Recent studies have suggested that statins, an established drug group in the prevention of cardiovascular mortality, could delay or prevent breast cancer recurrence but the effect on disease-specific mortality remains unclear. We evaluated risk of breast cancer death among statin users in a population-based cohort of breast cancer patients. The study cohort included all newly diagnosed breast cancer patients in Finland during 1995–2003 , identified from the Finnish Cancer Registry. Information on statin use before and after the diagnosis was obtained from a national prescription database. We used the Cox proportional hazards regression method to estimate mortality among statin users with statin use as time-dependent variable. A total of 4,151 participants had used statins. During the median follow-up of 3.25 years after the diagnosis (range 0.08–9.0 years) 6,011 participants died, of which 3,619 (60.2%) was due to breast cancer. After adjustment for age, tumor characteristics, and treatment selection, both post-diagnostic and pre-diagnostic statin use were associated with lowered risk of breast cancer death . The risk decrease by post-diagnostic statin use was likely affected by healthy adherer bias; that is, the greater likelihood of dying cancer patients to discontinue statin use as the association was not clearly dose-dependent and observed already at low-dose/short-term use. The dose- and time-dependence of the survival benefit among pre-diagnostic statin users suggests a possible causal effect that should be evaluated further in a clinical trial testing statins’ effect on survival in breast cancer patients. Breast cancer is the leading cause of cancer death among women globally. Statins reduce cholesterol biosynthesis in the liver by inhibiting 3-hydroxy-3-methylglutaryl-coenzyme-A reductase (HMGCR), the rate-limiting enzyme in the mevalonate pathway. In addition to cholesterol, this pathway produces isoprenoids that are critical for regulation of cell growth. Despite promising preclinical results, there is no clear association between statin use and breast cancer incidence. We studied the association between statin use and breast cancer mortality among breast cancer patients in a nationwide population-based cohort.We used the Finnish cancer registry to obtain information on all breast cancer cases diagnosed in Finland from 1995 to 2003. Due to mandatory reporting of all cancer diagnoses made in the Finnish health care units, the Finnish Cancer Registry has good national coverage, including over 99% of cancer cases in Finland. Detailed, individual-level information on usage of cholesterol-lowering drugs between Jan. 1,1995 and Dec. 31, 2003 was obtained from the national prescription database managed by Social Insurance Institution of Finland (SII). Cancer cases were linked to the prescription database using a unique personal identification number.SII is a governmental agency providing reimbursements to each Finnish citizen for the cost of medicines prescribed by a physician and purchased in outpatient setting. All reimbursed purchases of drugs approved by the SII  are recorded in the database. The cholesterol-lowering drugs in clinical use during the study period and recorded by the prescription database were statins , fibrates  and bile-acid binding resins (cholestyramin and cholestipol).All histologically confirmed invasive breast cancer cases diagnosed in Finnish health care units from 1995 to 2003 and recorded in the Finnish Cancer Registry were included in our study cohort, a total of 31,236 cases . Men were excluded from this analysis.The status on post-diagnostic statin use was updated prospectively for each year of follow-up since breast cancer diagnosis. The study participant was categorized as statin user only for the years with recorded statin purchases, regardless of the amount. Persons who discontinued prior post-diagnostic statin use were categorized separately as previous users. Cumulative amount (daily doses), duration (years) and intensity (doses/year of usage) of post-diagnostic use were analyzed as prospective time-dependent continuous variables. At discontinuation the cumulative amount/duration/intensity of statin use stayed at the level reached before the usage was stopped.For prediagnostic use women who were using statins at the year of diagnosis were categorized as current pre-diagnostic users; those who had use the drugs before but had stopped prior to the diagnosis were categorized as previous pre-diagnostic users. Total cumulative amount, duration and intensity of pre-diagnostic statin use were calculated since 1995 up to the year of diagnosis.The amount of usage was standardized for different statins using the defined daily doses (DDDs) recommended by the World Health Organization (WHO ATC/DDD index database). We used Chi-square test  and Mann-Whitney-U test (for continuous variables) to evaluate statistical significance of the differences in baseline characteristics between medication users and non-users.st, 2003), whichever came first.Hazard ratios (HRs) and 95% confidence intervals (CIs) for breast-cancer specific and all-cause mortality were estimated using Cox proportional hazards regression, with years since the date of breast cancer diagnosis as the time-metric. Each cohort member contributed person-time from the diagnosis until the date of death, emigration from the country or the end of study period  were included in the regression model as time-independent variables. The proportional hazards assumption was checked for each time-independent variable by including interaction term with follow-up time into the regression model. In each case, the interaction term was not statistically significant, confirming the assumption.All HRs are calculated using non-users of cholesterol-lowering drugs as the reference group. We performed the analyses separately with an age-adjusted model and a multivariable adjusted model . Analyses on non-statin cholesterol-lowering drugs (fibrates and resins) were additionally adjusted for prior statin usage. We report multivariable-adjusted HRs unless otherwise stated.Survival trends by increasing amount, duration or intensity of statin use were estimated by stratifying the analysis within tertiles of the amount/duration or deciles of intensity of statin usage. P values for trends by amount, duration or intensity of statin use were calculated by including these variables as continuous, time-dependent variables into Cox regression model.The analyses were repeated separately for pre-diagnostic (statin use occurring before the years of diagnosis) and post-diagnostic statin use.To address the potential for confounding by indication we evaluated and controlled for each person’s likelihood of being a statin user post-diagnosis we calculated propensity score using logistic regression model with post-diagnostic statin use as the dependent variable and age, tumor stage, morphology, treatment selection and pre-diagnostic statin usage as categorical independent variables. We evaluated the impact of death due to non-cancer causes on observed breast cancer mortality with a competing risks regression as described by Fine and Gray, All reported p-values are two-sided. IBM SPSS statistics 20 statistical software  was used for Cox regression analyses and STATA version 12  was used for competing risks regression.Of the participants, 4,151 (13.3% of the cohort) had used statins between 1995 and 2003, while 313 (1% of the cohort) had used fibrates or resins . Of the In total, 1,801 women  had used statins before breast cancer diagnosis, while 71 (0.2%) had used fibrates or resins. The usage continued after the diagnosis in 85% and 38% of previous statin and fibrate/resin users, respectively.A total of 2,350 new users started statin usage post-diagnosis. Of these 1,880 (80%) remained adherent users until the end of follow-up.During the median follow-up of 3.25 years post-diagnosis 6,011 (19.2%) participants died, of which 3,619 (60.2%) due to breast cancer. The median follow-up did not differ significantly by medication usage. Compared to the non-users, medication users were older and more likely to have localized invasive ductal carcinoma than lobular carcinoma . SurgicaCompared to the non-users, current post-diagnostic statin users had lowered risk of breast cancer death , whereas women who had stopped statin use post-diagnosis (previous users) had elevated risk compared to non-users . The risk decrease among current statin users was observed both in localized and metastatic cases at diagnosis .In stratified analyses the risk decrease strengthened by increasing cumulative amount and intensity of post-diagnostic use, especially among participants with metastatic tumors . No statWomen who had used statins pre-diagnosis and were still users at the year of breast cancer diagnosis had lowered risk of breast cancer death compared to non-users , whereas previous pre-diagnostic use (usage stopped before the year of diagnosis) was not associated with the risk  . A signiStratification by quartiles of propensity score ensured similar propensity for post-diagnostic statin use between users and non-users in the first two quartiles . In the third and fourth quartiles the propensity score was not perfectly balanced between statin users and non-users , mainly because post-diagnostic statin users in these quartiles were mostly also pre-diagnostic users, which was the strongest predictor of post-diagnostic use causing high propensity scores.For post-diagnostic statin use the risk of breast cancer death was similarly decreased in all quartiles of propensity score . FurtherThe risk estimates for pre-diagnostic statin use were mostly non-significantly decreased in stratified analysis, with no clear effect modification .Similar to breast cancer-specific mortality also all-cause mortality was lowered in current, but not previous pre- and post-diagnostic statin users. Again, the association was clearer with continued and more intensive usage .All three most commonly used statins were associated with decreased risk of breast cancer death in participants with localized tumors both when used pre- or post-diagnosis . Also poFibrates and bile-acid binding resins were not associated with all-cause mortality in patients with localized cancer  but were linked to higher mortality in patients with metastatic disease . The number of fibrate/resin users was too low to estimate breast cancer-specific mortality.Decreased risk of breast cancer death among statin users was not explained by increased risk of death from other causes; the mortality decrease was observed also in multivariable adjusted competing risks regression, with non-cancer deaths as a competing cause of death .Women dying of breast cancer may have been more likely to drop statin use during the final months of life. However, the inverse association between post-diagnostic statin use and breast cancer mortality remained after exclusion of changes to statin usage status during the final year of follow-up .The impact of prevalent user bias was evaluated by limiting the analysis to new post-diagnostic statin users only. The risk decrease was observed also in this group of statin users, but with no dose-dependence by amount, duration or intensity of use . HoweverHazard of breast cancer death remained decreased among post-diagnostic statin users when the minimum follow-up was set to be 5 or 7 years , suggesting that the risk decrease remains even in the long-term.We have demonstrated lowered risk of breast cancer death among statin users in a nationwide cohort of all breast cancer patients diagnosed in Finland during a period of nine years. The risk decrease was observed for both localized and metastatic disease at diagnosis, and both for pre-diagnostic and post-diagnostic statin use. The association was dose-dependent especially for pre-diagnostic usage. The risk decrease was not modified by differences in age, tumor characteristics and treatment selection between statin users and non-users. This association was not observed for other types of cholesterol-lowering drugs despite similar age, tumor and treatment characteristics, and was not explained by competing causes of death or decreased likelihood of statin usage at the end of life.Our results could have been affected by healthy user bias, created by a tendency of healthier patients’ greater likelihood to initiate and adhere to statin therapy, leading to decreased likelihood of outcomes not causally related to statin use, such as risk of accidents. A major strength of our study is the nationwide coverage of all incident breast cancer patients in Finland from 1995–2003, reducing the possibility of selection bias and allowing us several unique opportunities: the ability to evaluate the association by stage, perform analysis by statin type and compare mortality by the type of cholesterol-lowering drug being used. Another important strength is our detailed knowledge on timing, dosage and duration of statin use, allowing incorporation of the time varying nature of the medication use into analysis and reliable estimation of dose-dependence. Although our median follow-up was only 3.25 years post-diagnosis, the results were unchanged in sensitivity analysis with minimum follow-up set to seven years, showing that the mortality decrease remains also in the long-term.in vitro, Previous laboratory studies have demonstrated that statins inhibit breast cancer cell growth Cardiovascular disease prevention trials have shown lowered overall mortality in statin users compared to the non-users. The significant mortality decrease in our study was evident already after short-term post-diagnostic statin use. Spontaneous decrease in serum cholesterol has been reported for years before cancer death. in vivo are due to a systemic effect common to all statins, such as cholesterol-lowering.When analyzed separately the risk decrease was not clearly modified by statin potency, as similar risk decrease was observed for high-potent atorvastatin as for other statins. Also hydrophilic pravastatin was associated with a similar decrease as lipophilic statins. This suggests that statins’ anticancer effects Our study has several limitations. We could not evaluate whether statins’ effect on mortality was modified by tumor hormone receptor status as this information was unavailable. Neither did we have information on breast cancer screening history, which could have been more common among statin users, in vitroIn conclusion, statin users had lower risk of breast cancer death compared to non-users in a nationwide cohort of Finnish breast cancer patients. Combined with previous evidence from


No information is available on the attitudes of General Practitioners (GPs) and Breast Surgeons (BSs) to their delivery of genetic, environmental and lifestyle risk factor information about breast cancer. The aim of this study was to describe the Breast Cancer Risk Communication Behaviours (RCBs) reported by GPs and BSs in four European countries and to determine the relationships between their RCBs and their socio-occupational characteristics.a priori, the various RPFs used by the respondents were analyzed using cluster analysis.Self-administered questionnaires assessing breast cancer risk communication behaviours using vignettes were mailed to a sample of Breast Surgeons (BS) and General Practitioners (GP) working in France, Germany, the Netherlands, and the UK (N = 7292). Their responses to questions about the risk factors were first ordered and compared by specialty and country after making multivariate adjustments. Rather than defining a standard Risk Presentation Format (RPF) Family history and hormonal replacement therapy were the risk factors most frequently mentioned by the 2094 respondents included in this study. Lifestyle BC risk factors such as obesity and alcohol were rarely/occasionally mentioned, but this point differed (p < 0.001) depending on the country and the specialty of the providers involved. Five distinct RPF profiles including the numerical/verbal presentation of absolute/relative risks were identified. The most frequently encountered RPF (34.2%) was characterized by the fact that it included no negative framing of the risks, i.e., the probability of not developing cancer was not mentioned. Age, specialty and country of practice were all found to be significant determinants of the RPF clusters.The increasing trend for GPs and BSs to discuss lifestyle risk factors with their patients suggests that this may be a relevant means of improving breast cancer prevention. Physicians’ risk communication skills should be improved during their initial and vocational training. BRCA1/BRCA2 or a family history of breast cancer, hormonal factors increasing the duration of exposure to oestrogens such as early menarche/late menopause/hormonal replacement therapy/oral contraceptives, exposure to ionising radiation at an early age  and a high breast density can all contribute to breast cancer [BRCA1/2 mutation carriers [Multiple risk factors contribute to the occurrence of breast cancer. It has been clearly established by now that lifetime exposure to genetic, environmental and lifestyle risk factors play an important role in the aetiology of this disease. Convincing or at least strong evidence has been presented showing that genetic mutations such as t cancer . Lifestycarriers .As soon as the first genes predisposing their carriers to hereditary breast/ovarian/colorectal cancer were identified, cancer genetic clinics were organised in many industrialized countries to inform people at risk and their families -11. SincAs far as we know, no information is available so far about GPs’ and breast specialists’ attitudes to delivering genetic, environmental and lifestyle risk factor information about breast cancer. The state of the art and the effectiveness of risk communication have been reviewed extensively , especiaThe aim of this study was first to ascertain how General Practitioners (GPs) and Breast Surgeons (BSs) practicing in several European countries regarded their Breast Cancer Risk Communication Behaviours (RCBs), and to determine the relationship between their RCBs and their socio-occupational characteristics.The International Cancer Risk Communication Study (InCRisC study) was a multicentre European research project designed to describe risk communication practices and the management of familial breast cancer in primary care. It was carried out in 2010 in four European countries . Data collection was organised separately in each country by the co-authors involved in the project . Questionnaires taking about 25 min to complete were posted to a sample of 3999 GPs and a sample of 3293 breast surgeons in each of these four countries. The international study methodology was reviewed and approved by the German Federal Ministry of Education and Research «Ethical, Legal and Social Implication of Biomedical Research Programme» which funded the project. Each country was in line with its own national regulation. The review procedure included the assessment of ethical issues, informed consent, confidentiality and regulation to data access. A detailed description of the study design has been published elsewhere [BRCA1/2 genetic testing process. Here we present only the variables addressed in the questionnaire on the topic of risk communication . Scores ranging from 0 (never) to 5  were computed on each of these 8 variables. The questions used are given in Figure In the first scenario presented to the physicians Figure -Q11, theThese characteristics included all the participants’ gender, age, and number of years of practice. GPs were also asked approximately how many patients consulted them per week, while specialists were asked about their speciality and the number of newly diagnosed breast cancer patients who had consulted them during the previous year.2 and Fisher’s exact tests were used in the univariate comparisons on categorical data and Student’s t-tests on continuous data. Multivariate adjustment was performed using analyses of variance (ANOVA) on quantitative dependent variables. Logistic regressions were performed in order to compare the physicians’ profiles identified in the cluster analysis in terms of their risk presentation formats. In the multivariate analyses, systematic adjustments were made for age, gender, country and specialty.Chia priori, we decided to identify their profiles statistically, based on their answers to the questions about their risk presentation practices, using cluster analysis.Rather than defining the formats used by physicians a priori hypotheses about them. The cluster analyses were performed using the conventional agglomerative hierarchical procedure [a priori, an automatic procedure was used to select the best distributions (from 3–10) using Ward’s method [The advantage of this method was that the profiles could be tested without making any rocedure  to attris method .An overall score on the communication of risk factors other than family history and HRT was calculated by summing together all the risk factor scores except for family history. This score ranged from 0 to 30.The Statistical Package for Social Science (SPSS/PC released 18.0) was used to perform all the statistical analyses .The final sample analysed (N = 2094) consisted of 1189 GPs and 905 breast surgeons.The response rates differed significantly from one country to another (p < 0.001): 40.6% in France, 28.4% in Germany, 38.6% in the Netherlands, and 30.1% in the United Kingdom. Details of the response rates obtained in these countries have been presented elsewhere .Among the respondents, 7 GPs and 22 Breast Surgeons were excluded from the analysis because they declared that they had not been consulted by any breast cancer patients during the previous year.Doctors’ socio-occupational characteristics differed among the four countries Table .Table 1BS informed their patients more frequently than GPs about all the risk factors except for oral contraception and HRT, on which GPs obtained higher scores Table . InformaIn order to analyze this point, we opted for a five-cluster approach, which seemed to be the most relevant from both the statistical and clinical points of view Table .Table 4The first cluster included 17.6% of the respondents. These respondents reported that they presented the risks in absolute numerical terms and in a negatively framed way, without any verbal description of the absolute risk and without mentioning the relative risks. This cluster was labelled “No verbal formulation & No relative risks mentioned”.The second profile (34.2%) was that which occurred most frequently. It was characterized by the presentation of fairly heterogeneous information, and especially by the fact that only 2.9% stated that they would present negatively framed risks, i.e., the probability of not developing cancer. This cluster/profile was labelled “No negative framing”.The third profile (12.7%) included practitioners who always presented the absolute numerical risks, the relative risks, and negatively framed risks. None of them described the absolute risks verbally. This group was labelled “No verbal formulation”.In the fourth group (18.0%), the absolute risks were presented both numerically and verbally, and the risks were negatively framed. Nearly half of the members of this group also presented the relative risks. They were labelled as “Risks presented in all 4 ways”.The last cluster (17.5%) included doctors who did not present the risks in absolute numerical terms and always framed them negatively. Most of this group presented the absolute risks verbally as well as presenting the relative risks. It was labelled “Absolute numerical risks not presented”.The fourth cluster “Risks presented in all 4 ways”, which was taken to be one of the “best standards” for presenting risk information, was compared with each of the other clusters Table .Table 5In comparison with cluster 4, the respondents in cluster 1 “No verbal formulation & No relative risks mentioned” were more frequently GPs and belonged to a younger age-group, and were less frequently from the NTL.In comparison with cluster 4, cluster 2 “No negative framing” contained a higher proportion of GPs and a higher proportion of French doctors.In comparison with cluster 4, cluster 3 “No verbal formulation” included younger practitioners and a higher proportion of French doctors.In comparison with cluster 4, cluster 5 “Absolute numerical risks not presented” more frequently included GPs and doctors practicing outside the UK.To summarize, GPs were more frequently allotted to clusters corresponding to “incomplete” risk presentation formats; and the clusters brought to light some of the specificities of the countries under investigation . Although a younger age was associated with less verbal communication about the risks, gender was not found to be a significant determinant of the respondents’ risk communication profiles.This international survey is the first to assess how European GPs and specialised practitioners caring for healthy women under breast cancer surveillance regard their responsibility for assessing and communicating genetic, environmental and lifestyle breast cancer risk factors to their patients.First, the majority of these European practitioners reported that they frequently assessed family history and hormonal replacement therapy (HRT) but only occasionally discussed patients’ lifestyle BC risk factors such as obesity, physical exercise and alcohol Table . Breast The relatively similar attitudes to discussing patients’ family history and HRT risks observed in the various countries may have been due to the large body of research results published during the last fifteen years on the assessment of breast cancer genetic risks ,12 and tSecondly, the majority of the sample (more than two thirds) declared that they expressed the absolute risks numerically and framed them negatively when presenting them to patients Table . Risks aThis study has several limitations. First, it is about self-reported risk communication practices, which may differ from physicians’ actual practices. These declared practices are likely to be a combination between what the doctors said they would do and what they thought they ought to do. In addition, the vignettes used here provided only a short description of the complex clinical context. The results should be interpreted accordingly. Secondly, the questionnaire used in this study was mailed to the doctors eligible to participate, and the response rate obtained was low despite the reminders made by mail and telephone. The low response rate certainly reduce the possibility of generalizing the results obtained by taking them to be representative of doctors’ risk communication attitudes in a given country. Any country-specific differences will have to be investigated further. Although the response rate was low, it was comparable to that obtained in other surveys of this kind . HoweverThe occupational characteristics of the practitioners working in various countries’ healthcare systems have to be taken into account when interpreting the data collected. The role of the “GP gatekeeper” in the UK’s and Netherlands’ healthcare systems differs from what occurs in France and Germany, especially as regards referrals, prescriptions and the existence of highly specialized secondary and tertiary care centres. For example, mammographic screening of healthy women at risk is performed in the UK by breast surgeons, whereas this activity is mostly carried out in France by Gynaeco-Obstetricians, who form a very heterogeneous group of practitioners, some of whom are medical gynaecologists , while others are involved only in obstetric care or specialize in breast surgery.The differences between the breast cancer risk communication profiles observed among non-geneticist healthcare providers in these four European countries reflect the specificities of the respective healthcare systems, and especially the content of medical training programs and guidelines. Risk communication skills should be part of a core communication curriculum intended not only for geneticists/cancer geneticists and genetic counsellors, but also for primary care providers . Qualita


Descriptive statistics, chi-square tests, t-tests, Fisher’s exact test, and correlations were performed for data analysis. A total of 28 comorbidities were identified. Among the 134 patients, 73.8% had at least one of the comorbidities, 54.7% had 2–4, and only 7.4% had 5–8. Comorbidities did not change at 12 months after surgery. Numbers of comorbidities by patients’ self-report and weighted categorization of comorbidities by CCI had a similar negative correlation with overall quality of life scores as well as domains of general health, physical functioning, bodily pain, and vitality. Comorbidities, specifically hypertension, arthritis, and diabetes, were associated with poorer quality of life in multiple domains among breast cancer survivors. Future research should consider the combined influence of comorbidity and cancer on patients’ quality of life.Many breast cancer survivors have coexistent chronic diseases or comorbidities at the time of their cancer diagnosis. The purpose of the study was to evaluate the association of comorbidities on breast cancer survivors’ quality of life. A prospective design was used to recruit 140 women before cancer surgery, 134 women completed the study. Comorbidities were assessed using self-report and verified by medical record review and the Charlson Comorbidity Index (CCI) before and 12-month after cancer surgery. Quality of life was evaluated using Short-Form Health Survey (SF-36  Breast cancer is the most commonly diagnosed cancer among women worldwide. Approximately one in eight women will be affected by breast cancer during her lifetime, and more than 2.9 million breast cancer survivors currently reside in the United States . A womanThe presence of comorbidities in patients with cancer has been negatively associated with patients’ health outcomes. Poorer survival from cancer has been found overall in cancer survivors with comorbidities compared to those without ,6. BreasResearch studies investigating the effects of comorbidities upon breast cancer survivors’ quality of life have been limited by cross-sectional study designs and the assessment of comorbidities by using sole patient self-report. Deshpance and colleagues  investigA global measure of comorbidity frequently employed by researchers is the Charlson Comorbidity Index ,13. CCI In addition to the type of comorbidity index utilized, methodologies differ between studies in the assessment of patient comorbidities. Some studies rely upon sole patient self-report to evaluate comorbidities, whereas others utilize ICD-9 codes that reflect provider given diagnoses of that medical condition. The types of comorbidities evaluated in breast cancer survivors and the methods in which they are assessed, are therefore crucial to delineate in an investigation of the effects of comorbidities upon breast cancer survivors’ quality of life. The validity of comorbidity assessment must be verified and relevant comorbidities must be captured, in order to elicit the true influence of comorbidities within a patient population and detect pertinent patterns.Numerous investigations have evaluated the influence of comorbidities upon breast cancer survivors’ outcome , but fewv2) only at 12 months after surgery. Among 134 participants who completed the study, 4 patients did not provide data on quality of life, therefore the 4 patients were excluded in the data analysis regarding quality of life. We stratified the participants into women who had at least one or more comorbidities and those who had none since the average weighted categorization of comorbidities calculated by Charlson Comorbidity Index (CCI) score was 1.59 , whereas the average numbers of comorbidities reported by study participants and verified by medical record review was also 1.59 .This study was approved by the institutional review board at New York University Langone Medical Center. A prospective design was used to recruit women who were over the age of 21, first time diagnosis of breast cancer (Stage I-III), and scheduled for surgical treatment including lumpectomy or mastectomy, sentinel lymph node biopsy or axillary lymph node dissection. Women with metastatic cancer (Stage IV) or prior history of breast cancer were excluded, since trajectory of cancer treatment is different . BetweenRecruitment: After the institutional review board approved the study, we used the successful procedures of recruiting and consenting participants used by the team in the previous studies [Invitation Flyer that described the study. The Invitation Flyer was posted on the bulletin boards or breast cancer support website at the cancer center, and was also available in the reception areas of the center, examination rooms, and rooms holding support group meetings. In addition, healthcare providers such as nurses, oncologists, breast surgeons, and oncology radiologists at the cancer center referred women meeting the inclusion criteria to the study by distributing Invitation Flyer that described the study to the potential participants. studies ,16. SuccConsent and Data Collection Process: After reading the flyer, if a woman was interested in participating in the study, she would schedule a meeting with the researchers at that time or at other convenient time for them. During the meeting, the researchers confirmed her interest, determined if the woman is eligible for the study and the researchers again explained the study in detail and provide enough time for the woman to ask questions. If the woman agreed to participate, she would sign the consent form. All data collection was completed in person.Demographic and Medical Information: A structured interview tool [iew tool ,16 was uComorbidity Status: Two approaches were designed to elicit broader and more detailed information and to ensure reliability of the women’s report regarding comorbidity status. First, participants responded to two open-ended interview questions: (1) In addition to breast cancer, what other illnesses or diseases do you have? (2) What medications do you take? Secondly, the researchers verified and validated the listed comorbidities by reviewing patients’ medical records before and 12 months after surgery. Participants were categorized as patients with or without comorbidities if self-reports were consistent with the medical records. To avoid overestimation, data from medical records were used to resolve any discrepancies between self-report, medications, and medical records.The Charlson Comorbidity Index: A weighted index to evaluate risk of death from comorbid disease [ disease . This syThe Short-Form Health Survey (SF-36) version 2 (SF-36v2): A short-form health survey of 36 questions with five -level responses. It yields an 8-scale profile of functional health and well-being scores as well as psychometrically-based physical and mental health summary measures and a preference-based health utility index. A higher score indicates better overall quality of life and each domain of quality of life. Reliability and validity of the instrument has been established with the median reliability coefficients for each of the eight scales equal to or greater than 0.80 [han 0.80 . SF-36v2han 0.80 .Characteristics of the participants were summarized using descriptive statistics . Distributions of baseline patient demographic and clinical characteristics were compared for patients with and without comorbidities using Chi-Squared tests for contingency tables and one-way analysis of variance for continuous variables. Correlations and t-tests, without assuming equal variance, were performed to examine associations between comorbidities and quality of life. All statistical tests were conducted at the 0.05 significance level (2-sided).One hundred and forty women were recruited before breast cancer surgery, 134 women completing the study with a 4% attrition rate. The reasons stated by those who did not complete the 12-month follow-up included: (a) significant travel distance (three patients); (b) death from cardiac related event (one patient); and (c) withdrawal of consent due to stress from chemotherapy (two patients).The mean age of participants was 56 years (range from 25–84 years), with the majority being married (53%) and had a bachelor (36.6%) or master or doctoral degree (30.6%). The majority of the study participants described their ethnicity as white (71.6%), with the remaining participants classifying their ethnicity as Asian (13.4%), African American (9.7%) or Hispanic (4.5%).Participants had the following surgical procedures for breast cancer: sentinel lymph node biopsy (41.8%), axillary lymph node dissection (58.2%), mastectomy without construction (14.9%), mastectomy with immediate reconstruction (41.8%), and lumpectomy (43.3%). Participants also had the following adjuvant treatments: radiation (67.9%), chemotherapy (56.7%), radiation and chemotherapy (23.7%). There was no significant difference between participants with comorbidities and those without them in terms of cancer treatment .Participants with comorbidities were older, had a trend of high BMI at 12-month after cancer surgery. More participants with comorbidities were unemployed. More African American/black participants had comorbidities .The accordance of comorbidities between patient self-report verified by medical record review was 99%. Only one participant did not report depression when a diagnosis was documented in the medical record. A total of 28 comorbidities were identified through patient self-report verified by medical record review. Among the 134 patients, 73.8% had at least one of the comorbidities, 54.7% had 2–4, and only 7.4% had 5–8. The five most prevalent comorbidities in this patient population were as follows: hypertension (32.8%), arthritis (32.8%), thyroid problem (22.4%) hypercholesterolemia (12.7%) and diabetes (12.0%), see versus assessed by the Charlson Comorbidity Index, did not differ significantly except one condition, arthritis. Arthritis, the equally most prevalent comorbidity as hypertension, affected more than one third of the study participants but is not assessed in calculating the Charlson Comorbidity Index. The other top comorbidities reported by study participants, hypertension, diabetes and heart disease, are conditions that are recognized by CCI, yet hypertension is not weighted for CCI calculation and hypercholesterolemia is not assessed by CCI. The average weighted categorization of comorbidities, calculated by Charlson Comorbidity Index (CCI) score was 1.59 , whereas the average numbers of comorbidities reported by study participants and verified by medical record review was 1.59 .Comorbidities through self-report and verified by medical record review p < 0.01). Likewise, weighted categorization of comorbidities, as conveyed by the Charlson Comorbidity Index score, was found to have a negative correlation with overall quality of life assessed by the SF-36v2 .Numbers of comorbidities, as assessed through self-report and verified by medical record review, was found to have a negative correlation with overall quality of life , bodily pain , vitality , and social functioning . BMI prior to surgery  and age  had negative correlations with the domains of physical functioning.Numbers of self-reported comorbidities verified by medical record review had negative correlations with the domain of physical functioning  were negatively associated with multiple domains of quality of life, including physical functioning, general health, bodily pain, and vitality. There were no significant associations between individual comorbidities and the domains of role-physical social functioning, and role-emotional emotional health (vs. 83.6), bodily pain (69.3 vs. 81.4), and general health (64.6 vs. 74.2). Participants with diabetes had significantly lower scores in physical functioning (62.2 vs. 80.0) and bodily pain (65.5 vs. 79.2) in comparison to those without diabetes. In addition, patients with hypertension were found to have significantly lower scores in physical functioning (71.4 vs. 81.2) in comparison to those without it. However, after adjustment for multiple testing, only the association between arthritis and physical functioning remained significant (p < 0.01).In addition, certain individual comorbidities . Although these two measures differed in methodology and types of comorbidities assessed, they both revealed similar results; numbers of comorbidities by self-report and average weighted categorization of comorbidities by CCI had negative associations with overall quality of life among women treated for breast cancer 12 months after surgery.Assessing comorbidities in this investigation yielded the following five most prevalent conditions: hypertension (32.8%), arthritis (32.8%), thyroid problem (22.4%) hypercholesterolemia (12.7%) and diabetes (12.0%). Although tabulation and CCI measures revealed overall similar results in that increased comorbidities are being negatively associated with quality of life, the tabulation method of comorbidities provided additional information. By assessing for types of comorbidities representative of this particular patient population of breast cancer survivors, we were better able to evaluate the association of comorbidities relevant to this patient population with quality of life For instance, over a third of our patients had comorbidities of arthritis and hypertension; such disease entities were not included in the calculation of Charlson Comorbidity Index scores, but potentially could have a negative influence on quality of life domains. For example, arthritis had negative associations with quality of life in several domains, including physical functioning, general health, bodily pain, and vitality. It should be noted the negative association between arthritis and physical functioning remains even after adjusting for multiple testing. This indicates arthritis could be an important comorbidity that influences patients’ quality of life among this population. Therefore, by first identifying comorbidities most relevant to this particular patient population, we could then ascertain the effects of those conditions upon breast cancer survivors’ quality of life.Utilizing the SF-36v2, we were able to demonstrate that patients with arthritis had significantly lower scores in the quality of life domains of physical functioning, general health, bodily pain, and vitality. Patients with hypertension had significantly lower scores in the domain of physical functioning, whereas patients with diabetes had significantly lower scores in the domains of physical functioning and bodily pain. Not only were breast cancer survivors with an increased number of comorbidities found to experience poorer overall quality of life, but in stratifying by disease entity, we were better able to understand which domains of quality of life were negatively associated with specific comorbidities.A few limitations of this study deserve mention. First, our patient population consisted primarily of white women, and therefore certain comorbidities may have been over or under-represented. Thus, our findings may not be generalizable to a more heterogeneous patient population. Nevertheless, our study also found that African American/black participants all had at least one or more comorbidities. Second, patients’ quality of life scores were not assessed pre-operatively due to the fear that asking quality of life at the time point of cancer diagnosis might induce unnecessary emotional distress from patients. However, we are aware the absence of assessments of quality of life at pre-surgery prevents an evaluation of treatment effects on quality of life. The modest sample size limited the ability of the study to explore the effects of comorbidities in the context of other determinants of quality of life using advanced regression models. Future research needs to examine the effects of comorbidities on quality of life using larger samples. Despite these limitations, this study utilized a prospective, longitudinal design, assessing comorbidities before and after surgery, and verifying patient self-report of comorbidities with medically given diagnoses. By assessing beyond the comorbidities included in the Charlson Comorbidity Index, we were able to identify comorbidities relevant to this particular patient population, and discern patterns of disease presentation. In addition to illustrating an overall negative correlation between an increased number of comorbidities and breast cancer survivors’ quality of life, we were able to stratify by disease entity and demonstrate how particular disease entities were associated with particular domains of patients’ quality of life.Comorbidities are negatively associated with breast cancer survivors’ quality of life. Hypertension, arthritis, and diabetes have negative associations with multiple domains of breast cancer survivors’ quality of life. This study provides evidence as to the stability of comorbidity patterns within the breast cancer patient population, existing before and 12 months after surgery, and sheds light as to how such comorbidities are negatively associated with certain domains of patients’ quality of life. It is only after such knowledge is obtained regarding the relationships of comorbidities with breast cancer survivors’ quality of life that interventions can be designed to manage such comorbidities and optimize breast cancer survivors’ quality of life. Future research should consider larger and more diverse samples as well as the combined impact of comorbidity and cancer treatment upon breast cancer survivors’ quality of life.


Metabolic syndrome  is emerging as a risk factor for breast cancer; however few studies – most confined to postmenopausal women – have investigated associations between breast cancer risk and metabolic syndrome. The purpose of this study was to examine the association between metabolic syndrome and its components, and risk of breast cancer in postmenopausal and premenopausal women.We performed a case-cohort study on 22,494 women recruited in 1993-1998 to four Italian centres  of the European Prospective Investigation into Cancer and Nutrition (EPIC) and followed-up for up to 15 years. A random subcohort of 565 women was obtained and 593 breast cancer cases were diagnosed. Hazard ratios (HR) with 95% confidence intervals (CI), adjusted for potential confounders, were estimated by Prentice-weighted Cox proportional hazards models.Presence of metabolic syndrome was associated with significantly increased breast cancer risk in all women . When the analyses were repeated separately for menopausal status, the association was limited to postmenopausal women  and absent in premenopausal women ; P for interaction between metabolic syndrome and menopausal status was 0.001. Of metabolic syndrome components, only high blood glucose was significantly associated with increased breast cancer risk in all women  and postmenopausal women , but not premenopausal women .These findings support previous data indicating that metabolic syndrome is an important risk factor for breast cancer in postmenopausal women, but not in premenopausal women, and suggest that prevention of metabolic syndrome through lifestyle changes could confer protection against breast cancer. Breast cancer is the most common cancer in women, and second most common cancer; it is the first cause of cancer death in women and fifth most important cause of cancer death . AlthougMetabolic syndrome is a cluster of metabolic abnormalities that occur in persons with impaired insulin sensitivity . It is dSince breast cancer is conspicuously a hormone-related disease, risk factors could have different effects depending on menopausal status ; howeverThe aim of this case-cohort study was to investigate the association of metabolic syndrome and its components with breast cancer risk. We investigated all women and postmenopausal and premenopausal women separately.Our case-cohort study to investigate breast cancer risk in women with metabolic syndrome was nested in the population of four Italian centres of the European Prospective Investigation into Cancer and Nutrition (EPIC), and formed part of a wider case-cohort design study to investigate three other outcomes . The study protocol was approved by the ethics committee of the Human Genetics Foundation . The study complies with the Helsinki declaration, and participants gave informed consent to use clinical data for research.The cohort consisted of 22,494 women recruited prospectively in 1993–1998 to the four EPIC-Italy centres of Varese and Turin , Naples and Ragusa . At baseline, after participants had given written informed consent, detailed information was collected on lifestyle using a standardized lifestyle questionnaire, and on diet over the previous year using food frequency questionnaires specifically developed to capture local dietary habits . Also atA centre-stratified random sample of 565 participants was obtained from the 22,494 women, to serve as subcohort, which included 16 women who developed breast cancer during follow-up.In Varese, Turin, and Ragusa, incident breast cancers were identified by linkage to the databases of regional cancer registries. In Naples, incident cases were identified through linkage to the regional archive of hospital discharges, and by direct telephone contact where necessary.Cancers were primary incident cases (invasive and in situ) identified by codes C50.0–50.9 of the International Classification of Diseases (10th Revision). A total of 618 cases was identified.Women were followed-up from study entry until the first cancer diagnosis (except non-melanoma skin cancer), death, emigration, or end of follow-up, whichever occurred first. End of follow-up varied with centre: December 31, 2006 for Varese and Naples; December 31, 2008 for Turin and Ragusa.After excluding women with unavailable plasma samples or missing lifestyle information, the sample on which we performed statistical analyses therefore consisted of 1133 participants: 555 in the randomly selected subcohort and 593 cases (15 in the subcohort).Triglycerides, HDL cholesterol and glucose were measured in plasma samples using commercial colorimetric enzyme kits  and an automatic analyser . Quality control was checked using commercial (high and low) laboratory standards and an in-house plasma pool. Coefficients of variation (CV) for high level external standards were 5.0% for triglycerides, 6.1% for HDL cholesterol, and 5.0% for glucose. CVs for low level external standards were 7.9% for triglycerides, 7.0% for HDL cholesterol, and 7.6% for glucose. CVs for the in-house plasma pool were 3.5% for triglycerides, 5.3% for HDL cholesterol and 3.8% for glucose.To render the results in plasma samples comparable with literature data on serum samples, the following conversion factors were applied: 1.338 for triglycerides, 1.344 for HDL cholesterol, 1.181 for glucose. These factors were determined in the laboratory by comparison of analyte concentrations in plasma and serum from 222 persons. For all analyses, laboratory staff were blind to the case-control status of samples.Most definitions of metabolic syndrome require the presence of at least three of the following five components: abdominal obesity, high triglycerides, low HDL cholesterol, high blood glucose, and high blood pressure. Definitions differ mainly as regards the cut-offs used for each component. We used the latest harmonized definition  of metabBaseline characteristics of cohort members, according to presence/absence of metabolic syndrome, were summarized as means and standard deviations (continuous variables) or frequencies . Prentice-weighted Cox proportional hazards models, with age as underlying time variable, were used to assess associations of metabolic syndrome and its components with breast cancer risk . We compP values for interaction of exposure variables with menopausal status were calculated adding to the models product terms for exposure (presence/absence) and menopausal status. The analyses were performed with Stata version 11.2 .For premenopausal women, presence of metabolic syndrome was associated with a non-significantly lower breast cancer risk than absence of metabolic syndrome . A significant interaction (P = 0.001) between metabolic syndrome and menopausal status was found. Breast cancer risk did not vary significantly with number of metabolic syndrome components.When BMI was added to the models, results were closely similar to those of the fully-adjusted models (data not shown). The results of model run after excluding women who self-reported diabetes, were also closely similar to the results of the models  that incWhen presence versus absence of individual metabolic syndrome components was analysed , only hiIn this case-cohort study, we have found that presence of metabolic syndrome was associated with increased breast cancer risk in all women, but the risk was greater in postmenopausal women, while among premenopausal women, a non-significantly lower risk of developing breast cancer was found. Considering the individual components of metabolic syndrome, high fasting glucose was significantly associated with increased breast cancer risk in all women and in postmenopausal women, while in premenopausal women, the association tended in the opposite direction (not significant). High blood pressure also had opposing non-significant effects in postmenopausal (increased risk) and premenopausal women (decreased risk).Our finding of increased breast cancer risk in women with metabolic syndrome is in line with two recently published meta-analyses. The first, based on nine prospective studies on postmenopausal women, found that presence of metabolic syndrome was associated with a significant 52% increase in breast cancer risk . The othFew studies have assessed metabolic syndrome and breast cancer risk in premenopausal women, and results have been contrasting. The Me-Can project , which pSeveral mechanisms have been proposed to explain the association between metabolic syndrome and postmenopausal breast cancer risk. The pathophysiological state that underlies metabolic syndrome is insulin resistance, which can increase breast cancer risk  via seveInsulin may also enhance breast cancer risk, especially in postmenopausal women, by increasing levels of estrogens and androgens. Estrogens have a causal role in breast cancer , especiaMetabolic syndrome is characterized by high levels of inflammatory cytokines  and leptFinally, Beaulieu et al.  have sugOur finding of a non-significant inverse association between metabolic syndrome and breast cancer risk in premenopausal women is less easy to explain. We tentatively suggest that insulin’s stimulatory effect on ovarian androgen synthesis may lead to the development of ovarian hyperandrogenism in susceptible women , which iStrengths of our study are its prospective design, relatively large sample size, and availability of detailed information on lifestyle that made it possible to control for confounding effects.A limitation is that we assessed variables at baseline only and do not know to what extent they may have changed subsequently. Nevertheless there is good reason to believe that blood chemistry remains relatively stable over time . FurtherTo conclude, we found that metabolic syndrome is a risk factor for postmenopausal breast cancer but not for premenopausal breast cancer. Of the individual components of the syndrome, elevated fasting glucose had the strongest association with risk in postmenopausal women. These findings suggest that prevention of metabolic syndrome by lifestyle changes might have an important protective effect against the development of breast cancer.


N = 152–124). Self-reported surveillance was compared to surveillance recommendations. Consultations were videotaped. Counselees’ reactions to the risks and recommendations were coded. Statements about the risk perception and surveillance intentions of breast cancer unaffected counselees were transcribed. Associations with outcomes were explored. Almost all breast cancer unaffected counselees (>90 %) reacted to their risk estimate with an utterance indicating understanding and this reaction was not significantly associated with their post-visit risk perception alignment. Over one-third (38.6 %) overestimated their risk post-counseling. Few counselees (5.8 %) expressed surveillance intentions. One year after counseling, about three-quarters (74.0 %) of the breast cancer unaffected counselees had adhered to the surveillance recommendation. Almost one-quarter (23.3 %) had performed more mammograms/MRI scans than recommended, which was associated with prior mammography uptake . Counselees’ post-counseling overestimation of their risk, high levels of worry and high surveillance uptake were not reflected in their reactions to the counselor’s information during the final visit.We studied counselees’ expressed understanding of the risk estimate and surveillance recommendation in the final consultation for breast cancer genetic counseling in relation with their risk perception, worry and cancer surveillance adherence 1 year post-counseling. Consecutive counselees were included from 2008 to 2010. Counselees with an indication for diagnostic DNA-testing for themselves or a breast cancer affected relative were requested to complete online questionnaires before and after counseling and one year after counseling (The online version of this article (doi:10.1007/s10897-015-9869-x) contains supplementary material, which is available to authorized users. Breast cancer genetic counseling aims to promote informed decision making concerning surveillance of those at increased risk of (hereditary) breast cancer  , resident in clinical genetics (n = 5), genetic counselor (n = 3) or genetic counselor in training (n = 3). Most were female .All 14 counselors performing breast cancer genetic counseling consultations at the department participated and counseled 2 to 25 counselees each. Counselors were clinical geneticist  history was derived from the medical file if missing. Two missing values on education were imputed with the median. The breast cancer disease status (affected/unaffected), referral pathway , indication for DNA-test and test uptake were derived from the medical file. Counselors rated the counselees’ risk to (re-)develop breast cancer in the future on a scale from 0 to 100 % in this questionnaire. Their estimation was based on the Claus tables and the Claus extended formula develop breast cancer in the future and this risk for their first degree female relatives (FDFR) on visual analogue scales from 0 to 100 %. Risk perception was defined as aligned if the counselee and counselor estimates were within the same risk category . This measure was chosen because the recommendation for surveillance is based on these risk categories  in the past year. The answer categories were: no, less than once a month, monthly, weekly, daily, and not applicable because of risk reducing breast surgery  with any of the outcome variables. Counselees were nested within counselors. Analyses were performed with Stata 11.A variable was created for whether a counselee had uttered at least one clear understanding of the risk estimate or a statement of concordant risk perception (yes/no). Associations with risk perception alignment, breast cancer worry and adherence to breast surveillance recommendations were explored with Chi-square tests. Associations between prior mammography uptake and adherence and prior breast self-examination (BSE) uptake and post counseling BSE uptake were explored with Chi-square tests. Additionally, adherence to breast surveillance recommendation was the dependent variable in a multilevel regression equation for unaffected counselees with a positive surveillance recommendation. This regression was also performed for unaffected counselees with a recommendation not to perform surveillance. In both regression equations the following dependent variables were determined a priori: past uptake, risk perception alignment, intention, whether a surveillance recommendation was discussed and intervention allocation. Intervention allocation had no significant association (Chin = 97) counselees had a follow-up consultation, and 65 counselees had a single consultation . Most preferred the visit not be videotaped . There were no significant differences between participants and decliners in age, disease status, family history of cancer and referral pathway. Most . Seven of these counselees had performed surveillance, and this was initiated because of increased risk.All possible expressions of an intention were discussed by HD and the first author (AA). For 74 final visits the level of agreement was coded by two coders independently. The percentage of agreement between the raters for whether the counselee had expressed clear understanding varied from 70 to 85 %, for whether the counselee had expressed understanding agreement ranged from 75 to 91 %, and for misunderstanding it ranged from 83 to 96 %. When the coders did not agree, they discussed the response and again viewed the video, if needed, to reach consensus.understanding of the risk estimate. Twenty-five counselees expressed something about their view on their risk perception in the consultation. For four of them, their expressed view signaled a misunderstanding or unexpectedness of the risk estimate given by the counselor; for the others their view signaled understanding of the estimate (not in Table). Four of the five counselees who had uttered a misunderstanding of their risk estimate or a discordant risk perception had misaligned risk perceptions 1 year post-counseling.Twenty-three counselees had not received a personal breast cancer risk estimate in their final consultation  counselees expressed a surveillance intention . Most unaffected counselees (55.1 %) overestimated their risk. More than one-third of the affected counselees (35.0 %) overestimated the risk for their FDFR. Having received a personal risk estimate in the final visit was not significantly related to the risk perception alignment for themselves . Also, there was no significant association between the utterance of a clear understanding or concordant risk perception in the visit and the alignment of risk perception post-visit .Immediately post-counseling about half of the unaffected counselees (48.6 %) accurately perceived their breast cancer worry had lowered from pre- to post-counseling  and from pre- to 1 year post-counseling . Their breast cancer worry was not significantly associated with expressed understanding of the risk estimate at any of the time points.Counselees’ BSE  and 1 year post-counseling the uptake was higher than pre-counseling .Less than one-tenth of the breast cancer unaffected counselees performed more than monthly SE Table . Of the mammogram in the year before their first consultation . Post counseling almost all unaffected counselees  intended to have a mammogram/MRI if this was indicated. One year after the final consultation, almost three quarters of breast cancer unaffected counselees (74 %) adhered to the genetic counselor’s recommendation (Table n = 19) were younger than the recommended age to start mammography given their risk category. Others (n = 7) had an uptake of two instead of one mammograms/MRI scans in 1 year. Two counselees had not performed a mammogram/MRI scan while this was recommended. There were no significant differences in adherence between the unaffected counselees who had received BRCA1/2 negative test result from their affected relative (n = 17) and those in whom no DNA-testing was performed in relatives (n = 49). No significant associations were found between expressed a clear understanding of the surveillance recommendation and adherence . In bivariate analysis, the overuse of surveillance of counselees with a negative surveillance recommendation was associated to prior mammography uptake . In the multilevel multivariate regression analysis, no significant associations with adherence were found.Almost half of the breast cancer unaffected counselees had a on Table . Of the This study is the first to explore counselees’ expressed understanding of the risk estimate and surveillance recommendation in the final consultation for breast cancer genetic counseling counselees. Most counselees responded affirmatively to the disclosure of their risk estimate and the surveillance recommendation. This might have given counselors the impression that the counselee perceived her risk in accordance with the estimate given and would follow-up on the surveillance recommendation. However, in line with earlier findings understanding in the final visit. Furthermore, surveillance intentions were scarcely expressed and included little information about the when, where and how of the intended behavior. This might have lead counselors to believe that the counselee intended to follow up on the surveillance recommendation. Hence, more explicit exploration of misunderstandings might be needed to explore intentions.The need for a more elaborate discussion about counselees’ risk perception in the final visit is underlined by a significant decrease in accurate risk perception in the year post counseling. This might indicate that counselees’ perception of their risk drifts further away from the risk estimate given by the genetic counselor. Studies with shorter follow-up periods did not find significant decreases in risk perception . Third, our questionnaire did not include questions about how a referral for mammography/MRI was obtained. However, as a large majority of the breast cancer unaffected counselees was referred to genetic counseling by their GP, we assumed that these counselees also obtained their referral for a mammogram from the GP. Finally, as only nine counselees expressed their intention, we lacked power to statistically explore an association with adherence.This study showed that counselees’ risk perceptions and surveillance intentions are infrequently discussed in the final visit for breast cancer genetic counseling in the Netherlands. More elaborate discussion of these issues could enable counselors to discuss the disadvantages of periodic mammography, such as radiation risks and lack of sensitivity in young women. This might enable counselees to make a more informed decision. Moreover, motivational interviewing techniques could help counselors to discuss counselees’ motivation and intentions ESM 2(DOC 29 kb)ESM 3(DOC 27 kb)Below is the link to the electronic supplementary material.


Paradoxically, a breast cancer risk reduction with conjugated equine estrogens (CEE) and a risk elevation with CEE plus medroxyprogesterone acetate (CEE + MPA) were observed in the Women’s Health Initiative (WHI) randomized controlled trials. The effects of hormone therapy on serum sex hormone levels, and on the association between baseline sex hormones and disease risk, may help explain these divergent breast cancer findings.Serum sex hormone concentrations were measured for 348 breast cancer cases in the CEE + MPA trial and for 235 cases in the CEE trial along with corresponding pair-matched controls, nested within the WHI trials of healthy postmenopausal women. Association and mediation analyses, to examine the extent to which sex hormone levels and changes can explain the breast cancer findings, were conducted using logistic regression.Following CEE treatment, breast cancer risk was associated with higher concentrations of baseline serum estrogens, and with lower concentrations of sex hormone binding globulin. However, following CEE + MPA, there was no association of breast cancer risk with baseline sex hormone levels. The sex hormone changes from baseline to year 1 provided an explanation for much of the reduced breast cancer risk with CEE. Specifically, the treatment odds ratio  increased from 0.71  to 0.92  when the year 1 measures were included in the logistic regression analysis. In comparison, the CEE + MPA odds ratio was essentially unchanged when these year 1 measures were included.Breast cancer risk remains low following CEE use among women having favorable baseline sex hormone profiles, but CEE + MPA evidently produces a breast cancer risk for all women similar to that for women having an unfavorable baseline sex hormone profile. These patterns could reflect breast ductal epithelial cell stimulation by CEE + MPA that is substantially avoided with CEE, in conjunction with relatively more favorable effects of either regimen following a sustained period of estrogen deprivation. These findings may have implications for other hormone therapy formulations and routes of delivery.NCT00000611.clinicaltrials.gov identifier: The Women’s Health Initiative (WHI) randomized, placebo-controlled postmenopausal hormone therapy (HT) trials were instrumental in leading to changes in clinical practice, including much reduced use of HT in the U.S. and around the world. Among the most important reasons for this change was the substantial elevation in breast cancer risk-4 among et al.[Considerable effort has been devoted to understanding these divergent breast cancer findings, through investigation of hazard ratio (HR) variations among trial cohort subsets,6 and thet al.. A recenet al..Serum sex hormone concentrations changed markedly following CEE or CEE + MPA administration in the WHI trial cohorts, with an approximate doubling of estradiol, estrone sulphate and sex hormone binding globulin (SHBG), and an approximate tripling of estrone with active treatment in each trial. A recenHere we follow-up on this intriguing observation by examining the association between baseline serum sex hormones in the CEE + MPA and CEE trials and breast cancer risk, separately in the active treatment and placebo groups, during the intervention phases of the WHI trials. Concurrent associations of sex hormone changes from baseline to one year following randomization are also considered, and mediation analyses are conducted to examine the extent to which sex hormone changes can provide an explanation for the breast cancer findings in the two WHI trials.The design of the WHI Clinical Trial (CT) and corresponding baseline enrollee characteristics have been presented,15. All Women were excluded from the HT trials for breast cancer or other prior cancer (except non-melanoma skin cancer) within the past 10 years, baseline mammogram or clinical breast exam suggestive of cancer, or predicted survival of less than three years.Women having ongoing or recent HT use at screening required a three-month washout period before becoming eligible.The CEE + MPA trial intervention phase stopped early in July 2002, following an average of 5.6 years of intervention, when it was judged that health risks exceeded benefits. An elevation in breast cancer risk, in conjunction with an unfavorable global health risk versus benefit index, was key to the early stopping decision. The CEEClinical outcomes were repAll women provided written informed consent for their various components of WHI participation, and for their participation in the postmenopausal hormone therapy randomized controlled trials. The protocol and informed consent documents and procedures were approved by the Institutional Review Board (IRB) of the Fred Hutchinson Cancer Research Center, and by the IRBs of each of the participating clinical centers. All research was conducted in compliance with the Helsinki Declaration.There were 348 and 235 (invasive) breast cancer cases having sufficient serum for sex hormone analyses during the intervention phases of the CEE + MPA and CEE trials, respectively. Each was matched to a control from the same trial cohort who was without breast cancer during the trial intervention phase, on age at screening (within one year), race  and date of randomization (within 30 days).Blood samples were collected at baseline and year 1 after an overnight fast of at least 12 hours. SpecimeTotal estradiol and estrone concentrations were quantified by radioimmunoassays (RIA) using methods previously\described. EstroneSplit sample quality control specimens, derived from women who were screened for WHI participation but did not enroll, were included in each assay batch. There were 60 such samples selected for the baseline hormone assays, and 60 for the year 1 assays in this case-control study. The quality control specimens revealed substantial variations between blind duplicate samples for a small fraction of pairs, particularly at low concentrations. However, the intra-assay coefficients of variation for the various assays were acceptable, and ranged from 4.2% to 13.4%, after excluding outliers that had differences between duplicates following log-transformation that exceeded twice the interquartile range (IQR). The assay sensitivities for estradiol, estrone, estrone sulfate and SHBG were 2, 4 and 50 pg/ml, and 1 Nmol/L, respectively.Study subjects were excluded from analyses for each analyte if one or both of the baseline and year 1 assessments did not yield a measurement. The number of individuals excluded in the CEE + MPA trial was 49 for estradiol, 61 for bioavailable estradiol, 49 for estrone, 105 for estrone sulfate and 46 for SHBG. The corresponding numbers for the CEE trial were 35, 43, 33, 85 and 36.th to 75th percentiles of the data by more than twice the IQR, separately by trial and randomization group.Serum hormone measurements were log-transformed to achieve approximate normal distributions. In response to the split sample blind duplicate data mentioned above, cases or controls were excluded for a specific analyte if the logarithm of the ratio of one-year to baseline values was outside of the 25OR modeling relied on logistic regression with case (1) or control (0) defining the binary ‘response’ variable. Odds raP-values) are two-sided.Nominal 95% CIs are presented for odds ratios, and all significance levels  led to the further exclusion of the following number of placebo cases or controls in the CEE + MPA trial: estradiol - 20, bioavailable estradiol - 25, estrone - 25, estrone sulfate - 28, SHBG - 21. Corresponding numbers in the active treatment group in the CEE + MPA trial were 11, 19, 11, 7 and 10; with the smaller number of exclusions consistent with the notion that measurement reliability is primarily an issue at low concentrations. The corresponding numbers of cases or controls excluded from the CEE trial placebo group on the basis of this IQR criterion were 31, 30, 17, 16 and 31, and from the CEE trial active treatment group were 9, 10, 5, 10 and 3.Tables Table Table These analyses provide insight into the divergent breast cancer findings with CEE + MPA versus CEE in the WHI randomized, controlled trials. Specifically, women at a relatively low baseline breast cancer risk in the CEE trial continue at low risk if assigned to active treatment. Furthermore, the configuration of sex hormone changes among women assigned to active CEE provides an explanation for much of the observed breast cancer risk reduction Table .In sharp contrast, there is no evidence for any association between baseline sex hormone levels and breast cancer risk among women assigned to active treatment in the CEE + MPA trial, whereas associations are apparent in the placebo group Table . MoreoveThe analyses presented here excluded about 10 to 15% of placebo group, and about 5% of active treatment group cases and controls based on an IQR outlier criterion as applied to the differences between baseline and one-year log-analyte concentrations. These exclusion rates are consistent with a poor correspondence between split sample quality control specimens for about 10% of samples, especially at low sex hormone concentrations. To ensure that our outlier exclusion method was not unduly influencing results, the Tables The mechanisms whereby MPA would have such a dominant effect on breast cancer risk remain to be elucidated. MPA is a potent progestin with high affinity for progesterone and androgen receptors, and with little estrogen receptor affinity. It circulates in a form that is 88% bound to albumin, and is not bound by SHBG. MPA couThe analyses presented here suggest that the collective changes in sex hormones with CEE contribute strongly to the observed breast cancer risk reduction-7 in theP = 0.03) breast cancer risk. This observation could align with the intriguing hypothesis that estrogen exposure following a sufficient period of estrogen deprivation induces apoptosis of nascent breast tumor cells[The detailed analyses shown in the lower portion of Table or cells. Note, hThe strengths of this study are the randomized, controlled design of the WHI hormone therapy trials of adequate size, the quality sex hormone data assessment, and the ability to study CEE and CEE + MPA results side-by-side. Weaknesses include the absence of measurements on the biological changes resulting from the use of MPA.In summary, post-treatment changes in serum estrogens and SHBG concentrations, or changes in the association of such concentrations with disease risk, have the potential to substantially explain both the elevation in breast cancer risk with CEE + MPA and the reduction in risk with CEE. The CEE data suggest that a roughly two-fold increase in SHBG may offset risk that may otherwise attend corresponding major serum estrogen increases, and also support the observation that estBMI: body mass index; CEE: conjugated equine estrogens; CEE + MPA: CEE plus medroxyprogesterone acetate; CI: confidence interval; CT: clinical trial; HR: hazard ratio; HT: hormone therapy; IQR: interquartile range; IRB: Institutional Review Board; OR: odds ratio; SHBG: sex hormone binding globulin; WHI: Women’s Health Initiative.The authors declare that they have no competing interests.RC, GA, LK, JM, MG, RP (Patterson), DL, SB, JR and RLP (Prentice) were lead investigators from early in the WHI, and were active in the conception and design of the HT trials. These authors, as well as SZ, TR and SL, were actively involved in the analysis and interpretation of data for the present work. SZ and RLP developed an initial draft of the manuscript, and SZ was the principal data analyst. All authors  participated in critical revisions leading to the present version. All authors read and approved the final version of the manuscript.


Since targeting oxidative stress markers has been recently recognized as a novel therapeutic target in cancer, it is interesting to investigate whether genetic susceptibility may modify oxidative stress response in cancer. The aim of this study was to elucidate whether genetic polymorphism in the antioxidant enzymes is associated with lipid peroxidation in breast cancer.GPX1 (rs1050450), GPX4 (rs713041), SOD2 (rs4880), SEPP1 (rs3877899) and SEP15 (rs5859), lipid peroxidation, the activities of antioxidant enzymes determined in blood compartments as well as plasma concentration of selenium – an antioxidant trace element involved in cancer. Genotyping was performed using the Real Time PCR. Lipid peroxidation was expressed as plasma concentration of thiobarbituric acid reactive substances (TBARS) and measured with the spectrofluorometric method. Glutathione peroxidase activity was spectrophotometrically determined in erythrocytes (GPx1) and plasma (GPx3) by the use of Paglia and Valentine method. Spectrophotometric methods were employed to measure activity of cytosolic superoxide dismutase (SOD1) in erythrocytes (Beauchamp and Fridovich method) and ceruloplasmin (Cp) in plasma (Sunderman and Nomoto method). Plasma selenium concentration was determined using graphite furnace atomic absorption spectrophotometry.We conducted a study among Polish women, including 136 breast cancer cases and 183 healthy controls. The analysis included genetic polymorphisms in five redox related genes: GPX1 rs1050450 (Pro198Leu) polymorphism, showing a protective effect of variant (Leu) allele. As compared to the control subjects, lipid peroxidation and GPx1 activity were significantly higher in the breast cancer cases, whereas ceruloplasmin activity was decreased. After genotype stratification, both GPx1 activity and TBARS concentration were the highest in GPX1 Pro/Pro homozygotes affected by breast cancer. At the same time, there was a significant correlation between the level of lipid peroxidation and GPx1 activity among the cancer subjects possessing GPX1 Pro/Pro genotype , whereas such a correlation was completely absent in the cases carrying at least one GPX1 Leu allele as well as in the controls (regardless of GPX1 genotype).Breast cancer risk was significantly associated with GPX1 polymorphism may be an important factor modifying oxidative stress response in breast cancer subjects. Further studies are needed to elucidate its potential clinical significance.The online version of this article (doi:10.1186/s12885-015-1680-4) contains supplementary material, which is available to authorized users. BRCA1 and BRCA2 mutations) [Breast cancer is a multifactorial and a complex disease, with a major etiological contribution of hormonal origin and about 5–10 % of risk attributable to the inherited genetic factors (mainly associated with tations) ) are maitations) , 5.Since breast cancer is largely associated with lipid peroxidation, it may be hypothesized that the disease progression or response to treatment may highly rely on patient’s individual ability to scavenge either lipid peroxidation products or reactive species that lead to lipid oxidation . The interesting issue to be explored under this approach is whether genetic susceptibility associated with antioxidant system, may modify the prooxidative effects in breast cancer subjects. It is well known, that some genetic variations present in the antioxidant enzymes modify their activity or function, which may result in the altered ability to scavenge ROS . These aNatural antioxidant defense consists of many enzymatic and nonenzymatic systems that act in concert with dietary antioxidants . Most imEndogenous antioxidant system is supported by exogenous factors derived from diet (like vitamins and trace elements) and the element which probably gained most of scientific interest in terms of its antioxidant properties, is selenium (Se). Many experimental and epidemiological findings suggest significant role of Se in cancer, notably both in its prevention and promotion, though neither one nor the other mechanism is yet fully understood , 15. It GPX1, GPX4, SEPP1, SEP15  and SOD2 (encoding SOD2).The aim of this study was to investigate the overall relationship between lipid peroxidation, markers of antioxidant system and individual genetic susceptibility linked to antioxidant response in breast cancer subjects. Lipid peroxidation was measured as plasma concentration of thiobarbituric acid-reactive substances (TBARS). Markers of antioxidant system comprised the activity of the antioxidant enzymes in blood compartments  and plasma concentration of Se. Polymorphic genes  were collected using individual questionnaires, whereas clinical data  were obtained from medical records. The controls were selected from the population of the cross sectional study of nurses and midwives  who underwent mammography screening in the course of another study . A detaiBlood samples (7.5 mL) were collected into heparinized test tubes free from trace elements and separated by centrifugation into buffy coat (for DNA isolation), plasma and erythrocytes. Each fraction was stored at – 20 °C until analysis. Before freezing, erythrocytes were washed three times in isotonic saline and hemolysates were prepared followed freezing and thawing two times.DNA was isolated from buffy coat, using the QIAamp DNA Blood Mini Kit  according to the manufacturer’s instructions. DNA purity and quantity were determined with a spectrophotometer  at a wave length of 260 and 280 nm.GPX4 (rs713041), SEPP1 (rs3877899) and SOD2 (rs4880), we identified SNPs using Taqman® SNP Genotyping Assays  and Taqman Genotyping Master Mix . PCR reactions were carried out with 10 ng of DNA in a final volume of 10 μL, under following conditions: 10 min at 95 °C enzyme activation and 50 two-step cycles of denaturation at 95 °C for 15 s and annealing at 60 °C for 1 min. For genes: GPX1 (rs1050450) and SEP15 (rs5859), we employed the High Resolution Melt Curve technique. Oligonucleotide sequences for PCR primers, designed by Beacon Designer™ , were as follows: 5′-GCCGCTTCCAGACCATTG-3′ (forward) and 5′-GGTGTTCCTCCCTCGTAG-3′ (reverse) for GPX1, 5′-TTGCGTTAATGAAGACTACACAG-3′ (forward) and 5′-AAACATGAAAGAACAAACCAGAAG-3′ (reverse) for SEP15. The Real-time PCR was performed in 20 μL volume, in the presence of 20 ng of genomic DNA, primers (0.5 μM each each), SsoFast™ EvaGreen® Supermix  and nuclease-free water. The reaction protocol for both genes included enzyme activation at 98 °C for 3 min, followed by 40 two-step cycles of denaturation at 98 °C for 5 s and annealing at 57 °C (for GPX1) or 60 °C (for SEP15) for 10 s. The protocol for melting curve analysis, performed immediately after the PCR, included initial DNA denaturation at 95 °C for 1 min, followed by 150 two-step cycles: DNA renaturation at 65 °C for 1 min and DNA denaturation with the 0.2 temperature increment in each cycle (from 65 °C to 95 °C in the last cycle). Data analysis was performed using the Bio-Rad CFX Manager and the Bio-Rad Precision Melt Analysis Software. Particular genotypes for GPX1 and SEP15 were identified on the basis of PCR-RFLP method, using following restriction enzymes: DDeI  fo GPX1 and FspBI  for SEP15. Oligonucleotide sequences for PCR primers were: GPX1 forward 5′-ACCCTCTCTTCGCCTTCC-3′, GPX1 reverse 5′AGGACCAGCACCCATCTC-3′, SEP15 forward 5′– GCCTGCTCCTCAGAGTCTC –3′ and SEP15 reverse 5′–AAACATGAAAGAACAAACCAGAAG–3′. Digestion products were 158 bp, 232bo, 390 bp for GPX1 and 360 bp, 198 bp, 162 bp for SEP15. Accuracy of Real Time PCR genotyping was checked by retyping and randomly selected samples (15 % form cases and controls). The compatibility of the results was 100 %.Allelic discrimination was performed using the Real Time PCR method and the CFX96™ Real Time PCR Detection System . For genes: BRCA1 mutations, which are most frequently observed among Polish population i.e.,: 5382insC and T300G (C61G) [DDeI  for 5382insC and TaaI  for T300G mutation, according to the conditions described by suppliers. Digestion products were analyzed using electrophoretic technique in 2 % (w/v) agarose gel. Fragments’ length and interpretation of the results is indicated in Additional file To exclude hereditary cancer cases attributed to mutations in high penetrance genes, we conducted genotyping for the two G C61G) . Both muG . Both n = 8).Plasma TBARS concentration was determined by the use of a spectrofluorometric method . TBA-rean = 8) for GPx1 and 2.3 % (n = 7) for GPx3. The samples were analyzed in single measurements. The measurement was repeated whenever the value was out of the range.Activity of GPx1 and GPx3 was determined in erythrocytes (GPx1) and plasma (GPx3) using the method of Paglia and Valentine  with t-bn = 8).Activity of SOD1 was determined in erythrocytes by the use of the method of Beauchamp and Fridovich , which rp-phenylenediamine) as a substrate. Absorbance of the oxidation product was read in Unicam UV4 UV/Vis spectrophotometer , at a wavelength of λ = 535 nm. The activity of Cp was expressed as the amount of product formed per minute per 1 L of plasma. Intraassay variation (CV) was 4.7 % (n = 5).The oxidase activity of Cp was determined spectrophotometrically according to the method described by Sunderman and Nomoto , with a Plasma Se concentration was determined using the graphite furnace atomic absorption spectrophotometry with Zeeman background correction, in the Pye Unicam Solaar 989 QZ spectrophotometer . Lyophilized human serum containing selenium at a concentration of 78 ng/L  was used as a reference material for quality control and assurance. Additionally, the method was checked by participation in the interlaboratory comparison trials. Limit of detection for Se was 11 ng/mL and the precision calculated from 10 successive series of microelement determinations in the reference samples was 6.5 %.GPX1 x SOD2 and GPX1 x SEPP1 as suggested by literature data [p value less than 0.05.Normality for the data was evaluated with the Shapiro-Wilks test. The analysis of variance (ANOVA) or the Kruskal-Wallis test were used for the univariate analysis. Polymorphisms were entered individually into the ANCOVA model adjusting for clinical variables that could potentially affect the patient’s TBARS concentrations, including gene-disease interaction. Logistic regression analysis was used to evaluate the association of particular polymorphisms and their interactions with the disease status. Analysis of gene-gene interactions comprised ure data , 24. OthBRCA1 mutations.Epidemiological and clinical characteristics of the study subjects are presented in Table GPX1 (rs1050450), GPX4 (rs713041), SEPP1 (rs3877899), SEP15 (rs5859) and SOD2 (rs4880) genotypes in the study participants is presented in Table GPX1 rs1050450 polymorphism, for which carrying at least one variant allele (GPX1 Leu) was associated with a decreased risk of cancer both, in the univariate analysis and after adjustment for age, BMI, smoking status and menopausal status .Distribution of p = 0.0003 and p = 0.0036, respectively) were observed in the women suffering from breast cancer as compared to the controls, whereas there were no differences in GPx3 and SOD activity. Also plasma Se concentration did not differ between the cases and controls, and accounted for 55.2 μg/L and 57.0 μg/L, respectively. Ceruloplasmin activity was significantly lower in the cases as compared to the controls . Following that, we investigated whether this association would be linked directly through GPx1 activity. TBARS levels showed a positive correlation with GPx1 activity, which was close to statistical significance . Neither Cp , SOD1 , GPx3  activities nor Se concentration  showed such associations. However, we did not observe any direct associations between GPx1 activity and the GPX1 rs1050450 polymorphic allele presence in the univariate analysis (p = 0.2669) or after adjustment for age, BMI, smoking status and Se status , although Pro/Pro homozygotes with cancer showed GPx1 activity higher by 1.5–2.0 U/g Hb than all the other variants  but it was absent in the cancer patients who had one or two polymorphic GPX1 Leu alleles . This effect was completely absent in the Pro/Pro controls who obviously had the lowest range of both TBARS and GPx1  as well as in the controls positive for the Leu allele .Table us Table . ResultsThe role of lipid peroxidation in breast cancer remains not fully elucidated. The main focus of this study was to investigate whether lipid peroxidation in breast cancer subjects is associated with genetic polymorphism of antioxidant enzymes. In addition, we analyzed the risk of breast cancer in association with selected gene variants as well as with Se status.We observed a higher concentration of TBARS in plasma of the breast cancer cases as compared to the healthy women. This observation is consistent with the general observation of increased lipid peroxidation in breast cancer. Numerous studies have shown increased levels of different markers of lipid peroxidation  in plasma, serum, urine and also, in some cases, in cancer tissue of the women suffering from breast cancer –30. In oGPX1 rs1050450 polymorphism  [GPX1 polymorphism, being significant only among individuals carrying at least one Pro allele [GPX1 polymorphism on GPx1 activity in the whole group. However, the SNP effect seemed to be preserved among cancer cases, with Pro/Pro cancer homozygotes having the highest GPx1 activity as compared to other groups. Furthermore, only in this genotype group there was a significant and positive correlation between GPx1 activity and lipid peroxidation. This observation suggests that GPX1 rs1050450 polymorphism may actually determine not only the response of GPx1 activity to Se supplementation, but also its response to lipid peroxidation , at least in breast cancer subjects.Additionally, in our study we observed that TBARS concentration was associated with  (MCF-7) . In our o allele . In thisGPX1 polymorphism could have a potential role in breast cancer treatment. Notably it has been already observed that products of lipid peroxidation may modulate processes crucial in the breast cancer survival [GPX1 polymorphism may affect breast cancer treatment via modulating lipid peroxidation. It remains to be elucidated, which genotype would be more favorable in terms of a better therapy outcome. One could expect the individuals with GPX1 Pro/Pro to be less vulnerable to prooxidant effects of the treatment due to a higher antioxidant response under a permanent stress condition. The rationale for this assumption is supported by studies which indicated that increased GPx1 activity was associated with anticancer drug resistance [GPX1 polymorphism in modifying the response to anticancer therapy has already been suggested by Zhao et al. These authors conducted a prospective study on 224 patients with bladder cancer and observed that individuals possessing Pro/Pro genotype had shorter recurrence–free survival as compared to those with at least one variant (Leu) allele [n = 202) with a hazard ratio (HR) of 0.63; 95 % CI 0.42–0.96. Interestingly, after data stratification according to sex, the effect was preserved only among women. The authors of this study suggest that the unexpectedly observed protective effect of Leu allele may be explained by the fact that the patients with a reduced activity of ROS scavenging enzymes may have better prognosis after cancer treatment as most of the therapies  are based on ROS generation [Since lipid peroxidation products have been recently recognized as a therapeutic target in cancer, the possible relationship between lipid peroxidation and survival . Thus itsistance , 36. Pos) allele . A signineration .GPX1 rs1050450 polymorphism in this study. In this study we observed that carrying Leu variant was associated with a significant 40 % decrease in the risk  [GPX1 rs1050450 polymorphism are also inconsistent between each other, showing lack of any associations or the increased risk linked to the carriage of the variant allele [GPX1 polymorphism in the mentioned study by Meplan et al., has been restricted only to the non-ductal cancers [GPX1 polymorphism could occur by chance. However, it has been the first such a study regarding sporadic breast cancer risk and GPX1 polymorphism conducted among Polish women, and considering the fact that similar protective effect of GPX1 Leu variant has been found in Polish population also in the case of lung and laryngeal cancers [GPX4), rs3877899 (SEPP1), rs5859 (SEP15) and rs4880 (SOD2), we failed to find any associations with the breast cancer risk. Similarly, we did not observe any significant gene-gene interactions of potential interest as suggested by other studies, including GPX1 x SOD2 and GPX1 x SEPP1 [Breast cancer risk was significantly associated with sk Table . These f08–3.28) . The rest allele –41. Recet allele . Howevert allele . Notably cancers . Neverth cancers , the pren = 200) as compared to the healthy controls (n = 200), have concluded that altered Se status was a consequence rather than a cause of cancer [in vitro and in vivo observations, indicating for the regulatory activity of Se on estrogen receptors expression [In the study presented here, plasma Se concentration was relatively low  and cannot rule out that the observed associations were not influenced by potential confounding factors, not controlled for in the study (as for example diet or supplements use). Nevertheless, both groups were residents of the same area, and were not different in terms of age, BMI, smoking status and menopausal status. It should be also appreciated that all the subjects enrolled in the control group had negative screening mammograms and this information was crucial in the assessment of biochemical processes linked to breast cancer. Another weakness of the study concerns relatively small sample size, which limited the possibility to include more potentially important modifiers of both GPx1 activity and TBARS levels, such as for example ER status. Finally, this study lacked data on patients’ survival, which obviously would give further insights into the clinical significance of the observed association between lipid peroxidation and GPX1 polymorphism may be an important factor that modifies oxidative stress response in breast cancer. The potential link may have great significance in terms of potential implication in tumor progression or treatment thus these findings, if replicated elsewhere, require further investigation.Up to date, no studies have been conducted on the association between individual genetic background and markers of prooxidative effects in breast cancer. The results of this study suggest that