Mechanistic hypotheses suggest a potential effect of dietary fiber on breast carcinogenesis through the modulation of insulin-like growth factor bioactivity, estrogen metabolism and inflammation. An association between dietary fiber intake and breast cancer risk has been suggested in epidemiological studies but remains inconclusive. In particular, data is lacking regarding the different types of dietary fibers.The objective was to investigate the prospective relationship between dietary fiber intake and breast cancer risk, taking into account different types of dietary fiber .4684 women from the SU.VI.MAX cohort were included in this analysis as they completed at least three 24h-dietary records within the first two years of follow-up. Among them, 167 incident invasive breast cancers were diagnosed during a median follow-up of 12.6 years (between 1994 and 2007). The associations between quartiles of dietary fiber intake and breast cancer risk were characterized using multivariate Cox proportional hazards models.Quartile4vs.Quartile1 = 1.29 (95%CI 0.66–2.50), P-trend = 0.5), nor was fiber intake from cereals (P-trend = 0.1), fruits (P-trend = 0.9) and legumes (P-trend = 0.3). In contrast, vegetable fiber intake was related to a decreased risk of breast cancer (HRQ4vs.Q1 = 0.50 (0.29-0.88), P-trend = 0.03). Overall vegetable intake (in g/day) was not associated with breast cancer risk (P-trend = 0.2).Total fiber intake was not associated with breast cancer risk (HRThis prospective study suggests that vegetable fiber intake may contribute to reduce breast cancer risk, in line with experimental mechanistic data. Several mechanisms are involved in breast cancer development. First, insulin-resistance and its consequences such as higher insulin-like growth factor (IGFs) bioactivity However, epidemiological evidence is lacking. In the Continuous Update Project of the World Cancer Research Fund (WCRF) / American Institute for Cancer Research (AICR) published in 2010 Therefore, our objective was to prospectively investigate the association between different types of dietary fiber  and breast cancer risk.The SU.VI.MAX study was conducted according to the Declaration of Helsinki guidelines and was approved by the Ethics Committee for Studies with Human Subjects of Paris-Cochin Hospital  and the Commission Nationale de l’Informatique et des Libertés . Written informed consent was obtained from all participants.The SU.VI.MAX study (SUpplementation en VItamines et MInéraux AntioXydants) was at first designed as a randomized, double-blind, placebo-controlled primary prevention trial  aiming to assess the effect of a daily supplementation with nutritional doses of antioxidants on the incidence of cardiovascular diseases and cancers At enrollment, self-administered questionnaires related to socio-demographics, smoking status, physical activity and family history of breast cancer were filled-in by all participants. Anthropometric measures were performed by the study’s nurses and physicians during a medical examination.During the trial period (1994–2002), participants were invited to complete a 24h-dietary record every two months. These records were randomly distributed between weeks and week-ends and over seasons to take into account intra-individual variability. In order to be consistent with a prospective design, only dietary records from the first two years of follow-up were used in the present study. Completion was made through the Minitel Telematic Network, a French telephone-based terminal equivalent to an Internet prototype. Portion sizes were assessed thanks to a validated picture booklet Health events occurring during the follow-up were self-reported by participants. Medical data were then gathered through participants, physicians, and/or hospitals and reviewed by an independent physician expert committee. Pathological reports were used to validate the cases and to extract cancer characteristics . Cases were classified using the International Chronic Diseases Classification, 10th Revision, Clinical Modification (ICD-10) From the 7876 female participants in the SU.VI.MAX study, we excluded 120 women who reported a cancer diagnosis before the start of the follow-up. Among the remaining subjects, 4684 provided at least three valid 24h-dietary records within the first two years of follow-up and thus remained available for analysis. For overall breast cancer analysis, women contributed person-time until the date of diagnosis of breast cancer, the date of last completed questionnaire, the date of death, or September 2007, whichever occurred first. For analyses stratified by menopausal status, women contributed person-time until their date of menopause for premenopausal breast cancer analysis or from their date of menopause for postmenopausal breast cancer analysis. Women who reported a cancer other than breast cancer (N = 164) or a non-invasive breast cancer (N = 23) during the study period were included and censored at the date of diagnosis . Nutrient intakes were estimated by the average intake calculated from all dietary records for each woman.Baseline characteristics of participants were compared between quartiles of total dietary fiber intake, using Chi-square tests or Fisher tests where appropriate. Hazards ratios (HRs) and 95% Confidence Intervals (CIs)), obtained from Cox proportional hazards models with age as the primary time variable, were used to characterize the association between quartiles of dietary fiber intake and incident breast cancer. We verified that the assumptions of proportionality were satisfied through examination of the log–log  versus log–time plots. Different categories of dietary fibers were tested: according to their chemical properties (soluble and insoluble fibers) and according to their food sources . Tests for linear trend were performed using the ordinal score on quartiles of fiber intake. Multivariate models were adjusted for intervention group of the initial SU.VI.MAX trial (yes/no), smoking status , educational level , physical activity , height (continuous), body mass index , without-alcohol energy intake (continuous), alcohol intake (continuous), total fat intake (continuous), number of dietary records (continuous), family history of breast cancer (yes/no), number of children (continuous), menopausal status at baseline (yes/no) and use of hormonal treatment for menopause (HTM) at baseline (yes/no). Since a high fiber intake might reflect an overall healthy diet and since we aimed at disentangling the potential effect of dietary fiber from the effect of other components of a healthy diet, we adjusted the multivariate models for a healthy dietary pattern. This healthy pattern was extracted by principal component analysis, using the SAS “proc factor” procedure with the ‘‘Varimax’’ option, from mean intakes across all 24-h records collected during the first 2 years of the study, for 31 food groups. For interpreting the data, we considered food groups with a factor loading under –0.2 or over 0.2. The factor that was strongly correlated with vegetables, fruits and seafood intakes was considered as “healthy pattern”. A score characterizing the adequacy of each woman with this pattern was calculated by summing the intakes of all food groups weighted by the food group factor loadings During a median follow-up of 12.6 years , 167 women developed a first primary invasive breast cancer with a mean age at diagnosis of 55.8 years. Quartile4vs.Quartile1 = 1.29 (95%CI 0.66–2.50), P-trend = 0.5), nor was fiber intake from cereals (P-trend = 0.1), fruits (P-trend = 0.9) and legumes (P-trend = 0.3). In contrast, vegetable fiber intake was associated with a decreased breast cancer risk (HRQ4vs.Q1 = 0.50 (0.29-0.88), P-trend = 0.028). We verified that this result was observed for postmenopausal breast cancers , P-trend = 0.03), ductal breast cancers , P-trend = 0.02), ER+ , P-trend = 0.02) and PR+ , P-trend = 0.046) breast cancers (data not tabulated).Associations between dietary fiber intake and breast cancer risk are summarized in P-trend = 0.2, data not tabulated). Results regarding legume fibers (no association with breast cancer risk) were similar when excluding soya and soya products from the legume food group (data not shown). No interaction between fiber intake and BMI was detected (data not shown).Quartiles of overall vegetable intake (g/d) were not associated with breast cancer risk , nor did sensitivity analyses including only women who completed at least six 24h-dietary records during the first two years of follow-up  or including women who provided at least one 24h-dietary record . We also performed analyses considering dietary fiber intake as a time-dependent variable with one averaged value of intake per year of follow-up . Again, this did not modify our findings (data not shown).In this prospective study, we observed an inverse association between vegetable fiber intake and breast cancer risk, but no association with total dietary fiber intake or fiber intake from other food sources.trend = 0.03 but HRQ5–Q1 =  0.95 ). The fact that we did not observe any association between total dietary fiber and breast cancer risk in our study may be explained by lack of statistical power, and insufficient contrast between compared quartiles of dietary fiber intake. Indeed, in the recent meta-analysis published by Aune et al. The two recently published meta-analyses The meta-analysis of Aune et al. In this study, overall vegetable intake (in g/d) was not associated with breast cancer risk, which supports a specific effect of vegetable fiber in breast cancer prevention. In addition, we adjusted for a healthy dietary pattern and for several lifestyle factors . Thus, the inverse association observed in the present study between vegetable fiber intake and breast cancer risk could not be entirely explained by a more general effect of vegetable intake or overall dietary/lifestyle pattern.Mechanistic data support the plausibility of a protective effect of dietary fiber on breast carcinogenesis, especially vegetable fiber. Vegetable fibers combine insoluble (cellulose) and soluble (pectic substances) fibers The decrease of circulating estrogen concentration by dietary fibers Fermentation of dietary fibers in the colon produces SCFA Strengths of our study pertained to its prospective design with long follow-up and to the diversity of types and sources of dietary fibers investigated. Moreover, the precise assessment of dietary fiber intake through repeated 24h-dietary records  also represents a strength compared to studies that used a food frequency questionnaire (FFQ), which is known to provide a good classification of subjects but a less precise estimation of dietary (and thus fiber) intake and an attenuation of the estimated relative risks However, some limitations should be considered. First, although the number of overall breast cancer cases was reasonably large, it did not allow us to investigate all histological and receptor types of breast cancers . Nevertheless, even if our ability to detect some of the hypothesized observations may have been limited by the number of cases, this is unlikely to explain the observed relationships which were statistically significant despite the potential power limitation. Second, our results could also have been affected by residual or unmeasured confounding. However, a broad range of common breast cancer risk factors were taken into account . Third, the possibility of chance finding cannot be excluded. However, the number of tests performed in this study is relatively restricted. In addition, we strove to specify our models well, adjusting for the most pertinent covariates, to minimize the potential for Type I error. Moreover, our results are hypothesis driven and supported by epidemiologic literature and biologic plausibility. Thus, the observed findings cannot be explained entirely by chance. Next, caution is needed when extrapolating our results to the whole French female population as this study was based on a sample of volunteers in a cohort study on nutrition and health and were overall better educated and belonged to higher socio-professional categories. However, dietary fiber consumption levels in our study were close to the levels estimated in a national French descriptive survey based on a representative sample In conclusion, this prospective study supports the evidence of an inverse association between vegetable fiber intake and breast cancer risk, in line with experimental data. Further mechanistic studies, large prospective epidemiological cohorts and primary prevention intervention trials are needed to confirm these findings. Similarly, more research is needed regarding the potential effect of dietary fibers on breast cancer survival or recurrence, since few studies have investigated these aspects so far


High-density lipoprotein cholesterol (HDL-C) is reported to be associated with breast cancer risk. To better understand this association, we examined the relationship between HDL-C and mammographic density, a putative intermediate risk factor for breast cancer.The study subjects were 711 Korean women from the Healthy Twin study. Lipid parameters were assayed enzymatically in fresh sera, and percent dense area (PDA) and absolute dense area were measured from digital mammograms using a computer-assisted method.PDA was positively associated with HDL-C in both premenopausal and postmenopausal women in a multivariable-adjusted linear mixed model, but the association did not persist when the model was additionally adjusted for body mass index (BMI). BMI was inversely associated with PDA, and this association did not change after additional adjustment for any lipid parameter. Multivariable-adjusted analysis showed that there were significant additive genetic cross-trait correlations between PDA and both HDL-C  and triglyceride . However, those correlations disappeared after additional adjustment for BMI.HDL-C alone is unlikely to increase the risk of breast cancer in Korean women, particularly through changes in breast parenchyma that are apparent in mammographic density. BMI should be included in studies using analytical models where mammographic density is used as an intermediate risk factor for breast cancer. A few studies have examined the association between HDL-C and mammographic density,22,23 with inconsistent results. Boyd et al22 reported a positive association, but this association disappeared after adjustment for a wide range of covariates, including known risk factors for breast cancer, lifestyle factors, apolipoprotein (Apo) A, and Apo B. Another study found no evidence of an association between mammographic density and HDL-C.23 Clearly, further investigation is necessary.Because lipid levels are correlated with endogenous sex hormone levels24,25 and estrogen influences breast parenchyma proliferation.20,26–28 Thus, obesity may be involved in the associations of HDL-C with mammographic density and breast cancer.Obesity is closely related to serum lipid level and breast cancer. Obesity increases the risk of breast cancer in postmenopausal women through a hormonal mechanism involving the metabolism of an androgenic precursor to estrogen in adipose tissue,24 In addition, we investigated the extent to which any correlation between mammographic density and lipids could be explained by similar genetic or environmental factors in obese and nonobese women. To our knowledge, no study of the association of HDL-C with mammographic density or breast cancer has been conducted in Asian women, who differ from Western women in HDL-C level,29,30 mammographic density,31,32 and risk of breast cancer.33,34In this study, we examined the relationship between mammographic density and HDL-C and other lipid parameters in obese and nonobese women. We also examined the effect of menopausal status on this relationship, since the associations between breast cancer and some risk factors, such as obesity, often differ according to menopausal status.35 A total of 2278 Korean adults  comprising twins and their first-degree family members were recruited for the Healthy Twin study from April 2005 through December 2007. A mammogram was obtained for female participants who were 40 years or older at the time of participation in the study or were willing to undergo screening mammography. Among the 734 women who underwent mammography, 23 were excluded from this study: 4 because genetic tests indicated that they were unrelated to their family and 19 because they were taking lipid-lowering medications. Thus, 711 women were ultimately included in the analysis: 113 pairs of monozygotic twins, 30 pairs of dizygotic twins, and 425 singletons.The study participants were female members of the Healthy Twin study who had received a mammogram and had lipid profile data collected during a routine health examination. The Healthy Twin study is an ongoing nationwide community study conducted in 3 centers in Korea , and participants were voluntarily recruited without any ascertainment of health status, including breast diseases. Details regarding the overall methodology of the Healthy Twin study have been previously published.36 Mammograms were randomized first by family into reading sets of approximately 100, thereby ensuring that all twins and relatives of the same family were measured in the same set. The reader was blinded to all indentifying information, and a 10% random sample of repeats was included in each set and between every third set to test the reliability of the measurement.Mammograms were taken using a full-field digital mammography system . A single observer took measurements from 1 craniocaudal view of the right breast for each woman, using a computer-assisted thresholding technique called Cumulus, in which the total area of the breast and the area of dense tissue are measured and the percent dense area is calculated. This measure has been shown to be highly reproducible and reliable.Blood samples were drawn on the same day when the mammogram was obtained, after a 12-hour overnight fast. Serum concentrations of total cholesterol (T-C), HDL-C, triglyceride (TG), and low-density lipoprotein cholesterol (LDL-C) were assayed enzymatically in fresh sera using commercial kits in a designated central laboratory.2). The use of standardized protocols and training of research coordinators and research assistants ensured that all procedures for anthropometric measurement were consistent between centers.Weight (kg) and height (cm) were measured in light clothing using standardized scales and stadiometers. Body mass index (BMI) was calculated as the weight divided by the height squared , reproductive history , and medical and demographic characteristics . An additional face-to-face interview was conducted by a trained interviewer to clarify incomplete or ambiguous responses. Postmenopausal status was defined as no menstruation for more than 12 months. If a woman underwent hysterectomy but her ovarian function was unknown, she was classified as postmenopausal only if she had received estrogen replacement therapy or was 55 years or older.Zygosity of twin pairs was identified by 16 short tandem repeat (STR) markers  in 67% of twin pairs. In the remaining 33% of twin pairs, zygosity was determined by a self-administered zygosity questionnaire that was validated as being 94.3% accurate in an STR marker study (manuscript submitted for publication).All participants provided written informed consent when they visited one of the study centers. The study protocol was approved by the Korea Center for Disease Control and the institutional review boards of the 3 participating centers.Intra-class correlation coefficients were estimated to assess reliability of repeated measurements of mammographic density within reading sets in 65 randomly chosen women. Age-adjusted residuals of each of the mammographic measures were inspected for normality, and log transformations were applied to both of the mammographic measures.Because lipid parameters are closely related with age, we used analysis of covariance to calculate age-adjusted levels for these parameters according to the distribution of each selected characteristic and breast cancer risk factors, and the linear trend was examined using age-adjusted linear regression analysis.Associations of lipid parameters with mammographic density measures were evaluated using a linear mixed model in which household and twin effects were adjusted as random effects, and other covariates  were adjusted as fixed effects.We examined the effect of menopausal status on the relationship between mammographic density and lipid parameters by repeating the linear mixed model separately in premenopausal women and postmenopausal women, and by testing the statistical significance of interaction terms .37We examined the effect of obesity (measured by BMI) on the relationship between mammographic density and lipid profile by repeating the linear mixed model, with and without adjustment for BMI, and by repeating the analysis for obese (BMI ≥25) and nonobese (BMI <25) women. The cut-off level for obesity was determined according to the obesity guidelines for Asian-Pacific populations.G) and environmental correlations (ρE) using SOLAR  version 2.0.38 A significant genetic correlation was considered evidence of pleiotropy. To estimate independent genetic correlations with respect to obesity and other covariates, we adjusted first for age, then other covariates (except BMI), and, finally, BMI.To collect evidence of common genetic regulation between mammographic measures and lipid parameters, we conducted bivariate analysis to partition the phenotypic correlations into genetic . Although there was no association between HDL-C and dense area when participants were stratified by menopausal status, there was a positive association for all women combined. LDL-C and TG were inversely associated with percent dense area in premenopausal women only, but the interaction between menopausal status and lipid profile (LDL-C and TG) was not significant. However, when the model was additionally adjusted for BMI, the associations of lipid profile with percent dense area and dense area did not persist. We repeated the multivariable analysis separately for obese and nonobese women, but neither dense area nor percent dense area was associated with any lipid parameter (data not shown).Table Table Table 4,5 Exogenously administered estrogen has been shown to increase HDL-C level,39,40 the extent of parenchymal densities of the breast,41,42 and breast cancer risk.43–45Evidence indicates that HDL-C increases the risk of breast cancer through its role in cell proliferation in the breast. Although this has not been confirmed in vivo, HDL-C has been shown to affect cell proliferation in culture conditions that may be relevant to carcinogenesis.22,46 although the association did not persist when parity, BMI, Apo B, alcohol consumption, skinfold thickness, and urinary malondialdehyde were adjusted for. In the present study, percent dense area was not independently associated with HDL-C, LDL-C, or TG in either premenopausal or postmenopausal Korean women.In premenopausal Canadian women, HDL-C was positively associated with mammographic density, even after accounting for age and BMI,When obesity level was not included in the analysis, percent dense area was positively associated with HDL-C and inversely associated with LDL-C and TG. However, these associations disappeared after adjustment for BMI, which suggests that the relations were spurious and probably due to the confounding effect of obesity. When the relationship between percent dense area and HDL-C was examined separately in obese and nonobese women, there was no significant association in either group (data not shown). This suggests that obesity was a confounder rather than an effect modifier.To further elucidate the relations between BMI, percent dense area, and HDL-C, we investigated the role of HDL-C in the relationship between BMI and percent dense area. We found that HDL-C was inversely associated with BMI. When we examined the relationship between obesity and percent dense area, obesity was inversely associated with percent dense area, and the association was completely unaffected by additional adjustment for lipid parameters. This finding suggests that HDL-C is neither a confounder in the association of obesity with percent dense area nor an intermediate mechanism by which obesity is associated with percent dense area.24 Because HDL-C level is affected by estrogen replacement and menopausal changes,47 we examined whether menopausal status modified the relationship between HDL-C and mammographic density. The BMI-unadjusted association of lipid parameters with percent dense area differed by menopausal status. When we analyzed the combined data after adjustment for menopausal status, the association remained significant. However, the interaction term was not significant, and the association did not persist after adjustment for BMI. Therefore, menopausal status seems to be neither an effect modifier nor a major confounder in the relation between HDL-C and mammographic density.Biosynthesis of estrogen differs according to menopausal status, which likely explains why the increase in the risk of breast cancer due to obesity is confined to postmenopausal women.48–50 suggesting that the association between obesity and breast cancer is less likely to be mediated through breast tissue subcomponents that are reflected in mammographic density.If mammographic density is an intermediate marker of breast cancer risk, the inverse association between BMI and mammographic density in postmenopausal women is very unusual because BMI is positively associated with breast cancer in postmenopausal women. However, an inverse association between BMI and mammographic density has been consistently observed in many studies,Evaluations of cross-trait genetic correlation between percent dense area and lipid profile have yielded very consistent findings and strongly support the view that the association between percent dense area and HDL-C is not real.48 These findings suggest that, as compared with percent dense area, dense area is a simpler surrogate marker of proliferation in breast tissue, as it is less influenced by BMI level.Interestingly, we found that the associations of lipid parameters with dense area and percent dense area differed slightly when BMI was not included in the model, probably because calculation of percent dense area depends on nondense area, which is significantly associated with BMI, while dense area is more independent of BMI. A previous study showed that over one third of the variation in nondense area was explained by BMI, whereas BMI explained a much smaller fraction of the variation in dense area (less than 2%).51 In the present study, a high cholesterol level was initially associated with a greater risk of breast cancer; however, the association disappeared when the model was additionally adjusted for BMI. The relation between HDL-C and breast cancer was not examined in the cohort study because data on HDL-C were not available. Recently, a large case-control study in Korean women showed that high HDL-C had a protective effect against breast cancer among nonobese premenopausal women and that BMI modified the association between HDL-C and breast cancer.12 However, the HDL-C level of the breast cancer cases was measured after a diagnosis of breast cancer in the case-control study, and reverse causation cannot be completely ruled out. Further study will be needed to clarify the issue.Several limitations in this study should be considered. We were unable to investigate the direct relationship between HDL-C and breast cancer in Korean women. Therefore, an association between HDL-C and breast cancer cannot be completely excluded, even though findings from our study on lipid and percent dense area do not support a role for HDL-C as a risk factor in breast cancer. In a previous cohort study of postmenopausal Korean women, we observed that serum T-C level was not associated with breast cancer.15,52 may reflect cell proliferation activity in the breast. The known association of mammographic density with breast cancer has led to its use as a surrogate marker in research evaluating the mechanism by which factors that influence cell proliferation in breast tissue increase the risk of breast cancer. However, mammographic density may have limitations as an intermediate marker of breast cancer risk, because not all risk factors for breast cancer have the same association with mammographic density.52 We used a single measurement of lipid parameters, and substantial biological variation might have biased results. In addition, mammographic density and lipid parameters change during the menstrual cycle.53,54 However, we could not fully assess the menstrual cycle phase in premenopausal women and were thus unable to perform mammograms and blood testing during the same menstrual cycle phase in premenstrual women. The association between HDL-C and other lipid parameters with mammographic density may differ by ethnic group, given that Asian women differ greatly from Western women in HDL-C and obesity level. Therefore, findings from our study may not be generalizable to other ethnic populations.Mammographic density is a relative value, and the characteristics of X-ray attenuation in connective and epithelial tissue (dense area) and fat tissue (nondense area)In conclusion, there was no independent association between HDL-C, LDL-C, or TG and mammographic density in Korean women. These findings suggest that HDL-C is unlikely to increase the risk of breast cancer, particularly via changes in breast parenchyma that are reflected in mammographic density. In addition, studies that use mammographic density as an intermediate marker of breast cancer risk should control for BMI.


Selective serotonin reuptake inhibitors (SSRIs), a popular class of antidepressants, may increase breast cancer risk by stimulating the secretion of prolactin, a potential tumour promoter. We evaluated the effects of duration of SSRI use, cumulative dose, and latency on the risk of breast cancer by conducting a population-based case-control study utilizing Saskatchewan health databases.Cases included 1,701 women with primary invasive breast cancer diagnosed from 2003 to 2006, and controls consisted of 17,017 women, randomly selected from the population registry. Use of SSRIs was compiled using the Saskatchewan prescription database. Unconditional logistic regression was conducted to evaluate the impact of duration of combined SSRI use , cumulative dose  and timing of use  on the risk of breast cancer.Overall, SSRI use was not associated with an increased risk of breast cancer regardless of our definition of cumulative use . In addition, our results indicate that prolonged SSRI use does not have a latent effect on breast cancer risk. Also, our findings are not suggestive of an increased risk of breast cancer with the use of individual SSRIs.Our study improved upon most previous studies by having a longer follow-up period, a larger sample size of long-term SSRI users and consideration of risk during specific exposure time windows that take latency into account. Given the potential health benefits of using SSRIs, our results suggest that the issue of breast cancer risk may no longer be a concern for women requiring long-term SSRIs. Experimental evidence suggests that SSRIs, a popular class of antidepressants, enhance breast cell proliferation during a relatively late phase in breast cancer development, either directly through SSRI tumour-promoting mechanisms -3 or indPrevious epidemiologic studies examining the relationship between SSRI use and breast cancer were mainly conducted in the 1990's when the prevalence of SSRI use was low and therefore those studies were limited by a lack of subjects with prolonged use of SSRIs . As suchIn this study, we evaluated the effects of duration of use, cumulative dose, and latency on breast cancer risk using a population-based case-control study.This population-based case-control study utilized three administrative health databases from the province of Saskatchewan (SK), Canada: (1) the person registry system (PRS) (population registry) for information on demographics and dates of health coverage for the majority of SK residents, (2) the Saskatchewan prescription drug plan (SPDP) database for all outpatient prescriptions covered by the drug plan filled since the mid-1970's for most SK residents, and (3) the Saskatchewan Cancer Agency (SCA) cancer registry database for detailed information on cancer diagnoses since 1970 [in situ cervical cancer. We included all incident cases of primary invasive breast cancer, diagnosed between 1 January 2003 and 31 December 2006, who met the eligibility criteria listed above. Controls were selected from the underlying study population using an incidence density (or risk-set) sampling approach [The underlying study population for cases and controls was conceptualized as all women eligible for outpatient prescription drug benefits who, during the case accrual period 2003 to 2006, were aged 28 to 79, had prescription coverage for 10 or more consecutive years prior to their index date, and no previous cancer diagnosis at any site in the 10 years preceding the index date, with the exception of non-melanoma skin cancer and in situ),  between 1 January 2003 and 31 December 2006 and 17,020 matched controls. One case and three controls were excluded from the analysis because of missing demographic data leaving 1,701 cases and 17,017 controls.We initially identified 1,702 women diagnosed with breast cancer  primary invasive cancers and 3 (0.2%) carcinomas Information was obtained on all SSRI prescriptions dispensed for cases and controls between the start of their drug plan coverage or 1 July 1989 (when the first SSRI was listed on the SK Formulary), whichever was later, and the index date. SSRIs covered by the provincial drug plan during the study period included citalopram, fluoxetine, fluvoxamine, paroxetine and sertraline and were available with no prescribing restrictions. SSRIs were first considered as a group, then as individual agents. Data extracted from the prescription drug database included the dispensing date, name, strength, dosage formulation, and quantity of the SSRI dispensed. The prescription database did not include information on the dosage prescribed , the duration of each prescription, or the indication for the SSRI prescription.The observation period was divided into three exposure time windows of interest. First, breast cancer risk was examined in relation to total SSRI use during the exposure time period two or more years prior to index date thereby representing a two-year latency between SSRI use and breast cancer diagnosis. SSRI use within two years of index date was not considered etiologically relevant and was therefore excluded from the analysis similar to previous studies ,12, and a priori (two to seven years preceding index date representing a two-year latency and more than seven years prior to index date representing a latency of seven years). We hypothesized that either prolonged SSRI use within the time period two to seven years or more than seven years prior to index date may be associated with increased risk, associations that may be missed if risk was examined only in relation to SSRI use over the exposure time window two or more years prior to index date. The comparator group for each of these analyses was women with no SSRI prescriptions (non-use of SSRIs) during the specific exposure time window being analyzed.To further evaluate the effect of latency on the association between SSRI use and breast cancer risk, the exposure time window two or more years prior to the index date was subdivided into two shorter mutually exclusive exposure time windows chosen Two measures of cumulative SSRI use were used: duration  and cumulative dose . These were modelled as categorical variables in order to facilitate the analysis of the most clinically relevant contrast, that is, long-term users versus non-users.Duration of use for all SSRIs combined was based on the total number of SSRI prescriptions dispensed in each of the SSRI exposure time windows of interest . Since SSRI prescriptions in Saskatchewan are typically dispensed to accommodate a 34-day treatment period, this measure of SSRI use approximated the number of months exposed. For each exposure time period, duration of SSRI use was categorized on the basis of clinically relevant cut-offs with the intention of creating an uppermost category of SSRI users that included an adequate number of subjects. For the time periods two or more years and two to seven years prior to the index date, duration of SSRI was categorized as never, 1 to 35 prescriptions and ≥36 prescriptions. Due to the smaller number of subjects who had used SSRIs in the period of time more than seven years prior to index date, exposure categories chosen were never, 1 to 23 and ≥24 prescriptions.th percentile) and high dose (≥85th percentile) based on the distribution of total dosages among exposed controls for each of the three exposure time windows. This cut-off was chosen to identify a comparable group of highly exposed individuals to that used in the duration of use (number of prescriptions) analysis.The cumulative dose of SSRIs was calculated in terms of fluoxetine-equivalent milligrams for each prescription using the defined daily doses (DDD) published by the World Health Organization  and summFor the analysis of individual SSRIs, duration of use was represented by the total number of prescriptions dispensed and limited to SSRI use two or more years prior to index date because of small sample sizes. 'Any use' referred to women who had used the individual SSRI of interest alone or in combination with one or more other SSRIs, whereas 'exclusive use' referred to the subset of 'any use' who had used only one type of SSRI during the study period.Using yearly demographic data available from the population registry, subjects were categorized for marital status , residence status  and income support status   and hormone therapy (HT) was compiled for the period between (a) 1 September 1975 (the year that the SPDP database was started) or (b) the date of prescription coverage initiation, (whichever occurred later), and the subject's index date , cumulative dose  and timing of use  on the risk of breast cancer. For each individual SSRI, duration of use  was analyzed only for the time period two or more years prior to index date. To evaluate potential confounders, the 'change in estimate' method was used with a ≥10% criterion for inclusion ,17. No cin situ and 2.5% unknown (stage could not be assessed). The proportion of breast cancer cases diagnosed each year was similar across the four-year accrual period.The study population consisted of 1,701 cases and 17,017 controls. Cases were diagnosed at a mean age of 60.4 years (SD 11.5) and represented a homogeneous group with respect to morphology, with approximately 75% having infiltrating ductal carcinoma, 10% lobular carcinoma, and 15% with a mix of other morphologies. There was more variability in relation to stage at diagnosis, with 44.9% of cases presenting as stage one, 35.3% stage two, 12.6% stage three, 4.5% stage four, 0.2% Cases and controls were followed for an average of 28.4 years and were similar with regard to age, income support, and residence status Table . HoweverTable Compared with no use of SSRIs, higher total dosages  did not increase the risk of breast cancer during each exposure time window of interest, that is, two or more years prior to index date , two to seven years prior to index date  and use more than seven years prior to index date   and prospectively collected drug information that afforded precise and objective exposure definitions. Further, few previous studies assessed risk associated with long-term use of SSRIs of comparable duration  or during specific exposure time windows that take latency into account. However, despite these methodological improvements, our results are consistent with most other observational studies, including six that used self-reported SSRI exposure information -24, and et al. [Haukka et al.  in a recNo previous peer-reviewed published studies have considered a delayed effect of SSRI exposure using similar time periods. However, results from other studies that assessed the effect of timing of SSRI use on breast cancer risk using less precise measures of past SSRI use, such as 'time since first use' or 'time since last use' ,20,28 oret al. [P-trend = 0.10). Although the associations for 'exclusive use' of high doses of paroxetine, sertraline and fluvoxamine were inconclusive, it is important to remember that the confidence intervals were wide and less than 1% of women in our study had used these agents exclusively for two years or more, suggesting that these results are likely not a source of concern.Our findings of no increased risk of breast cancer for long-term use of individual SSRIs were consistent with most other observational studies that specifically assessed these relationships ,23,26-28et al.   would more likely occur within the low exposure categories (one or two prescriptions filled), rather than in the contrast of most interest . That is, if prescriptions were repeatedly refilled, we assume that they were more likely to be consumed. Therefore, especially within the higher exposure group, misclassification of non-users of SSRIs as users would be less likely. Further, non-compliance with dispensed medications would likely affect cases and controls equally in this study, leading to non-differential misclassification, if any.The Saskatchewan prescription database lacked information on SSRI medications dispensed in hospitals or as samples from physicians . Also, eThe SK databases did not contain information on some determinants of breast cancer including reproductive history, family history of breast cancer, anthropometric variables and lifestyle factors. However, residual confounding is unlikely to be a concern in our study since previous studies of the SSRI-breast cancer association that have collected information on these factors have demonstrated that they are not a source of confounding bias ,21,23,33Given that SSRIs are mainly prescribed for the treatment of depression , and thaIn conclusion, few epidemiologic studies have investigated the long-term safety of SSRIs or considered a latent effect of SSRI use on breast cancer risk. Using precise and objective SSRI exposure measures of long-term use that took into account the duration, dosage and timing of SSRI use, our results do not indicate that the risk of breast cancer is increased with short- or long-term use of SSRIs or provide evidence of a latent effect of past SSRI use. Given the potential health benefits of using SSRIs, our results have important implications within the realm of clinical medicine, suggesting that the issue of breast cancer risk may no longer be a concern for women requiring long-term use of SSRIs.CI: Confidence Interval; DDD: Defined Daily Doses; HSN: Health Services Number; HT: Hormone Therapy; NSAIDS: Non-steroidal Anti-inflammatory Drugs; OCS: Oral Contraceptives; OR: Odds Ratio; PRS: Population Registry System; SCA: Saskatchewan Cancer Agency; SD: Standard Deviation; SK: Saskatchewan; SPDP: Saskatchewan Prescription Drug Plan; SSRIS: Selective Serotonin Reuptake Inhibitors.All authors  have no conflicts of interest, or financial or other relationships to declare that may influence or bias this work.Each author contributed to this manuscript. JA analyzed the data and wrote the manuscript. LL contributed substantially to the statistical analysis and interpretation of the data, and to the manuscript organization and editing. PB coordinated all aspects of data collection involving Saskatchewan personnel including data retrieval, linkage procedures and quality control. KA contributed to the conception and design of the study and the on-going progress of the study. All authors reviewed and revised the manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1741-7015/8/90/prepub


The aim of this study was to investigate the effects of exercise training on maximum aerobic capacity, resting heart rate (RHR), blood pressure and anthropometric variables of postmenopausal women with breast cancer.2max, RHR, blood pressure, body weight, body mass index (BMI) and waist to hip ratio (WHR) were measured in both groups. Data was analyzed using analysis of covariance (ANCOVA).Twenty nine women with breast cancer who received surgery, chemotherapy and radiotherapy with current hormone therapy were divided into two groups; intervention and control. Subjects in the intervention group performed 15 weeks combination exercise training including walking for 25 to 45 minutes (2 sessions per week) and resistance training for 60 minutes . In pre and post tests, VO2max, RHR, body weight, BMI and WHR between intervention and control groups after 15 weeks (p < 0.05). In fact, exercise training had positive effects on the VO 2max, RHR, body weight, BMI and WHR in postmenopausal women with breast cancer. No significant different was found for blood pressure between two groups (p > 0.05).Significant differences were observed for VO It can be concluded that exercise training may improve maximum aerobic capacity, RHR and anthropometric variables in postmenopausal women with breast cancer. After diagnosis and treatment of breast cancer, the functional capacities of women with breast cancer significantly decline and remain low for a long time after treatment.32max is an important factor in the determining of the cardiorespiratory function or aerobic capacity; VO2max is the maximum oxygen that one can utilize during a maximum activity.2max of women.22max in women with breast cancer. The findings of these studies showed that exercise training can improve VO2max in breast cancer survivors.22max in women with breast cancer up to 12%, on average.2max in postmenopausal women with breast cancer. Perhaps, exercise training can improve VO2max in these patients.It is obvious that the maximum oxygen consumption or VOSurgery, chemotherapy and radiotherapy are current treatment for breast cancer patients.9Body weight, body mass index (BMI) and the ratio of waist to hip (WHR) are important anthropometric variables. High BMI and overweight are important factors that can increase the risk of breast cancer and possibility of its recurrence.109Although, there are some reports about the aerobic capacity, blood pressure and anthropometric variables as a result of exercise training in women with breast cancer, however these important variables have not well been documented. So, the aim of this study was to evaluate the effects of exercise training on maximum aerobic capacity, RHR, blood pressure and anthropometric variables of postmenopausal women with breast cancer.Subjects selected from the Center of Oncology and Radiotherapy of Hazrate Seyodoshohada Hospital in Isfahan. A list of the names and medical records of 1341 women with breast cancer who came to this center for treatment from 2005 to 2008 were given a survey. After primary survey, 342 women of 50 to 65 years old were selected. These women received surgery, chemotherapy and radiotherapy and they had current hormone therapy. They were in stage I to IIIB. They should not have specific illness and in the past 6 month should not have any experience of a menstrual cycle. Also, they should not have participated in any exercise training or physical activity in past 6 month and their body weight should not have changed in this period (last 6 month) as much as 10% of their whole body weight. All the patients invited to participate in this study by telephone. Among all, 58 women indicated their readiness to participate in this study and 38 women were present in meeting day. The physical activity readiness questionnaire (PAR-Q) and written informed consent was obtained from all of the subjects. By surveying the questionnaire, it was specified that 32 of them had conditions for taking part in this study. These 32 women divided into two groups randomly; intervention group and control group. At the end of exercise training program 29 women (15 women in control group and 14 women in intervention group) completed the relevant measurements of the post tests. This study was approved by the Faculty of Physical Education and Sport Sciences of the University of Guilan.2max in two groups modified Bruce protocol was used. Bruce protocol is one of the most common methods for estimating VO2max. This test performed on a treadmill. The standard Bruce test was started at 2.74 km/h (1.7 mph) and at incline of 10% for 3 minutes. At three minutes intervals the incline of treadmill increased by 2% and speed increase to 4.02, 5.47, 6.76, 8.05, 8.85, 9.65, 10.46, 11.26 and 12.07 km/h in each stage , respectively. The modified Bruce protocol started at 2.74 km/h and incline of 0% and 2.74 km/h and 5% incline and third stages corresponding to the first stage of the standard Bruce test. The time taken on the treadmill recorded in minutes (T). The VO2max formula for women is :Subjects’ height was measured by stadiometer . Body weight of subjects was measured without shoes by a digital scale . BMI was obtained by dividing the weight in kilogram to square of the height in meter. Waist and hip circumference was obtained by band tape in meter. WHR was calculated by dividing the waist circumference to hip circumference. Blood pressure was measured with a Japanese sphygmomanometer model ALPK2 in seated position. Since any activity can increase HR it was measured immediately after waking up. Also, HR is in lowest rate in the morning, immediately after waking up. Therefore, the RHR was recorded using the heart rate monitor belt (Polar model) by the subjects immediately after waking up. For measuring the VO2max = 4.38 × T - 3.9VOAll the measurements were obtained twice and recorded by one staff that was blinded to subjects in pre and post tests.st to 5th week, 12 repetitions per set from 6th to 10th week and 14 repetitions per set from 11th to 15th week. The nine resistance training exercises included exercises performed on Cybex strength training equipment  and with free weights . Indeed, these subjects took part in supervised walking program for two times per week, differed from resistance training days. The walking program started at 45% of maximum heart rate for 25 minutes in weeks 1-5. Duration of walking from 6th -10th weeks was 35 minutes and intensity was 55% of maximum heart rate. From 11th -15th weeks, duration of walking was 45 minutes with intensity of 65% of maximum heart rate. Heart rate controlled by Polar heart rate belt. The control group participated in measurements only and they were asked not to participate in any physical activity or exercise training.This protocol was only designed for the intervention group. This group performed 60 minute resistance training twice weekly for 15 weeks at the Foolad Mobarake Sepahan Sport Club. They performed three sets each of nine common resistance training exercises; subjects lifted as much weight as they could for 10 repetitions per set from 12max, RHR, blood pressure, body weight, BMI and WHR. The significance level of this study was set at p < 0.05.Data were analyzed using SPSS software (Version 13.0). For the description of data, mean and standard deviation were used. Also, mean values of two groups in pre and post tests were compared by analysis of covariance (ANCOVA) for VO2max, RHR, blood pressure, body weight, BMI, waist circumference, hip circumference and WHR values of two groups in pre and post tests. In the intervention group, mean of VO2max (from 17.5 to 20.65 ml.kg-1. min-1) increased and means of RHR (from 88.57 to 83.92), blood pressure (from 124.33 to 123.61 mmHg), body weight (from 70.39 to 69.40 kg), BMI (from 28.04 to 27.74 kg/m2) and WHR (from 0.982 to 0.956 m) decreased after 15 weeks of exercise training. There were significant differences between (two) groups in VO2max , RHR , body weight , BMI  and WHR  at post tests. However, there was no significant difference between groups in blood pressure  at post tests. Findings showed that exercise training had significant effect on the VO2max, RHR, body weight, BMI and WHR in the intervention group after 15 weeks.The aim of this study was to investigate the effects of exercise training on maximum aerobic capacity, RHR, blood pressure and anthropometric variables of postmenopausal women with breast cancer.-1. kg-1 and maximum aerobic capacity of the control group was decreased by 0.7 ml.min-1.kg-1 at post tests.The results of this study showed that the maximum aerobic capacity of intervention group was increased by 3.49 ml.min2max in the postmenopausal woman with breast cancer. Although the aerobic capacity of women decreases as a result of breast cancer and its treatments, but exercise training may improve the aerobic capacity. It seems that the improvement in the maximum aerobic capacity as a result of exercise training could cause an improvement in the functional capacity of the postmenopausal woman with breast cancer. Also, improvement in the maximum aerobic capacity may decrease the signs of exhaustion resulting from the treatment in postmeno-pausal women with breast cancer.Also, it demonstrated that combination of resistance and aerobic exercise training for 15 weeks had significant effect on the aerobic capacity of the postmenopausal women with breast cancer. In Visovski et al 2005) study functional and aerobic capacity was improved in postmenopausal women with breast cancer after 12 weeks.005 study6In this study, RHR of the intervention group was decreased by 4.65 beat/min and RHR of the control group was increased by 0.93 beat/min. There was a significant difference between RHR of two groups, after 15 weeks. Also, this finding shows that the resistance and aerobic exercise training can have a significant effect on the decrease of RHR in postmenopausal women with breast cancer. This finding is in agreement with others.26In the present study exercise training did not have a significant effect on the decrease of blood pressure of the postmenopausal women with breast cancer. Nevertheless, after 15 weeks blood pressure had a 0.72 mmHg decrease in the intervention group and 1.68 mmHg increases in the control group. This finding is not in agreement with others.92, respectively. In the control group after 15 weeks, body weight and BMI increased by 1.43 kg and 0.54 kg/m2, respectively. Also, the findings of this study showed that combination exercise training has a significant effect on WHR of postmenopausal women with breast cancer. This finding is in agreement with Wilson et al (2005) and Ohira et al (2006) studies.1210The findings of this study indicated that exercise training has significant effects on body weight loss and BMI of the intervention group. After 15 weeks, body weight and BMI of the intervention group decreased by 0.99 kg and 0.3 kg/mIn conclusion, supervised exercise training may have positive effects on the maximum aerobic capacity, RHR and anthropometric variables of postmenopausal women with breast cancer. However, exercise training does not have a significant effect on blood pressure of postmenopausal women with breast cancer. Therefore, exercise training has positive effects for postmenopausal women with breast cancer, however, these findings need to be confirmed in future studies.


Deficiencies in B vitamins may promote tumor carcinogenesis.B vitamins, including vitamin B6 intake with overall breast cancer risk and breast cancers stratified by hormone receptor status. This case-control study included 391 breast cancer cases and 782 control subjects enrolled at the Tri-Service General Hospital in Taipei, Taiwan. Energy-adjusted intake of vitamin B6 was derived from a food frequency questionnaire. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using logistic regression.We examined the association of dietary vitamin B6 intake were 0.78  and 0.64 (0.26–0.92), respectively. In addition, higher vitamin B6 intake was associated with a significantly lower risk of developing ER-negative breast tumors.As compared with women in the lowest tertile, the multivariate-adjusted ORs for breast cancer among women in the second and highest tertiles of vitamin B6 is associated with a reduction in breast cancer risk, particularly ER-negative tumors.Our findings suggest that higher intake of vitamin B However, epidemiologic studies of the relationship of dietary factors with breast cancer risk in Taiwanese women are relatively rare. B vitamins such as folate, vitamin B6, and vitamin B12 play important roles as coenzymes in 1-carbon metabolism, which is critical for nucleotide synthesis and DNA methylation.2 Aberrations in nucleotide synthesis or DNA methylation can contribute to carcinogenesis.3 Among the nutrients involved in 1-carbon metabolism, vitamin B6 is a crucial coenzyme in the conversion of tetrahydrofolate to 5,10-methylenetetrahydrofolate,2 which is needed for nucleotide synthesis in DNA synthesis, repair, and methylation. Thus, inadequate vitamin B6 intake might lead to imbalances in DNA precursors, disruption in DNA repair, and aberrations in DNA methylation, any of which might enhance carcinogenesis. Apart from its role in the synthesis, repair, and methylation of DNA, vitamin B6 is necessary for the synthesis of glutathione from homocysteine via cystathionine and cysteine.4 Glutathione is a cofactor of the glutathione S-transferases and glutathione peroxidase, which function in the detoxification of many carcinogenic compounds and in the protection of cells from oxidative DNA damage.5 Vitamin B6 has been shown to reduce oxidative stress as well as cell proliferation and angiogenesis, and moderate doses of vitamin B6 have been shown to suppress colorectal carcinogenesis in mice given injections of a carcinogen.4,6Breast cancer is the most commonly diagnosed cancer in Taiwanese women, and age at tumor onset is younger in this population.6 intake or circulating concentrations of pyridoxal 5′-phosphate  with the risk of carcinogenesis, especially in the breast. To gain a better understanding of the role of vitamin B6 in breast cancer risk, we conducted a case-control study of the association between dietary intake of vitamin B6 and breast cancer risk in Taiwanese women. In addition, Zhu and Williams hypothesized7 that estrogen receptor (ER)-negative and perhaps progesterone receptor (PR)-negative breast tumors, which result from hypermethylation of the promoter region of ER and PR, respectively,8 are linked to low intake of B vitamins. Thus, we also examined the association with respect to the hormone receptor status of breast tumors.Despite its importance in 1-carbon metabolism and the reduction of oxidative stress, there is limited epidemiologic evidence of an association of vitamin B9–13 The study comprised subjects attending the Department of Surgery and health examination clinics at the Tri-Service General Hospital Taipei, Taiwan from January 2004 to June 2008. Using hospital chart numbers, 391 women aged 24 to 72 years (the cases) were consecutively selected from subjects with a first confirmed histopathologic diagnosis of breast carcinoma. These patients accounted for 91.7% of women with breast cancer who attended our breast cancer clinics during the study period. More importantly, because the clinics in which this study was performed are major breast cancer clinics in northern Taiwan, our patients accounted for a sizable proportion (approximately 20%) of all breast cancer cases diagnosed during the study period in this region.14 The histopathologic profile included 282 cases of invasive ductal carcinoma, 42 cases of invasive lobular carcinoma, and 67 cases of carcinoma in situ. There were 227 premenopausal and 164 postmenopausal breast cancer cases. Data on breast tumor ER and PR status were obtained primarily from the hospital laboratory that routinely conducts immunohistochemical assays to determine steroid receptor status of tumor tissues from breast cancer patients. Immunohistochemical assays were interpreted as positive (presence of antibody nuclear staining) or negative by pathologists who recorded this result directly on the pathology report. The ER and PR status were obtained for 95% (371 of 391) of the breast cancer cases: 268 of the cases were ER-positive and 295 were PR-positive. The control subjects were women with no history of cancer and were simultaneously recruited from the health examination clinics of the same hospital during the same study period. They underwent a 1-day comprehensive health examination (including regular breast cancer screening using X-ray mammography and ultrasonic examination), and those with any evidence of breast cancer, suspicious precancerous lesions of the breast, or other cancers were excluded from the control group. Because the examination was not sponsored by the National Insurance Program, the controls might represent a group of women who have greater concern for their health. Approximately 80.4% of women who were initially identified as potential controls participated in the study, and these participants accounted for approximately 50% of all women attending the clinic. No significant differences in breast cancer risk factors were found between the included and excluded control subjects. Two control subjects were matched to each case by date of enrollment (±3 months) and duration of fasting (±4 hours). Overall, 391 breast cancer cases and 782 matched controls were included in the analysis. This study was conducted according to the guidelines specified in the Declaration of Helsinki, and all procedures involving human subjects were approved by the Institutional Review Board of the Tri-Service General Hospital in Taipei . Written informed consent was obtained from all subjects.This study is an extension of a previously reported case-control study.15–17 The regression-residual model was used to adjust intake of vitamin B6, vitamin B12, and folate.18 Although the FFQ might not be applicable for estimating actual intake of B vitamins among subjects, it is likely to be adequate for ranking individuals by dietary intake of B vitamins. The reliability and validity of the FFQ have been evaluated previously among participants of the MJ Health Screening Center, a population that is comparable to our present study subjects attending health examination clinics.19 The intra-class correlation coefficients for vitamin B6, vitamin B12, and folate intake from FFQ repeated measurements over the 1-year period were 0.644, 0.743, and 0.513, respectively. In addition, the Spearman correlation coefficients between energy-adjusted nutrient intakes estimated from the FFQ and a 4-day dietary record in a subsample of 59 individuals were 0.38 for vitamin B6, 0.33 for vitamin B12, and 0.30 for folate. Moreover, the validity of the FFQ was further assessed in the present study on the basis of laboratory analyses of biochemical indicators of dietary intake20 in a randomly selected subsample of the control group (n = 89). The Spearman correlation coefficient between vitamin B6 intake from the FFQ and plasma level of PLP was 0.31. The correlation between folate intake from the FFQ and plasma folate levels was 0.34. These results indicate that the predictive power of our dietary assessment methodology was relatively good. Information on multivitamin supplement use was also requested on the FFQ, but data on nutrient intake from supplements were not included in the analyses. Participants were queried as to whether they had ever taken multivitamin supplements in the preceding year (control subjects) or the 1 year before breast cancer diagnosis (cancer cases). However, information regarding the specific brand, composition, dosage, and duration of use of multivitamin supplements was not available. Accordingly, use of multivitamin supplements among participants was categorized as never or ever use in the statistical analyses. To avoid the influence of treatment on measurements, questionnaire data were obtained before cases were scheduled for surgery and radio- or chemotherapy.All participants underwent a personal interview administered by well-trained interviewers in conformity with institutional guidelines for studies including human subjects. Trained interviewers collected information on sociodemographic characteristics, menstrual and reproductive history, menopausal status, lifestyle behaviors, and medical history. In this study, postmenopausal was defined as absence of menses during the last 12 months or history of oophorectomy or hysterectomy; no attempt was made to distinguish between artificial and natural menopause. In addition, because the average quantities of cigarettes and alcohol consumed by Chinese women are not large in Taiwan, habitual cigarette smoking was defined as smoking cigarettes at least once a week for more than 1 year. Similarly, habitual alcohol drinking was defined as consuming any alcoholic beverage at least once a week for more than 1 year. A 31-item semi-quantitative food frequency questionnaire (FFQ) was administered to estimate dietary intake among participants. The FFQ was designed to assess usual dietary intake over a 1-year period, ignoring any recent changes. This FFQ inquired about how often participants consumed individual food items (frequency of consumption) and about representative sizes (as compared with standard portions) during either the preceding year (control subjects) or 1 year before their breast cancer diagnosis (cancer patients). Photographs of foods, showing different portion sizes, were used to facilitate quantification of intakes. Nutrient values in foods were computed by multiplying the frequency of responses by the nutrient content of specified portion sizes according to a previously established Taiwanese nutrient database.6, vitamin B12, and folate, we used tertile cut points to categorize B vitamins intake into 3 groups, with cut points based on the distributions in the control subjects. Individuals in the lowest tertile were treated as the referent in the statistical analyses. To maintain matched triplet integrity, we used conditional logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the association between dietary intake of B vitamins and breast cancer risk. Age at enrollment (treated as a continuous variable), reproductive risk factors , postmenopausal hormone use, and family history of breast cancer , which had been identified in the literature as potential confounders, were included in the logistic regression model. In addition, to increase statistical power, unconditional logistic regression was used to further examine the association of vitamin B6 with breast cancer by level of folate intake, use of multivitamin supplements, menopausal status, and hormone receptor status. Tests for trend were conducted by entering the categoric variables as continuous variables in the model and calculating a Wald statistic. All statistical analyses were performed using SAS statistical software . A P value less than 0.05 was considered statistically significant.Differences between cases and controls in the distributions of age at menarche, age at first full-term pregnancy (FFTP), age at menopause, parity, cigarette smoking, alcohol drinking, use of multivitamin supplements, menopausal status, postmenopausal hormone use, and family history of breast cancer were evaluated using the chi-square test. For statistical analysis of data on B vitamin intake, including vitamin BThe baseline characteristics of patients with breast cancer and control subjects are summarized in Table P = 0.33). For all women, greater intakes of vitamin B6, vitamin B12, and folate were associated with lower risk of breast cancer  for vitamin B12, and 0.71 (0.24–2.15) for folate. However, a significant inverse trend was observed only between vitamin B6 intake and breast cancer risk (P for trend test = 0.04). When breast cancer cases were stratified by diagnosis (in situ vs invasive disease), the inverse trend of ORs for breast cancer in relation to the intake of B vitamins did not differ substantially from that for all women combined (data not shown).Overall, there was no statistically significant difference between cases and controls in terms of total caloric intake  and 0.50 (0.31–0.88), respectively. In contrast, intake of vitamin B6 was not appreciably associated with breast cancer among postmenopausal women  and those who did not take multivitamin supplements.It has been proposed that the effects of vitamin B8 are linked to low intake of B vitamins.7 We thus examined the association between vitamin B6 intake and breast cancer risk stratified by the ER and PR status of breast tumors  and 0.62 (0.30–0.98), respectively. In contrast, there was no appreciable inverse trend in risk of ER-positive tumors in relation to vitamin B6 intake. Furthermore, the association between vitamin B6 intake and breast cancer risk did not significantly differ according to the PR status of breast tumors.It has been hypothesized that ER-negative and perhaps PR-negative breast tumors, which result from hypermethylation of the promoter region of ER and PR,rs Table . It is n6 was associated with a significantly lower risk of breast cancer among Taiwanese women. This inverse association was particularly evident among premenopausal women, women with low folate intake, and women who had never used vitamin supplements. Moreover, analysis of cases stratified by ER status of breast tumors revealed that the reduction in risk was more pronounced among women with ER-negative breast tumors.In this case-control study, we observed that dietary intake of vitamin B6 on breast cancer risk. The folate metabolism pathway has been reported to be associated with breast carcinogenesis.9,23–28 Vitamin B6 acts as a critical coenzyme in 2 different steps in this pathway: in the synthesis of 5,10-methylenetetrahydrofolate, which is critical for synthesis, repair, and methylation of DNA,2,3 and in catabolism of homocysteine to glutathione, which is involved in the detoxification of many carcinogenic compounds and in the protection of cells from oxidative DNA damage.4,5 Laboratory studies using mice suggest that vitamin B6 exerts other anticarcinogenic effects by reducing cell proliferation, nitric oxide production, and angiogenesis.4,29 Despite this laboratory evidence, epidemiologic studies examining the relationship of dietary or plasma levels of vitamin B6 with breast cancer risk have been unable to provide unequivocal evidence for a protective effect of vitamin B6 in preventing breast cancer development. Several investigators have observed, as we did, an inverse association between dietary or plasma levels of vitamin B6 and breast cancer risk,30,31 although other studies have not.32–35 The inconsistent data obtained regarding vitamin B6 and breast cancer risk might be at least partly due to differences in vitamin B6 intake between populations and by lack of adjustment for factors that potentially influence dietary or plasma levels of vitamin B6. In the present study, we found that the inverse association between dietary intake of vitamin B6 and breast cancer risk was more prominent among women whose diets were low in folate intake and among those who never used vitamin supplements. Indeed, previous studies have shown that the effects of vitamin B6 were modified by the intake of other nutrients involved in the 1-carbon metabolism pathway.24,32 In an earlier report, Zhang et al found an inverse association between dietary intake of vitamin B6 and the risk of colorectal cancer among women who did not take vitamin supplements.21 Furthermore, results from a randomized trial indicated a beneficial effect on cancer risk in participants treated with vitamin B6 alone as compared with those assigned to placebo. In contrast, combined folic acid, vitamin B6, and vitamin B12 treatment had no significant effect on overall risk of total invasive cancer or breast cancer.36 Taken together, these findings indicate the possibility of a threshold effect of vitamin B6 on cancer risk. During vitamin B6 absorption, cellular uptake and the metabolic pathway itself are saturated systems; thus, micronutrient intake beyond a certain level might have little additional effect.There is a substantial body of data supporting the biological plausibility of a protective effect of vitamin B6 to breast cancer risk was stronger among premenopausal women. This contrasts with previous studies, which noted that the inverse association between vitamin B6 and breast cancer risk was primarily present in postmenopausal women.30,31 This apparent contraindication may be explained by the unique characteristics of breast cancer in Taiwanese women, ie, the age of onset in Taiwanese women is much younger than in women from Western countries. Indeed, 29.3% of Taiwanese breast cancer patients develop early-onset (age ≤40 years) breast cancer.1,37 The biological mechanism that explains the effect modification by menopausal status in our data is that cell proliferation in breast epithelial cells is much higher in premenopausal women than in postmenopausal women,38 and cells that are dividing and differentiating may be particularly susceptible to aberrations in DNA synthesis, repair, and methylation. Vitamin B6 plays a critical role in these processes. Thus, if vitamin B6 is important in breast carcinogenesis, it is likely to be more strongly associated with premenopausal breast cancer than with postmenopausal breast cancer. Further studies of larger numbers of both premenopausal and postmenopausal women is needed to help clarify this issue.In this case-control study of Taiwanese women, we observed that the inverse relation of vitamin B6 was associated with significantly lower risk of developing ER-negative breast cancer among women. B vitamins such as folate and vitamin B6 play an important role in DNA methylation,2,3 and molecular studies show that ER-negative breast cancer is caused by the lack of ER gene transcription due to the methylation of the CpG island 5′ to the gene.39 Likewise, previous epidemiologic studies have shown an elevated risk of ER-negative tumors among women who had a low intake of folate.23,24 Our data and previous study results support the hypothesis that low B vitamin status promotes breast carcinogenesis, at least in part, through its influence on DNA methylation. However, our study found that the association between vitamin B6 intake and breast cancer risk did not differ according to PR status, which suggests that the effects of vitamin B6 may be more specific to ER.Another interesting finding from this study is that higher dietary intake of vitamin B40 Previous studies have reported that 35% to 44% of women in Taiwan regularly consume 1 or more vitamin/mineral supplements.41,42 Our observation suggests that vitamin supplement use may become more common among women in Taiwan. Vitamin supplement use is a marker of a healthy lifestyle in many populations.43,44 In this study, the enrollment of control subjects who were selected from people presenting to a health examination clinic might have overrepresented vitamin supplement use.A notable result of the present investigation is that multivitamin supplement use was common among study subjects. Indeed, commercially available vitamin supplements in Taiwan have seen tremendous growth during the last decade.45,46 Adding to this complexity is the intercorrelations among numerous foods and nutrients, which result in interactions that are difficult to isolate.47 Thus, many dietary components and lifestyle factors may potentially confound the relation of a single dietary component  with breast cancer risk observed in the present study. The results of this study should therefore be interpreted with caution.Diet represents a complex set of exposures, and the action of a dietary compound is strongly affected by the biochemical milieu in which it resides.48 Second, although high participation rates among both eligible case and control subjects minimized potential selection bias, cancer-free women attending health examinations might have dietary habits that differ from those of the general population due to greater health consciousness or disease concerns, which might have led to selection bias and underestimation of the nutrient–cancer risk association. Third, measurement error in a FFQ is an issue for all study designs. Errors in the values reported on FFQs could profoundly affect the results of our case-control study. However, FFQs have been shown to accurately rank the relative intake of micronutrients among individuals and are therefore an adequate, albeit not perfect, instrument for measuring relative dietary intake.49,50 Fourth, dietary intakes assessed in case-control studies are sensitive to recall bias. In particular, as compared with controls, case subjects might have been more motivated to recall their diet, depending on their beliefs regarding the association between diet and their disease. We aimed to limit this bias by recruiting incident cases and interviewing them at an early stage of their disease—and before their acceptance of treatment—thus reducing the likelihood of dietary changes resulting from a cancer diagnosis and subsequent treatment effects. Finally, because our study was based on a small-scale case-control comparison and many subgroup analyses were performed in the study, our findings are subject to chance.Several limitations of this study warrant mention. First, control subjects were selected from attendees of health examination clinics and might represent a group of women who are more concerned about their health. However, the case and control groups were recruited from the same hospital, and the control group comprised individuals who would likely be diagnosed at that hospital were they to develop the disease of interest.6 are associated with the risk of developing premenopausal breast cancer and ER-negative breast tumors. These observations suggest a possible complex role for this nutrient in breast cancer development. Further prospective follow-up studies are needed to confirm our results and to elucidate the mechanisms for the observed inverse associations of vitamin B6 intake with the risk of developing premenopausal breast cancer and ER-negative breast tumors.In conclusion, our data indicate that higher dietary intakes of vitamin B


The association between breast cancer and tobacco smoke is currently unclear. The aim of this study was to assess the effect of smoking behaviours on the risk of breast cancer among three ethnic groups of New Zealand women.A population-based case-control study was conducted including breast cancer cases registered on the New Zealand Cancer Registry between 2005 and 2007. Controls were matched by ethnicity and 5-year age-group. Logistic regression was used to estimate the association between breast cancer and smoking at different time points across the lifecourse, for each ethnic group. Estimated odds ratios (OR) were adjusted for established risk factors.The study comprised 1,799 cases  and 2,540 controls . There was no clear association between smoking and breast cancer for non-Māori/non-Pacific women, although non-Māori/non-Pacific ex-smokers had statistically significant increased risk of breast cancer when smoking duration was 20 years or more, and this remained significant in the fully adjusted model . Māori showed more consistent increased risk of breast cancer with increasing duration among current smokers . There was a clear pattern of shorter duration since smoking cessation being associated with increased likelihood of breast cancer, and this was apparent for all ethnic groups.There was no clear pattern for cigarette smoking and breast cancer incidence in non-Māori/non-Pacific women, but increased risks were observed for Māori and Pacific women. These findings suggest that lowering the prevalence of smoking, especially among Māori and Pacific women, could be important for reducing breast cancer incidence. Breast cancer is the most commonly registered cancer among New Zealand women; it accounts for 28% of all new female registrations and 16% of female cancer deaths Tobacco smoke is the most important known cause of cancer and has been associated with an extensive list of specific cancers Furthermore, there is also some evidence to suggest that exposure to tobacco smoke at particular time points Consent was obtained from all study participants and ethical approval was granted by the Central Health and Disability Ethics Committee (WGT/03/12/126) of New Zealand.Ethics approval was granted for collection of information explicitly for the purposes of this study and the data are not publicly available.st April 2005 and 30th April 2006 were eligible for inclusion. To ensure sufficient numbers of cases, the eligible time period was extended for a further year to 30th April 2007 for Māori and Pacific women. Control women were recruited from the New Zealand electoral roll, on which registration is mandatory for all New Zealand residents from 18 years of age. Controls were matched on ethnicity and frequency matched on 5-year age bands. The response rate among cases was 78% in non-Māori/non-Pacific women, 46% in Pacific, and 81% in Māori; for controls response was 57% in non-Māori/non-Pacific women, 15% in Pacific, and 38% in Māori.The New Zealand Breast Cancer Study, a population-based case-control study, was conducted to investigate risk factors throughout the lifecourse for breast cancer among three different ethnic groupings in New Zealand: Māori, Pacific, and non-Māori/non-Pacific women. The study design and methods have been published previously, and therefore will only be described briefly here All participants completed comprehensive questionnaires on lifetime behaviours including socio-demographics; lifestyle; and reproductive and medical histories. Information on smoking was based on questions regarding current smoking and previous smoking patterns, including average amount per day at age 20 and 40 years. Participants were asked if they had ever smoked, now or in the past; at what age they started smoking regularly; and whether they are a current smoker. Current and former smokers were asked to select from pre-specified categories, on average, how many cigarettes they smoked in a day: under 10; 10 to 19; 20 or more; or whether they did not smoke at that particular age (for ages 20 and 40 years). Smoking duration was derived from deducting the age of starting to smoke regularly (initiation) from the age of stopping for ex-smokers, and for current smokers, the age at interview for controls, and age at diagnosis for cases. For ex-smokers the number of years since quitting was derived from the difference between age at interview (age at diagnosis for cases) and the age at which they ceased smoking. Duration prior to first birth was estimated by subtracting age of smoking initiation from the age of first live birth.2, 25–30 kg/m2 (overweight), and 30 kg/m2 or higher (obese).Body mass index (BMI) was estimated from participant self-reported information (weight in kilograms divided by height in metres squared). Information on exercise was based on questions about the average frequency of leisure activities over the preceding year (Godin Leisure Time Exercise Questionnaire) Women were classified as premenopausal if they had had a menstrual period in the last three months, or if their periods had stopped due to pregnancy/lactation, or use of hormonal birth control. Women were classified as postmenopausal if they reported natural menopause, surgical menopause involving bilaterial oophorectomy, or use of hormone replacement therapy (HRT). Women who did not fall into these categories, who reported surgical menopause without bilaterial oophoretoomy, and other or unknown reasons for menses cessation were classified in an ‘other amenorrhea’ category; we then assumed that those aged less than 49 years were premenopausal and those aged 49 years or more were postmenopausal based on data from New Zealand and the UK, which indicate 49 years as the median age at menopause for similarly aged birth cohorts Descriptive analyses were initially conducted to explore the variable values and summarise the data, and chi-squared tests were used to compare exposure distributions between cases and controls. Unconditional logistic regression models were used to estimate odds ratios (OR) and 95% confidence intervals (CI) for the associations between breast cancer and smoking at different points across the lifecourse for each ethnic group, adjusted for age and menopause status, and additionally adjusted by all other covariates . Interactions by ethnic group were assessed using likelihood ratio tests.Subgroup analysis and likelihood ratio tests were performed by menopausal and BMI statuses, which found no evidence of interactions (data not shown). As never smokers are different in many ways to smokers, using non-smokers as a reference group could result in confounding due to these unmeasured factors. Therefore, a range of sensitivity analyses were conducted, in which other smokers or ex-smokers were used as a reference group. For example, smokers who had stopped for less than 10 years were compared to smokers who had stopped for 10 or more years (reference group). In general, this made little difference to the results, and no difference to the interpretation of our data (data not shown), suggesting that the possibility of confounding due to these unmeasured factors was unlikely. Further sensitivity analysis was performed to investigate non-response bias, using post-stratification weights. A weight was calculated for each stratum of ethnicity*deprivation, by dividing the expected deprivation distribution of each ethnic group by the observed deprivation distribution in the controls from our study. The expected distributions were estimated from the 2002/03 New Zealand Health Survey (unpublished data), and were: 2%, 3%, 10%, 20% and 65% for Māori and Pacific women in quintiles 1 to 5 of the NZDep2006 categories, and 23%, 20%, 20%, 20% and 17% for non- Māori/non-Pacific women. Logistic regression models were then weighted using the “svy: logistic” command.All analyses were performed using Stata version 11.2.There were 1799 cases included in the study: 302 Māori, 70 Pacific and 1427 non- Māori/non-Pacific. Three controls were excluded due to missing age information, leaving a total of 2540 controls: 746 Māori, 191 Pacific, and 1603 non- Māori/non-Pacific. The associations between smoking status and duration, and breast cancer are presented in The associations between the quantity of cigarettes consumed per day and breast cancer are presented in The associations between smoking before and during pregnancy, and breast cancer are presented by ethnic group in Overall, the effect of weighting the controls for differential non-response attenuated the effect estimates slightly for Māori (e.g. ever smoked OR changed from 1.49 to 1.43 (95% CI 0.95 to 2.17)); for Pacific, the estimates, although unstable, showed some evidence of a strengthening of effect (e.g. ever smoked OR changed from 1.23 to 1.36 (95% CI 0.49 to 3.76)); and for non-Māori/non-Pacific, there was almost no change in effect (e.g. ever smoked OR remained at 1.02 (95% CI 0.86 to 1.21)).To explore the relative confounding effect of variables across ethnic groups, each potential confounder was added individually to models which included ‘ever smoking’ and we checked whether the OR for ever smoking and breast cancer then changed . Among MThis study has found little evidence of associations between cigarette smoking and breast cancer incidence in non-Māori/non-Pacific women, but increased risks were observed for Māori and Pacific smokers. In the latter ethnic groups, elevated risks were observed for both ex-smokers and current smokers. Length of time since quitting smoking was inversely associated with the risk of breast cancer, and elevated risks were observed for those who smoked for 20 years of more. The findings in Pacific women were in general not statistically significant, but the numbers were relatively small, and the odds ratios were consistent with those found for Māori women. Furthermore, variations were found in the magnitude of the change in the smoking effects after adjustment for confounders among the different ethnic groups.Findings of the current study are consistent with several previous studies which found a strong association between long duration of smoking and breast cancer A large collaborative study found that smoking appears to have little or no independent effect on breast cancer risk beyond the risk conferred by drinking alcohol Most studies that have examined associations between smoking and breast cancer for premenopausal and postmenopausal women separately, have observed no meaningful difference in risk by menopausal status Among non-Māori/non-Pacific, statistically significant elevated risks were only observed among ex-smokers who smoked for more than 20 years, and smokers who had stopped for less than 10 years. Our findings regarding the length of time since stopping smoking are consistent with some previous studies The association between smoking and breast cancer was stronger for Māori than in the other ethnic groups. Māori women have extremely high rates of smoking and the different effects observed for different ethnic groupings could be affected by these. Few populations have such high smoking rates among women; in 2009 the smoking prevalence for Māori women was more than three times that for non-Māori: 48.3% compared with 16.2% respectively The current study had several limitations, including the potential selection and recall biases commonly associated with case-control studies involving patient interviews. We know from comparison of control distributions with distributions of the New Zealand Deprivation Index that affluent women are over-represented and deprived women are under-represented in the study. Therefore, control weighting adjustment was applied to account for this difference, and this did not materially change our results. The response rates were particularly poor among Pacific controls (15%) and therefore this group is unlikely to be representative of the population of Pacific women in New Zealand. However, there is a paucity of research in this population group and more is needed to increase the limited evidence available regarding breast cancer risk for Pacific women. There were small numbers in some strata, especially among Pacific women, which limit the precision of the effect estimates. Limited numbers also restricted the analyses conducted with regard to categorical comparisons and ability to assess differences among breast cancer subtypes.Another limitation of this study is the potential for residual confounding. For example, the odds ratio for ever smokers in Māori fell from 1.82 to 1.49 when the analyses were adjusted for BMI, exercise, HRT, OC, maternal breast cancer, parity, alcohol and SEP; the odds ratio in Pacific women fell from 1.69 to 1.23. Thus, about 40% of the excess risk in Māori, and more than half of the excess risk in Pacific women was removed by adjustment for these confounders. Given that we did not have perfect confounder information , it is likely that the excess risk would have reduced even further if we had been able to obtain ‘perfect’ confounder information. Thus, if one considered only the findings for ever smokers  it is possible that the observed excess risk could be due to residual confounding. However, when we considered more detailed smoking information, including smoking duration, the associations were stronger and the reduction in excess risk was relatively less, when adjusting for potential confounders. Thus, it appears to be unlikely that all of the excess risks we observed were due to residual confounding.Adjustment for confounding factors affected the smoking odds ratios differently among the ethnic groups. The magnitude of the change following the adjustment, and the relative importance of the relationship between smoking and factors such as BMI, exercise, OC, and family history of breast cancer, are likely to differ between ethnic groups and populations. The amount of residual confounding is also likely to vary and affect the findings for specific populations depending on the suitability of adjustment for each population. Therefore, the appropriateness of adjustments for potential confounders could play a role in the observed inconsistent findings for smoking and breast cancer in various populations Previous studies have found that positive associations between active smoking and breast cancer were strengthened when passive smokers were excluded from the reference comparison In conclusion, there was no clear pattern for cigarette smoking and breast cancer incidence in non-Māori/non-Pacific women, but clear patterns of higher risk were observed for Māori and Pacific smokers. These findings suggest that smoking could play a role in the ethnic disparities which have been observed in the distribution of breast cancer in New Zealand. Lowering the prevalence of cigarette smoking, especially among Māori and Pacific women, could be important for reducing breast cancer incidence.