Young-onset breast cancer (<40 years) is associated with worse prognosis and higher mortality. Breast cancer risk factors may contribute to distinct tumor biology and distinct age at onset, but understanding of these relationships has been hampered by limited representation of young women in epidemiologic studies and may be confounded by menopausal status.We examined tumor characteristics and epidemiologic risk factors associated with premenopausal women’s and young women’s breast cancer in phases I–III of the Carolina Breast Cancer Study . Unconditional logistic regression was used to assess heterogeneity by age (<40 vs. ≥40 years) and menopausal status.In both premenopausal and postmenopausal strata, younger women had more aggressive disease, including higher stage, hormone receptor-negative, disease as well as increased frequency of basal-like subtypes, lymph node positivity, and larger tumors. Higher waist-to-hip ratio was associated with reduced breast cancer risk among young women but with elevated risk among older women. Parity was associated with increased risk among young women and reduced risk among older women, while breastfeeding was more strongly protective for young women. Longer time since last birth was protective for older women but not for young women. In comparison, when we stratified by age, menopausal status was not associated with distinct risk factor or tumor characteristic profiles, except for progesterone receptor status, which was more commonly positive among premenopausal women.Age is a key predictor of breast cancer biologic and etiologic heterogeneity and may be a stronger determinant of heterogeneity than menopausal status. Young women’s breast cancer appears to be etiologically and biologically distinct from that among older women.The online version of this article (doi:10.1186/s13058-016-0736-y) contains supplementary material, which is available to authorized users. Breast cancer among young women (<40 years of age) is associated with more proliferative disease, worse prognosis, and higher mortality than disease among older women (≥40 years) –6. YoungThe present study was conducted within the Carolina Breast Cancer Study (CBCS), a large, population-based case-control study of breast cancer biology and epidemiology enriched for breast cancers occurring among young women. In our analysis, we had two objectives: (1) to identify breast tumor characteristics and epidemiologic risk factors associated with young vs. older women’s breast cancer in the CBCS and (2) to assess heterogeneity in these associations independently by age (<40 years vs. ≥40 years) and menopausal status .n = 5309) from phases I–III for case-case analyses as well as phases I and II cases (n = 2311) and control subjects (n = 2022) for case-control analyses. All study protocols were approved by the University of North Carolina (UNC) School of Medicine Institutional Review Board, and all participants gave their written informed consent.The CBCS is a population-based case-control study conducted in 24 (phases I and II) and 44 (phase III) counties of central and eastern North Carolina. Women were eligible for inclusion if they were 20–74 years of age at the time of diagnosis (cases) or study recruitment (control subjects). As described previously , 21–23, k-statistic = 0.62, concordance = 81 %) [−, PR−, HER2−, HER1+, and/or CK 5/6+), luminal (ER+ and/or PR+), HER2+/ER− , and unclassified . Collection of molecular subtype data is ongoing for phase III cases; only phases I and II cases were included in analyses of these characteristics.Breast tumor tissue and medical records were obtained from local hospitals for all in situ and invasive breast cancer cases. Stage at diagnosis , lymph node status (positive vs. negative for metastasis), estimated tumor size , nuclear grade , and histologic grade  were obtained from medical record reviews, although nuclear and histologic grade data were unavailable for all phase II cases. Immunohistochemistry (IHC) assays conducted at the UNC Immunohistochemistry Core Laboratory were completed to define human epidermal growth factor receptor 2 (HER2) status (positive defined as ≥10 % cells staining vs. negative) . Estroge = 81 %) . Breast  = 81 %) : basal-l2, overweight 25.0–29.9 kg/m2, and obese ≥30 kg/m2) [In-home interviews were conducted by study nurses for all cases and control subjects . Partici0 kg/m2) . Waist-t0 kg/m2) : age at n = 2373). Similarly, to consider the effects of menopause independent of age, case-case analyses were conducted among women ≥40 years of age. However, postmenopausal women ≥40 years of age represent a wide range of ages (40–74 years), and associations estimated within this group are susceptible to residual confounding by age. Therefore, we conducted a sensitivity analysis estimating case-case associations for tumor characteristics among pre- vs. postmenopausal women aged 40–49 years and 40–59 years of age. Analyses were conducted among all women and stratified by race (African American and non-African American) to examine effect measure modification by race.To examine the baseline exposure distributions, descriptive analyses examining the distribution of breast cancer risk factors among all control subjects were conducted. For case-case analyses of tumor characteristics, unconditional logistic regression was used to calculate ORs and 95 % CIs. Age and menopausal status are strongly correlated but may influence breast cancer etiology through distinct mechanisms. To estimate age effects independent of menopausal status, case-case analyses were restricted to premenopausal cases  vs. older (≥40 years) groups were evaluated among premenopausal women and pre- vs. postmenopausal status was evaluated among women ≥40 years. All analyses were adjusted for age (5-year age categories) and race (African American vs. non-African American). Similar to the case-case analyses described above, we restricted our analyses of risk factor associations by menopausal status to pre- and postmenopausal women aged 40–59 years to address residual confounding by age and to control for nonpositivity . Heterogeneity in risk factor associations by age or menopausal status was evaluated by conducting likelihood ratio tests in which the estimated log-likelihood of adjusted models was compared with that of the adjusted model including a multiplicative interaction term for age  and the corresponding risk factor. Statistically significant heterogeneity was defined with α = 0.1. To explore racial differences in etiologic heterogeneity by age and menopausal status, case-control analyses were further stratified by race. Models for age at first live birth, history of breastfeeding, and lifetime breastfeeding duration were restricted to parous women. Statistical significance was defined with α = 0.05. All analyses were performed using SAS version 9.3 software .To identify possible confounders of the risk factor and age-at-diagnosis association, we examined the distribution of breast cancer risk factors among young (<40 years) vs. older (≥40 years) control subjects Table . AlthougTumor characteristics for in situ and invasive cases were examined together in this study, as sensitivity analyses did not reveal any difference in results when excluding in situ cases (results not shown) nor any difference in the prevalence of in situ cases by age Table . In logip = 0.003) and duration of breastfeeding (interaction p = 0.04). Parity and longer time since last term pregnancy (10–19 years) were protective among older women and had either null or weakly increased risk for young women, although this heterogeneity was not statistically significant. High WHR was protective among younger cases and either null (BMI) or associated with elevated risk (WHR) among older women. Oral contraceptive use was more strongly, but not significantly, associated with risk among younger women, while associations with BMI, age at first birth, age at last birth, and age at menarche were similar between young and older premenopausal cases. Thus, patterns of risk factor associations differed substantially between young and older premenopausal women.To evaluate whether young- and older-onset breast cancers are etiologically distinct, we estimated associations with risk factors stratified by age Table . These a+ disease as well as larger tumors than postmenopausal women , in that age at last birth ≥30 years was not associated with increased risk among premenopausal women but did increase risk among postmenopausal women. No other risk factors were differentially associated with pre- or postmenopausal breast cancer after adjusting for age and race.Similarly, stratification on menopausal status showed limited evidence of etiologic heterogeneity . Only HER2 positivity, lymph node positivity, and histologic grade showed a suggestion of heterogeneity by race: Young age was associated with increased HER2 positivity  and increased lymph node positivity  among premenopausal white women but not African American women . Additionally, among white women, younger cases had a higher prevalence of poorly differentiated histologic grade ; this association was qualitatively different among African American women . No strong heterogeneity by race was observed in the associations between tumor characteristics and menopausal status after controlling for age at diagnosis (results not shown).Likewise, little heterogeneity was observed by race for associations between breast cancer risk factors and menopausal status. With regard to breast cancer risk factors, higher WHR increased risk among African American women regardless of age, while age appeared to modify the association between WHR and risk in white women (results not shown). History of breastfeeding and longer breastfeeding duration strongly reduced risk among both young and older African American women , while the protective effect of breastfeeding in white women appeared to be restricted to young women. No other risk factors were associated with breast cancer risk in race- and age-stratified analyses.Among premenopausal women in the CBCS, early-onset breast cancers (<40 years) are more aggressive than those among older women. Young women had more advanced stage disease at diagnosis, larger tumors, more hormone receptor-negative disease, marked pleomorphism, and lymph node positivity than older women. We also found that younger cases were more likely to be nonwhite and to have reduced adiposity (lower WHRs) than older cases. We found evidence for the dual effects of parity on risk, similar to other previous studies , 27–29; + disease may lose receptor expression as menopause ensues. Further work examining PR positivity in relation to age and menopausal status is warranted to replicate these findings. Moreover, many of the associations we detected may reflect a complex combination of etiologic and progression differences. Previous epidemiologic studies have identified heterogeneity in the associations between breast cancer risk factors and risk of distinct tumor subtypes. For example, reproductive and body size exposures are differentially associated with luminal and basal-like tumors [− breast cancer and in our study is associated with young women’s breast cancer. It is possible that patterns of tumor characteristics by age, both in our present study and in other previous studies, reflect these underlying etiologic assumptions.This heterogeneity in the prevalence of aggressive tumor characteristics by age at diagnosis has been well-documented –10, 32, e tumors , 34. BreYoung age and premenopausal status have often been used almost interchangeably to define women with early-onset breast cancer; however, we observed that these factors may be better considered as separate factors. While young vs. older age at onset produced patterns similar to those of pre- vs. postmenopausal status, nearly all menopause associations (with the exception of PR status and nuclear grade) became null after restricting on age, suggesting that heterogeneity in breast cancer characteristics by menopausal status was driven by differences in age. Previous studies have also suggested age-confounding of menopause etiologic associations; for example, Lee et al.  reportedWe observed limited heterogeneity by race in our analyses, suggesting that young women’s breast cancers may have similar etiologies and biological characteristics regardless of race. However, African American women have higher breast cancer incidence prior to age 40 years , 36–38, + tumors among young women. Additionally, in our analyses of ER and PR positivity, we used 5–10 % nuclear staining to define hormone receptor positivity, consistent with clinical standards during the study period. However, this cutpoint differs from current guidelines issued by the American Society of Clinical Oncology/College of American Pathologists, which recommend a 1 % positivity cutpoint [Our results should be interpreted in light of some limitations. Analyses of tumor subtype, HER2 status, and histologic/nuclear grade were limited by missing data for some tumors. Data for tumor grade were unavailable for phase II cases, and data collection for HER2 status is currently ongoing for phase III of the CBCS. In prior work considering the association between HER2 and age at diagnosis, researchers reported mixed findings, although recent studies have suggested increased HER2 positivity among young women , 10, 32.cutpoint . Recent cutpoint , suggestcutpoint , 44, andOur findings suggest that young women’s breast cancer is biologically and possibly etiologically distinct from breast cancers arising in older women. Age appears to be a key driver for breast cancer heterogeneity that is at least as important, or perhaps even more important, than the effects of menopausal status. Clarifying the etiologic and biological features of young women’s breast cancer is important for identifying modifiable targets for prevention of aggressive, early-onset breast cancers.BMI, body mass index; CBCS, Carolina Breast Cancer Study; CK, cytokeratin; ER, estrogen receptor; HER2, human epidermal growth factor receptor 2; IHC, immunohistochemistry; PR, progesterone receptor; WHR, waist-to-hip ratio


Mammographic density is well-established as a risk factor for breast cancer, however, adjustment for age and body mass index (BMI) is vital to its clinical interpretation when assessing individual risk. In this paper we develop a model to adjust mammographic density for age and BMI and show how this adjusted mammographic density measure might be used with existing risk prediction models to identify high-risk women more precisely.We explored the association between age, BMI, visually assessed percent dense area and breast cancer risk in a nested case-control study of women from the placebo arm of the International Breast Cancer Intervention Study I . Linear regression was used to adjust mammographic density for age and BMI. This adjusted measure was evaluated in a multivariable logistic regression model that included the Tyrer-Cuzick (TC) risk score, which is based on classical breast cancer risk factors.P =0.002).Percent dense area adjusted for age and BMI  was a stronger measure of breast cancer risk than unadjusted percent dense area  0.62 versus 0.59). Furthermore, in this population at increased risk of breast cancer, the density residual added information beyond that obtained from the TC model alone, with the AUC for the model containing both TC risk and density residual being 0.62 compared to 0.51 for the model containing TC risk alone (Approximately 16% of controls and 19% of cases moved into the highest risk group (8% or more absolute risk of developing breast cancer within 10 years) when the density residual was taken into account. The net reclassification index was +15.7%.In women at high risk of breast cancer, adjusting percent mammographic density for age and BMI provides additional predictive information to the TC risk score, which already incorporates BMI, age, family history and other classic breast cancer risk factors. Furthermore, simple selection criteria can be developed using mammographic density, age and BMI to identify women at increased risk in a clinical setting.http://www.controlled-trials.com/ISRCTN91879928 (Registered: 1 June 2006).The online version of this article (doi:10.1186/s13058-014-0451-5) contains supplementary material, which is available to authorized users. Mammographic density is well-established as a risk factor for breast cancer . Neverthet al. to  to et alThe subjects of this study are 558 women from the placebo arm of the IBIS-I, a randomized trial of tamoxifen versus placebo in women at high risk of developing breast cancer. The IBIS-I trial is registered with controlled-trials.com as ISRCTN91879928, which has been reported in full elsewhere ,13]. Th. Th13]. Written informed consent to participate in the study and allow access to medical records was obtained from all participants in IBIS-I prior to entry. Further written consent for their mammograms to be used was obtained subsequently. Both IBIS-I and the mammography study were approved by North Somerset and South Bristol Research Ethics Committee. For the IBIS-I density case-control study the mammograms relating to 942 controls (women without breast cancer) and 123 cases (British and Finnish participants diagnosed with breast cancer prior to 1 October 2007) were retrieved from local centres and mammographic density (percent dense area) measured centrally by RW (a consultant radiologist). Film mammograms of the left and right mediolateral oblique views were placed together on the light-box and read as a single entity. Percent dense area was assessed visually to the nearest 5%.Only participants from the placebo arm of the IBIS-I density study  were used in this study as tamoxifen itself has a major impact on both mammographic density and breast cancer development. The majority of cases (64/72) were invasive. Median follow-up for controls was 11.6 years. Median time to diagnosis for cases was 5.1 years.Logistic regression  was used to evaluate the association between breast cancer risk and age, BMI and percent dense area.d = log(z/(1-z)), where z = [0.025 + 0.95{x-min(x)}/max(x)]1/2 and x = percent dense area, was used to ensure that the residuals followed an (approximately) normal distribution. Age and BMI were centred for interpretability. Adjusted percent dense area  was calculated as the difference between the observed percent dense area (after transformation) and the fitted value. Density residuals were standardised to have mean 0 and variance 1. To be certain that all relevant breast cancer risk factors had been included in the density adjustment, we also investigated the effect of adding age at menarche, parity, menopausal status, previous biopsy, hormone replacement therapy, and atypical hyperplasia or/and lobular carcinoma in situ to the model.Linear regression, fitted by ordinary least squares with percent dense area at baseline as the dependent variable and age and BMI as independent variables, was used to adjust percent dense area for age and BMI. The transformation P values were two-sided.In order to explore the additional effect on estimates of breast cancer risk of adding density residual to a breast cancer risk assessment model based on standard breast cancer risks factors, we fitted a logistic regression model with density residual and absolute risk of developing breast cancer within 10 years (as computed by the Tyrer-Cuzick (TC) model ) as indeFor each subject the absolute risk of developing breast cancer within the next 10 years  was calculated first from the TC model then modified to reflect the effect of mammographic density . The net reclassification index for the TC model compared to TC plus density residual, and for the TC model compared to TC plus unadjusted density, was calculated and re-classification tables presented .Agreement between density readings obtained at different time points, or by different readers, was assessed using Lin's concordance correlation coefficient ,19]..19].The number of cases and controls, the total years follow-up and baseline characteristics of the study group are shown in Table The reproducibility of the density readings was assessed by having the images re-read by RW and another trained reader (JS) 10 years after the initial reading. For the baseline mammograms the concordance coefficient between the original and repeat readings by the original reader (RW) was very high : 0.87 to 0.90) with an average difference between readings of −3.04. The concordance coefficient between the original readings by RW and repeat readings by JS was also very high (0.88 95% CI: 0.87 to 0.90) with an average difference between readings of 4.42.P =0.20) per 10-year change in age at entry to IBIS-I, 1.05  per one unit of BMI (kg/m2), and 1.16  per 10% change in percent dense area.The odds ratios for risk of developing breast cancer from the multivariate logistic regression model including age, BMI and percent dense area were 1.33 . Unadjusted percent dense area was not significant in a model that already included the density residual.The odds ratios, confidence intervals, area under the receiver operating characteristic curve (AUC) and associated The numbers reclassified  when the TC risk score was modified using the density residual are given in Table We have shown that by adjusting percent dense area for age and BMI a better measure of breast cancer risk is obtained. This adjusted measure provided additional predictive information when added to the TC risk estimates calculated from classic breast cancer risk factors. Our findings suggest that even within known high-risk groups, prevention strategies might be better targeted as, with the addition of information from the density residual, the number of women identified as having the highest breast cancer risk (>8%) increased from 14% (75/552) to 26% (145/552) and the proportion of cases arising in the highest risk group increased from 21% (15/72) to 39% (28/72). We also found that a woman with high density residual but low TC risk might have a greater chance of developing breast cancer than a similar woman with low density residual but high TC risk. Furthermore, the density residual was better at modifying TC risk than unadjusted percent dense area.Our study has a number of limitations. First, our model for adjusting percent dense area for age and BMI is based on a relatively small number of women and therefore requires validation. Second, since our subjects are from a higher-risk population, our adjustment may not be appropriate for use in the general population. This may also explain the poor discrimination of the model containing TC risk alone. Nevertheless, our results highlight the fact that even among high-risk women the addition of mammographic density to existing breast cancer risk prediction models seems likely to improve discrimination. The further development and validation of these models should therefore be a priority.2 = 13.4 vs. 3.50). Therefore, an important step will be to develop the TC model further by incorporating an adjusted density measure into the model. Further validation of these results in the Predicting Risk Of breast Cancer At Screening (PROCAS) study [et al. [A weakness of previous attempts to incorporate information on breast density into established risk prediction models is that the only available measure of breast density was categorical and therefore a less sensitive measure. In our study group including breast density adjusted for age and BMI improved the predictive ability of the model. The model with TC risk and density residual had almost four times as much information on breast cancer risk as the TC risk alone (χS) study  is plannS) study -10] on  on 2 = 1 1/2 and x = percent dense area) as the dependent variable. The use of hormone replacement therapy and age at menarche was not significant. BMI explained around 15% of the variation in transformed percent dense area, age explained 5%, parity explained 0.8%, menopausal status 0.6%, previous biopsy 1.8% and atypical hyperplasia or/and lobular carcinoma in situ 1.3%. Compared with age and BMI, the additional explanatory value of the other risk factors was quite low so we decided not to include them in the adjustment.Age, BMI, menopausal status, parity, age at menarche, use of hormone replacement therapy, previous biopsy and atypical hyperplasia or/and lobular carcinoma Adjusted percent dense area was calculated from the following linear regression lineDensity residual was calculated as:transformed percent dense area-adjusted percent dense area.To standardise, the density residual was divided by its standard deviation (1.30).


Women with high levels of mammographic density (MD) have a four- to six-fold increased risk of developing breast cancer; however, most neither have a prevalent tumor nor will they develop one. Magnetic resonance imaging (MRI) studies suggest that background parenchymal enhancement, an indicator of vascularity, is related to increased breast cancer risk. Correlations of microvessel density (MVD) in tissue, MD and biopsy diagnosis have not been defined, and we investigated these relationships among 218 women referred for biopsy.MVD was determined by counting CD31-positive vessels in whole sections of breast biopsies in three representative areas; average MVD was transformed to approximate normality. Using digital mammograms, we quantified MD volume with single X-ray absorptiometry. We used linear regression to evaluate associations between MVD and MD adjusted for age and body mass index (BMI) overall, and stratified by biopsy diagnosis: cases  versus non-cases . Logistic regression adjusted for age, BMI, and MD was used to calculate odds ratios (ORs) and 95 % confidence intervals (CIs) for associations between MVD and biopsy diagnosis. We also assessed whether the MVD-breast cancer association varied by MD.Adjusted = 1.69, 95 % CI = 1.17–2.44). MVD-breast cancer associations were strongest among women with greater non-dense volume.MVD and MD were not consistently associated. Higher MVD was significantly associated with higher odds of in situ/invasive disease  contains supplementary material, which is available to authorized users. Mammographic density (MD), a radiographic reflection of the proportion of fibroglandular tissue in the breast, is one of the strongest risk factors for the development of ductal carcinoma in situ (DCIS) and invasive breast cancer , 2. NoneMultiple breast imaging techniques , includiThis study included 465 women aged 40–65 years undergoing image-guided breast biopsies at the University of Vermont College of Medicine and the University of Vermont Medical Center that participated in the National Cancer Institute (NCI) Breast Radiology Evaluation and Study of Tissues (BREAST) Stamp Project from October 2007 to June 2010, as previously described [Mammograms were acquired on one of six full-field digital mammography systems. Raw images were encrypted and transferred to the University of California at San Francisco for quantitative volume and area density assessment. This analysis was restricted to pre-biopsy views [craniocaudal (96 %) or mediolateral oblique (4 %)] of the ipsilateral breast. For three women who underwent bilateral breast biopsies, the breast with the most severe diagnosis was selected for analysis. If more than one mammogram was available, the mammogram taken closest in time prior to the breast biopsy date was selected.3) and percent tissue volume using single X-ray absorptiometry (SXA), as described previously [Mammographic density  was quantified as an absolute tissue volume  and percent lesional volume were estimated using SXA within the biopsy target, centered at the biopsy site [To compute localized density measures of the biopsied lesion, two radiologists  recorded the biopsy location and radius of the biopsy target on the pre-biopsy standard digital mammogram . Absolute lesional volume , and proliferative with atypia  (n = 174). Cases included diagnoses of ductal or lobular carcinoma in situ (n = 36) and invasive cancer (n = 8).As part of the clinical workup, tumor blocks from in situ and invasive cancer were sectioned and stained for estrogen receptor (ER) and progesterone receptor (PR). We obtained these slides and one observer (RLC) rescored all sections microscopically. The percentage of stained cells (range: 0–100 %) and intensity  were recorded and an overall score was calculated as the product of these components (range: 0–300). We dichotomized expression as negative (<10) or positive (≥10). When information on these stains was missing, we obtained tumor blocks and performed immunohistochemistry according to routine protocols, also scored by the same microscopist (RLC).Paraffin-embedded whole section slides were deparaffinized and antigen retrieval performed with citrate buffer pH6 using a pressure cooker. Endogenous activity was blocked with 3 % peroxidase and primary antibody CD31  was applied for 2 hours at room temperature. Subsequently, antibody was detected using DAKO Env + labeling system and visualized with 3,3′-diaminobenzadine (DAB) for 20 min. After rinsing, slides were counterstained with modified Harris hematoxylin, dehydrated with graded alcohol, cleared with xylene and a coverslip applied.We performed a pilot study including 20 participants to determine the within-woman variability of MVD on whole section slides, based on counting vessels within three regions, each consisting of ten × 400 high-power fields, randomly selected from the 1) top, (2) center, and (3) bottom portions of the slide. When multiple tissue fragments existed, one randomly selected region from each of the three largest fragments was selected for MVD counting. Coefficient of variations (CVs) and ICCs were similar based on analyzing 30 or 15 fields; accordingly, in the full study, 15 MVD scores per slide were assessed by a pathologist (PL) masked to biopsy diagnosis A masked independent review of 20 randomly selected slides after study completion by two pathologists  demonstrated an intra-rater agreement (ICC) of 0.88 and inter-rater agreement (ICC) of 0.82.Of 465 participants enrolled, 12 were not subsequently biopsied and two went straight to surgery without a biopsy and were excluded. We excluded women who underwent ultrasound-guided core (n = 225) and MR-guided vacuum-assisted biopsies (n = 1). Ultrasound-guided biopsies were generally used to sample mass lesions, providing less non-lesional tissue for MVD analysis than vacuum-assisted breast biopsies, and were therefore excluded. We further excluded participants with invalid SXA volumetric MD measurements (n = 5) and insufficient tumor tissue on slide (n = 2), resulting in a final sample of 218 women.p value. Age at biopsy  and BMI  were coded as categorical variables. Other breast cancer risk factors were not significantly associated with MVD, and were therefore not included as potential confounders. We also examined the relationship between MVD and MD measures stratified by menopausal status based on previous findings demonstrating a decline in BPE after menopause in some women [Relationships between baseline characteristics according to final pathologic diagnosis (in situ and invasive cancer versus benign diagnoses) were examined using chi-square or Fisher’s exact tests for categorical variables and Wilcoxon rank sum tests for continuous variables. Spearman rank correlation coefficients were computed to estimate correlations of MVD with age at biopsy, body mass index (BMI), and MD measures overall and by final pathologic diagnosis. Based on a Box-Cox transformation analysis, we used a power of 0.2 to improve normality of the average MVD score. Age- and BMI-adjusted linear regression models were used to examine relationships between MVD with participant characteristics and MD measures overall and by case status. We tested for differences by case status by including a multiplicative term between participant characteristics and MD measures with a binary indicator for case status and evaluating the Wald test me women .p value. We used SAS  software for all analyses and two-sided p values less than 0.05 were considered statistically significant.Logistic regression models were used to estimate odds ratios (ORs) and 95 % confidence intervals (CIs) for associations between MVD (the average of MVD within a woman was standardized by one standard deviation) and final pathologic diagnosis (benign versus in situ/invasive) adjusted for age at biopsy and BMI. Subsequent models were adjusted for individual MD measures. We also evaluated whether a “gradient” of MVD and lesion severity existed using polytomous logistic regression with the following outcome categories: (1) benign, carcinoma in situ , and invasive cancer and, in a second model, (2) benign, proliferative, proliferative with atypia, carcinoma in situ  and invasive cancer. We also examined the association between MVD and final pathologic diagnosis stratified by MD. In these analyses, each MD measure was dichotomized at the median based on the distribution among the non-cases. We formally tested whether the ORs in each MD stratum were significantly different by including a multiplicative term between the dichotomous MD variable and MVD and evaluating the Wald test p value = 0.13).Among the non-cases, 50 had benign diagnoses, 99 had proliferative diagnoses, and 25 had proliferative disease with atypia Table . Cases rp < 0.0001) and BMI  (data not tabled). In multivariable linear regression models adjusted for age and BMI, MVD was inversely associated with age at biopsy and BMI among non-cases (Table p = 0.04). We did not observe significant associations between MVD and other risk factors.Among non-cases, MVD was inversely correlated with age at biopsy . Among non-cases, MVD was inversely related to absolute dense volume  and non-dense volume . We observed positive associations of MVD with non-dense lesional volumes among all women and among cases (p ≤ 0.04). Finally, when the association between MVD and MD measures was stratified by menopausal status, we did not observe significant deviations from these patterns (data not tabled).Age- and BMI-adjusted linear regression models were used to evaluate associations between MVD and the MD measures Table . MVD was/invasive disease compared with non-cases   but not global density (p heterogeneity = 0.11).To test our primary hypothesis of an interaction between MVD and MD, Table p heterogeneity = 0.23). A similar pattern was noted for lesional absolute dense volume.Among women categorized as high  absolute dense volume, higher MVD was significantly associated with increased breast cancer odds. For example, among women with high global absolute dense volume, higher MVD was associated with a 1.78-fold increase in breast cancer odds (95 % CI = 1.07–2.98); however, this was not significantly different than the odds observed among women in the low global absolute dense volume category . A similar pattern was noted for lesional non-dense volume.Regarding the non-dense volume measures, the association between MVD and breast cancer differed between women with lower versus higher amounts of non-dense volumes, such that higher breast cancer odds were observed among women with greater amounts of non-dense tissues. For example, higher MVD was associated with a 2.51 (95 % CI = 1.41–4.46) times higher odds of breast cancer among women in the high absolute non-dense volume stratum compared with a 1.14 (95 % CI = 0.67–1.95) times higher breast cancer odds among women in the low absolute non-dense volume stratum  among those with mild, moderate, or marked BPE [MRI-assessed BPE is directly related to vascular supply and vessel permeability , which erked BPE . This laWhen we launched the BREAST Stamp Project in 2007, there was not sufficient scientific evidence to recommend supplemental MRI screening for women with dense breasts . In our In a cohort of approximately 2000 women who underwent a biopsy for a benign breast lesion, 24 women subsequently developed breast cancer (median time to diagnosis was not provided) . For eacWe initially hypothesized that the combination of high MD and high MVD would be significantly associated with breast cancer compared with other combinations of these two features . The underlying rationale for this hypothesis was two-fold: first, while higher mammographic breast density is strongly associated with breast cancer risk, many women with dense breasts do not subsequently develop breast cancer. Therefore, other biological mechanisms must work in concert with elevated density to increase breast cancer risk. Second, higher levels of BPE, a measure of vascular supply, are positively associated with breast cancer independent of fibroglandular content , 6. We pWe observed that the MVD-breast cancer association was stronger among women with greater amounts of non-dense tissue, as revealed in the analyses stratified by percent density and absolute non-dense volume. Regardless of the density measure , these analyses consistently demonstrated a significant positive OR for the relationship between MVD and breast cancer odds within strata of low percent density and within strata of high absolute non-dense volume. Reasons for this association are unclear. Non-dense breast tissue is primarily composed of adipose tissue, which is radiolucent and appears dark on a mammogram. In a recent meta-analysis of area density measure studies, absolute non-dense area was inversely associated with breast cancer risk among pre- and postmenopausal women, with slight attenuation after adjustment for absolute dense area, particularly among premenopausal women . ConversWe did not detect clear relationships between MVD and the quantitative assessments of volumetric MD  in the overall study population or stratified by menopausal status. In accordance with our findings, several MRI reports also failed to observe an association between BPE and MD –28. Our We are unaware of any study relating breast cancer risk factors to histologic markers of angiogenesis among women with benign breast disease. Our analysis revealed few associations: MVD was inversely associated with age and BMI among women without breast cancer. Interestingly, BPE appears to be hormonally regulated: premenopausal women have been reported to have higher BPE levels compared with postmenopausal women  whereas Strengths of our study include the quantitative, reliable global density measures that have been validated with respect to breast cancer risk factors  and riskIn summary, our histopathologic analysis suggests that tissue vascularity, as reflected by MVD, is associated with breast cancer independently of MD, and the effect may be stronger among women with lower breast density. Although women with low MD tend to have lower breast cancer risk, these women account for a high percentage of breast cancers overall. Our results add to prior findings suggesting that the features of benign parenchyma, assessed radiologically or histologically, may be related to breast cancer. Specifically, prior analyses have found that women with benign breast disease who have more associated terminal duct lobular units (TDLUs) experience increased breast cancer risk , 36, indMicrovessel density was positively associated with breast cancer odds in our study, independent of mammographic density, an established breast cancer risk factor. Further, the association between microvessel density and higher breast cancer odds was stronger among women with lower mammographic breast density, which account for a high percentage of breast cancers overall. These results need to be replicated in larger studies, particularly in prospective studies with mammograms and breast biopsy material available years prior to the cancer diagnosis. This would provide evidence that increased vascularity is related to cancer development, rather than a finding that manifests after cancer occurs.


Studies reporting the association between change in weight or body mass index during midlife and risk of colorectal cancer have found inconsistent results, and only one study to date has reported the association between change in waist circumference  and risk of colorectal cancer.We investigated the association between risk of colorectal cancer and changes in directly measured waist circumference and weight from baseline (1990-1994) to wave 2 (2003-2007). Cox regression, with age as the time metric and follow-up starting at wave 2, adjusted for covariates selected from a causal model, was used to estimate the Hazard Ratios (HRs) and 95 % Confidence Intervals (CIs) for the change in waist circumference and weight in relation to risk of colorectal cancer.A total of 373 cases of colorectal cancer were diagnosed during an average 9 years of follow-up of 20,605 participants. Increases in waist circumference and weight were not associated with the risk of colorectal cancer . For individuals with a waist circumference at baseline that was less than the sex-specific mean value there was a slight increased risk of colorectal cancer associated with a 5 cm increase in waist circumference at wave 2 .Increases in waist circumference and weight during midlife do not appear to be associated with the risk of colorectal cancer.The online version of this article (doi:10.1186/s12885-016-2144-1) contains supplementary material, which is available to authorized users. There is substantial evidence that excess body fat, commonly measured by body mass index, increases the risk of colorectal cancer , 2. ReceWeight and body mass index might not be the best measures of the health risks associated with obesity since they provide no information on body fat content or distribution. Waist circumference and waist-to-hip ratio, simple measures of central or abdominal adiposity, have stronger associations with all-cause mortality, cardiovascular disease, cancer and type 2 diabetes compared with weight or body mass index –11. To oUsing a prospective cohort study in Melbourne, Australia, in which anthropometric measurements were directly measured at baseline and approximately 12 years later, we investigated associations between gain and loss in weight, waist and hips circumference during middle adult life and incidence of colorectal cancer.The Melbourne Collaborative Cohort Study is a prospective cohort study of 41,514 people , aged between 27 and 77 years at baseline (99.2 % of whom were aged 40 to 69 years). Participants were recruited between 1990 and 1994 (baseline) and attended clinics where demographic, anthropometric, lifestyle and dietary information were collected and anthropometric measurements were performed . A folloAll anthropometric measurements were taken by trained staff according to standard protocols. Height was measured at baseline, to 1 mm, using a stadiometer. At both baseline and wave 2, weight was measured to 100g using a digital electronic scale, and waist circumference and hips circumference were measured to 1 mm using a 2-meter metal anthropometric tape. Waist circumference was measured at the narrowest part of the torso and hips circumference was measured at the point of maximum circumference over the buttocks. For both waist circumference and hips circumference measurements participants were measured in light clothing with belts and restricting garments removed. Change in anthropometric measures were calculated as the value at baseline (1990–4) subtracted from the value at wave 2 (2003–7).Information about country of birth and level of educational attainment was collected at baseline. Residential postcodes at baseline were used to classify participants into quintiles of an area-based measure of socioeconomic status . At bothCases were participants with a primary diagnosis of adenocarcinoma of the colon or rectum  between date of wave 2 attendance and 30 June 2014. Cases were ascertained from record linkage to the population-based Victorian Cancer Registry and the Australian Cancer Database. Addresses and vital status of all participants were determined by record linkage to Electoral Rolls, Victorian death records, the National Death Index, from electronic phone books and from responses to mailed questionnaires and newsletters.Participants with extreme values for the baseline anthropometric variables  and energy intake were excluded due to potential measurement errors. Analyses for this paper were restricted to participants who attended both waves and who had not been diagnosed with any cancer before their wave 2 attendance.n=373), diagnosis of an unknown primary cancer (n=29), diagnosis of an in situ colorectal cancer or cancer of the anus (C21) (n=17), death (n=1814), or 30 June 2014 , whichever came first. To estimate separate HRs for colon  and rectal cancer (C19 and C20), we fitted competing risk models [The HRs for change in body size and the incidence of colorectal cancer were estimated using Cox regression with attained age as the time metric. Follow-up began on the date of the wave 2 measurement and ended at diagnosis of colorectal cancer (k models .We used the likelihood ratio test to test the assumption of a linear association between the change in body size measures and the log(hazard) by comparing models with categorical  and pseudo-continuous change in body size variables. Because we did not find evidence of departure from linearity of associations for any of the anthropometric measures, we included them as continuous variables in the analyses. Tests based on Schoenfeld residuals showed no evidence that the proportional hazard assumptions were violated.A causal diagram was developed and the following confounding variables were included in the models: country of birth, sex, quintile of socioeconomic status, family history of any cancer, the anthropometric measurement at baseline, cumulative smoking status, physical activity and Mediterranean diet score at baseline and wave 2 , smoking, length of time after wave 2, and undiagnosed diseases by fitting separate interaction terms between change in anthropometric measures and the following variables: (i) sex, (ii) age at wave 2 (≥ 65 vs < 65 years), (iii) baseline value of the anthropometric measure dichotomised at the sex-specific mean of body size , (iv) smoking status (never smoked compared with ever smoked), (v) length of follow-up after wave 2 (first two years of follow-up compared with more than two years of follow-up), and (vi) previous history of disease , with the primary exposure of interest ‘the change in the anthropometric measure’ and tested the interactions with likelihood ratio tests.Statistical analyses were performed using Stata version 13.1 .Of the 41,514 participants in the Melbourne Collaborative Cohort Study, 44 did not have baseline anthropometric measurements, 866 had baseline measurements in the extreme 0.5 or 99.5 sex-specific centile, 831 had a total energy intake in the 1 or 99 centile at baseline, and 1818 had a diagnosis of cancer before baseline. Between baseline (1990–1994) and wave 2 (2003–2007), 3224 participants died or left Australia and 2,461 were diagnosed with cancer, leaving 32,270 available for invitation to wave 2 and eligible for this analysis. Of these participants, 9707 (30 %) did not attend wave 2, and 57 did not have at least one of their anthropometric measurements recorded  at wave 2. Finally, 1890 were excluded due to missing information for at least one of the confounding variables at baseline or wave 2, or for an extreme change in body size (i.e. 0.5 or 99.5 centile of sex-specific change in body size), leaving 20,605  participants with complete data available for this analysis  diagnosed over an average of 9.0 years after wave 2. Characteristics of the participants with and without colorectal cancer are shown in Additional file Table p-value = 0.01 from likelihood ratio test). For individuals with baseline waist circumference below the sex-specific mean, the HR for an increase in waist circumference was slightly elevated , whereas it was not for those whose baseline waist circumference was above the sex-specific mean value:   and previous history of disease  modified the association , smoking status , and length of follow-up  did not modify the associations for change in body size and risk of colorectal cancer.The association between change in waist circumference and risk of colorectal cancer differed by the baseline value of waist circumference 7) Table . There w Table . In this cohort study of middle-aged men and women, an increase of 5 units in waist circumference, weight or hips circumference, measured between 1990–1994 and approximately 12 years later, was not associated with a higher risk of colorectal cancer.The strengths of our study include its prospective design, almost complete follow-up of participants after wave 2 , updated covariate information at wave 2, and directly measured body size measurements, using standard protocols, at both waves.Its principal limitations are the small number of colorectal cancer cases; attrition before wave 2 ; and the lack of information on intentionality of weight change for the study participants.The proportion of living participants attending wave 2 (i.e. 71.5 %) was similar to the proportion reported by other studies . Those wPrior to performing this analysis, we conducted an extensive simulation study to identify whether multiple imputation or complete-case analysis should be used to handle the missing anthropometric data at wave 2. We found that in the framework of this study, both methods provide unbiased estimates and there is minimal gain in precision when using multiple imputation . MultiplPhysical activity and diet  may confound the association between obesity and risk of colorectal cancer . A meta-2. In our population, with an average height of 1.73 m for men and 1.61 m for women, a body mass index of 25 kg/m 2 corresponds to a weight of 75 kg for men and 65 kg for women.To define strata of adiposity status, we used the mean sex-specific values for the participants of the Melbourne Collaborative Cohort Study . These values correspond to the National Health and Medical Research Council Dietary Guidelines for Adults , which rOur results for weight gain showed a slight, non-statistically significant, decreased risk of colorectal cancer. Three recent meta-analyses showed that comparing the highest category of weight gain to a reference category was associated with an increased risk of colorectal cancer (HRs from 1.15 to 1.25) , 6, 7. HTo date, only one study has looked at the association between change in waist circumference and the risk of colorectal cancer . Song etSong et al.  also invWe were unable to differentiate between unintentional and intentional weight change. As a result, reverse causation is a potential concern. When we excluded cancer cases diagnosed during the first two years of follow-up, the results were similar.In conclusion, we found no associations between changes in waist circumference, weight or hips circumference during middle adult life and the risk of colorectal cancer. However, previous studies have shown that weight gain from early life (i.e. age 18 to 21) to midlife is associated with an increased risk of colorectal cancer and weight gain from midlife to older age can have other detrimental effects. Therefore, recommendations should focus on maintaining a healthy body weight throughout the lifespan.


During adolescence the breasts undergo rapid growth and development under the influence of sex hormones. Although the hormonal etiology of breast cancer is hypothesized, it remains unknown whether adolescent sex hormones are associated with adult breast density, which is a strong risk factor for breast cancer.Percentage of dense breast volume (%DBV) was measured in 2006 by magnetic resonance imaging in 177 women aged 25–29 years who had participated in the Dietary Intervention Study in Children from 1988 to 1997. They had sex hormones and sex hormone-binding globulin (SHBG) measured in serum collected on one to five occasions between 8 and 17 years of age. Multivariable linear mixed-effect regression models were used to evaluate the associations of adolescent sex hormones and SHBG with %DBV.Ptrend ≤0.03) but not when measured in postmenarche samples . The multivariable geometric mean of %DBV across quartiles of premenarcheal DHEAS and SHBG increased from 16.7 to 22.1 % and from 14.1 to 24.3 %, respectively. Estrogens, progesterone, androstenedione, and testosterone in pre- or postmenarche serum samples were not associated with %DBV .Dehydroepiandrosterone sulfate (DHEAS) and SHBG measured in premenarche serum samples were significantly positively associated with %DBV (all Our results suggest that higher premenarcheal DHEAS and SHBG levels are associated with higher %DBV in young women. Whether this association translates into an increased risk of breast cancer later in life is currently unknown.NCT00458588 April 9, 2007; NCT00000459 October 27, 1999ClinicalTrials.gov Identifier,  Breast density is a measure of the relative proportion of glandular and stromal tissue to fatty tissue in the breasts , 2 and iPrevious studies mainly enrolled middle-aged and older women. It remains unknown whether adolescent sex hormone levels are associated with breast density and breast cancer risk during adulthood. Adolescence is a time of rapid breast growth and development and increased susceptibility of breast tissue to carcinogens –26. ModuTo our knowledge, no prior study has evaluated associations between adolescent sex hormones and adult breast density, possibly because of few cohorts initiated at a young age. Therefore, we prospectively evaluated associations of adolescent serum sex hormones with breast density measured in young women in the Dietary Intervention Study in Children (DISC) and the DISC 2006 (DISC06) Follow-up Study , 31, 32.DISC was a two-armed, multicenter, randomized, controlled clinical trial evaluating the efficacy and safety of a dietary intervention to reduce serum low-density lipoprotein cholesterol (LDL-C) in children , 34. BetOf the 301 female DISC participants, 286 had sex hormones measured at baseline or follow-up visits that took place at year 1, 3, 5 and last visits (approximately 7) years after randomization; none were pregnant or had used oral contraceptives within 3 months before blood collection . Among tFor the DISC trial, assent from DISC participants and informed consent from parents and guardians were obtained. All participants in the DISC06 Follow-up Study provided informed consent. The institutional review boards at participating centers approved all DISC protocols .2). Diet was assessed by three nonconsecutive 24-hour dietary recalls over a 2-week period. Sexual maturation was assessed by Tanner stage [At all clinic visits during the DISC trial and a single clinic visit in the DISC06 Follow-up Study, participants completed questionnaires inquiring demographic and lifestyle information, medical and reproductive history, and medication use. Weight and height were measured using a standardized protocol ; body maer stage  and onseAt baseline and at year 1, 3, 5 and last follow-up visits in the DISC trial , a singlAll laboratory assays were performed at Esoterix, Inc.  using standard procedures. Steroid sex hormones were measured by radioimmunoassays (RIAs) following extraction  and chromatography  or directly (dehydroepiandrosterone sulfate (DHEAS))  Estrone Analytical samples collected from the same clinic visit were assayed together in the same assay batches. Masked quality control (QC) samples that were aliquots from three serum QC pools were included in each batch . The witBreast density was measured using noncontrast MRI on a whole-body 1.5 Tesla or higher field-strength MRI scanner with a dedicated breast-imaging radiofrequency coil . At all The total breast volume and absolute dense breast volume (ADBV), which quantifies fibroglandular tissue volume, were measured. The absolute nondense breast volume (ANDBV) was calculated by subtracting ADBV from total breast volume. The percentage of dense breast volume (%DBV) was calculated as the ratio of ADBV to total breast volume. The density measures of both breasts were averaged for analysis. We considered %DBV as primary outcome given the established association of mammographic %DBV with breast cancer .Breast density measures were initially described using nonparametric statistics, and prior to modeling were log-transformed to improve normality. Because hormone levels change during adolescence , 45, we We calculated the geometric mean of %DBV, ADBV, and ANDBV and 95 % confidence interval (CI) across quartiles of standardized hormone concentrations by exponentiating the coefficients from a multivariable linear mixed-effects regression model with robust standard errors . The cliIn sensitivity analyses, we conducted analyses stratified by DISC visit , stages of breast development (≤3 and ≥4), and treatment assignment . We also excluded participants with more than 33 days from blood draw to their next menses during the DISC trial and those using hormonal contraceptives at DISC06 follow-up visits.P values <0.05 were considered statistically significant.Analyses were conducted using SAS  and STATA  statistical software. All tests were two sided. 2. The mean age at menarche was 12.8 years. The median and interquartile range of %DBV was 24.3 (9.7–41.2). The mean ages at blood collection were 10.2, 12.1, 14.2, and 16.6 years at ≤year 1, year 3, year 5, and the last DISC trial visits, respectively. Additional information on lifestyle, diet, pubertal characteristics, and levels of sex hormones and SHBG during DISC trial visits is summarized in Table S1 in Additional file Among 177 women available for analyses, the mean age was 27.1 years at the DISC06 follow-up visit (Table Ptrend <0.001). The multivariable geometric means of %DBV in women increasing quartiles of premenarcheal SHBG quartiles were 14.4 % to 18.7 %, 18.3 % and 24.3 % (Ptrend = 0.03). In contrast, adolescent DHEAS and SHBG concentrations after menarche were not associated with adult %DBV. Estrogen, progesterone, androstenedione, and testosterone concentrations in serum collected during adolescence before or after menarche were not associated with adult %DBV. Results generally were similar when nonstandardized hormone levels measured separately at each clinic visit were examined in association with %DBV (data not shown). An exception was follicular phase total and non-SHBG estradiol measured at the last DISC trial visit when women in the highest quartiles of these hormones had significantly lower %DBV compared to women in the lowest quartiles. These associations were not consistently observed for postmenarcheal samples across clinic visits and could be due to chance.Tables Ptrend = 0.02). Treatment assignment did not significantly modify the association of pre- and postmenarcheal sex hormones and SHBG with %DBV  except non-SHBG-bound estradiol (Pinteraction = 0.03); however, non-SHBG-bound estradiol results were nonsignificant in either treatment group.In sensitivity analyses, excluding women who reported menstrual cycles longer than 33 days or who were parous did not change the results (data not shown). Restricting analyses to women not currently taking hormonal contraceptives at DISC06 visits did not change results substantially (data not shown). However, the positive association of premenarcheal SHBG with %DBV was attenuated and no longer statistically significant, whereas the positive association of premenarcheal DHEAS with %DBV became more linear; the geometric means of %DBV across premenarcheal DHEAS quartiles (Q1–Q4) were 16.4 %, 20.9 %, 21.7 % and 26.2 % ; the geometric mean ANDBV increased from 294.5 to 336.0 cm3 between the lowest and highest estradiol quartiles.Associations of sex hormones and SHBG with ADBV are shown in Tables S2 and S3 in Additional file In this study examining adolescent sex hormones in relation to young adult breast density, DHEAS and SHBG levels during adolescence before, but not after, menarche were significantly positively associated with adult %DBV. Estrogens, progesterone, androstenedione, and testosterone levels during adolescence were not significantly associated with adult %DBV.It is largely unknown whether adolescent sex hormones levels predict breast cancer development later in life. Nonetheless, the breast undergoes rapid growth and development during adolescence , 25. AniTo our knowledge, this is the first epidemiologic study that directly related adolescent sex hormone levels with adult breast density. Previous studies used sex hormone data collected from middle-aged and older women –21. The The breast matures mostly before menarche under the influence of sex hormones and growth factors, and DHEAS may have its greatest effect on breast morphology at this time of expansion of the breast ductal architecture. DHEAS can be metabolized to estrogens and has been shown to have estradiol-like proliferative effects in a low-estrogen environment , typicalOur significant positive association between premenarcheal SHBG levels and adult %DBV is consistent with some studies of premenopausal , 10, 11 Notably, breast density was significantly positively associated with DHEAS and SHBG before menarche, but not after menarche. Although few prior data exist to explain our results, breast tissue typically starts to develop around 9 years of age and matures near the onset of menarche , 64, 65.Irrespective of menarche status, other sex hormones measured during adolescence were not significantly associated with adult breast density in our study, which is consistent with the largely null results reported for estrogens –12, 67, A strength of our study is the prospective design of enrolling prepubertal children, and following them to their late 20s. With repeated measurements of sex hormones, we could examine sex hormones at different stages of puberty. MRI avoids exposing participants to ionizing radiation and measures breast density not impaired by the high parenchymal breast density typical of young women . Even soOur study had limitations. Despite the cyclic variation of estrogens and progesterone after the onset of menarche, postmenarcheal samples were not collected timed to the menstrual cycle. Even so, luteal and follicular phase estrogens and progesterone were analyzed separately, and days until start of next menses were taken into account in analyses. Circulating sex hormone levels are an indirect marker of breast tissue exposure, but their associations with breast cancer risk indicate serum levels are a meaningful measure of exposure , 77. ParIn conclusion, circulating levels of premenarche DHEAS and SHBG were significantly positively associated with %DBV. Associations with other adolescent sex hormones were not detected. Our results suggest that differences in sex hormones during adolescence may be relevant to breast morphology during adulthood. Large studies that measure hormones using highly sensitive and specific mass spectrometry that can detect lower levels of circulating hormones in children and adolescent are warranted.


Higher serum 25-hydroxyvitamin D [25(OH)D] concentrations have been associated with a lower risk of multiple cancer types across a range of 25(OH)D concentrations.To investigate whether the previously reported inverse association between 25(OH)D and cancer risk could be replicated, and if a 25(OH)D response region could be identified among women aged 55 years and older across a broad range of 25(OH)D concentrations.Data from two cohorts representing different median 25(OH)D concentrations were pooled to afford a broader range of 25(OH)D concentrations than either cohort alone: the Lappe cohort , a randomized clinical trial cohort (median 25(OH)D = 30 ng/ml) and the GrassrootsHealth cohort , a prospective cohort (median 25(OH)D = 48 ng/ml). Cancer incidence over a multi-year period (median: 3.9 years) was compared according to 25(OH)D concentration. Kaplan-Meier plots were developed and the association between 25(OH)D and cancer risk was examined with multivariate Cox regression using multiple 25(OH)D measurements and spline functions. The study included all invasive cancers excluding skin cancer.Age-adjusted cancer incidence across the combined cohort  was 840 cases per 100,000 person-years . Incidence was lower at higher concentrations of 25(OH)D. Women with 25(OH)D concentrations ≥40 ng/ml had a 67% lower risk of cancer than women with concentrations <20 ng/ml .25(OH)D concentrations ≥40 ng/ml were associated with substantial reduction in risk of all invasive cancers combined. There were 14 million new cases of cancer worldwide in 2012 and 8.2 million cancer-related deaths [P = 0.01). For women free of cancer at one year into the trial, the reduction in incidence was 77% .Thirty-five years ago, Garland and Garland first proposed a link between cancer and vitamin D from observations of higher colon cancer mortality in higher latitudes and areas with less solar radiation . Since tThe objective of this analysis was to quantify more precisely the association between 25(OH)D concentration and risk of non-skin cancer among women aged 55 years and older, and to do so across a broader range of 25(OH)D concentrations than had been previously analyzed. The present study used data from two cohorts representing different median 25(OH)D concentrations. The first was a cohort from a randomized controlled clinical trial performed by Lappe et al. ,15 in NeThe Lappe cohort participated in a four year, double-blind, placebo-controlled trial of vitamin D and calcium supplementation. A detailed description of the participants and study design can be found elsewhere ,15. BrieParticipants were randomly assigned to one of three groups: calcium , calcium plus vitamin D , or control . The calcium group and the calcium plus vitamin D group each comprised 40% of the total cohort, with 20% serving as the control group. Health status and supplement intake according to bottle weight were assessed at 6-month interval visits. When a diagnosis of cancer was reported, medical records were examined to confirm diagnosis and ascertain diagnosis date. Serum 25(OH)D concentrations were measured at baseline and annually thereafter using radioimmunoassay after extraction with the use of the IDS Radioimmunoassay kit  at the Creighton University Osteoporosis Research Center Laboratory . The laboratory participates in the Vitamin D Quality Assessment Scheme (DEQAS), whose objective is to ensure the analytical reliability of 25(OH)D assays, with findings on test samples collected during the course of the study regularly close to the international mean.GrassrootsHealth, a non-profit public health research organization, has been running a large prospective population-based study allowing voluntary participants to reach and sustain a serum 25(OH)D concentration of their choice, and tracking self-reported health status measures through a questionnaire. Participants were individuals who responded to an invitation to attendees at a GrassrootsHealth seminar in 2008 and others recruited via internet. There were no exclusion criteria for enrollment. Participation required submission of a home blood spot 25(OH)D test kit and completion of an online health questionnaire. All participants provided informed consent and this research study was approved by the Western Institutional Review Board .R2 values of 0.998 and 0.994 respectively. LC-MS/MS has been validated against the radioimmunoassay method, with an R2 value of 0.91 and with a slope not different from 1.0 [This current analysis included all non-Hispanic white female participants aged 55 years and older without known cancer at enrollment or within 10 years prior who completed at least two health assessments and 25(OH)D measurements. These inclusion criteria were chosen to match GrassrootsHealth members to features of the Lappe cohort. Between January 2009 and December 2014, participants completed health questionnaires and home blood spot test kits at approximately 6 month intervals. Cancer diagnosis dates and types were reported as well as average daily calcium supplement intake, smoking status, and height and weight for calculation of body mass index (BMI). Serum 25(OH)D concentrations were determined by blood spot test kits analyzed using liquid chromatography-mass spectroscopy (LC-MS/MS) by ZRT Laboratory  or Purity Laboratory . Both the ZRT and Purity assays had been validated against the LC-MS/MS consensus group reporting to DEQAS, with from 1.0 .Overall, this analysis included 1,169 women from the Lappe cohort  and 1,135 women from the GrassrootsHealth cohort  . The total person-time was 4,239 person-years in the Lappe cohort and 2,175 person-years in the GrassrootsHealth cohort . The most common type of cancer diagnosed during the study was breast cancer .Demographic characteristics for the Lappe and GrassrootsHealth cohorts were summarized and compared using Mann-Whitney tests for age, BMI, and baseline 25(OH)D, and the chi-square test was used to compare smoking status. Mean 25(OH)D concentration was calculated for each participant by taking the mean of all 25(OH)D measurements during the observation period . The outcome of interest was the diagnosis of any non-skin cancer during the period of observation. A previous analysis of the Lappe cohort  included(-X/C)), where Y = cancer incidence rate, X = serum 25(OH)D).Cancer incidence rates and 95% confidence intervals were calculated for successive 20 ng/ml groups of 25(OH)D concentration, using a moving average method –20 to asTo estimate cancer-free survival over time and account for varying lengths of follow-up, Kaplan-Meier cancer-free survival curves were developed . The proportion of cancer-free participants for 25(OH)D concentrations of <20 ng/ml, 20–39 ng/ml, and ≥40 ng/ml were computed.Multivariate Cox regression was used to determine the association between serum 25(OH)D and the risk of developing cancer, adjusting for age, BMI, smoking status, and calcium supplement intake. Hazard ratio (HR) estimates and 95% confidence intervals (CIs) were calculated for 25(OH)D concentration as a categorical variable divided into three a priori categories: <20 ng/ml, 20–39 ng/ml, ≥40 ng/ml (the 20 ng/ml cut point is from the Institute of Medicine (IOM) recommendation for bone health  and the www.r-project.org).The association between 25(OH)D concentration and cancer risk was assumed to be non-linear, based on the typical nutrient physiological response which consists of a response region where improved nutrient status produces significantly lower risk, and an upper region where less benefit is observed with increasing status . A multiP<0.0001). The baseline characteristics of the Lappe and GrassrootsHealth cohorts are shown in The median baseline serum 25(OH)D concentration in the Lappe cohort was 28 ng/ml (IQR: 23–34) and in the GrassrootsHealth cohort was 43 ng/ml (IQR: 34–58) (P<0.0001). Corresponding values for the pooled cohort were 37 ng/ml (IQR: 29–49). 55% of women in the Lappe cohort and 17% in the GrassrootsHealth cohort had a mean calcium supplement intake of ≥1000 mg/day (P<0.0001) (36% in the pooled cohort). Those in the Lappe cohort with a mean calcium supplement intake of <1000 mg/day were either assigned to the control group or took <70% of assigned calcium doses.Mean 25(OH)D concentration was computed for each participant as the mean of all 25(OH)D measurements during the observation period as a single measure of overall 25(OH)D concentration status during the study. The median of the within-subject mean 25(OH)D values, calculated for each cohort, was 30 ng/ml (IQR: 25–37) in the Lappe cohort and 48 ng/ml (IQR: 39–61) in the GrassrootsHealth cohort . The age-adjusted incidence rate of cancer was 840 cases per 100,000 person-years in the pooled cohort, 1020 cases per 100,000 person-years in the Lappe cohort and 722 cases per 100,000 person-years in the GrassrootsHealth cohort. Cancer types for each cohort are shown in P = 0.002) and a 71% lower incidence rate for mean 25(OH)D . To assess cancer incidence trends across the range of 25(OH)D in the pooled cohort, incidence rates were calculated according to categories of 25(OH)D for both baseline 25(OH)D and mean 25(OH)D D concentration during the study) . For botP = 0.02). The ≥40 ng/ml group diverged early from the other groups and the 20–39 ng/ml diverged from the <20 ng/ml group at approximately 2 years.To estimate cancer-free survival over time and account for varying lengths of follow-up, Kaplan-Meier curves comparing the proportion of cancer-free participants for <20 ng/ml, 20–39 ng/ml, and ≥40 ng/ml  were computed for the pooled cohort . These cP = 0.03) (P = 0.18). Women taking ≥1000 mg/day of calcium supplements had a 19% lower risk of cancer, but this association was not significant ; also, the association of 25(OH)D with cancer risk did not vary based on the level of calcium supplement intake. Age, BMI, and smoking status were also not significant predictors of cancer risk.Multivariate Cox regression was used to quantify the association between 25(OH)D and cancer risk, adjusting for other risk factors D values per participant to accommodate changes over the course of the study). Women in the pooled cohort with 25(OH)D concentrations ≥40 ng/ml had a 67% lower risk of cancer compared to women with concentrations <20 ng/ml, adjusting for age, BMI, smoking status, and calcium supplement intake  . Those wMultivariate Cox regression with spline terms was used to identify the nature of the non-linear association between 25(OH)D and cancer risk. Spline regression revealed a sharp decrease in the risk of cancer with increased 25(OH)D concentration in the lower range of 25(OH)D and a gradual decline as serum concentrations neared 40 ng/ml and above, with no evidence of increased risk in the upper 25(OH)D concentrations . The redP = 0.007). In the Lappe cohort, women in the highest tertile (≥32 ng/ml) had a 61% lower risk of cancer compared to women with concentrations in the lowest tertile (<25 ng/ml) .Findings were similar when we limited the analysis to just the Lappe cohort  and whenWe found a clear association between 25(OH)D serum concentration and cancer risk, according to multiple types of analyses. These results suggest the importance of vitamin D for the prevention of cancer. Women with 25(OH)D concentrations ≥40 ng/ml had a significantly lower risk of cancer (~70%) compared to women with concentrations <20 ng/ml. When looking at the risk of cancer across the 25(OH)D continuum available in the pooled cohort, we observed the greatest decrease in risk occurring between ~10–40 ng/ml, with additional benefit also observed at ≥40 ng/ml. We would have preferred to have randomized clinical trial data in the higher 25(OH)D ranges, but since these do not currently exist, using the GrassrootsHealth prospective cohort data allowed us to observe results across a wider range of 25(OH)D concentrations than using the Lappe cohort alone.P<0.001) [Other studies have found a similar reduction in risk for individual cancers –13. LoweP<0.001) . A recenP<0.001) .Two previous studies of the Women’s Health Initiative (WHI) randomized trial did not find an association between vitamin D treatment group and colorectal or breast cancer risk ,29. ThatFuture studies should base their study design on nutrient physiology, taking into account the sigmoidal nature of nutrient response by assessing participants whose basal status was deficient (<20 ng/ml) and using a vitamin D dose sufficient to raise 25(OH)D concentrations to above the response range (~40 ng/ml as seen in 2D3 [2D3 (~60 times) [2D3.Of interest, several newly-identified, naturally occurring vitamin D3 metabolites have been detected in human epidermis and serum that are products of CYP11A1-mediated metabolism of vitamin D . These v2D3 ,34. AlsoCalcium supplement intake was not a significant independent predictor of cancer risk in this analysis. This finding is similar to the results of the previous analysis based on assigned treatment group by Lappe et al., that found that women assigned to the calcium treatment group did not have a significant reduction in cancer risk compared to women in the control group , including among the subgroup of women who were free of cancer at one year  . Since iThe median follow-up time for the Lappe cohort was 4.0 years, compared to 1.2 years for the GrassrootsHealth cohort. All rates were calculated using person-time denominators, so the difference in length of follow-up did not affect the rates. Also, Kaplan-Meier plots and Cox regression were used because these analyses account for varying lengths of follow-up. Still, there could be a difference between the two cohorts if a certain amount of time must pass for the serum 25(OH)D to exert its influence. For example, in the original analysis of the Lappe cohort , the effP = 0.11, and could be explained by alternative explanations, it is consistent with the existence of an inverse relationship between vitamin D status and risk of lung cancer [There were three times as many cases of breast cancer in the Lappe cohort than in the GrassrootsHealth cohort; however, median follow-up time for the Lappe cohort was 3.3 times longer than for the GrassrootsHealth cohort. Also, the GrassrootsHealth cohort had higher 25(OH)D concentrations than the Lappe cohort, which has been associated with lower risk of breast cancer . It is og cancer ,35. SomeThe strengths of this analysis include using serum 25(OH)D concentration, which is the physiological measure of vitamin D status accounting for all input sources including cutaneous, supplementation, and food. Using serum 25(OH)D concentration also overcomes the inherent bias of treatment compliance and inter-individual variability in dose response which are features of analyses based on assignment to treatment groups. Also, entering 25(OH)D concentration and calcium supplement intake as separate covariates allowed us to assess the independent roles of vitamin D and calcium on cancer risk. This analysis also used multiple analysis techniques, including comparing cancer incidence across 25(OH)D groups, computing Kapan-Meier plots, and conducting adjusted Cox regression analyses with multiple 25(OH)D measurements per participant to account for changes in vitamin D status, all of which found a >65% lower risk or rate of cancer for those with 25(OH)D concentrations ≥40 ng/ml compared to those with concentrations <20 ng/ml. Additionally, this analysis included individuals with a wider range of serum 25(OH)D concentrations than other studies and identified the response region of cancer risk related to 25(OH)D.Limitations of this study include the use of self-report data for certain variables where recall bias may have occurred. This analysis also was not able to control for some covariates related to cancer risk such as family history of cancer, diet, physical activity, or alcohol use. Differences in methods and demographics between the Lappe and GrassrootsHealth cohorts may have affected pooled analyses, which is why results for the Lappe cohort were also presented separately. The small proportion of current smokers in the study population did not allow for an adequate assessment of the association between smoking status and cancer risk, a known risk factor for cancer. However, this provided a unique opportunity to assess other risk factors without the potentially overpowering influence of smoking. An additional limitation is that we did not have sufficient power to assess associations for individual cancer types. While this analysis did show a significant inverse association of 25(OH)D concentration and risk of cancer for non-Hispanic white women aged 55 years and older, results may not be generalizable to other ethnicities, age groups, or to males.The findings from this analysis support the inverse association between 25(OH)D and risk of cancer and highlight the importance for cancer prevention of achieving a concentration substantially above 20 ng/ml, the concentration recommended by the IOM for bone health . IncreasS1 FigThe bars represent the number of non-cases by groupings of 10 ng/ml, white dots represent the 25(OH)D concentration for each cancer case, black dots represent cancer incidence rates per 100,000 person-years for indicated 25(OH)D groupings (plotted at the median 25(OH)D value for each grouping: baseline 25(OH)D groups at 17, 24, 29, 35, and 43 ng/ml; mean 25(OH)D groups at 17, 25, 30, 36, and 43 ng/ml). Vertical error bars indicate the 95% confidence intervals.(EPS)Click here for additional data file.S2 FigP = 0.16).Four-year cumulative cancer-free proportion was 97% among participants with 25(OH)D concentrations ≥40 ng/ml compared to 93% for those with 25(OH)D concentrations <20 ng/ml Click here for additional data file.S3 FigSolid black line represents the estimated hazard ratio for the Cox regression model with restricted cubic splines with 3 knots and dashed lines represent the 95% confidence interval of the estimate. The reduction in risk from 20 ng/ml to 40 ng/ml was approximately 80%.(EPS)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.


BRCA1, BRCA2, TP53 and CDH1. Germline mutations in BRCA1 and TP53 are predominantly associated with invasive ductal carcinoma, while BRCA2 mutations are associated with both ductal and lobular cancers. CDH1, the gene coding for the E-cadherin adhesion protein, is of special interest as mutations are associated with invasive lobular carcinoma, but never with ductal carcinoma. It was initially known as the main susceptibility gene for gastric cancer of the diffuse type, but the excess of breast cancers of the lobular type in CDH1 families led researchers to identify it also as a susceptibility gene for invasive lobular carcinoma. The risk of invasive lobular carcinoma is high in female mutation carriers, as about 50% are expected to develop the disease. Carriers must therefore undergo intensive breast cancer screening, with, for example, yearly magnetic resonance imaging and mammogram starting at age 30 years.While most invasive breast cancers consist of carcinomas of the ductal type, about 10% are invasive lobular carcinomas. Invasive lobular and ductal carcinomas differ with respect to risk factors. Invasive lobular carcinoma is more strongly associated with exposure to female hormones, and therefore its incidence is more subject to variation. This is illustrated by US figures during the 1987 to 2004 period: after 12 years of increases, breast cancer incidence declined steadily from 1999 to 2004, reflecting among other causes the decreasing use of menopausal hormone therapy, and these variations were stronger for invasive lobular than for invasive ductal carcinoma. Similarly, invasive lobular carcinoma is more strongly associated with early menarche, late menopause and late age at first birth. As for genetic risk factors, four high-penetrance genes are tested in clinical practice when genetic susceptibility to breast cancer is suspected,  In this review, we focus on the specificities of ILC regarding incidence and risk factors. We show that ILC is more strongly associated with exposure to female hormones than IDC and that, as a result, its incidence in the past 25 to 30 years has varied more than that of IDC, depending on environmental and lifestyle factors such as menopausal hormone therapy (MHT). As for genetic risk factors, we show that ILC is often underrepresented in patients carrying mutations in the best-known breast cancer susceptibility genes , but that it is the only invasive histological type associated with CDH1, the diffuse gastric cancer susceptibility gene.Invasive breast cancer is a heterogeneous disease of two main histological types, invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC), IDC being by far the most common. IDC and ILC differ with respect to risk factors, and these differences are often overlooked as researchers and clinicians tend to treat breast cancer as a single, homogeneous entity, or only explore the potential differences between the two types in ILCs represent about 10% of invasive breast cancer cases . PatientMore specifically, an average annual decrease of 4.6% for ILC was noted between 1999 and 2004 in 44 American states and the District of Columbia, with the largest drop in 2003 when an 8.5% decrease was observed. The average annual decrease for IDC was smaller, 3.3% for the same five-year period. It is likely that the decreasing use of MHT contributed to this decline, with an acceleration in use reduction from 2002 onwards associated with the publication of the Women’s Health Initiative (WHI) trial results [Most breast cancers are related to female hormones, and therefore any factor that increases exposure to these hormones is a potential risk factor. In particular, reproductive factors associated with increased exposure to endogenous estrogens produced by the ovaries, such as earlier menarche, late menopause, low parity, and late age at first birth, are recognized breast cancer risk factors -8. Simil2 in body mass index (BMI) resulting in an 8% increase in disease risk [Lifestyle factors are also associated with breast cancer. There is an estimated 10% increase in risk per 10 g of ethanol consumed every day . Being oase risk . On the ase risk . In postase risk .ILC being more often hormone receptor-positive than IDC, one would expect hormone-related risk factors to be more strongly associated with lobular than ductal carcinoma.MHT in the form of combined estrogen plus progestin treatment (combined hormone therapy or CHT) most likely increases the risk of breast cancer, whereas the effects of estrogen-only treatments (estrogen hormone therapy or EHT) are less clear ,15-17. ITwenty-five observational studies (15 case control and 10 cohort studies) have evaluated the association between MHT and breast cancer risk by histological types -46. AlthOral contraceptives are expected to become less of a risk factor as recent formulations contain less hormones than those available decades ago . To our P heterogeneity = 0.0001) [P heterogeneity = 0.006).A recent meta-analysis of individual participant data from 85 studies showed a significantly stronger association with age at menarche for ILC than for IDC  that examined the association between alcohol consumption and breast cancer by histological subtype ,45,59-62Four cohort studies ,43,45,63Along with environment and lifestyle, a woman’s genetic background contributes to her risk of having breast cancer. Her risk of developing breast cancer increases if she has a family history of the disease. In a re-analysis of 52 studies comparing cancer incidence in relatives of breast cancer cases and in controls, RR for breast cancer increased with increasing numbers of affected first-degree relatives: compared with women who had no affected relative, the RR was 1.80, 2.93, and 3.90, respectively, for women with one, two, and three or more affected first-degree relatives . RR was About 90 genes or genetic loci are involved in breast cancer susceptibility in general, through rare, moderate to high penetrance mutations (lifetime risk >20%), the penetrance being the risk for a mutation carrier of developing a disease, or through common variants associated with risks that are only slightly increased compared with the wild-type allele (RR = 1 to 1.5). Mutations and variants are germline; that is, they are part of the genetic identity of the individual. A comprehensive review of genetic susceptibility to breast cancer is beyond the scope of this article, as we are focusing here on the specificities of ILC. Numerous reviews have been written on the issue, and we invite those interested to read two recent and extremely well-written articles ,68.BRCA1, BRCA2, TP53 and CDH1. Germline mutations in BRCA1 and TP53 are predominantly associated with IDC, BRCA2 mutations are associated with both ductal and lobular tumors, while mutations in CDH1 are exclusively associated with ILC. Mutations in PTEN and STK11 cause, respectively, Cowden and Peutz-Jaeger syndrome, and breast cancer risk is also high in affected females. However, the presenting manifestations are usually not related to breast cancer  and we shall therefore not discuss these two syndromes further [Four high-penetrance genes are tested in clinical practice when genetic susceptibility to breast cancer is suspected:  further ,70.BRCA1 and BRCA2 [BRCA1 and 55% for BRCA2 by age 70 years [BRCA1 or BRCA2 [BRCA1 or BRCA2. For example, up to 15% of unselected women with triple-negative breast cancer have a BRCA1 mutation, while there does not seem to be an association with BRCA2 [BRCA1/2 mutation carriers, and found that only 2.2% of tumors associated with BRCA1 were ILC. In contrast, the proportion of ILCs in BRCA2 mutation carriers was 8.4%, closer to the characteristics of breast cancers from the general population [In the 1990s, linkage analyses and positional cloning in breast and breast-ovarian cancer families led to the identification of nd BRCA2 ,72. Both70 years . Howeveror BRCA2 . For exaor BRCA2 . These ath BRCA2 . Similarpulation .TP53. Affected individuals are at increased risk of sarcoma, premenopausal breast cancer, brain cancer, adrenocortical cancer, leukaemia, lymphoma, germ cell tumor, melanoma, lung cancer and cancer of the digestive tract [TP53 mutations, but the two studies that have examined the issue have only shown tumors of the ductal type - and none of the lobular type - out of a total of 48 cancers in mutation carriers [TP53 might predispose exclusively to IDC, and not to ILC. Confirmatory studies are nevertheless needed, and it seems premature at this stage to exclude ILC from the tumor spectrum associated with Li-Fraumeni syndrome.Li-Fraumeni syndrome is characterized by early onset of a variety of tumors. It is caused by mutations in the tumour-suppressor gene ve tract . Cancer ve tract . The majcarriers ,81. ThesBRCA1 and TP53 mutations, while their frequency in BRCA2 mutation carriers is more similar to that in the general population. This overall underrepresentation of lobular cancers contrasts with observations made in over 40,000 Utah cases with genealogical records showing unusually high levels of familial clustering for ILC, and therefore a higher contribution of genetic, inherited factors compared with IDC [CDH1 susceptibility gene likely explains at least some of this excess in familial risk, the remainder being accounted for by genes and loci that are yet to be discovered.ILCs are therefore very much underrepresented in carriers of with IDC . The CDHCDH1 is located on chromosome 16q22 and codes for the E-cadherin protein. E-cadherin maintains tissue integrity as it mediates cell-cell adhesion. There is also evidence that forced expression of the protein inhibits the growth of breast cancer cells via mechanisms that are yet to be determined, and that the protein therefore controls cell proliferation in addition to its anti-invasion properties [CDH1 inactivation following the two-hit loss-of-function model [CDH1 is at increased risk of ILC as a single somatic event is sufficient to generate tumorigenesis.operties ,84. Its operties . On the operties . First-eCDH1 was initially known as a susceptibility gene for gastric cancer of the diffuse type, following the identification of germline mutations in Caucasian, Maori and African-American families with multiple affected individuals [CDH1 families, the International Gastric Cancer Linkage Consortium showed that the clinical penetrance for diffuse gastric cancer was high, as the estimated risk for carriers of developing the disease was 67 to 83% [CDH1 families, some of them at an early age, and histology, when documented, was systematically of the lobular type. The estimated risk for ILC was 39% by age 80 years. Subsequent studies of families with CDH1 mutations led to similar conclusions: in four families with a total of 22 breast cancers, all invasive tumors for which a pathological report was available were lobular [Readers should be reminded here that ividuals -91. Likeividuals ,92,93. I7 to 83% . Interes7 to 83% . Indeed, lobular ,96. As fCDH1 germline mutations. Masciari and colleagues [CDH1 [in situ), Petridis and colleagues [BRCA1/2 mutations had not been excluded in all cases. Cancer geneticists should therefore consider prescribing CDH1 germline analysis in patients with a personal or family history of multiple pathologically proven early-onset ILC, but no diffuse gastric cancer, as the identification of a mutation would have direct and dramatic clinical implications. The patient would be offered risk-reducing gastrectomy (assuming her ILC has been successfully treated), given the high risk of diffuse gastric cancer [CDH1 mutations in patients and families with multiple cases of ILC are needed.There is increasing evidence that a personal history of early-onset bilateral ILC or family history of multiple ILC at a young age, in the absence of diffuse gastric cancer in the family, can be associated with lleagues  describees [CDH1 . In the lleagues  found mulleagues  had prevc cancer ,101. Herc cancer ,103. LarCDH1 mutation justifies personalized, intensive surveillance. The consensus 2010 CDH1 paper recommended that breast cancer surveillance be carried out within specific research protocols, and suggested annual magnetic resonance imaging (MRI) and mammogram starting at age 35 years [BRCA1/BRCA2 mutations, it seems reasonable to offer the same type of surveillance as a routine procedure, and start screening at age 30 years with annual MRI and mammogram [CDH1 mutation carriers that will address the issue are expected soon.The high risk of ILC in females carrying a 35 years . As ILC ammogram ,105. Rispost hoc analysis of 36 case–control studies [Over 80 other breast cancer susceptibility genes and loci have been identified in the past few years, but again none have entered clinical practice either because of the difficulty in interpreting results from sequencing analyses or because the RR associated with the mutated alleles is so low that there is at best limited clinical relevance ,106. OnlCDH1 proves that genes involved in susceptibility to ILC do not have to be involved in IDC susceptibility. The type-specific hypothesis is hardly ever explored in breast cancer epidemiology. It is essential, therefore, that, in the near future, studies start turning their attention specifically to ILC instead of relying on post hoc exploratory analyses, or on data extracted from families with mutations predisposing primarily to other cancers. More epidemiological studies are still needed to establish whether associations with other known  or still unidentified risk factors differ depending on the histological type. As for genetic studies, large-scale projects focusing on women with unexplained early-onset or familial ILC are urgently needed, as there are certainly many more clinically relevant susceptibility genes to discover. The identification of specific risk factors would help define high-risk groups that could benefit from adapted, personalized screening strategies.We have reviewed in this article the specificities of ILC regarding disease incidence and environmental, lifestyle and genetic risk factors, and have shown that there were notable differences with IDC. ILC is more strongly related to endogenous and exogenous female hormones and its incidence, therefore, is more subject to variation, depending, for example, on key reproductive factors such as age at menarche or at first pregnancy, or on MHT use. Genetic risk factors vary depending on breast cancer histology, and Lobular breast cancer, edited by Ulrich Lehmann. Other articles in this series can be found at http://breast-cancer-research.com/series/LBCThis article is part of a series on