Obesity has been shown to be inversely associated with breast cancer risk in premenopausal women, while increasing risk in postmenopausal women. However, the current evidence is largely based on studies in Caucasian populations. Associations in women of African ancestry (AA), who have a higher prevalence of obesity, have been evaluated in few studies and results suggest different effects.in situ or invasive breast cancer, age 20–75 yrs. In NYC, cases were recruited through hospitals with the largest referral patterns for AA women and controls through random digit dialing (RDD). In NJ, cases were identified in seven counties in NJ thorough the NJ State Cancer Registry, and controls through RDD and community-based recruitment. During in-person interviews, questionnaires were administered and detailed anthropometric measurements were obtained. Body composition was assessed by bioelectrical impedance analysis.We evaluated the impact of body size, body fat distribution, and body composition on breast cancer risk among AA women (978 cases and 958 controls) participating in the Women’s Circle of Health Study, a multi-site case–control study in New York City (NYC) and New Jersey (NJ). Cases were newly diagnosed with histologically confirmed ductal carcinoma BMI did not have a major impact on pre- or post-menopausal breast cancer, but was significantly associated with reduced risk of ER-/PR- tumors among postmenopausal women . Furthermore, increased premenopausal breast cancer risk was found for higher waist and hip circumferences after adjusting for BMI, with ORs of 2.25 (95% CI: 1.07-4.74) and 2.91 (95% CI: 1.39-6.10), respectively, comparing the highest vs. lowest quartile. While ORs for higher fat mass and percent body fat among postmenopausal women were above one, confidence intervals included the null value.Our study suggests that in AA women BMI is generally unrelated to breast cancer. However, higher waist and hip circumferences were associated with increased pre-menopausal breast cancer risk, while general obesity was associated with decreased risk of ER-/PR- tumors. Larger studies are needed to confirm findings and to evaluate the impact of obesity on breast cancer subtypes. In the United States, breast cancer is the most common cancer in women excluding skin cancer and the second leading cause of cancer mortality . Rates vObesity is a major public health concern in AA women, with the prevalence of obesity BMI ≥ 30) being 58.6% for “non-Hispanic black women” and 33.4% for “non-Hispanic white women”, according to 2009–2010 National Health and Nutrition Examination Survey (NHANES) data . Further0 being 5in situ (DCIS). Controls had the same eligibility criteria and no history of cancer and were identified, recruited, and interviewed during the same time period as the cases.The Women’s Circle of Health Study (WCHS) is a multi-site case–control study in New York City (NYC) and New Jersey (NJ) specifically designed to evaluate genetic and lifestyle risk factors for early/aggressive breast cancer and to compare the distribution of these factors in AA and EA women. The study design has been described in detail elsewhere . In brieIn NYC, cases were identified through collaborations with hospitals in Manhattan, Bronx, Brooklyn, and Queens with the largest referral patterns for AA women. Controls in NYC were ascertained by RDD, using the telephone exchanges (area code plus three-digit prefixes) of breast cancer cases who received medical care at the participating hospitals in previous years for sampling, frequency matched by 5-year age groups and race. In New Jersey, cases were identified through the NJ State Cancer Registry (NJSCR), using rapid case ascertainment in seven counties , with extension Monmouth and Burlington counties in 2012. Controls were identified by RDD in NYC and NJ, frequency matched by age group and county of residence to the cases. In NJ, controls were also recruited through community sources, as described in detail elsewhere .After confirming eligibility, an in-person interview was scheduled at the participants’ homes or a mutually agreed upon location. All interviewers underwent rigorous standardized training and testing before they were allowed to start conducting interviews and anthropometric measurements. Informed consent was obtained in person at the visit before data collection began. During the in-person interview several questionnaires were completed, body measurements taken, and biospecimens collected.The WCHS survey instrument covered established and suspected risk factors for breast cancer, including family history, reproductive and menstrual history, hormone use, alcohol intake and smoking, occupational history, and physical activity. Women were also asked to report their weight and height one year before diagnosis (for cases) or reference date (for controls), and at several times during their life.Anthropometric measurements were taken at the end of the visit using a standardized protocol based on the Women’s Interview Study of Health  and measA total of 979 AA cases and 958 AA controls completed the interview. Height and/or weight measurements were not available for 25 cases and 13 controls because the participants refused (n = 24), were more than 3 months pregnant (n = 2), or for other reasons  (n = 12). Because we found high correlation between BMI based on measurements and based on self-reported weight and height (r = 0.92), missing values for height and/or weight were substituted with self-reported values when available to compute the final BMI variable used to compute risk estimates. One case was excluded because she did not have measured or self-reported weight and height, leaving 978 cases and 958 controls for analyses.The study was approved by the Institutional Review Boards at the Cancer Institute of New Jersey (now Rutgers Cancer Institute of New Jersey), Mount Sinai School of Medicine (now the Icahn School of Medicine at Mount Sinai), and Roswell Park Cancer Institute and all participants provided written informed consent before participating in the study.All analyses were conducted separately in pre- and postmenopausal women. BMI was computed as weight in kilograms (kg) divided by the square of height in meters (m). Self-reported BMI one year prior to reference date (diagnosis date for cases and comparable date for controls) was calculated using measured height at interview and self-reported weight, except for 26 women for whom measured height was missing and instead, self-reported height was used. Fat mass index and fat free mass index were calculated as fat mass or fat free mass in kg, respectively, divided by the square of height in meters. BMI was categorized according to the World Health Organization (WHO) International Classification. For all other variables we used quartiles, based on the distribution of all controls combined. We used the same cutpoints in the two subgroups by menopausal status to be able to compare risk estimates across categories.t-test. Multivariable unconditional logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI), controlling for relevant confounders. Tests for trend were derived by assigning the median value to each category. Covariates considered included age, ethnicity (Hispanic vs. not Hispanic), country of origin , education, family history of breast cancer, history of benign breast disease, age at menarche, age at menopause, parity, breastfeeding (never/ever), age at first birth, hormone replacement therapy use (never/ever), oral contraceptive use (never/ever), years since menopause , and BMI in young adulthood. We also controlled for waist circumference when evaluating relationships with BMI, and BMI when evaluating relationships with body fat distribution to assess the potentially independent effects of general and central obesity, respectively.Distributions of selected risk factors between cases and controls stratified by menopausal status were compared using chi-square tests and means compared using the Possible effect modification by hormone receptor status was evaluated by conducting stratified analyses according to the major subtypes (ER+/PR + and ER-/PR-) in addition to conducting case-case analyses to estimate risk of ER-/PR- tumors compared to ER+/PR+ tumors. Analyses were repeated excluding HRT users and non-invasive tumors, as well as community controls. A finding with a p value of less than 0.05 was considered statistically significant. SAS version 9.2  was used for analyses.Selected characteristics for study participants by menopausal status are shown in Table As shown in Table When we evaluated measures of body fat distribution in pre- and post-menopausal women Table , there wRestricting analyses to invasive cases led to essentially the same results (data not shown). Because it has been suggested that the relationship between BMI and breast cancer risk may be limited to non-HRT users ,15, we aWe also explored possible effect modification by the major breast cancer subtypes based on hormone receptor status: ER+/PR+ and ER-/PR- Tables  and 7. TIn this study we found that BMI did not play a major role on breast cancer among AA women, except for a significant inverse association for ER-/PR- tumors in post-menopausal women. Furthermore, higher waist and hip circumferences increased pre-menopausal breast cancer risk, independent of BMI. While there was a suggestion of increased risk with higher fat mass and percent body fat among post-menopausal women, confidence intervals included the null value.Very few studies have previously evaluated the role of recent BMI on breast cancer risk among AA  andIn contrast to the findings for general obesity, we found a strong association with waist and hip circumferences, after adjusting for BMI in pre-menopausal women. While studies have typically used WHR to measure body fat distribution, waist circumference has been shown to be a better marker of central obesity than WHR in AA women . Other sFor post-menopausal breast cancer, the two case–control studies ,28 suggeTo examine breast cancer relationships with obesity and central adiposity independently, our analytic strategy involved generating mutually adjusted risk estimates. Because measures of central obesity  and BMI in general tend to be correlated, however, there is potential for multicollinearity and inadvertent introduction of bias . To ensuThe role of body composition on breast cancer risk has received little attention, particularly among AA women and, to our knowledge, we are the first study to evaluate it and found no significant associations. It should be noted that we used bioelectrical impedance to measure body composition, which is not as precise as other methods, such as dual energy x-ray absorptiometry (DXA) and computed axial tomography (CAT) . TherefoOur findings generally confirm the small but growing body of literature suggesting that obesity may have a different impact on AA compared to EA women. The association of BMI with body fatness varies by age, gender, and race/ethnicity . Body weCase–control studies are subjected to well-known limitations such as recall bias and selection bias. It is well known that women tend to underestimate weight and overestimate height, which could affect BMI computation. However, for the main variables under investigation we did not rely on participants’ recall and, instead, objective body measurements were taken. Case–control studies are also prone to selection bias if the participating controls are not representative of the source population that gave rise to cases. To improve participation among AA controls, we supplemented RDD recruitment for AA women in NJ with community recruitment. Community-based recruitment was efficient in recruiting participants and even some cases and RDD controls who refused to participate in our study when they were first approached, called us to do it after they saw the study advertised in their communities . This gave us some reassurance that the three groups  came from the same source population . AnotherOur study contributes to the limited literature on BMI and other measures of adiposity and breast cancer risk in AA women. As more evidence accumulates on the relationship between BMI and breast cancer, it is becoming obvious that the association is not straightforward, with obesity affecting differently the various subgroups defined by age, race/ethnicity, hormone receptor status, and use of exogenous hormones. For AA women, the evidence remains scarce, but points to a different relationship from that reported in EA, suggesting possible different mechanisms. Larger studies in AA women are needed to further evaluate these issues, as well as evaluate the effect by “intrinsic” subtypes , which were suggested in one study to be affected differently by adiposity measures . Future In summary, we found that higher waist and hip circumference were associated with increased risk of premenopausal breast cancer. While we did not find increased risk for general obesity, other studies have found that a higher BMI is associated with more advanced disease at diagnosis -39. TherAA: African ancestry; EA: European ancestry; NYC: New York City; NJ: New Jersey; RDD: Random digit dialing; SD: Standard deviation; OR: Odds ratio; CI: Confidence interval; BMI: Body mass index; WHR: Waist-to-hip ratio; HRT: Hormone replacement therapy; OC: Oral contraceptives; ER: estrogen receptor; PR: Progesterone receptor; NHANES: National Health and Nutrition Examination Survey; WCHS: Women’s Circle of Health Study; NJSCR: New Jersey State Cancer Registry.The authors declare that they have no competing interests.EVB and CBA designed the study. EVB, CBA, GC directed its implementation. EVB and UC designed the analytic strategy. UC and GZ conducted data processing and cleaning. UC conducted statistical analyses. SEM and CCH provided expertise in the interpretation of results. EVB wrote the first draft of the manuscript and all co-authors provided substantive comments and editorial review and approved the final version of the manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2407/13/475/prepub


The purpose of this study was to determine the proportion of breast cancer survivors with 2 or more risk factors for CVD exhibiting a low VO2max and to determine whether sub-maximal endpoints which could be applied more readily to intervention research would correlate with the maximal treadmill test. We performed a single VO2max test on a treadmill with 30 breast cancer survivors age 30–60 (mean age 50.5 ± 5.6 years) who had 2 or more cardiac risk factors for CVD not related to treatment and who had received systemic therapy and or left chest radiation. Submaximal VO2 endpoints were assessed during the VO2max treadmill test and on an Arc trainer. Resting left ventricular ejection fraction (LVEF) was also assessed by echocardiogram (ECHO) or multi-gated acquisition scan (MUGA). A majority (23/30) of women had a VO2max below the 20th percentile based on their predicted normal values. The group mean resting LVEF was 60.5 ± 5.0%. Submaximal VO2 measures were strongly correlated with the maximal test including; 1) 85% age predicted maximum heart rate VO2 on treadmill, , 2) treadmill VO2 at anaerobic threshold (AT), , and 3) Arc VO2 at AT, . Breast cancer survivors with 2 or more CVD risk factors but normal LVEF had a low cardiorespiratory fitness level compared to normative values in the healthy population placing them at increased risk for breast cancer and cardiovascular mortality. Submaximal VO2 exercise testing endpoints showed a strong correlation with the VO2max test in breast cancer survivors and is a good candidate for testing interventions to improve cardiorespiratory fitness.Maximal oxygen uptake (VO In contSubmaximal exercise testing has been used to provide a measure of cardiorespiratory fitness, with outcomes based on anaerobic threshold in patients with a history of congestive heart failure  with different submaximal testing endpoints in breast cancer survivors. We hypothesized the VO2 at submaximal endpoints would be highly correlated with VO2max in breast cancer survivors and they would have a lower VO2max than age and gender matched normative values. Important clinical implications can arise from evaluating cardiorespiratory fitness in breast cancer survivors and targeting those in the greatest need of preventive measures.A recent meta-analysis indicates a need for a standardized and objective measure of fitness which can be readily utilized in the breast cancer survivorship population ,(ACSM .dL-1) . An arc Trainer was used instead of a treadmill in cases where minimization of vertical stress was needed such as women with knee and back problems. Arc Trainers use a low-impact mechanical design with production of lower vertical forces and joint loading compared to walking on a treadmill . Inclusion criteria were as follows: previously diagnosed with stage I-IIIa breast cancer; ages 30–60; no evidence of metastatic disease; at least 3-months from completing initial chemotherapy and/or radiation therapy; and within 10 years of initial diagnosis. Subjects had to also have 2 of the following cardiac risk factors: body mass index (BMI) ≥ 25 kgHg),ACSM  elevated-1) NCEP , positivThe study was approved by the University of Kansas Medical Center Human Subjects Committee (HSC #12251) and written informed consent was obtained from all participants at an orientation meeting prior to conducting any study testing or activities.All study procedures were conducted during three testing sessions within a two week time frame at the Clinical Translational Science Unit (CTSU) on the University of Kansas Medical Center campus and the cardiovascular lab located at the University of Kansas Hospital. Participants were instructed to refrain from exercise 48 hours prior to maximal and submaximal cardiorespiratory testing. In addition, all participants were asked not to consume any food, caffeine, alcohol, and tobacco products three hours prior to exercise tests. The exercise testing sessions were between 2 and 14 days apart and at the same time of the day. All cardiorespiratory tests followed the American College of Sports Medicine (ACSM) guidelines for procedures during graded exercise testing ACSM . In addi2 and CO2. Heart rate, blood pressure, and rating of perceived exertion score were determined at the end of each two minute stage. Confirmation of a maximal effort was determined by meeting three out of four of the following criteria; 1) plateau in heart rate and oxygen uptake with increased workload, 2) respiratory exchange ratio > 1.1, 3) rating of perceived exertion > 17, and 4) heart rate > 90% of age predicted maximal heart rate.Cardiorespiratory fitness was assessed using a modified Balke protocol Balke . Tests w2 at anaerobic threshold and 85% age predicted maximum heart rate. Initial criteria for anaerobic threshold was established by using the respiratory exchange ratio ≥ 1.0. Participants were allowed to continue for three consecutive 15 second averages at a respiratory exchange ratio ≥ 1.0 to ensure anaerobic threshold was reached. Post-test confirmation of the anaerobic threshold was made upon visual assessment of 1) V-slope method, and 2) ventilatory equivalent technique to rule out hyperventilation. Submaximal VO2 at 85% age predicted maximum heart rate was assessed with the calculation [(220-age) × 0.85] and determination of the corresponding VO2 at that heart rate during maximal testing on the treadmill.Cardiorespiratory fitness submaximal endpoints on the treadmill were determined by the VO2 at anaerobic threshold. Criteria for anaerobic threshold was determined by the same method as the submaximal treadmill endpoint.After a brief familiarization trial followed by a short rest period, participants began the Arc submaximal test. Participants’ weight was input into the console before starting the test. The manual mode was used for testing, with initial workload set at a resistance level of 15. Participants were asked to maintain between 80–100 strides per minute and a level grade was used throughout the test. Workload was adjusted to allow a steady increase in heart rate until subjects reached the anaerobic threshold endpoint. Increased workload was performed manually by a gradual increase in wattage while adjusting resistance in two minute stages. Resistance at each two minute stage varied between participants to allow a steady increase in heart rate, and was adjusted by a 5–10 numerical increase on the Arc trainer console resistance key pad. The cardiorespiratory fitness submaximal endpoint on the Arc trainer was determined by the VO2max during the maximal treadmill test. Group mean VO2max was compared to the normative VO2max value for healthy age-matched women  was assessed by a cardiologist not associated with the study..m-2).Body weight was assessed to the nearest 0.1 kg, using an electronic scale . A stadiometer was used to measure height without shoes to the nearest 0.1 cm (SECA). Body composition was measured by dual-energy x-ray absorptiometry in the total body scanning mode with a Lunar Prodigy DXA machine . Body mass index was calculated as the weight in kilograms divided by the height in meters squared , elevated LDL (66%), family history of heart disease (40%), and sedentary lifestyle (33%). Additionally, the group mean body fat % was 44.5 ± 7.7%. Treatment related risk factors are listed in Table Cohort characteristics and non-treatment CVD risk factors are listed in Table 2max as established by the American College of Sports Medicine  was similar to the 20th percentile threshold value (25.1 mL.kg-1.min-1) for age and gender group matched normative values.All cardiorespiratory fitness measures are listed in Table ine ACSM , despites Figure , and theAll 30 maximal and 30 submaximal cardiorespiratory tests were completed without any adverse events. During maximal testing twenty-eight of thirty participants met our established criteria for a maximal effort as explained previously. Two of the participants discontinued the test secondary to a claustrophobic sensation related to the mouthpiece, fatigue, and/or shortness of breath. Symptoms were resolved by discontinuing the test and having the participants rest while monitoring all post-test vitals. Even though two participants discontinued the maximal test prior to reaching maximal criteria, both participants achieved > 85% APMRH on the treadmill and have been included in the analyses.2max despite a normal LVEF at time of study. These results suggest that they are at a higher risk of breast cancer and cardiovasular mortality  to the standardized treadmill test used for determining normative values   to submaximal VO2 tests in breast cancer survivors who had been treated with adjuvant therapy. The findings from this study indicate that breast cancer survivors with ≥ 2 CVD risk factors had low cardiorespiratory fitness and submaximal testing on the treadmill is a feasible, objective measure of fitness that can be used in breast cancer survivors. Limitations of this study include the small sample size (n = 30), lack of racial diversity, and lack of non-cancer controls.This is the first study to investigate the association between the gold standard for cardiorespiratory fitness (VO2 measures. In addition, novel approaches should be made to improve cardiorespiratory fitness during sustainable exercise interventions for breast cancer survivors.Future research should focus on using a high-risk breast cancer control group with ≥ 2 CVD risk factors to compare maximal and sub-maximal VOAll work described within this manuscript complies with United States and institutional regulations for the protection of human subjects.Co-authors: Patricia Kluding, Charles Porter, Carol Fabian, Jennifer Klemp.


To reduce mortality, women with a family history of breast cancer often start mammography screening at a younger age than the general population. Breast density is high in over 50% of women younger than 50 years. With high breast density, breast cancer incidence increases, but sensitivity of mammography decreases. Therefore, mammography might not be the optimal method for breast cancer screening in young women. Adding MRI increases sensitivity, but also the risk of false-positive results. The limitation of all previous MRI screening studies is that they do not contain a comparison group; all participants received both MRI and mammography. Therefore, we cannot empirically assess in which stage tumours would have been detected by either test.The aim of the Familial MRI Screening Study (FaMRIsc) is to compare the efficacy of MRI screening to mammography for women with a familial risk. Furthermore, we will assess the influence of breast density.This Dutch multicentre, randomized controlled trial, with balanced randomisation (1:1) has a parallel grouped design. Women with a cumulative lifetime risk for breast cancer due to their family history of ≥20%, aged 30–55 years are eligible. Identified BRCA1/2 mutation carriers or women with 50% risk of carrying a mutation are excluded. Group 1 receives yearly mammography and clinical breast examination (n = 1000), and group 2 yearly MRI and clinical breast examination, and mammography biennially (n = 1000).Primary endpoints are the number and stage of the detected breast cancers in each arm. Secondary endpoints are the number of false-positive results in both screening arms. Furthermore, sensitivity and positive predictive value of both screening strategies will be assessed. Cost-effectiveness of both strategies will be assessed. Analyses will also be performed with mammographic density as stratification factor.Personalized breast cancer screening might optimize mortality reduction with less over diagnosis. Breast density may be a key discriminator for selecting the optimal screening strategy for women < 55 years with familial breast cancer risk; mammography or MRI. These issues are addressed in the FaMRIsc study including high risk women due to a familial predisposition.Netherland Trial Register NTR2789 A positive family history is one of the most important risk factors for breast cancer. Women wIn the last decade several screening trials in high-risk women have been completed and Magnetic Resonance Imaging (MRI) had a significantly higher sensitivity for invasive breast cancer than mammography in all studies-12. HoweBRCA1 and BRCA2 gene mutation carriers aged 30–60 years or women who have a 50% chance of carrying such a mutation[Despite the higher costs of MRI and the false-positive results, screening with yearly MRI in addition to mammography is considered cost-effective for female mutation-16. For mutation,18. SincApart from a positive family history and age, high breast tissue density is a well documented risk factor for breast cancer. Breast density increases breast cancer incidence significantly,20. At tTo the best of our knowledge, no study has been published assessing the cost-effectiveness of MRI specifically in women with a familial risk for breast cancer, without a known genetic predisposition. Therefore, guidelines for breast cancer screening for women with a familial risk vary widely internationally and are weakly underpinned. The 2008 American Cancer Society and 2010 American College of Radiologists guidelines advise MRI screening for women with a familial cumulative lifetime risk (CLTR) > 20%, while tRobust cost-effectiveness analyses cannot be based on the published studies, as all had a paired design . These studies cannot examine the improvement in tumour stage at diagnosis, as one cannot know in what stage the tumour would have been diagnosed by either test alone. A randomized controlled trial is needed for a valid answer to these questions.Furthermore, cost-effectiveness of either imaging technique may vary across categories of mammographic density. Breast density has not yet been evaluated as a parameter to identify sub-groups of women with a familial risk, for whom MRI is cost-effective. A prospective randomized trial in women with increased breast cancer risk, taking breast density into account, will give robust evidence on which screening tool, MRI or mammography, is best suited for a particular woman. These issues are addressed in the Familial MRI Screening study (FaMRIsc).The FaMRIsc study is a multicentre, randomized controlled trial (RCT), with balanced randomisation (1:1), and a parallel group design conducted in the Netherlands. The study is in compliance with the Helsinki declaration and ethical approval has been granted on 8 November 2010 by the Institutional Review Board of the Erasmus University Medical Centre, Rotterdam, the Netherlands (reference-number: MEC-2010-292).BRCA1 and/or BRCA2 mutation carriers or women with a 50% likelihood of such a mutation are excluded, since MRI screening is already advised for these women by the American Cancer Society (ACS), the American College of Radiologists (ACR), the United Kingdom’s NICE guideline and the European guideline of the European Society of breast imaging (EUSOBI)[Eligible participants are women aged 30–55 years with a cumulative lifetime risk (CLTR) of >20% because of a familial predisposition according to the modified tables of Claus,27 or as(EUSOBI),28-30. EParticipants are recruited from outpatient breast or family cancer clinics at all eight academic medical centres in the Netherlands and the Netherlands Cancer Institute/Antoni van Leeuwenhoek Hospital . Women wAfter informed consent is obtained participants are randomized through a computer-generated randomization sequence with stratification for centre, in one of the two groups.Group 1 receives screening according to the 2012 Dutch guidelines with yeaGroup 2 is screened with yearly MRI and CBE, and mammography biennially Figure. AdditioPrimary endpoints are the number and stage of detected breast cancers, both DCIS and invasive, in each arm. Secondary endpoints are the false-positive results in the screening arms, and the sensitivity and positive predictive value of both screening strategies. Furthermore, cost-effectiveness and breast cancer mortality reduction of both strategies will be assessed. All analyzes will also be performed stratified for mammographic density.A positive screening test is defined as a mammographic or MRI examination with a BI-RADS score of 0, 3, 4, or 5 and/or a clinical breast examination classified as ‘suspicious’. Interval cancers are defined as tumours diagnosed after a negative screening examination but before the next scheduled screening examination. Sensitivity is calculated as the number of screen-detected tumours divided by the total of screen-detected and interval tumours. The positive predictive value of a screening strategy is calculated as the proportion of women with a positive screening test, which after pathology indeed proved to be breast cancer.Prospective assessment of mortality reduction requires a very lengthy follow-up and a large study population, which may not be feasible. To study this issue we will start with a less costly and time-consuming approach and estimate mortality reduction through a micro-simulation model: MISCAN, a well-validated micro-simulation model, originally developed to estimate the cost-effectiveness of the population-based screening program in the Netherlands-40. In tWe will develop a family history risk model by using the number of women enrolled in the study, the age distribution at entry of the study, the duration of follow-up and the screening protocol, attendance and sensitivity of different screenings methods as inputs. The model will be calibrated using the number of screens, the number of screen detected cancers and interval cancers, the stage distribution and the age at diagnosis. Likelihood ratio tests will be used to compare the goodness of fit. Using the calibrated model, predictions of the number of screens, number of screen detected and interval cancers, the stage distribution, the mortality reduction and the life years gained will be made for the different screening arms in the study.A cohort of 5 million women will be simulated. All costs and effects will be predicted for a life-time follow-up. The costs will be presented in European currency (€). Cost-effectiveness ratios will be expressed as cost per life year gained (LYG). Costs and effects will be discounted at an annual rate of 3.5%.Our primary aim is to detect a difference in tumour stage between the intervention and the current practice group. In the Dutch MRI Screening Study (MRISC) study, conducted from 1999 to 2007, over 1500 women with familial risk were included in the 6 participating centres. The incThe accrual will be evaluated after two years. If adequate inclusion numbers cannot be achieved, appropriate measures will be taken in the remaining two years, consisting of expansion of the number of participating centres or longer continuation of the study.t-test. If not normally distributed, medians will be estimated and differences between distributions will be tested with the non-parametric Mann–Whitney U test.Primary outcome will be incidence and the difference in mean tumour size at diagnosis between the two arms. If normally distributed, this will be tested by means of the independent samples (unpaired) Breast cancer incidence rates will be calculated as the total number of breast cancers detected per 1000 woman-years at risk. This will be calculated both including and excluding DCIS. Differences between these proportions will be compared using a chi-square test or Fisher’s exact test as appropriate.All tests will also be performed stratified by mammographic density to examine the influence of density on the efficacy of MRI screening versus usual care. The influence of breast density on detection rates, tumour stage and false positive results in both arms will be analysed by means of analysis of variance (ANOVA).Twenty-five percent of all breast cancers occur before age 50 and especially familial breast cancer is seen at younger ages. A randoStudies that offered MRI and mammography screening simultaneously have several shortcomings due to their paired design. Sensitivity of neither test without the other can be assessed. Nor the stage in which either test separately would have detected tumours.With the results of our study we will be able to estimate the mortality reduction for screening women with familial risk with either digital mammography or additional MRI.Furthermore, we will be able to assess whether mortality reduction by earlier detection differs with increasing breast density between screening with digital mammography or with additional MRI.Breast density may be a key discriminator for choosing the optimal screening strategy below age 50 years for women with familial risk. If we can assess this, personalized cancer screening can be offered, based on a woman’s age, risk and breast density. This may optimize mortality reduction, whilst possibly decreasing over diagnosis. Compliance to screening will be best if there is convincing evidence that the most effective tool with the lowest side-effects is offered.ANOVA: Analysis of variance; ACS: American Cancer Society; ACR: American College of Radiologists; BI-RADS: The Breast Imaging Reporting and Data System; CBE: Clinical Breast examination; CLTR: Cumulative Lifetime Risk; DCIS: Ductal Carcinoma In Situ; EUSOBI: European Society Of Breast Imaging; FaMRIsc: Familial MRI Screening Study; FFDM: Full Field Digital Mammography; LYG: Life Year Gained; MISCAN: Microsimulation Screening Analysis; MRI: Magnetic Resonance Imaging; MRISC: MRI Screening Study; RCT: Randomized Controlled Trial.The authors declare that they have no competing interests.MMAT-L is the scientific coordinator of this research and designed the study. MMAT-L, IMO, HJK and SS applied for funding. MMAT-L and SS have drafted the manuscript with critical input from all other authors who have read, and approved the final manuscript. All authors are involved in data acquisition.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2407/12/440/prepub Academic Medical Centres participating in the FaMRIsc in the Netherlands. (DOC 31 kb)Click here for file


Risk prediction algorithms are an important tool for identifying individuals at high risk of developing the disease who can then be offered individually tailored clinical management. Several algorithms that predict the probability of breast cancer incidence are currently used in clinical practice. It is uncertain, though, as to which of the breast cancer risk prediction models performs best for female relatives of Australian women with breast cancer.We evaluated the performance of the risk prediction algorithms BOADICEA, BRCAPRO and the Gail model using 879 families of ABCFS case probands, half of whom were diagnosed before age 40 years and the remainder before age 60 years. Cumulative breast cancer risks over 10 years of follow-up were calculated for 2000 unaffected female relatives.A total of 93 incident breast cancers were reported. The ratios (95% CI) of expected to observed number of breast cancers were 0.69 (0.56-0.84) using BOADICEA, 0.62 (0.51-0.77) using BRCAPRO, and 0.89 (0.73-1.09) using the Gail model. Tests for discrimination (ROC curve) were BOADICEA=0.61, BRCAPRO=0.64, and the Gail model=0.65.Similar analyses using other models, including the Tyrer-Cuzick (IBIS) and Claus models, will also be presented.


Causes of the rapidly increasing incidence of breast cancer in Middle East and Asian countries are incompletely understood. We evaluated risk factors for postmenopausal breast cancer and estimated their attributable fraction in Iran.We performed a hospital-based case–control study, including 493 women, diagnosed with breast cancer at 50 years or later between 2005–2008, and 493 controls. We used logistic regression models to estimate multivariable odds ratios (OR) and 95% confidence intervals (CI), and population attributable fractions (PAF) for significant risk factors.The risk of breast cancer decreased with increasing parity. Compared with nulliparous women, the adjusted OR (95% CI) was 0.53 (0.25-1.15) for parity 1–3, 0.47 (0.29-0.93) for parity 4–6 and 0.23 (0.11-0.50) for parity ≥7. The estimated PAF for parity (<7) was 52%. The positive association between body mass index (BMI) and breast cancer risk was confined to women diagnosed at 58 years or later. Compared with normal weight women (BMI 18.5-24.9), overweight (BMI 25–29.9) and obese (BMI ≥30) women were at increased risk of breast cancer diagnosed at 58 years or later . The estimated PAF for obesity/overweight (BMI >25) was approximately 25%. The family history was significantly associated with increased breast cancer risk, but not increasing height, early age at menarche, late age at first birth or short breastfeeding.Decreasing parity and increasing obesity are determinants of increasing breast cancer incidence among Iranian women. These trends predict a continuing upward trend of postmenopausal breast cancer. With an estimated 1.4 to 1.6 million new cases diagnosed around the world in 2008, breast cancer is the most common cancer among women in high-and middle-income, but also in a growing number of low-income countries , especiaIn Iran, the annual number of new breast cancer cases is estimated to double from 2008 to 2030 due to the demographic transition alone . HoweverWe performed a hospital-based case control study to identify risk factors for postmenopausal breast cancer in Iranian women. Cases were recruited from Motahari Breast Clinic of Shiraz University of Medical Sciences. This center collects data from about 80% of all incident breast cancer patients treated in main hospitals of Shiraz city, including general hospitals of Faghihi and Namazi and private hospitals of Dena and Ordibehesht. Shiraz, the capital city of Fars province, is located in the southern part of Iran. Faghihi hospital is the major hospital providing oncology services for breast cancer patients, and more than 85% of newly diagnosed breast cancer patients within the Fars province are referred to this hospital for treatment. In addition, the Faghihi hospital is also the referral center for other provinces in the southern part of Iran, including Bushehr, Khuzestan, Hormozgan and Kohgiluye & Boyer Ahmad. Women with histopathologically confirmed breast cancer are referred to Motahari clinic for postoperative care and follow-ups. Women with newly diagnosed breast cancer are interviewed using a structured questionnaire that contains questions about risk factors for breast cancer and other reproductive cancers.Eligible cases were women with an incident histopathologically confirmed breast cancer, diagnosed at 50 years of age or older. Most patients (93%) were interviewed within six months after diagnosis. All women were interviewed between September 2005 and December 2008. We excluded five cases with missing information on age and eleven case patients from other provinces because we could not find any matched controls for them.Controls were frequency-matched with cases on five-year age groups and province of residence. Controls were primarily selected from healthy female visitors accompanying patients referred to the Faghihi hospital for general surgery (60%), urology (24%) and cardiovascular (16%) diseases. Controls did not have a history of breast cancer at enrollment. For a small number of old case patients (11%), for whom we could not find a healthy control, we selected controls from patients referred to urology, cardiovascular and general surgery wards for conditions unrelated to known or likely risk factors for breast cancer, like gynecologic, hormonal or neoplastic diseases. A total of 487 potentially healthy visitor controls and 98 patient controls were selected, but 49 (10%) healthy women and 43 (44%) patients refused to participate. Finally, a total of 493 cases of postmenopausal breast cancer and 493 controls were included in the study.Reliable information about age at menopause was not available for the study subjects. When information on menstrual history is not available, 50 years of age may be the best proxy for all menses-based definitions of menopause in western countries. It has For both cases and controls, face-to-face interviews were performed, using an identical structured questionnaire to collect information on age, place of residence, marital status, educational level, family history of breast cancer, age at menarche, occupation, parity, past use of oral contraceptives, age at first pregnancy and lifetime duration of breastfeeding. Cases were interviewed at their first time of treatment between September 2005 and December 2008. Controls were interviewed from May 2009 through August 2009. Interviews were conducted by two trained female nurses (one for cases and one for controls), and the time of interviews was similar for cases and controls. Height and weight were measured at the end of the interview. None of interviewers were aware of the study hypotheses.All included subjects were informed about the study protocol and provided oral informed consent. The study was approved by the Research Ethics Committee of Shiraz University of Medical Sciences.2) and categorized as <18.5, 18.5-24.9, 25–29.9 and ≥30 kg/m2.Information on parity was collected as a categorical variable , and therefore analyzed accordingly. Information on age at menarche and age at first childbirth was collected using categorical variables in the questionnaire: < 12, 12–15 and >15 years for age at menarche; and <15, 15–24 and ≥25 years for age at first childbirth. Education was categorized as illiterate, elementary, high school and university degree. Occupation was grouped as housewife and employed. Life time duration of breastfeeding was categorized as never and in approximate tertiles based on the distribution among controls . Average months of breastfeeding per child was categorized as <12 months and ≥12 months. Oral contraceptive use was categorized as never/ever, and (among ever users) the duration of usage, categorized based on the tertile values of the distribution among controls . Height was categorized based on its approximate quartile cut-off points of the distribution among controls . BMI was calculated as weight (kg) divided by height squared  to estimate the odds ratios (ORs) and 95% confidence intervals (CI). We used univariable analyses to estimate the crude ORs and 95% CI. Multivariable logistic regression models were fitted to estimate the association between each independent variable and postmenopausal breast cancer while adjusting for other potential confounding variables. Additional analyses were performed on data restricted to parous women (n = 936). The models for these analyses were stratified for categories of parity.aflogit module developed for Stata. All P values were 2-sided. All analyses were conducted using Stata 11.0 software .To examine the hypothesis that the obesity-related risk is smaller among perimenopausal or recently postmenopausal women than among elderly women, we also conducted analyses stratified by the mean of age of breast cancer (less than 58 years and 58 years or older). We assessed significance of interaction using Wald test statistics. We also computed adjusted population attributable fractions and 95% confidence intervals for significant variables  as described by Greenland and Drescher [The mean age of the 493 women diagnosed with postmenopausal breast cancer was 58.2  and 58.0  among the 493 frequency-matched controls. As depicted in Table Compared with nulliparous women, parous women had a reduced risk of postmenopausal breast cancer in both univariable and multivariable analyses Table . The risBMI revealed a significant linear association with breast cancer risk (P-trend = 0.01). Compared with normal weight women (BMI 18.5-24.9), overweight (BMI 25.0-29.9), and obese women BMI ≥30) had, in the unadjusted and adjusted analyses, approximately a 40% and a 60% increased risk of breast cancer, respectively. In the association between BMI and breast cancer, parity was a weak positive confounder and only adjusting for parity slightly attenuated the OR related to overweight  but not obesity . In analyses stratified by the mean age of breast cancer (less than 58 years and 58 years or more), the positive association between BMI and breast cancer was restricted to women aged 58 or older. However, the (multiplicative) interaction term between BMI and age was not significant  accounted for approximately 64% of breast cancer among postmenopausal women in Iran.To the best of our knowledge, this is the largest case–control study of postmenopausal breast cancer in Iran. Nonetheless, our study has some important limitations. Hospital-based case–control studies are particularly susceptible to selection bias . We are We found that the grand multiparous women differed from those with fewer childbirths; they were less educated, had a younger age at first pregnancy, breastfed their children for longer periods and were less likely to use oral contraceptives. We find it likely that the protective effect of grand multiparity can to a large extent be explained by unmeasured lifestyle factors, which distort the association away from the null and strengthened it. For example, differences between women with high and low parity with respect to exposures to traditional low calorie high fiber diets, physical activity due to traditional way of life, early life events and conditions may play a role for the breast cancer risk in parous women . FurtherIn most studies, the association between parity and breast cancer risk is modified by age at first pregnancy. MacMahon et al. discovered that younger age at first childbearing reduces the risk of breast cancer . This asWe found no significant association between breastfeeding and risk of postmenopausal breast cancer. Results of a collaborative study, combining epidemiological data from 47 studies, found a protective role of breastfeeding on the risk of breast cancer . HoweverWe found no significant association between education and breast cancer after adjusting for other variables in multivariable analysis. In Iran, womens’ literacy rates increased from 57% to 97% between 1966 and 1996 in urban areas, while corresponding increase in rural areas was even more dramatic (from 5% to 86%) . In 1998The positive association between BMI and risk of postmenopausal breast cancer in our study is consistent with the results of other studies in high-risk and low-risk countries-40. In sIran experienced a high fertility rate until the 1980s . In 1980In summary, low parity and obesity were the main risk factors among postmenopausal women. The estimated attributable fraction combined for parity less than 7 children and overweight/obesity (BMI > 25) accounted for approximately 64% of breast cancer among postmenopausal women in Iran. We predict a birth cohort effect with an uprising trend in incidence rate of breast cancer in Iran and many other Middle Eastern countries in the near future.BMI: Body mass index; CI: Confidence interval; OR: Odds ratio; SD: Standard deviation; PAF: Population attributable fraction.The author(s) declare that they have no competing interests.RGH participated in the design of the study, performed the statistical analysis and drafted the manuscript. SHB contributed in the conception of the study and manuscript preparation. KZ contributed in the conception of the study and manuscript preparation. ST and AT contributed in the data acquisition and manuscript preparation. HOA contributed in the development of methodology and manuscript preparation. SC participated in the conception of the study, development of methodology and manuscript preparation. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2407/12/414/prepub


A Mediterranean diet has a recognized beneficial effect on health and longevity, with a protective influence on several cancers. However, its association with breast cancer risk remains unclear.We aimed to investigate whether adherence to a Mediterranean dietary pattern influences breast cancer risk.The Swedish Women’s Lifestyle and Health cohort study includes 49,258 women aged 30 to 49 years at recruitment in 1991–1992. Consumption of foods and beverages was measured at enrollment using a food frequency questionnaire. A Mediterranean diet score was constructed based on the consumption of alcohol, vegetables, fruits, legumes, cereals, fish, the ratio of unsaturated to saturated fat, and dairy and meat products. Relative risks (RR) for breast cancer and specific tumor characteristics  associated with this score were estimated using Cox regression controlling for potential confounders.1,278 incident breast cancers were diagnosed. Adherence to a Mediterranean dietary pattern was not statistically significantly associated with reduced risk of breast cancer overall, or with specific breast tumor characteristics. A RR  for breast cancer associated with a two-point increment in the Mediterranean diet score was 1.08 (1.00–1.15) in all women, and 1.10 (1.01–1.21) and 1.02 (0.91–1.15) in premenopausal and postmenopausal women, respectively. When alcohol was excluded from the Mediterranean diet score, results became not statistically significant.Adherence to a Mediterranean dietary pattern did not decrease breast cancer risk in this cohort of relatively young women. The Mediterranean diet has been inscribed on the heritage list of the United Nations Educational, Scientific and Cultural Organization Hormonal risk factors, such as exposure to endogenous and exogenous hormones Body fatness reduces the risk of premenopausal breast cancer, and increases the risk in postmenopausal women We used data from the prospective Swedish Women’s Lifestyle and Health (WLH) cohort study to investigate whether adherence to a Mediterranean dietary pattern influences breast cancer risk. We separately examined specific breast cancer tumor characteristics and adjusted for an extensive range of potential confounders.As previously described in detail In 2003, these 49,258 women were sent a follow-up questionnaire, which was completed by 34,402 women. This questionnaire updated information collected in the baseline questionnaire. The WLH study was approved by the Swedish Data Inspection Board and the regional Ethical Committee, Uppsala University, Uppsala, Sweden and the Ethical Committee of the Karolinska Institutet in Stockholm, Sweden. All participants signed an informed consent form.The baseline questionnaire included a validated food frequency questionnaire that assessed the frequency and quantity of approximately 80 food items and beverages consumed during the 6 months preceding study recruitment. Reported consumption of foods and beverages were then translated into nutrient and energy intakes using the Swedish National Food Administration database a priori, namely alcohol, vegetables, fruits, legumes, cereals, monounsaturated to saturated fat ratio, dairy and meat products. The variant of the score that we used, also proposed by Trichopoulou et al We measured adherence to a Mediterranean dietary pattern using a variant of the Mediterranean diet score proposed by Trichopoulou et al We calculated the median consumption of each component in the WLH cohort, and constructed a Mediterranean diet score for each participant based on her consumption of each component compared to that of the overall cohort. We treated components differently according to whether they are traditionally consumed more or less in Mediterranean countries. We assigned components that are more frequently consumed, such as vegetables, fruits and nuts, legumes, cereals, fish and a high ratio of unsaturated to saturated lipids, a value of 1 if a participant’s consumption was above the cohort median for that component, and a value of 0 otherwise. For components that are less frequently consumed in Mediterranean countries  we assigned a value of 1 if a participant’s consumption was below the cohort median, and 0 otherwise.As alcohol is usually consumed moderately and regularly in Mediterranean countries, we assigned a value of 1 to participants who reported a consumption of 5 to <25 g/day, and a value of 0 for all other intakes. We then summed the values for all components  to obtain a participant’s Mediterranean diet score. The score varied between 0 and 9; the higher the score, the closer the adherence to a Mediterranean dietary pattern. Because alcohol is an established risk factor for breast cancer All participants were followed up through linkages with nationwide health registers using the individually unique national registration number assigned to all legal residents in Sweden. The study population was linked to the population register for information on emigration and death. Data on breast cancer was obtained through linkage with the national cancer register through 2008, and the breast cancer quality register in the Uppsala health care region (that started in September 1992). Information on breast tumor characteristics was available in the regional, but not in the national cancer register. During follow-up, 322 participants had a diagnosis of breast cancer  in the national cancer register that was not recorded in the regional quality breast cancer register in Uppsala, as they had moved out of Uppsala County after cohort recruitment.Information from both baseline and follow-up questionnaires was used to determine menopausal status. We extracted data on oophorectomy and hysterectomy from the national in-patient register st and 99th percentiles  were excluded.Participants were excluded if they had been diagnosed with breast cancer before or at recruitment (N = 244). In addition, 981 participants with a total energy intake outside the 1Crude distributions of various possible breast cancer risk factors were calculated, and we examined how these factors were associated with breast cancer risk in the WLH study by estimating RRs for breast cancer in premenopausal and postmenopausal women.The association between breast cancer incidence and adherence to a Mediterranean dietary pattern was examined by fitting Cox regression with attained age as a time scale, considering all participants together, as well as premenopausal and postmenopausal participants separately. We followed up premenopausal participants from the date the baseline questionnaire was completed until primary breast cancer diagnosis, death, emigration, end of follow-up (31 December 2008), or the date of menopause, whichever occurred first. For postmenopausal participants, women-years were calculated from the date of menopause or the date the baseline questionnaire was completed (whichever occurred last), until the date of primary breast cancer diagnosis, death, emigration, or 31 December 2008 (whichever occurred first). Therefore, participants who were both premenopausal and postmenopausal during follow-up are included in the stratified analyses of both premenopausal and postmenopausal participants.As information on specific breast tumor characteristics, obtained through the regional quality breast cancer register in Uppsala, was available as from September 1992, we used this date as the start of follow-up when examining these characteristics. When examining a specific breast tumor characteristic, the event of interest was that characteristic, and participants with other breast tumor characteristics or with missing information were censored at breast cancer diagnosis.versus time 2), height , age at first birth and total number of children , educational level , age at menarche , total energy intake , consumption of beverages , potatoes , sweets , and eggs . These possible confounding factors were selected a priori due to their possible effect on breast cancer risk and their potential association with diet. Potatoes intake was consider as a possible confounder because while being a vegetable, the effect of potatoes consumption on health has been reported to differ from the commonly acknowledged beneficial effect of vegetables. Meat consumption is one the component of the Mediterranean diet score and we adjusted the analyses for eggs intake as it is another high source of animal protein. Our analyses were adjusted for energy intake, sweets, whose consumption has been reported to be detrimental for health, are a high source of energy and we, therefore, adjusted analyses for sweets consumption. We performed the statistical analyses adjusting also for physical activity and found similar results. However, due to lack of completeness of physical activity reporting (2392 missing answers), this variable was not included in the final model. Possible modifying effects of BMI, age at menarche, age at first birth and number of children, history of breast cancer in mother and/or sister(s), smoking status, total energy intake at baseline, and ever-use of oral contraceptive and hormone therapy at follow-up were ascertained by adding interaction terms to the statistical model. We used baseline and follow-up questionnaires to ascertain hormone therapy and oral contraceptive use: women who reported to have never used these in both questionnaires were considered never users. If a woman reported using hormone therapy and oral contraceptives at baseline or follow-up, she was classified as an ever user, and women who did not complete the follow-up questionnaire, or did not reply to this question in both questionnaires were classified in the “unknown” category. Analyses were further adjusted for use of oral contraceptives and hormone therapy . For overall analyses, menopausal status was entered in the model as a time-dependent variable (in addition to the above-mentioned covariates). We excluded 3,193 participants with missing information on at least one of the following covariates: BMI , height (N = 904), age at first birth and total number of children (N = 3), age at menarche (N = 579), or use of oral contraceptives (N = 49).Relative risks (RR) and corresponding two-sided 95% Wald type CIs were estimated by calculating hazard ratios. The Cox proportional hazards assumption was checked assessing graphs of scaled Schoenfeld residuals We used Cox regression to examine premenopausal and postmenopausal participants separately. We estimated RRs for breast cancer associated with each component of the Mediterranean diet score. These analyses were mutually adjusted for other score’s components, further to the adjustments mentioned above. We also examined the association between Mediterranean dietary pattern and breast cancer risk among non-alcohol drinkers only for breast cancer overall, as well as for specific breast tumor characteristics. All analyses were performed using the statistical software SAS version 9.2 .in situ and invasive breast cancers together. We also carried out all analyses presented here for in situ and invasive tumors separately, and found similar results (results not shown). For this, we used data from the regional quality breast cancer register (that gave information on the invasiveness of the tumor), and considered 1,176 invasive and 188 in situ breast cancers .In this report, we examined The 44,840 participants included in the final analyses were followed up for 16 years on average, during which 1,278 incident breast cancers were diagnosed. Having three or more children, especially below age 30 years, was associated with a decrease in breast cancer risk in premenopausal women . Furtherversus a lower consumption, compared with participants with a lower Mediterranean diet score  with breast cancer, to be never- or former- smokers, to have used oral contraceptives and/or hormone therapy, and to have a moderate alcohol consumption et score . ParticiThe possible association between Mediterranean dietary pattern was examined separately in all women and in premenopausal or postmenopausal women . AdherinWhen examining the possible association between the nine components’ of the Mediterranean diet score and breast cancer risk in all women and in premenopausal and postmenopausal women , we founWe investigated the risk of several breast cancer tumor characteristics associated with adherence to a Mediterranean dietary pattern . No decrAdherence to a Mediterranean dietary pattern was not associated with reduced risk of breast cancer overall, nor of specific breast tumor characteristics, overall, or in premenopausal and postmenopausal participants. Previous studies investigating the possible association between a Mediterranean diet and breast cancer risk have reported conflicting results. While some studies found no association of this diet with the risk of breast cancer overall The Greek EPIC cohort found a reduction in total mortality with closer adherence to a Mediterranean diet, and reported that moderate alcohol consumption was one of the components with greater contribution to this association Risk factors for breast cancer might differ by hormone receptor status a priori knowledge of the composition of the Mediterranean diet Previous studies have used different methods to ascertain adherence to a Mediterranean diet. Most of them used pattern identification methods to define a specific dietary pattern The strengths of the WLH study are its prospective design, and extensive information on potential confounders. Furthermore, the use of national registries to identify disease outcome allowed for an almost complete follow-up. Diet was measured using a validated food frequency questionnaire Furthermore, our results may be explained to a certain extent by residual confounding. Indeed, we found that women who adhered more closely to a Mediterranean dietary pattern were more likely to have a family history of breast cancer, to use oral contraceptives and hormone therapy, and to have a higher alcohol consumption, all of which are risk factors for breast cancer. Another concern is the single measurement of diet at baseline and the interval between diet ascertainment and breast cancer outcome. This, however, is likely to create non-differential misclassification, and would attenuate any true association.The diet of WLH study participants is different from that of participants in studies conducted in Mediterranean countries. For example, the consumption of vegetables and fruits in this cohort was lower than in the Greek EPIC cohort, which also examined the association between Mediterranean diet and breast cancer risk To our knowledge, this is the first Scandinavian study that investigates the possible association between adherence to a Mediterranean dietary pattern and breast cancer risk, and no reduction in breast cancer risk was found. This was true regardless of participant characteristics, and for all breast tumor characteristics examined.


BRCA1 and BRCA2 mutation testing offered shortly after a breast cancer diagnosis to inform women’s treatment choices - treatment-focused genetic testing ‘TFGT’ - has entered clinical practice in specialist centers and is likely to be soon commonplace in acute breast cancer management, especially for younger women. Yet the optimal way to deliver information about TFGT to younger women newly diagnosed with breast cancer is not known, particularly for those who were not suspected of having a hereditary breast cancer syndrome prior to their cancer diagnosis. Also, little is known about the behavioral and psychosocial impact or cost effectiveness of educating patients about TFGT. This trial aims to examine the impact and efficiency of two models of educating younger women newly diagnosed with breast cancer about genetic testing in order to provide evidence for a safe and effective future clinical pathway for this service.Germline BRCA mutations. Decision-related and psychosocial outcomes are assessed over 12 months and include decisional conflict (primary outcome);uptake of bilateral mastectomy and/or risk-reducing salpingo-oophorectomy; cancer-specific- and general distress; family involvement in decision making; and decision regret. A process-oriented retrospective online survey will examine health professionals’ attitudes toward TFGT; a health economic analysis will determine the cost effectiveness of the intervention.In this non-inferiority randomized controlled trial, 140 women newly diagnosed with breast cancer (aged less than 50 years) are being recruited from nine cancer centers in Australia. Eligible women with either a significant family history of breast and/or ovarian cancer or with other high risk features suggestive of a mutation detection rate of > 10% are invited by their surgeon prior to mastectomy or radiotherapy. After completing the first questionnaire, participants are randomized to receive either: (a) an educational pamphlet about genetic testing (intervention) or (b) a genetic counseling appointment at a family cancer center (standard care). Each participant is offered genetic testing for germline This trial will provide crucial information about the impact, efficiency and cost effectiveness of an educational pamphlet designed to inform younger women newly diagnosed with breast cancer about genetic testing. Issues regarding implementation of the trial are discussed.The study is registered with the Australian and New Zealand Clinical Trials Group (Registration no: ACTRN12610000502033) BRCA1 and BRCA2 mutation testing for younger women with breast cancer is in rapid transition because of advances in gene sequencing technologies and accumulating evidence for the contribution of BRCA mutation status to acute management of early breast cancer. Women diagnosed with breast cancer are offered genetic counseling and testing for germline mutations in BRCA1 and BRCA2 if they have a strong family history of the disease and/or they meet other criteria which point to a mutation detection rate that exceeds a predefined threshold for her local service. Genetic risk assessment has usually been offered on completion of surgery and adjuvant therapy for a new breast cancer, and routine genetic test results in Australia has to date taken between one and six months from blood draw. In contrast, genetic counseling and testing offered around the time of breast cancer diagnosis aims to provide the patient with genetic information that will assist in the choice of breast cancer treatment, primarily the choice between breast-conserving therapy (BCT) and mastectomy. The secondary effects of directing risk-reducing ovarian surgery and informing family members of their own cancer risks are not time dependent but useful outcomes of a genetic test at any time.The clinical role of BRCA mutation must choose whether to undergo BCT, unilateral mastectomy, or prophylactic bilateral mastectomies to prevent future breast cancers [BRCA mutation carriers with longer follow-up [BRCA1 and BRCA2 mutation carriers treated with BCT compared to carriers treated with mastectomy at 10 years (10.5% versus 3.5%) and at 20 years (30.2% versus 5.5%) [BRCA1 and BRCA2 mutation carriers have a substantially increased lifetime risk of contralateral breast cancer that is age dependent and can be up to 68%, if the age of the first cancer is <40 [BRCA mutation carriers [BRCA mutations also confer a 13-46% lifetime risk of ovarian cancer [BRCA1) and 72% (BRCA2) [BRCA1 and BRCA2 mutation testing can now be made available rapidly, within 5 working days if required. Soon, further advances in sequencing will substantially reduce the cost of genetic analysis [BRCA mutation status can feasibly be used now to inform her surgical decisions regarding BCT or mastectomy . In the future, timely BRCA mutation testing will extend to selection of specific adjuvant systemic chemotherapy once the optimal systemic therapy for BRCA mutation carriers is established, including the role of poly (ADP-ribose) polymerase (PARP) inhibitors [Women newly diagnosed with breast cancer with a  cancers . The incollow-up  and it aollow-up . Pierce n cancer . The secanalysis  and willhibitors ,13 and pBRCA1 or BRCA2 mutation opted for bilateral mastectomy (BM), compared to 4% of women who declined genetic testing. Compared to women who chose BCT or unilateral mastectomy, those who chose BM did not report diminished quality of life or increased distress [A concern shared by both patients and health professionals is that TFGT may create undue psychological burden among women diagnosed with breast cancer at a very vulnerable time in their life . There idistress . The Dutdistress . Anotherdistress .BRCA mutation status [BRCA mutations. For example, between 30-50% of women with a BRCA1/2 mutation have no significant or known family history of breast or ovarian cancer [BRCA1 mutation carriers [BRCA mutation in these younger age-of-onset cases increases especially when combined with triple negative disease [BRCA mutation. Meiser and colleagues conducted in-depth semi-structured interviews with 26 younger women (aged 50 years or less) diagnosed with breast cancer (14 had undergone TFGT and 12 had not), which explored their actual and hypothetical attitudes toward, and experiences (if any) of TFGT [A limitation of these studies is that they have selected or are selecting women based primarily on a significant family history of breast and/or ovarian cancer ,18 or han status . In addin cancer ,21 and un cancer . Up to 2carriers . Of overcarriers . In rela disease . Yet lit of TFGT . Women w of TFGT .In this paper, we report the design of a study that compares two different models of delivering information about TFGT to younger women newly diagnosed with breast cancer. We also report several key issues encountered in the implementation of the study, which will have important implications for the integration of TFGT into acute breast cancer management in the near future.The aim of this study is to compare the behavioral and psychosocial impact, efficiency and safety of offering information about TFGT to younger women newly diagnosed with breast cancer (a) using a brief educational pamphlet about TFGT  or (b) using pre-test genetic counseling at a family cancer service . The efficiency of offering information about TFGT will be operationalised in a health economic analysis and through an assessment of health professionals’ views on the effectiveness of the TFGT process. The safety of the intervention will be determined by assessing its impact on psychological distress. This is a non-inferiority trial, in which our primary hypothesis is that patient decisional conflict regarding TFGT will be no worse in the intervention compared to that of the control group. A summary of the research questions that are addressed in the study are presented in Figure Our secondary hypotheses are: (i) that other decision-related and psychological outcomes  will not be inferior in the intervention group compared to the control group, and (ii) that women who opt for TFGT will have a higher uptake of BM compared to data from the Royal Australasian College of Surgeons National Breast Cancer Audit on over 12,000 women with early breast cancer diagnosed annually .This is a multicenter randomized controlled trial which is being conducted at nine hospital sites located in three states in Australia  in two stages. The study protocol adheres to CONSORT guidelines . The stuA health economic analysis is also included with the objective of ascertaining the cost effectiveness of the intervention compared to standard care, and the potential benefit of the intervention in terms of number of life years saved. The health economic analysis is modeled on similar evaluations conducted in a cancer/medical setting . The cosin situ and has not had a mastectomy for her current cancer or radiotherapy at the time of invitation. The eligibility and exclusion criteria are presented in detail in Figure A woman is eligible to participate if she is aged less than 50 years at diagnosis of invasive breast cancer or ductal carcinoma The educational materials entitled ‘Making a decision about treatment-focused genetic testing’ were developed by the research team on the basis of the information preferences expressed by women in our qualitative interviews. The development and pilot-testing of the educational materials is reported in detail elsewhere . The briParticipants in the intervention group who elect to have TFGT receive an intake interview over the telephone, when their family history is collected, including cancer history and ages of diagnoses of the patient’s biological first- and second-degree relatives, approximately one week prior to their results disclosure appointment.Participants allocated to the control group receive pre-test genetic counseling ranging from 40-60 minutes in duration, which typically covers the following topics:BRCA1/BRCA2);(i) Explanation of hereditary breast cancer and the breast cancer ‘protection genes’  Discussion of patient’s risk of having a BRCA1/BRCA2 mutation search involves;(iii) What a (iv) Explanation of the potential advantages and disadvantages of genetic testing according to the patient’s family history and personal situation;(v) An explanation of what type of information genetic testing may or may not provide and the implications for treatment/prevention;(vi) Checking patient understanding of the concepts discussed;(vii) Obtaining informed consent for genetic testing if the patient wishes to proceed.Participants in the control group are contacted by telephone by the genetic counselor prior to their pre-test appointment for a brief intake interview equivalent to the intervention group.Participants are offered TFGT with a turn around time of 10 working days from blood draw, free of charge, as part of the study.All participants who elect to have TFGT receive their test results in a face-to-face appointment at a family cancer service attached to their treating hospital, regardless of their randomization. The results disclosure appointment of 20-40 minutes typically covers the following content:(i) Disclosure and explanation of the test result;(ii) Implications of the result for the patient’s personal risk of another primary breast cancer and risk of ovarian cancer;(iii) Options for reduction of future risk of these cancers;(iv) Implications of the test result for genetic relatives;(v) Communicating test results with genetic relatives, informed consent and privacy issues;(vi) Checking patient understanding of the concepts discussed.Recruitment commenced in July 2010 and details of the process are presented in Figure The four self-administered patient questionnaires are completed over a 12 month period. A summary of the measures included at each time point is provided in Figure Demographic, disease- and family history-related data: Sociodemographic data are collected including age, marital status, language spoken at home, education, employment, occupation, and parity.(i) Decisional conflict scale (DCS): This 10-item validated scale measures decisional conflict in relation to genetic testing choices, including uncertainty about alternatives, modifiable factors contributing to uncertainty, and perceptions of effectiveness of decision-making [(ii) n-making . Responsn-making .Impact of Event Scale (IES): The 15-item IES, which has been validated in this population [(iii) pulation , is beinHospital Anxiety and Depression Scale (HADS): The 14-item HADS is a widely used measure of emotional disturbance and has two subscales measuring anxiety and depression [(iv) pression . Each quKnowledge of TFGT: Ten items were purpose designed and pilot-tested for this study to assess knowledge and understanding of TFGT. There are three response options including ‘true’, ‘false’ and ‘don’t know’. Correct responses are assigned a score of ‘1’ and incorrect or ‘don’t know’ responses are scored ‘0’. Correct answers are summed to give a score out of 10 (range: 0-10).(v) Acceptability of the educational materials (intervention group only): have The length, pace, amount of information, and balance and whether other family members used the educational materials is assessed using five structured response categories [(vi) tegories .Family involvement in decision-making about genetic testing: Two items assess whether other family members participated in the decision-making process.(vii) Test-Related Distress and Positive Experiences (women who choose testing only): This measure includes 10 items from a validated questionnaire  [(viii) t Scale)  assessinDecision Regret Scale (DRS: Genetic Testing Choice): This five-item scale measures distress or remorse after health care decisions, and has excellent psychometric properties [(ix) operties . It has operties .Decision Regret Scale : A second version of the DRS measures decision regret in relation to women’s decisions about bilateral mastectomy and RRSO.(x) Patient preferences regarding TFGT: Two items have been adapted from a previous study conducted by our team exploring patient preferences and perceived survival benefits among younger women with early breast cancer considering endocrine therapy [(xi)  therapy . The iteBRCA mutation status.Clinical information will be gathered from participants’ medical records retrospectively including family history of breast and/or ovarian cancer; date of diagnosis; tumor size and grade; nodal and receptor status; menopausal status at diagnosis; type and date of surgery ; adjuvant treatment/s, and The 17 item online retrospective survey has been developed for the current study using items adapted from a previous health service evaluation  and alsoIt is estimated that less than 10% of breast cancer patients of all ages will be eligible for the study.A total sample size of 128 has 80% power to test the non-inferiority of the intervention on the primary outcome, the Decisional Conflict Scale (DCS). For the DCS, a non-inferiority margin will be -10 units, that is, the intervention group will be considered no worse than the standard care group if the 95% CI of the mean difference in DCS between the two groups lies wholly above -10 units. The DCS has 10 items, with the following response options: ‘Yes’, ‘Unsure’ and ‘No’ to items such as: ‘Do you know which options are available to you?’ The DCS total score ranges from 0 to 100 and thus a non-inferiority margin of -10 units on the DCS corresponds to only one of the 10 items having been endorsed as ‘No’ instead of ‘Yes’. The power calculation is based on a 5% significance level (2-sided), a true mean difference of zero units and a conservative SD of 20 units.An intention-to-treat analysis will be conducted on the differences in means between the intervention and standard care groups on psychological and decision-related outcomes. Linear regression shall be used for each outcome measured at 12 months, adjusting for the patient baseline scores. Further multivariate analyses will be used if preliminary analyses suggest a need to adjust for potential confounding variables . In order to investigate whether, and how, patient outcomes differ between the intervention and standard care groups over time, the repeated measurements  shall be analyzed using linear mixed effects . This apThis study aims to compare the impact, efficiency and safety of two different ways of offering information about TFGT to women using (a) brief educational materials or (b) standard care (pre-test genetic counseling). In June 2012, 110 participants have been recruited to the study. During the recruitment period, several issues have been encountered that warrant consideration to ensure successful integration of TFGT into standard clinical practice for women diagnosed with breast cancer in the future.The treating surgeon is responsible for inviting eligible patients into the study and for completing the recruitment fax . Therefore, the surgeon has the role of ‘gatekeeper’ of delivery of brief initial information about TFGT, which is likely to be the case in the future clinical setting. Some eligible patients, however may be missed by the surgeon if he or she does not recognize the patient as being eligible, forgets to invite them or does not have time to complete the recruitment sheet. Hence, a multidisciplinary and streamlined approach is required to ensure that all patients who are eligible for testing are informed about the opportunity to have TFGT. New models of ascertainment will need to be developed using the members of the multidisciplinary team.The hospital sites in the current study are located in major cities, or in large regional centers, so patients referred for recruitment to the study have access to a dedicated onsite family cancer service, which is staffed by at least one genetic counselor and a genetics specialist. Genetic test results are disclosed to each patient who elects to have TFGT in a face-to-face appointment with the genetics team. However, if TFGT is to be expanded across clinical services, rapid access to a genetics practitioner is unlikely to be possible especially in smaller rural and regional hospitals, where visiting non-genetics specialists may need to deliver the results of genetic testing to the patient. One alternative that is already utilized by cancer genetics practitioners for oncology patients located in rural or remote areas is disclosure of genetic test results via telehealth technology (‘telegenetics’), with the genetics specialist providing the consultation from their city or regional hospital site. This model may be feasible for the TFGT context given a recent study conducted with 195 Australian women with a moderate or high-risk family history of hereditary breast and ovarian cancer seeking genetic counseling, in which telegenetics was found to be equally effective to face-to-face genetic counseling .The process-related issues that have emerged in offering TFGT at our nine hospital sites have important implications for effective integration of TFGT into clinical practice. The delivery of the genetic testing result to the genetics specialist and/or genetic counselor by the test laboratory staff in a password-protected email is efficient and confidential. Blood collection for patients in the intervention arm, either at a local pathology service or by a general physician, has on several occasions been problematic, with some delays experienced in pick up of the blood by the courier for transport to the test laboratory. When TFGT is integrated into standard clinical pathways for women with breast cancer, blood will be collected according to usual hospital protocols avoiding this issue. For patients in rural or remote areas, establishing time efficient protocols for sample processing will be an important part of the service set up. If family history is to be used as a selection factor, timely verification of the reported cancer diagnoses will need to be considered. While individuals can report family histories of cancer accurately , it is pn = 4, 3.6%) or after initial contact with the study co-ordinator . Several women reported that their reason for declining was that they felt overwhelmed and could not cope with additional decision-making when dealing with a breast cancer diagnosis. This is in keeping with the findings of focus groups conducted with 13 women diagnosed with breast cancer who were identified BRCA mutation carriers [To date, although 100% of 110 women who have enrolled in the study have opted to have TFGT, a small proportion of women (8.2%) invited to participate have either declined participation when invited by the surgeon ; Calvary Health Care Sydney and Cunningham Centre for Palliative Care, Sydney (E.A. Lobb); Department of Medical Oncology, Prince of Wales Hospital ; Hereditary Cancer Clinic, Prince of Wales Hospital, Sydney ; Monash Medical Centre, Melbourne ; Nambour Hospital, Nambour ; Peter MacCallum Cancer Centre, Melbourne ; Royal Brisbane and Women's Hospital ; Royal North Shore Hospital, Sydney ; St George Hospital, Sydney ; The Poche Centre, Sydney ; University of Melbourne (J. Hopper); University of Western Australia, Perth (L. Geelhoed); Westmead Hospital, Sydney .The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2407/12/320/prepub


Background: Epidemiologic evidence suggests a negative relation between sunlight exposure and breast cancer risk. The hypothesized mechanism is sunlight-induced cutaneous synthesis of vitamin D.VDR) gene variants on breast cancer risk.Objectives: Our goal was to examine sun exposure and its interaction with vitamin D receptor .Results: We observed a small decrease in breast cancer risk in association with usual sun exposure of ≥ 1 hr/day (versus < 1 hr/day) 10 years before the start of follow-up among all participants . The association appeared to be slightly stronger in relation to estrogen receptor–positive tumors  than estrogen receptor–negative tumors . The HR for joint exposure ≥ 1 hr/day of sunlight and one VDR variants. Larger studies are warranted, particularly among populations in whom low levels of usual sun exposure can be more precisely characterized.Conclusion: Our results suggest that sun exposure may be associated with reduced risk of breast cancer, but we did not find clear evidence of modification by http://dx.doi.org/10.1289/ehp.1206274Citation: Engel LS, Satagopan J, Sima CS, Orlow I, Mujumdar U, Coble J, Roy P, Yoo S, Sandler DP, Alavanja MC. 2014. Sun exposure, vitamin D receptor genetic variants, and risk of breast cancer in the Agricultural Health Study. Environ Health Perspect 122:165–171;  The hypothesized mechanism for this relationship is sunlight (ultraviolet B)–induced dermal synthesis of vitamin D, which experimental and nonexperimental evidence suggests may reduce risk of several cancers, including breast cancer. Dermal synthesis is the primary source of vitamin D for most individuals, with diet and supplements generally being minor contributors . In derm effects . Thus, sMost cohort and case–control studies that have examined sunlight and/or ultraviolet light (UV) exposure—either through self-reported personal behaviors or via ambient levels at place of residence—have reported evidence of a negative association with breast cancer . In addi2D exerts most of its known physiological effects through binding to the vitamin D receptor (VDR) 2D to induce cell cycle arrest and apoptosis in breast cancer cells or (VDR) . The VDRor (VDR) , regulator (VDR) . Experimer cells . In addier cells . The VDRer cells .VDR gene variants among wives of farmers in a large, prospective, two-state agricultural cohort. This population has a very wide range of sun exposure; detailed, prospective data on demographic, lifestyle, and occupational factors; and a high rate of follow-up. This research was motivated in part by previous reports of reduced risks of breast cancer among female farmers and agricultural workers relative to the general population  cohort between 1993 and 1997 (http://www.cdc.gov/nchs/ndi.htm). Estrogen receptor (ER) and progesterone receptor (PR) status of the tumor was available from the registries for 475 (82.2%) and 447 (77.3%) cases, respectively. Excluding 1,106 wives with a malignant cancer diagnosis other than nonmelanoma skin cancer before enrollment left 31,021 participants for the present cohort analyses. Among these, 578 were diagnosed with malignant breast cancer  were genotyped, as described in our related work  was used as the reference category in all analyses. The majority of women (84.5%) reported the same levels of sun exposure during the two time periods. Therefore, we estimated associations according to time period using separate models and did not create a composite exposure estimate. We also estimated the association between breast cancer and sun exposure for ≥ 1 hr/day compared with < 1 hr/day.n = 6). Body mass index, age at menarche, smoking status, and education were not included in the final models because they did not change risk estimates by at least 10%. Time-varying covariates  were classified at each time point based on the most recent value reported; only values reported before the end of follow-up for each participant were used.Cohort study of sun exposure. We used Cox proportional hazards regression to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between breast cancer and each measure of sunlight exposure. Person-years at risk for each participant were calculated from date of enrollment until the earliest of the following: first breast cancer diagnosis, first malignant non-breast cancer diagnosis (excluding nonmelanoma skin cancer), movement out of state, death, or 31 December 2004. All analyses were adjusted for known breast cancer risk factors, including age , race , age at menopause , and first-degree family history of breast cancer . Analyses were additionally adjusted for state  and for combined parity and age at first birth , with nulliparous women and those with first births after age 30 years combined because of the small number of nulliparous cases  or showed evidence of departure from multiplicativity in interaction analyses. The multiplicative interaction between sun exposure and each SNP was evaluated via the statistical significance (p < 0.05) of the likelihood ratio test comparing the models with and without the product term. All analyses were adjusted for age at menopause, combined parity and age at first birth, and first-degree family history of breast cancer, as described above, based on status at enrollment.Nested case–control study of sun exposure and gene–environment interaction. Conditional logistic regression was used to estimate odds ratios (ORs) and 95% CIs for usual sun exposure and interactions with genetic variants. Because the genotype data were unphased, we estimated expected haplotypes and their frequencies using the haplo.stats software  in R, veThere was insufficient DNA for genotyping for 23 cases and 32 controls. To account for missing genotype and sun exposure data, we used the missing-indicator method  in our aIn both the cohort and the case–control analyses, missing data for adjustment covariates were imputed using IVEware . This program, which assumes an ignorable-missing-data mechanism, simultaneously imputes values for specified variables by fitting a sequence of regression models and drawing values from the corresponding predictive distributions. Missing values were imputed for race (3.2%), family history of breast cancer (5.0%), parity (17.6%), and age at menopause (2.0%). Risk estimates including imputed data were not materially different from those including only observed data, so we present risk estimates adjusted using the imputed and observed data.p-values for multiple comparisons because of the exploratory nature of our genetic analyses. Analyses were based on AHS data releases P1REL0506.01 and P2REL0506.04.All statistical analyses were performed using SAS, version 9.1 , except where otherwise noted. Statistical significance was assessed at the 5% level. Tests for trend were assessed using midpoints of categories as continuous measures. In analyses of covariate risk  and ER– (n = 105) tumors, respectively]. We observed no evidence of differences in associations by menopausal status, usual use of sunscreen/sunblock, or PR status of the tumor  . The neghe tumor .Adjustment for self-reported duration of pesticide use and self-reported measures of occupational and recreational physical activity from the enrollment questionnaire did not materially alter risk estimates (data not shown). Results were also similar in subanalyses restricted to whites (data not shown), which was expected given the small proportion of nonwhites in this study.Gene–environment interactions. p < 0.05) or showed evidence of departure from multiplicativity in interaction analyses. The interaction between rs2239181 and usual sun exposure 10 years before enrollment on breast cancer risk showed some evidence of a departure from multiplicativity . We found no evidence of departure from multiplicativity between other SNPs and usual sun exposure 10 years before enrollment.cativity . Among tp-value = 0.07) (There was a suggestion of sub-multiplicativity between haplotype TCAGCTTCGCA (haplotype “B6”) and usual sun exposure ≥ 1 hr/day 10 years before enrollment; however, this was not significant (interaction  = 0.07) . Among c+ tumors. The timing of sun exposure may be important because exposure 10 years before start of follow-up was negatively associated with breast cancer, whereas sun exposure at the start of follow-up was not, although this difference could be due to other factors such as missing data. There was some evidence that the association between usual sun exposure and risk of breast cancer was modified by one of the 13 haplotypes evaluated.Results from this large, prospective cohort study of women living and/or working on farms suggest that sunlight exposure may be associated with a reduced risk of breast cancer, particularly for EROur findings regarding sunlight exposure and breast cancer risk are consistent with most previous studies on this topic. Negative associations have been observed in both case–control studies  and cohoWe found no evidence of a dose–response relation between self-reported sun exposure ≥ 1 hr/day and breast cancer risk, but the relative risk of breast cancer did appear to be reduced in association with ≥ 1 hr/day of usual sun exposure compared with < 1 hr/day. The exposure distribution in this occupationally exposed population is likely skewed high compared with general population samples in previous studies. However, once individuals achieve a circulating 25(OH)D level of about 40 ng/mL, the effects of additional sun/UV exposure appear to become blunted, with a much lower rate of increase in circulating 25(OH)D per unit of sun exposure . Self-reWe observed no modification of the association between sunlight exposure and breast cancer risk by sunscreen use, which is consistent with the lack of association between sunscreen use and breast cancer risk reported in other studies . This ma+/PR+ tumors, ER–/PR– tumors, and ER+/PR– tumors associated with increased vitamin D intake via sun and diet. In contrast, a study involving 1,019 incident cases within the prospective Women’s Health Study 2D–mediated growth regulation D, and dietary vitamin D intake—on breast cancer risk have produced inconsistent, but largely null, results. A case–control study of breast cancer reported limited evidence of an interaction between BsmI (rs1544410) genotype and serum 25(OH)D concentrations measured in blood samples collected after diagnosis   .Limitations of this study include use of self-reported usual sun exposure, which likely introduced some exposure misclassification. However, studies indicate that reliability of recall of usual or total sun exposure is good, with interclass correlation coefficients of about 0.7–0.8 ; that seStrengths of this study include collection of all information on exposures and covariates before disease diagnosis; thus, any misclassification was likely nondifferential with regard to disease status. In addition, this cohort is large and includes a substantial number of incident cases. Follow-up of this cohort is excellent. Also, this cohort has an unusually wide range of usual sun exposure compared with the general population, with a substantial proportion of women in the upper end of the exposure distribution providing greater exposure contrasts, although no dose–response association was observed. Reliability of reporting for a range of lifestyle and occupational factors is good to excellent in this cohort . FinallyVDR gene. Our results further suggest that this association may be stronger for ER+ tumors, although these analyses are based on a relatively small sample size. Larger studies, particularly among populations in which usual sun exposure at the low end can be more precisely characterized, are warranted to help clarify this relationship.Our results suggest that sun exposure may be associated with reduced risk of breast cancer, but we did not find clear evidence of modification of this association by variants in the (295 kB) PDFClick here for additional data file.