle Netherlands, and on data provided by the participating hospitals, it is estimated that there will be a total of 2550 newly diagnosed breast cancer patients during the recruitment period. Approximately 15% of these women is expected to be eligible for participation. Based on prior experience with recruitment of patients into similar studies, we expect an 80% response rate. This results in an expected N of 306 patients. This allows for an attrition rate of 17%, while retaining 255 women for the primary analysis.The sample size calculations are based primarily on the type of surgery chosen, and specifically on the uptake of bilateral mastectomy. With a total sample of 255 women (170 in the RGCT arm and 85 in the UC arm), the study will have 80% power to detect a difference of 18% versus 5% in the uptake of bilateral mastectomy, with the p-value set at 0.05. The sample size ratio of 2:1 was chosen to ensure that the RGCT sample is sufficiently large to obtain stable estimates of bilateral mastectomy and delayed prophylactic contralateral mastectomy uptake among Analyses will first be performed to evaluate the comparability of the RGCT and the UC groups at study entry in terms of sociodemographic and clinical characteristics. Student's t-test or appropriate non-parametric statistics will be used, depending on the level of measurement. If the groups are not comparable on one or more background variables, those variables will be employed routinely as covariates in subsequent analyses. Between group differences in choice of surgery will be tested using the chi-square statistic or, if statistical adjustment is required for covariates, multiple logistic regression analysis. Analysis of (co)variance will be employed to assess group differences at 6 and 12 month follow-up in risk perception, psychological distress, knowledge, decisional satisfaction, and HRQL. Where appropriate, sociodemographic and clinical background variables, as well as baseline scores on the outcomes of interest, will be used as covariates. Effect sizes will be calculated using standard statistical procedures. Supplementary, descriptive analyses  will be used for reporting the patients' experiences with RGCT. All primary analyses will, to as great an extent as possible, be conducted on an intention-to-treat basis. That is, all women in the RGCT group will be included in that group in the analyses, regardless of whether they actually carried through with RGCT. Supplementary analyses will be undertaken to examine sociodemographic, clinical and psychosocial factors associated significantly with (non-) attendance at the RGCT and uptake of BLM.BRCA1 or BRCA2 gene may opt for additional preventive surgery following their initial surgical treatment. A complicating factor in delaying genetic counseling and testing until after the completion of primary treatment is that, when that treatment includes radiotherapy, additional, preventive surgical procedures  may be quite challenging for the plastic surgeon [BRCA-associated cancer [It is common practice to refer breast cancer patients with suspected hereditary breast cancer for genetic counseling and testing after their initial treatment has been completed . Women f surgeon . By offed cancer .The major methodological strength of this study is the use a randomized controlled trial design which will allow a rigorous test of the effects of RGCT with optimal internal validity. The relatively large sample size and the use of primarily standardized measures represent additional strengths of the study. Finally, the trial's multicenter nature should increase the external validity or generalizability of the study findings.A limitation of this study is the relatively short period of follow-up (12 months). While this is sufficient for examining the effect of RGCT on primary treatment choice and on short term psychosocial outcomes, it does not permit longer term follow-up on these latter outcomes.This study is expected to provide important information on the impact of RGCT among newly diagnosed breast cancer patients on the choice of surgical treatment and on psychosocial well-being. Since RGCT is anticipated to become common practice in the future, the results of this study can contribute to improving the quality of multidisciplinary breast cancer care.NutsOhra Foundation, a charitable fund linked to the private insurance company NutsOhra, has financially supported this study. There are no other competing interests.NKA, MGEMA and SV are the principal investigators of this study. MRW is the doctoral student on this study, and generated the first draft of this manuscript based on the study protocol. EMAB, DEEH, and HBV contributed to the development of the study protocol. EJThR and RvH are the lead surgeons. FH and RBvdL are the collaborating molecular geneticists.All authors approved the final version of the manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2407/11/6/prepub


To assess the association between height and risk of cancer and cancer death.The metabolic syndrome and cancer project is a prospective pooled cohort study of 585,928 participants from seven cohorts in Austria, Norway, and Sweden. Hazard ratios (HRs) and 95 % confidence intervals (CIs) for cancer incidence and death were estimated in height categories and per 5-cm increment for each cancer site using Cox proportional hazards model.During a mean follow-up of 12.7 years (SD = 7.2), 38,862 participants were diagnosed with cancer and 13,547 participants died of cancer. Increased height (per 5-cm increment) was associated with an increased overall cancer risk in women, HR 1.07 (95 % CI 1.06–1.09), and in men, HR 1.04 (95 % CI 1.03–1.06). The highest HR was seen for malignant melanoma in women, HR 1.17 (95 % CI 1.11–1.24), and in men HR 1.12 (95 % CI 1.08–1.19). Height was also associated with increased risk of cancer death in women, HR 1.03 (95 % CI 1.01–1.16), and in men, HR 1.03 (95 % CI 1.01–1.05). The highest HR was observed for breast cancer death in postmenopausal women (>60 years), HR 1.10 (95 % CI 1.00–1.21), and death from renal cell carcinoma in men, HR 1.18 (95 % CI 1.07–1.30). All these associations were independent of body mass index.Height was associated with risk of cancer and cancer death indicating that factors related to height such as hormonal and genetic factors stimulate both cancer development and progression. To The aim of this prospective cohort study was to assess the association between height and risk of cancer and cancer death in a large prospective cohort in order to provide precise estimates for risk of incident cancer and cancer death overall and for specific cancer sites.This study was conducted within the metabolic syndrome and cancer project (Me-Can), which consists of data from health examinations performed in seven cohorts, which have been described in detail previously . In brieAs part of the health examination data on height, weight and smoking status were obtained. In all cohorts, weight and height were measured with participants wearing light indoor clothes and no shoes, and height was measured to the nearest centimeter.We only used data from first health examination , and we Cancer diagnoses were identified through linkages with the National Cancer Registry in Sweden and Norway and Vorarlberg State Cancer Registry in Austria –21. The Hazard ratios and 95 % confidence intervals (95 % CI) for increased height were analyzed with Cox proportional hazards regression with attained age as the time scale. Participants were followed from date of health examination until date of cancer diagnosis or death of cancer, or until censoring at the date of death from any cause, emigration, or end of follow-up , whichever occurred first.The Cox models were adjusted for ten categories of date of birth and ten categories of age at health examination, and stratified for sub-cohort within the model. The proportional hazards assumption was tested using Schoenfeld residuals and found valid for this model. For total cancer and cancer death, we calculated hazard ratios (HRs) in categories of height. For total cancer and cancer death and also for specific sites, we calculated HRs using height as a continuos variable for 5 cm increment in height.2 (kg/m2)) was divided into categories as defined by WHO  [Body mass index  , and smod above) . For thoWe specifically examined potential effect modification using a separate model with only subjects from Austria and Norway born before 31 December 1945, since participants in these countries may have been affected by dietary restrictions . SimilarTo investigate whether the association with height differed by menopausal status, we calculated HRs of breast cancer in groups according to age at diagnosis; assuming that women before age 50 had not undergone menopause , women aged 50–60 were equivocal regarding menopausal status  and that women above age 60 years had undergone menopause .Smoking-related cancers were defined according to definition by International Agency for Research on Cancer and include cancer of the cervix, colorectum, kidney, liver/intrahepatic bile ducts, larynx/trachea/bronchus/lung, lip/oral cavity/pharynx, esophagus, pancreas, stomach, bladder, and bone marrow (acute and chronic myeloid leukemia) . All remp values lower than 0.05 were considered statistically significant. Calculations were performed with STATA MP/2 version 11.2.All statistical tests were two-sided, and The pooled study cohort consisted of 297,156 women and 288,772 men, in total 585,928 participants with a mean age at health examination of 43.1 years (SD = 11.0), and mean year of birth 1949 for women and 1948 for men. Mean follow-up time was 12.7 years (SD = 7.2) and mean height at health examination was 164.3 cm (SD = 6.3) in women and 177.3 cm (SD = 6.9) in men, Table 2) versus 7 % of women above 175 cm, and 12 % of men below 170 cm were obese versus 9 % of men above 185 cm, Table Study participants with short stature had a higher BMI than taller participants; 16 % of women below 160 cm were obese  for men of 185 cm and above compared to men of 170–175 cm, p-trend < 0.001, Fig. p-trend = 0.004, and HR 1.10 (95 % CI 1.01–1.19) for men of 185 cm and above compared to men of 170–175 cm, p-trend = 0.0035, Fig. Increasing height was associated with an increased risk of cancer in both women and men: HR 1.22 (95 % CI 1.13–1.22) for women of 175 cm and above compared to women of 160–165 cm, Increasing height (per 5 cm) was associated with an increased risk for total cancer in women, HR 1.07 (95 % CI 1.06–1.09), and in men, HR 1.04 (95 % CI 1.03–1.06), as well as an increased risk for 8 out of 21 cancer sites in women and 9 out of 19 cancer sites in men, Fig. Increasing height (per 5 cm) was associated with an increased risk for total cancer death in women, HR 1.03 (95 % CI 1.01–1.06), and in men, HR 1.03 (95 % CI 1.01–1.05), as well as an increased risk of death from 2 out of 17 cancer sites in women and 2 out of 14 cancer sites in men, Fig. p values for multiple testing, we found an interaction between BMI and height for total cancer in men (p < 0.001), but no interaction between height and smoking. In subsequent analysis of categories of BMI, HRs for total cancer (per 5 cm increment) was slightly higher in men that were overweight or obese; HR 1.06 (95 % CI 1.05–1.08) for BMI 25–30 and HR 1.07 (95 % CI 1.03–1.11) for BMI > 30, as compared to HR 1.02 (95 % CI 1.01–1.04) for BMI < 25. We found no effect modification among those subjects born before 31 December 1945 in Austria and Norway that may have been affected by nutritional restrictions during World War II, after adjustment for multiple testing.After adjusting the There was an association between height and risk of breast cancer in postmenopausal women (age > 60), HRs (per 5 cm increment) was 1.11 (95 % CI 1.07–1.15) for incident breast cancer and HR 1.10 (95 % CI 1.00–1.21) for breast cancer death. There were no associations with breast cancer in premenopausal women (age < 50); HR 0.98 (95 % CI 0.94–1.02), or breast cancer death, HR 1.02 (95 % CI 0.94–1.11).There were no significant differences in height-associated HRs for total cancer in non-smoking-related cancers and smoking-related cancers in women, Fig. In this population-based study with more than 38,800 cancer cases and 13,500 cancer deaths, height was associated with an increased risk of cancer incidence and death for all sites combined. The highest height-related HR for cancer incidence was found for malignant melanoma in both women and men. For shared-site cancers, height was positively associated with risk in both women and men for lymphohematopoietic malignancies, colon and rectal cancer, and non-melanoma and melanoma skin cancer. For thyroid cancer, the association was restricted to women and for renal cell carcinoma to men. The highest HR for cancer death was observed for breast cancer in postmenopausal women and renal cell carcinoma in men. For shared-site cancers, height was positively associated with death of colon cancer in women, and for men the association was of border line significance. Associations to death of lymphohemapoietic malignancies and renal cell carcinoma were restricted to men.Our study has several strengths, it was large and population-based, it included both cancer diagnosis and death from different cancers, height was measured at health examination, and the end points of cancer diagnoses were obtained through linkages with national cancer registers with almost complete capture of cancer cases –21. HoweIn our study, as well as in four previous large studies on height and risk of all-sites cancer, height has showed positive association to risk of cancers of the colon, breast, and ovary in women , 13–15. In our study, height-associated HR for total cancer was higher in not smoking-related cancers than in smoking-related cancers in male smokers, similar to the finding in women in the Million Women Study, a population-based study including over 97,300 cancer cases . For womFor cancer death, our findings of positive associations between height and risk of death of breast and colon cancer in women and lymphohematopoietic malignancies and renal cell carcinoma in men are in line with a study on height and the risk of cause-specific death that included over one million individuals and over 47,000 cancer deaths , with thOur finding of an inverse association for height and risk of diagnosis and death of gastric cancer in men was not seen in the Korean all-sites cancer study which included 8,777 male cases of gastric cancer  but is iIn our study, the highest HRs for height and risk of cancer was for malignant melanoma in both women and men. For women, two other studies on all-sites cancer have also shown highest relative risks for malignant melanoma , 14, whiThe incidence of many cancers that occur in both sexes is higher in men than in women. In our study, this was true for colon and rectal cancer and malignant melanoma (data not shown), even after adjustment for smoking status and BMI. Interestingly, one recent study that included 3,466 cases of cancer at shared sites as well as information on several medical and lifestyle risk factors reported that over 30 % of this difference in total cancer risk could be attributed to differences in height .Adult height is determined to a large part by genetic factors, but also by nutrition during childhood and adolescence, mediated by factors in the growth hormone/insulin-like growth factor axis, and other factors such as living conditions and serious disease in childhood , 33. CirThere are genes that are related both to increased height and to oncogenic pathways such as c-Myc, p53, and SMAD3, which are related to increased risk of cancer tumorigenesis . Also, hOur study is, to the best of our knowledge, the first to analyze height in relation to incidence and death of all-sites cancer in the same cohort. For cancer with short overall survival, the estimates of incidence and mortality are expected to concur. In our study, this is mainly evident for the inverse association between height and risk of diagnosis and death of gastric cancer in men. For cancers with longer overall survival, such as cancer of the breast and colon in women in our study, the association between height and risk of cancer death might also to some part indicate an association to more aggressive disease at diagnosis or to progression. However, mortality in cancer is strongly influenced by stage of disease at diagnosis and treatment, factors that we were unable to control for in the present study.Our data from a large prospective pooled European cohort study provide further evidence that height is associated with increased risk of cancer and cancer death, indicating that factors related to height such as genetic and hormonal factors stimulate both cancer development and progression.


TGF-β1 is a multi-functional cytokine that plays an important role in breast carcinogenesis. Critical role of TGF-β1 signaling in breast cancer progression is well documented. Some TGF-β1 polymorphisms influence its expression; however, their impact on breast cancer risk is not clear.We analyzed 1222 samples in a candidate gene-based genetic association study on two distantly located and ethnically divergent case-control groups of Indian women, followed by a population-based genetic epidemiology study analyzing these polymorphisms in other Indian populations. The c.29C>T  and c.74G>C  polymorphisms in the TGF-β1 gene were analyzed using direct DNA sequencing, and peripheral level of TGF-β1 were measured by ELISA.c.29C>T substitution increased breast cancer risk, irrespective of ethnicity and menopausal status. On the other hand, c.74G>C substitution reduced breast cancer risk significantly in the north Indian group (p = 0.0005) and only in the pre-menopausal women. The protective effect of c.74G>C polymorphism may be ethnicity-specific, as no association was seen in south Indian group. The polymorphic status of c.29C>T was comparable among Indo-Europeans, Dravidians, and Tibeto-Burmans. Interestingly, we found that Tibeto-Burmans lack polymorphism at c.74G>C locus as true for the Chinese populations. However, the Brahmins of Nepal (Indo-Europeans) showed polymorphism in 2.08% of alleles. Mean TGF-β1 was significantly elevated in patients in comparison to controls (p<0.001).c.29C>T and c.74G>C polymorphisms in the TGF-β1 gene significantly affect breast cancer risk, which correlates with elevated TGF-β1 level in the patients. The c.29C>T locus is polymorphic across ethnically different populations, but c.74G>C locus is monomorphic in Tibeto-Burmans and polymorphic in other Indian populations. Transforming growth factor beta (TGF-β) signaling is one of the most commonly altered cellular pathways in human cancers CG) to leucine (CTG) change at codon 10 (Pro10Leu) of the protein (29). Another substitution, c.74 G>C (rs1800471), resulting in replacement of arginine (CGG) with proline (CCG) at codon 25 (Arg25Pro) of the protein, has been relatively less studied TGF β are known as low penetrance genes in cancer We conducted the present case-control study on a fairly large sample size to; 1) investigate the association between TGF-β1 polymorphisms (c.29C>T and c.74G>C) and breast cancer risk in India, 2) evaluate variation of the association across ethnically different populations, 3) compare genotype frequencies of these polymorphisms between Dravidian, Indo-European and Tibeto-Burman populations of India, and 4) compare TGF-β1 genotypes with other Asian populations from medico-evolutionary point of view.This case-control study was carried out with the approval of the Ethics Committee of the King George's Medical University, Lucknow. The subject recruitment and sample collection were done only after obtaining written informed consent of the participants.The north Indian group, consisting of 113 patients and 113 control samples, was recruited from the Department of Surgery, King George's Medical University, Lucknow. The South Indian group, consisting of 352 patients and 126 control samples, was recruited from the Rai Memorial Hospital, Chennai, Nizam's Institute of Medical Sciences, Hyderabad, and Kasturba Medical College, Manipal University, Manipal. Women with histopathologically confirmed diagnosis of breast cancer were recruited as cases. Women visiting the clinic for problems other than breast cancer were recruited as controls after proper clinical investigation and/or a mammogram confirming no evidence of breast cancer. Women with any breast disorder or other systemic inflammatory disease were excluded from the control group. General health history of the cases and controls was collected with an appropriately designed proforma. A detailed description of the general and clinical characteristics of the patients is provided in Three  out of four major linguistic groups, inhabiting the Indian mainland, have been included in this study. After analyzing Indo-European case-control group from northern India and Dravidian case-control group from southern India, we extended the analysis to the Tibeto-Burman populations from north-eastern India. Striking differences in the allele frequency between Indian and East-Asian (Chinese) populations GAGGCCCTCCTACCTTTTG (F) and GCAGCTTGGACAGGATCT (R), and PCR products were analyzed on 2% agarose gel stained with ethidium bromide. The amplified products were analyzed by direct DNA sequencing using big dye chain terminator cycle sequencing kit (ABI) on a 3730 DNA analyzer (Applied Biosystems).Isolation of DNA for genotyping was carried out as described in our earlier report http://ihg.gsf.de/cgi-bin/hw/hwa1.pl was employed for this purpose. The frequencies of the two alleles at the polymorphic sites were compared between cases and controls to find the risk allele. Genotype data were compared using 2×3 contingency table of Chi Square test or Fisher's exact test using statistical computational tools available at http://www.vassarstats.net. Fisher exact P values were calculated using 2×2 or 2×3 contingency tables, but wherever the software could not calculate Fisher exact values due to large sample size, Chi Square P value was used. Peripheral values of TGF- β1 were compared between cases and controls using non-parametric Mann-Whitney U-test. Age dependent multivariate Cox regression analysis was used to assess the genotype associated risk factors of breast cancer, considering genotypes as a risk event and socio-demographic factors as other variables (confounder covariates). Two sided P-values of less than 0.05 were considered significant for statistical inference.Genotype data for control population were subjected to test for fitness in the Hardy Weinberg equilibrium. Statistical computational software available at We did not find any statistically significant difference in general characteristics between cases and controls . HoweverGenotype data were in Hardy Weinberg equilibrium for both north Indian  and south Indian groups . Analysis of the pooled data for all breast cancer patients versus controls showed that C>T substitution increased breast cancer risk  . Group-wGenotype data for this polymorphism were found to be in Hardy Weinberg equilibrium for both north Indian  and south Indian groups . Analysis of the pooled data for both the study groups showed that codon 25 polymorphism was not associated with breast cancer risk  . In grouThe polymorphic status of +29C>T was comparable among the Indo-European (North), Dravidian (South), and the Tibeto-Burman (North-East) Indian populations . InteresWe also measured the serum level of TGF-β1 in a subset of cases and controls of the North Indian group . PeripheTo determine the predictors (covariates) of breast cancer risk, genotype data for both the polymorphisms (c.29C>T and c.74G>C) of North Indians were further analyzed by multivariate Cox regression . None ofWe observed that the c.29C>T substitution at codon 10 of the TGF-β1 gene significantly increases the risk of breast cancer in Indian populations. The patients exhibited a far higher frequency of the substitution in comparison to the controls. We found that the allele frequency at this locus in Indian populations is comparable to other populations across the globe (refer NCBI database). In sub-group analysis, we found this substitution to increase breast cancer risk irrespective of ethnicity, as both North- and South-Indian women having substitution were at an increased risk of breast cancer. Comparison of the pre-menopausal and post-menopausal cases with all controls suggested that c.29C>T substitution increases breast cancer risk irrespective of the menopausal status. Three other studies from India have analyzed c.29C>T locus in breast cancer Published data on c.29C>T polymorphism in breast cancer lack consensus. As a result, five meta-analyses have been conducted on this polymorphism. Interestingly, all five meta-analyses were published in the same year MyBPC3 gene (causing various forms of cardiomyopathy) in these populations despite its presence in almost all other Indian populations at about 4% frequency We observed that c.74G>C substitution was significantly protective against breast cancer in the north Indian population only. North Indian patient population exhibited a higher frequency of the substitution in comparison to the controls. Sub-grouping of North Indian cases according to the menopausal status revealed significant protective effect of this substitution in case of pre-menopausal women only. A clear ethnicity based impact on breast cancer risk of the genotypes at c.74G>C site was evident, as the protective effect of ‘CC’ genotype was not seen in the South Indian group. This polymorphism has been relatively less studied in comparison to c.29C>T substitution. Only one study on breast cancer from India has analyzed this polymorphism, finding no significant difference between cases and controls Highly polymorphic status of the c.29C>T locus among Indian and North-Eastern Indian populations shows widespread existence of this polymorphism. Monomorphism at the c.74G>C locus unveils important medical and evolutionary significance associated with this locus. The absence of the protective allele (C) may suggest relatively higher risk of breast cancer in the Tibeto-Burmans in comparison to the Dravidians and Indo-Europeans. Similarly, the absence of ‘C’ allele in the Chinese populations may indicate increased breast cancer risk in comparison to the Indian populations. This notion is supported by a higher incidence of breast cancer in the Chinese populations in comparison to the Indian populations (Dravidian) as reported in an epidemiological study comparing breast cancer incidence over a period of three decades We observed that TGF-β1 level in the breast cancer patients was significantly elevated as compared to the control group. The elevated TGF-β1 level could be due to a higher frequency of the risk genotypes in the cases. Further analysis on the basis of genotypes suggested that TGF-β1 level of cases in comparison to control was significantly higher in all the genotypes of c.29C>T locus, while in case of c.74G>C locus, it was only significant in absence of “C” allele. Intra-tumoral expression of TGF-β1 has been found to be significantly higher in invasive breast cancer patients in vitro studies are required in order to decipher the mechanism of increased cancer risk in the carriers of certain TGF-β1 genotypes. Significant impact of c.74G>C polymorphism on breast cancer risk encourages more studies on this polymorphism. In addition to identifying genetic risk factors for breast cancer, our study has revealed striking differences in the genetic variations between different ethnic groups, which could have important implications on human health.In conclusion, c.29C>T substitution increases breast cancer risk irrespective of ethnicity and menopausal status. This polymorphism is quite common across the world. c.74G>C polymorphism, on the other hand, showed ethnic variations such that the substitution decreased breast cancer risk in the north Indian populations, but not in their south Indian counterparts. This could be due to a significant impact of other co-occurring genetic variations affecting the risk due to this polymorphism. In other words, the genetic background perhaps becomes more influential in case of c.74G>C polymorphism. The c.74G>C locus is polymorphic across the world with moderate frequency of ‘CC’ genotype, except in case of the North-East Indians, Nepalese, and Chinese populations. Monomorphism at this locus may suggest increased breast cancer risk in these populations in comparison to other ethnic groups. The increased level of TGF- β1 in the patients in comparison to the controls could suggest the possible mechanism of the effect of TGF-β1 polymorphisms on breast cancer. However, further


When comparing postmenopausal women who use estrogen-only HRT to postmenopausal women who do not use HRT, the model predicts an increased risk of breast cancer associated with use of estrogen that diminishes with increasing BMI, with a relative risk of 1.6 for women with BMI of 18, 1.2 for women with BMI of 25, and 1.0 for women with BMI ≥ 30. Model predictions agree with data from five major epidemiological studies.We present a mathematical model that lends support to the hypothesis that estrogen levels mediate the complex relationship between body mass index (BMI), menopausal status, estrogen-only hormone replacement therapy (HRT), and breast cancer risk. Themodel predicts a decrease in the relative risk of breast cancer of 3% per unit increase in BMI(kg/m The relationship between body mass index (BMI), menopausal status, and breast cancer risk is complex. In premenopausal women, higher BMI is associated with a decreased risk of breast cancer, while in postmenopausal women who do not use hormone replacement therapy (HRT) higher BMI is associated with an increased risk of breast cancer . Use of Estrogen pathways provide a biological explanation for the relationship between BMI and breast cancer. For postmenopausal women, estrogen levels increase with increasing BMI, presumably because conversion of androgens to estrogen in adipose tissue is a primary source of estrogen , 5. EstrEstrogen pathways also are hypothesized to explain the relationship between BMI and breast cancer risk in premenopausal women , 10. StuThis qualitative explanation for the relationship between BMI, menopausal status, and breast cancer risk based on estrogen levels has been discussed in detail elsewhere , 9, 12. In this study, we use a mathematical model to evaluate the hypothesis that free estradiol levels drive the association between BMI, menopausal status, estrogen-only hormone replacement therapy, and breast cancer risk. We focus our attention on estrogen-only HRT, also referred to as estrogen replacement therapy (ERT), rather than combined estrogen/progestin hormone replacement therapy. Combined hormone replacement therapy is associated with a greater increase in risk of breast cancer than ERT , suggestWe performed a search of MEDLINE using the MeSH search terms: body mass index, estradiol, breast neoplasm, risk factors, premenopause, postmenopause, menopause, and hormone replacement therapy. We selected articles that reported quantitative relationships between BMI, HRT, and blood serum concentrations of free estradiol or between blood serum concentrations of free estradiol and breast cancer risk. We excluded articles that summarized data using fewer than three strata for BMI, articles on premenopausal women that did not report data on follicular phase estradiol levels, and articles on postmenopausal women based on fewer than 100 observations. We derived model inputs from published meta-analyses where available; in particular, reanalyses from the Endogenous Hormones and Breast Cancer Collaborative Group were the primary source for model inputs for postmenopausal women.EF2) from summary data from the reanalysis of eight prospective studies reported in Table 2 of Key et al. [We derived an exponential relationship between BMI and free estradiol concentration   2) resul2).−13 mol/L of free estradiol corresponds to the concentration of free estradiol predicted for a woman of BMI = 30 according to 13) and s2).The model of BMI and breast cancer reported here supposes that breast cancer risk associated with BMI is mediated primarily by free estradiol, with no other important causes. The model agrees with studies that measure relative risk of breast cancer directly as a function of BMI, lending support to this hypothesis. All of the data sources used in the comparisons that follow were independent of those used to build the model, with the exception of the Pooling Project , which o2). The Pooling Project reported an 11% reduction of relative risk per 4 kg/m2 increase in BMI, which is approximately a 3% reduction per unit increase in BMI [2 increase in BMI, which is about a 1.5% decrease per unit increase in BMI [For premenopausal women, the model finds a reduction in relative risk of 3% per unit increase in BMI  in the Women's Health Initiative , a relatThe ability of this mathematical model to capture complex quantitative relationships suggests that estrogen levels are indeed responsible for the relationship between BMI, ERT, menopausal status, and breast cancer risk. Additional support for this hypothesis comes from an analysis of EPIC data and a reanalysis by the Endogenous Hormones and Breast Cancer Collaborative Group. Both analyses find that after adjusting for free estradiol concentration, the relative risk of breast cancer associated with BMI in postmenopausal women is not significantly different from 1.0 , 23.The model proposes a threshold for free estradiol concentration in postmenopausal women, beyond which additional free estradiol does not incur additional risk of breast cancer. This hypothesis is speculative yet compelling, because it results in a model that neatly reproduces quantitative observations with respect to three phenomena: (i) the leveling off of breast cancer risk due to BMI for BMI > 30 in postmenopausal women who do not use HRT, (ii) the lack of effect of BMI on breast cancer risk for post-menopausal HRT users, and (iii) the attenuated effect of HRT on breast cancer risk for women with high BMI. Alternatively, it is possible that additional free estradiol beyond a certain concentration has a gradually decreasing effect on breast cancer risk rather than no effect. Available data on free estradiol and breast cancer risk could be used to test these hypotheses and to determine where the proposed threshold might lie.The model has a number of limitations. First, the model was based on summary data from a number of different studies, which necessitated certain approximations. For example, summary data points, rather than individual level data, were used to estimate the relative risk of breast cancer per doubling of estradiol for premenopausal women. A second limitation is the variability in estradiol concentrations based on the assay used . HoweverAnother limitation of the model for premenopausal women is that the underlying equations are based on limited data. Evidence from additional studies of hormone levels in premenopausal women was not used to build this model because the authors did not report follicular phase free estradiol concentrations –29. HoweThe current model explains known relationships between BMI, ERT, and breast cancer risk in a mathematical framework that can be extended and refined. The model could potentially be used to estimate the effect of weight loss on breast cancer risk reduction, through estrogen pathway changes. In addition, it may be possible to incorporate physical activity into this estrogen model, since there is evidence that the protective effect of physical activity on breast cancer risk may be mediated through estrogen levels . The modThe estrogen-based mathematical model presented here predicts patterns in breast cancer risk that quantitatively agree with observations from epidemiological studies and randomized clinical trials, including the European Prospective Investigation into Cancer and Nutrition, the Million Women Study, the Cancer Prevention Study II, and the Women's Health Initiative. The model thus gives mathematical support to the hypothesis that estrogen levels are largely responsible for complex relationships between BMI, menopausal status, ERT use, and breast cancer risk.


Effects of dietary factors, such as adherence to Mediterranean diet, multivitamin-multimineral supplements use and alcohol consumption on mammographic breast density, an important biomarker of breast cancer risk, are not sufficiently consistent to elaborate preventive recommendations. This study aims to investigate the association between current diet and mammographic density.We performed a cross-sectional study in 424 pre- and post-menopausal women aged 21 to 84 years. Current Mediterranean dietary pattern, multivitamin-multimineral supplements use, alcohol consumption and potential confounders were assessed with a self-administered questionnaire in the University Hospital Ulm (2007–2008). Radiologists evaluated mammographic density according to the American College of Radiology (ACR) classification, which was summarized in low = ACR1/2 and high = ACR3/4 mammographic density. Logistic regression models were used to assess the association between current diet and mammographic density.Adherance to Mediterranean dietary pattern was inversely associated with mammographic density in the models adjusted for age and BMI . Current use of multivitamin-multimineral supplements was also inversely associated with mammographic density . Further adjustment revealed similar point estimates but the associations were no longer statistically significant. Compared to non-drinkers, excessive alcohol consumption (<10 g/d) was positively associated with mammographic density .Our results show that dietary factors are associated with mammographic density. Adherence to Mediterranean diet and current use of multivitamin-multimineral supplements could be inversely associated with mammographic density and may suggest a protective effect against breast cancer, whereas high alcohol consumption was associated with increased mammographic density. Breast cancer is a malignant tumor, originating from the breast’s glandular tissue. It is one of the most frequent malignant tumors in most Western countries . Breast Mammography is a radiological method for the measurement of breast density  and for Breast density may be a possible surrogate marker in the prevention of breast cancer . It is iThis study aims to investigate the association between Mediterranean dietary pattern, current intake of multivitamin-multimineral supplements, and alcohol consumption with mammographic density.Between April 2007 and September 2008 494 women aged 21 to 84 years, who underwent mammography at the breast center in University Hospital Ulm, were recruited in this cross-sectional study. After informed consent they completed a self-administered questionnaire. From the statistical analysis 65 participants were excluded due to history of breast ablation and breast cancer and 5 participants filled in the questionnaire twice. Thus 424 women remained for the analysis.A study protocol was approved by the ethics committee of the medical faculty of Ulm University.The questionnaire assessed socio-demographic characteristics, including date of birth, nationality, body weight, height and education. Furthermore, participants were asked to comment on their consumption of food, beverages, physical activity and their smoking status. The food questionnaire of this study was partially adapted from the food questionnaire of the Million Women Study . The choIn this study, we collected information of the supplementary intake of vitamins and minerals both individually and combined. Due to the small numbers on single vitamin and mineral use, we investigated the association between intake of multivitamin-multimineral supplements and mammographic density. The corresponding question in our questionnaire was: “Do you take vitamins, minerals or dietary supplements regularly?”Data on the consumption of wine, beer and spirits beverages in glasses per week has been collected to assess a drinking of alcoholic beverages. We calculated how much alcohol in g (gram) each woman consumed according to conversions described in other German studies ,16. The wine: 1 glass = 0.25 liter .beer: 1 glass = 0.3 liter.spirits beverage: 1 glass = 0.02 liter.1 liter wine = 100 g alcohol, and1 liter beer = 40 g alcohol .There were 25 g alcohol in 1 glass wine; 12 g alcohol in 1 glass bier and 6.2 g alcohol in 1 glass spirits beverage . On the We selected the dietary components contributing to a score based on other studies of adherence to Mediterranean diet. Based on other studies on the adherence to Mediterranean dietary pattern ,17 we se2), ever use of hormone replacement therapy (HRT) (yes/no), menopausal status at recruitment  and postmenopausal (≥50) women), age at recruitment (years), mother with history of breast cancer (yes/no), school education (9 years of school/13 years of school), ever use of oral contraceptives (yes/no), age at menarche (years), smoker at recruitment (yes/no), ever breast feeding (yes/no), number of live births , age at the first birth , alcohol consumption at recruitment (yes/no) if not exposure variable.As potential confounders were considered: physical activity at recruitment (yes/no), Body-Mass-Index (BMI) at recruitment  including four categories: ACR 1 = almost entirely fat, glandular tissue <25%; ACR 2 = scattered fibroglandular densities (ca. 25–50% of the breast); ACR 3 = heterogeneously breast dense (ca. 51–75% of the breast); ACR 4 = extremely dense (>75% of the breast) , the intX2-test, the t-test and the Wilcoxon-test were used to analyze the significance of different frequencies and distribution, respectively. We defined the level of statistical significance as 0.05. We used these tests to investigate the significance of relationships between possible confounders  and either the target variable (mammographic density) or influencing variables . Tests for trend across quartiles were performed by assigning the mean level within specific quartiles of alcohol intake to all individuals in that quartile, and using this as a continuous variable in a linear regression. Logistic regression models were fitted to obtain Odds Ratios (ORs) with 95% confidence intervals (95%CIs) for high mammographic density. Additionally interactions between influencing variables and the target variable were tested. Variables, which were identified as potential confounders because they had a biological plausibility and statistically significant relationships with the target variable and/or influencing variables, were tested with manual step-by-step regression. A variable showed an effect and was identified as a confounder, if it had changed estimator more than 10%. The parsimonious models were adjusted for age and BMI based on results of the manual step-by-step regression and/or the biological plausibility. These models were computed stratified by smoking status in order to account for differential association according to hormonal and oxidative stress, respectively. Also the fully adjusted models were calculated, adjusted for physical activity, BMI, HRT use, menopausal status, age, mother with history of breast cancer, school education, ever use of oral contraceptives, age at menarche, smoker at recruitment, number of live births, alcohol consumption. Statistical analysis was assessed with the Analyst Interface of the SAS  Version 9.2.The 2) and most women were physically active (76%). Overall, 80% women had ever taken oral contraceptives and 30% hormone replacement therapy. 80% of the women had ever breastfed.The study sample is characterized in Table There were 35% of the women who consumed multivitamin–multimineral supplements. Alcohol consumption was reported by 67% and smoking by 12%. Most women consumed wine (61%). High scores of Mediterranean diet score (more than 24 points) indicating adherence to Mediterranean diet was observed in 25% of the women. Overall, 56% of the women had high mammographic density (ACR3/4). Among premenopausal women mammographic dense breast parenchyma was more prevalent (73%) than among postmenopausal women (46%).Adherence to the Mediterranean diet was inversely associated with mammographic density adjusted for age and BMI    we observed a statistically significant inverse association of Mediterranean diet score with mammographic density among non-smoking women.Our findings of an inverse association between the current use of multivitamin-multimineral supplements and mammographic density in postmenopausal women are in contrast to results from a case–control study showing that multivitamin-multimineral supplement use is associated with higher breast density among premenopausal women . Our resEpidemiological studies on diet have shown inverse associations between vitamin D intake and mammographic density . For theWomen who take multivitamin-multimineral supplement may have a healthier lifestyle than others. However, differences in the composition of the multivitamin-multimineral supplement pills and the inclusion of potential confounders could have influenced the associations. Data on use of vitamin and mineral supplements and its combination are scarce .In our study, current alcohol intake of more than 10g/d was associated with high mammographic density in pre- and postmenopausal women. Results from prospective ,28, caseThere is evidence linking alcohol by Insulin-like growth factor (IGF) and Insulin-like growth factor binding protein (IGFBP)-3 to mammographic density ,33. In aOne potential limitation of this study is that measurement error is inherent in dietary assessment. However, our data for alcohol were consistent with other data from Germany , and forIn the Mediterranean diet score in cases with no information on food items (e.g. for fish), 0 points were given. However, exclusion of individuals without information revealed similar results in the fully adjusted model without elimination of these women.Since a cross-sectional study was performed, we cannot appraise the time sequence of the associations. The data on exposure variables were collected retrospectively, which may have introduced recall bias. However, it is likely to be non differential.The assessment of the mammograms by experienced radiologists is one of the strengths of our study. In addition, we calculated the fully adjusted and the parsimonious models which revealed similar results but only statistical significance was reached in the parsimonious models.The inter-rater reliability for the analyzed categories of ACR classification as indicator for mammographic density was good. ACR classification of mammographic density is widely applied and it has been shown that it is correlated with more refined measurement methods . InformaIn summary, this study suggests that adherence to the Mediterranean diet and current use of multivitamin-multimineral supplements are associated with mammograhically less dense breast parenchyma as intermediary marker of breast cancer risk. Further studies are needed to investigate the value of dietary intervention in the prevention of breast cancer.BI-RADS: The breast imaging reporting and data system; ACR-categories: Categories of the American College of Radiology; BMI: Body-mass-index; HRT: Hormone replacement therapy; SAS: Statistical analysis system; IGF: Insulin-like growth factor; IGFBP: Insulin-like growth factor binding protein.The authors declare that they have no competing interests.GN, AB conception of the study; CB, BA data collection; OV, GN data analyses; OV wrote the first draft, which was refined by contributions of CB, BA, GN. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2458/13/203/prepub