Background. To evaluate whether insulin use was predictive for mortality from breast cancer in Taiwanese women with diabetes mellitus. Methods. A total of 48,880 diabetic women were followed up to determine the mortality from breast cancer during 1995–2006. Cox models were used, considering the following independent variables: age, sex, diabetes type, diabetes duration, body mass index, smoking, insulin use, and area of residence. Insulin use was also considered for its duration of use at cutoffs of 3 years and 5 years. Results. Age was a significant predictor in all analyses. The multivariable-adjusted hazard ratio  for insulin use without considering the duration of use was not statistically significant . Compared with nonusers, insulin users showed the following adjusted hazard ratios for insulin use <3 years, ≥3 years, <5 years, and ≥5 years: 0.567 , 2.006 , 1.045 , and 1.899 . Conclusions. Insulin use (mainly human insulin) for ≥3 years may be associated with a higher risk of breast cancer mortality. Patients with diabetes may suffer from a higher risk of cancer involving the liver, pancreas, endometrium, colorectum, bladder, and breasts . The useIn addition to its metabolic effect, insulin has mitogenic properties and can regulate cell proliferation, differentiation, and apoptosis . StudiesBecause the prevalence of diabetes is increasing and insulin is used to treat millions of diabetic patients, it is clinically important to clarify the effects of insulin use on the risk for breast cancer. Therefore, this study evaluated whether the use of insulin in a nationally representative cohort of female patients with diabetes in Taiwan increased the risk of mortality due to breast cancer, over a 12-year period of followup.n = 128,572), and among them, 93,484 (72.7%) were successfully interviewed by well-trained interviewers. Verbal informed consent from the participants was given after the purpose of the research was explained to them, and they were informed that the study was conducted under the approval of the Department of Health. Written informed consent was not obtained because it was not a necessary requirement for telephone questionnaire interviews, according to local regulations, at the time when the study was approved and the interviews were conducted.Since March 1995, a compulsory and universal National Health Insurance program was implemented in Taiwan, which encompassed >96% of the entire population of Taiwan. The establishment of a cohort of diabetic patients with a structured baseline questionnaire using the National Health Insurance for long-term followup by telephone interview was approved by an ethics committee of the Department of Health, Executive Yuan, Taiwan. The detailed processes for the establishment of the study cohort, the compilation of data, and the questionnaire interview were described previously . In brieThe interviewers submitted the questionnaires every week, and all returned questionnaires were checked for internal consistency by an assistant and then again by the investigator (C.-H. T.). The information obtained during the interview included demographic data, self-reported height and weight, ethnic background of both parents , history of lower-extremity amputation, initial symptoms or clinical events that led to the diagnosis of diabetes, current treatment of diabetes, history of smoking and use of betel nut, hypertension, family history of diabetes and hypertension, and area of residence.The following variables were abstracted for analysis in the present study: age, diabetes duration, diabetes type (diagnosis of type 1 diabetes mellitus was based on a history of diabetic ketoacidosis at diabetes onset or the need for insulin injection within 1 year after diabetes diagnosis), body mass index , smoking, insulin use, and area or residence.In Taiwan, every resident has a unique identification number, and events such as birth, death, marriage, and migration should be registered in the household registration offices. The data included on the death certificates, including the unique identification number, date of birth, sex, and date and cause of death, have been computerized since 1971 and can be used for academic research. Since 1981, causes of death have been coded according to the ninth revision of the International Classification of Diseases in Taiwan. The code for death due to breast cancer is 174.All patients were followed until December 31, 2006. The dates and causes of death for those who died were obtained by matching with the national death certificate database. A total of 171 patients died of breast cancer, and among them, only 5 had type 1 diabetes mellitus .The Cox proportional hazards model was used to evaluate the risk factors associated with breast cancer mortality in the whole cohort, in which breast cancer mortality was the dependent variable and the independent variables included age, diabetes type (type 2 or type 1), diabetes duration, body mass index, smoking (yes or no), insulin use (yes or no), and area of residence . The area of residence was defined as urban for the Metropolitan Taipei area (including Taipei city and Taipei county) and other administratively named cities across Taiwan and as rural for administratively named counties and offshore islands. Sensitivity analyses for the abovementioned Cox regression model were also created after excluding patients who died of breast cancer within 3 years, 5 years, and 7 years of diabetes onset, respectively, to minimize the possibility that diabetes may be caused by incipient breast cancer or may occur after the diagnosis of breast cancer.To further examine whether the risk of breast cancer mortality might vary with the duration of insulin use, Cox models were also created by comparing insulin use for <3 years and ≥3 years to nonuse and that for <5 years and ≥5 years to nonuse, after adjustment for all covariates in the whole cohort . Additional fully adjusted models were created for various causes of mortality as dependent variables to examine whether the association between duration of insulin use might differ for different causes of mortality. The following causes of mortality were evaluated: all-cause, all-noncancer, all-cancer, and all cancer other than breast cancer. For breast cancer mortality, additional models were created for estimating hazard ratios and their 95% confidence intervals for insulin use for ≥3 (or ≥5) years versus nonuse/use for <3 (or <5) years.Because insulin use is highly dependent on the duration of diabetes, residual confounding effect from diabetes duration might not be completely excluded in the abovementioned analyses of the whole cohort. To completely exclude such a residual confounding effect, additional analyses were conducted in a subgroup of patients comprised of all cases of breast cancer mortality plus a group of randomly selected patients without breast cancer mortality, matched by diabetes duration, with a ratio of 1 : 5. These analyses estimated the adjusted hazard ratios and their 95% confidence intervals for insulin use for <3 (or <5) years and ≥3 (or ≥5) years as compared to nonuse and insulin use for ≥3 (or ≥5) years as compared to nonuse/use <3 (or <5) years.P < 0.05 was considered statistically significant.Analyses were conducted using the SAS statistical software, version 9.3 . n = 171) and those who did not die  of breast cancer. Patients who died of breast cancer had significantly older age, with a higher proportion aged ≥65 years (48.5% versus 39.9%), and a higher proportion of living in urban areas (55.0% versus 45.9%). In addition, in these women, mean diabetes duration was longer (8.5 years versus 7.5 years) but with borderline significance (P = 0.0706). The other variables, including use of insulin, diabetes type, body mass index, and smoking, did not differ significantly between the 2 groups. For those who died of breast cancer and those who did not, the median duration of followup was 3.7 and 7.4 years, respectively, and the median duration of insulin use in insulin users in the 2 groups was 6.0 and 4.0 years, respectively. The median follow-up duration for insulin users and nonusers in the cohort was 7.3 years and 7.5 years, respectively.A total of 48,880 female patients were included in the present study .  Table P < 0.1). Insulin use was associated with a significantly higher risk of all-cause mortality and all-noncancer mortality, regardless of the duration of its use, and the magnitude of the hazard ratios was smaller with a longer duration of insulin use. On the other hand, the hazard ratios were all similar and not statistically significant for all-cancer mortality and all cancer other than breast cancer mortality. This was different from the disproportionately higher risk associated with insulin use for a longer duration of ≥3 years or ≥5 years for breast cancer mortality.The findings suggest that insulin use might be associated with a higher risk of breast cancer mortality if the duration of its use is ≥3 years . Such anIn previous European studies, the link between insulin use (including human insulin and insulin glargine) and cancer (including breast cancer) risk was not conclusive –20. As pStrengths of the present study included a complete ascertainment of vital status by confirming data with the national death certificate database. The consistency in different analyses  suggestsSome might still argue that an exposure to insulin treatment for 3 or 5 years was too short for the development of breast cancer and its progression to mortality. In clinical practice insulin is always used subsequently and thereafter once it is prescribed. Therefore, the actual duration of insulin exposure in those who died of breast cancer in the present study should include the exposure period at baseline plus the follow-up duration before breast cancer mortality. Because the median duration of followup among those who died of breast cancer was 3.7 years, these patients should have been exposed to exogenous insulin for at least 6 years or 8 years, respectively, for those who had received insulin treatment for 3 or 5 years at baseline.Another important issue regarding the plausibility is that since this study is essentially conducted in patients with type 2 diabetes mellitus, the hyperinsulinemia resulting from insulin resistance preceding the use of exogenous insulin might have exerted an adverse effect on the development of breast cancer. Therefore, the relatively short term effects of exogenous insulin could be explained by a preconditioning of long exposure to endogenous hyperinsulinemia as a result of insulin resistance since the prediabetes stage. Insulin receptors are expressed on breast epithelial cells and overexpressed on breast cancer cells . Thus, tIn clinical practice, it may be difficult to deliver the exact dosage of insulin to meet physiological requirements. Therefore, patients receiving exogenous insulin in the presence of insulin resistance may be repetitively exposed to high levels of insulin, which may trigger the mitogenic pathways leading to cancer in susceptible patients. Endogenous hyperinsulinemia resulting from insulin resistance is predictive for the development of and mortality from breast cancer –14. StudIt is worth mentioning that, at the time of enrollment of the diabetes cohort, insulin analogues were not yet available in Taiwan. No insulin analogues were in use in Taiwan before January 2004. Therefore, the findings of the present study on the link between insulin use (mainly human) and breast cancer mortality cannot be readily extrapolated to insulin analogues.Obesity is a well-recognized risk factor for breast cancer , 26 and  per se.Diabetes control and obesity are known to be associated with more advanced or aggressive breast cancer , 31–33. The analyses on the relationship between different durations of insulin use and different causes of mortality  might prStudy limitations included a lack of actual measurement of confounding factors such as age of menarche, menopause, use of hormone replacement therapy, concurrent use of metformin and other antidiabetic drugs, alcohol drinking, family history, lifestyle, dietary factors, and genetic parameters. Second, we did not have biochemical data such as hormonal profiles, blood glucose levels, hemoglobin A1C concentrations, insulin, C-peptide levels, or calculation of homeostasis model assessment for insulin resistance for evaluating their impact. Third, we were not able to evaluate the effects of insulin analogues  and the different types of insulin such as regular insulin or neutral protamine Hagedorn (because of the lack of information). Fourth, we studied the link between insulin use and breast cancer mortality rather than its incidence. Because mortality and incidence are different clinical entities and may be linked to different factors, whether insulin use is a risk factor for breast cancer incidence awaits further investigation. Fifth, data related to the following were lacking: features of breast cancer such as the pathology, staging, grading, tumor size, and nodal involvement at diagnosis; estrogen receptor status and other molecular features; administered therapy; response to therapy; and related outcomes of local or distant recurrence. Finally, it should be pointed out that a clear dose-response relationship could not be demonstrated in the present study because of the lack of information on the amount of insulin use for these patients.In summary, in a followup of a nationally representative cohort of female patients with diabetes, insulin use (mainly human insulin) for 3 years or more may be associated with breast cancer mortality, with a fully adjusted hazard ratio  of 2.006 (1.102–3.653). This study adds to the literature suggesting a link of insulin use to breast cancer mortality. Because of the limited numbers of breast cancer deaths and the lack of clear duration-risk relationship, future confirmation is required.


Although cancer promotes inflammation, the role of inflammation in tumor-genesis is less well established. The aim was to examine if low-grade inflammation is related to post-menopausal breast cancer risk, and if obesity modifies this association.st, 2010). In laboratory analyses of blood from 446 cases, and 885 controls (matched on age and date of blood sampling) we examined systemic inflammation markers: oxidized (ox)-LDL, interleukin (IL)-1β, IL-6, IL-8, tumor necrosis factor (TNF)-α, white blood cells, lymphocytes and neutrophils. Odds ratios (OR) and 95% confidence intervals (CI) for breast cancer risk was calculated using multivariable conditional logistic regression.In the Malmö Diet and Cancer cohort, a nested case-control study was defined among 8,513 women free of cancer and aged 55–73 years at baseline (1991–96); 459 were diagnosed with invasive breast cancer during follow-up : 0.65 (0.47–0.90), 0.63 (0.45–0.89) respectively, p-trend = 0.01; and for the 3rd tertile of TNF-α, 0.65 (0.43–0.99), p-trend = 0.04. In contrast, those in the highest IL-1β category had higher risk, 1.71 (1.05–2.79), p-trend = 0.01. Obesity did not modify associations between inflammation biomarkers and breast cancer.Inverse associations with breast cancer were seen in fully-adjusted models, for 2Our study does not suggest that low-grade inflammation increase the risk of post-menopausal breast cancer. According to the World Cancer Research Fund International, breast cancer is the commonest cancer in women worldwide, accounting for a total of 1.7 million new cases diagnosed in 2012 .It is accepted that low-grade inflammation is part of the pathogenesis of several chronic diseases such as cardiovascular diseases (CVD), type 2 diabetes mellitus, and of certain types of cancer –11. AlthObesity  is known to increase the risk of several cancers . ObesityExamples of inflammatory mediators are pro-inflammatory cytokines (such as tumor necrosis factor (TNF)-α, interleukin (IL)-1β, IL-6), chemokines, leptin and adiponectin. These potentially have important roles in the development of obesity associated breast cancer , 20. BreAlthough there is a great deal of evidence describing the influence of low-grade inflammation and specifically of cytokines in the promotion, angiogenesis, and metastasis of breast cancer –25 theirThe Malmö Diet and Cancer study (MDC) is a prospective population-based study. The baseline examinations took place between 1991 and 1996 in Malmö, Sweden. The source population invited to participate was all men and women born between 1923 and 1945 and women until 1950 . The cohort and the recruitment procedures details have been published elsewhere . The basin situ, were excluded. As a result a total of 8,513 women were considered for the study. Of these, 459 women were diagnosed with invasive breast cancer during follow-up (until 31st of December 2010).This nested case-control study includes women aged 55–73 years at baseline. The age criteria of inclusion (≥ 55 years) intended to minimize the probability of selecting pre-menopausal women. Women with other prevalent cancers, except cervix cancer Three controls per case  were randomly selected  and matched on age at baseline (±3 months) and date of blood sampling (±1 month). As additional requirements: controls had to be alive at the time of matching, living in Sweden and free of breast cancer. Plasma samples were available and laboratory analysis of the inflammation markers was successful in 446 cases, and in 910 controls. However, the analytical sample consisted of 446 cases and 885 controls, due to the conditional logistic regression procedure, which included only controls matched with the specific cases. Seven of the cases had only one control with successful laboratory analysis, and the remaining eighteen controls had been matched with cases excluded previous to statistical analysis due to unsuccessful laboratory analysis.st of December 2010. Women who were diagnosed with invasive breast cancer during follow-up were considered cases, and invasive breast cancer was defined as all cancers except in situ cancer. Information on vital status was obtained from the Swedish Cause of Death Register , and from the Total Population Register (of Statistics Sweden).Data on case definition was provided by the Swedish Cancer Registry and the Southern Swedish Regional Tumor Registry until the end of follow-up, 31Blood samples were drawn from the participants during their first visit to the study center (at baseline). The leukocyte counts were assessed at this point in time using fresh heparinized blood, and a SYSMEX K100 automatic counter  . LeukocyThe biochemical analyses of the other inflammation markers were conducted during the autumn of 2011. Plasma samples were thawed and the concentration of ox-LDL in plasma was analyzed with an ELISA , which is a capture ELISA using the mAb-4E6 antibody against a conformational epitope in oxidized ApoB-100, developed by Holvoet et al . The intnd of March 1991) to week 287 (on the 24th of September 1996). Based on the dates of measurement, the season  was noted. Trained nurses measured participants’ height (m), weight (kg) and hip and waist circumferences (cm), at the baseline examinations. Body Mass Index (BMI) was calculated dividing weight by the squared height (kg/m2) and categorized into under/normal weight, overweight and obese . Waist-to-hip ratio (WHR) was calculated by dividing the waist by the hip circumferences. It was further divided into tertiles and sextiles.Information on birthdate and gender were retrieved from the personal identification number, and age was calculated. The week of blood sampling refers to the screening date in the MDC study, and it ranges from week 0 . A four category variable described the consumption of alcohol. Zero consumers were participants who reported no alcohol consumption both in the general questionnaire and during the diet history assessment ; low consumers (<15 grams/day), medium (15–30 g/d) and high consumers (>30 g/d) were defined according to cut-offs based on a biological risk assumption .The questionnaire also assessed leisure time physical activity (PA) with a list of 18 different activities, which were adapted from Minnesota Leisure Time Physical Activity . An actiParticipants reported their age at menarche, age at menopause and age at the birth of the first child in the questionnaire. In addition, they also reported the number of months each child had been breastfed. The time span between age at menarche and age at menopause was computed. We then subtracted the interruptions caused by periods of pregnancies and lactation, and calculated the number of years with menstrual cycles.Parity was divided into 5 categories; nulliparous (no children), 1, 2, 3, and 4 or more children. Participants reported use (or not) of oral contraceptives (OC), as well as current use of menopausal hormone therapy (MHT). The information on MHT use was retrieved from a questionnaire item regarding medications used on a regular basis, and from the 7-day food record .The baseline characteristics of established risk factors were examined among cases and controls and differences were explored with odds ratios (OR) and 95% confidence intervals (CI) by using conditional logistic regression, in basic models (unadjusted). All significant factors were further introduced in the same model. When studying the baseline characteristics of the controls across tertiles of several inflammation markers, we used the chi-square test to calculate proportional differences in categorical variables, and the ANOVA to examine mean differences (for continuous variables).In order to address the skewedness of most biomarkers, levels were ranked into tertiles, or transformed logarithmically when necessary. Since the IL-1β variable included many zeros and values below the LLOD, this variable was classified into 4 categories containing: 0 values (n = 340); all values below LLOD except zeros (n = 640); and the values above LLOD (n = 351) were split into two categories above and below the median (0.40 pg/mL) of the distribution (n = 176 and n = 175). In order to enable ln-transformation of the IL-1β variable , a small value was added to this variable.We have examined the correlations between levels of inflammation markers (ln-transformed) and obesity/adiposity measures (BMI and WHR), adjusting for matching factors (age and week of blood sampling), among controls.We computed OR and 95% CI for breast cancer risk in tertiles of several biomarkers of inflammation such as ox-LDL, IL-1β, IL-6, IL-8, TNF-α, WBC, lymphocytes and neutrophils, using conditional logistic regression, and controlling for matching variables (age and week of blood sampling); model I. A second model was created adding BMI; model II. A third model included additional adjustments for established risk factors for breast cancer which were significantly associated with breast cancer in our project: hormonal factors  and abdominal obesity (WHR); model III. In addition, a final model also included possible lifestyle confounders such as smoking status, alcohol, physical activity, and education; model IV. The choice of confounders used in the models was guided by the literature, and by its significance in this study sample. We included all biomarkers significantly associated with breast cancer in the same model in order to assess independent risks. Conditional logistic regression models were successful in 446 cases and 885 corresponding controls.In sensitivity analysis we sequentially excluded women who were diagnosed during the first, second, and third years of follow-up. In an additional step, women with history of CVD (n = 27) and diabetes (n = 52) at baseline were excluded. We also examined if the season at the time of blood sample collection influenced the observed associations: the differences in the controls; the association between season and breast cancer risk; and evaluating if season influenced associations with inflammation markers. Finally, in an additional step all models were also adjusted for batch effect by adding plate number as a covariate in all models.We examined the potential interactions between the biomarker concentrations and measures of obesity/adiposity  by including interaction terms in the basic and fully-adjusted models predicting breast cancer risk, using unconditional logistic regression.ad hoc analysis including women with missing values for the MHT and parity variables in a separate category, including a total of 1300 women in the fully adjusted modelThe fully adjusted models included 1142 people in the analysis; 146 (11%) of the subjects had missing data in one or more of the covariates, and 68 cases were censored before earliest event in a stratum. In the MHT variable 8.3% (n = 110) had missing information, whereas in the parity 2.5% (n = 33) had missing information. Sixteen individuals had missing information for the PA variable, and all other variables were either complete or had missing only 1 to 4 people. In the MHT and parity variables, the proportion of case/controls was 1/2 and the missing cases were evenly distributed across categories of the other confounders. Thus, we performed complete case analysis. Additionally, we performed an p<0.05.All statistical analyses were performed with IBM SPSS Statistics (version 22.0), and all statistical tests were two-sided and significance level was set at Cases had higher WHR, tended to be more overweight or obese  and had The distribution of the matching factors and possible confounders across categories of the inflammation markers among controls are described in p<0.001). However, when adjusting for age, we still see a significant, but less pronounced, difference between week number across different categories of ox-LDL, IL-1β, and TNF-α. By design, the participants that joined the MDC study in the last 2 years of baseline measurements (1995–96) were older . When repeating all analyses excluding the older age group (>70 years), the results remained unchanged. Nevertheless, we adjusted for week of blood sampling in all analyses. Although WBC, lymphocytes and neutrophils were analyzed at baseline , these biomarkers also seemed to be affected by week of blood sampling  when adjusting for matching factors . Particist of follow-up (n = 45), and were slightly attenuated with the exclusion of 1st and 2nd (n = 64) year of follow-up. When excluding women diagnosed until the 3rd year of follow-up (n = 83), most associations with breast cancer were attenuated , but the magnitude of the estimates remained. Associations with IL-1β were no longer significant when excluding cases diagnosed during the first year of follow-up.Associations remained similar for ox-LDL and TNF-α when excluding those diagnosed within the 1When adding season to the models in sensitivity analysis, no changes in the estimates were seen. Season was also related to the year of the baseline examination; participants in the later 2 years (1995–96) were more likely to be measured during the fall or winter. Finally, when accounting for batch effect, results  remained virtually the same.ad hoc analysis, when labeling the missing values for MHT and parity as such and studying the association between inflammation markers and breast cancer risk for 1300 women, we observed that the associations in the highest category of IL-1β in models III and IV were no longer significant; 1.43 (0.94–2.19), 1.53 (0.98–2.37) respectively. However, the p-value for trend remained significant (0.04 and 0.02) as well as for category 1 of IL-1β, 1.61 (1.02–2.57). In addition, an inverse and significant association with breast cancer was observed for the second tertile of IL-6, 0.72 (0.53–0.98).In p = 0.57), ox-LDL x BMI (p = 0.63), IL-1β x WHR (p = 0.09), IL-1β x BMI (p = 0.79), TNF-α x WHR (p = 0.11), and TNF-α x BMI (p = 0.49).Interactions between obesity measures and biomarkers were examined with tertile variables entered as continuous variables in the fully adjusted model using unconditional logistic regression. Interactions were not significant; ox-LDL x WHR , is well powered and population based . We alsoWe analyzed several biomarkers, in order to obtain a broader view of inflammation in our study sample, and Ni H., et al., reported a significant reduction of total breast cancer risk  for higher levels of triglycerides and in subsequent sub-group analysis an inverse association was observed for higher levels of HDL . Touvier, M. and colleagues observed an inverse association between total cholesterol and the risk of breast cancer . However, in the current study we cannot exclude that other underlying mechanisms are the culprits for both the increased breast cancer risk, and lower levels of ox-LDL.Oxidized-LDL is a marker of oxidative stress –42, and p<0.001). TNF-α is a highly pleiotropic cytokine, and dual roles have been reported in carcinogenesis [TNF-α is produced by several cells such as macrophages, neutrophils, and lymphocytes. It is considered an acute phase reaction cytokine involved in systemic inflammation , and actogenesis , 25, 55.ogenesis . Additioogenesis . The fewogenesis , 59.st year of follow-up might be indicative of reverse causality. However, loss of power as an alternative possibility for the attenuated association cannot be excluded, since there is a significant reduction in size in the higher categories, due to the fact that 74% of the IL-1β levels were below LLOD; this is also a major limitation.The IL-1β was the only cytokine in our study where higher levels were associated with increased risk of post-menopausal breast cancer. It has a role in cell proliferation and differentiation, but an involvement of IL-1β in apoptosis has also been described . The preOne single measurement of these biomarkers was previously found to be highly reliable within a period of few months, in sub-samples drawn from the MDC cohort . HoweverIn order to obtain a clearer picture, future studies with continuous evaluation of the inflammation levels over a long period are required. It is probably easier to establish a relationship between inflammation and CVD, as disease progression is faster and inflammation biomarkers, such as C-reactive protein, are well established . The lacAnother factor that could have influenced our results is that systemic inflammation might not be as important as local inflammation, in the development of breast cancer. In fact, the release of inflammatory mediators, that will increase aromatase expression (and consequently the production of estrogens), takes place in the adipocytes close to the ducts of the breast tissue . This miWe did not observe any interaction between obesity/adiposity and the inflammation biomarkers in relation to breast cancer. Previous reports from the MDC cohort point to the importance of these obesity/adiposity measures in breast cancer risk , 68, butst to the 3rd years of follow up. When excluding women diagnosed within the first 3 years of follow up all associations were attenuated, but the magnitude of the estimates remained. This observation points to the loss of power, and, probably excludes the possibility for reverse causality for ox-LDL and TNF-α.It is accepted that cancer development and progression increase inflammation . Hence tIn breast tumors, which are estrogen responsive (ER+), inflammation could potentially contribute to the development of tumors through the induction of aromatase action . It is, In conclusion, our results do not support the hypothesis that low-grade systemic inflammation is associated with increased risk of post-menopausal breast cancer. According to the results demonstrated in this study, the association between breast cancer and inflammatory markers, and breast cancer and obesity indicators appear independent of each other. These observations prompt confirmation in larger studies with routine analyses of inflammation markers during longer periods, and also with information on different tumor types.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.


The aim of this study was to evaluate the association of diabetes and diabetes treatment with risk of postmenopausal breast cancer.N = 916) cancer were recruited from 23 Spanish public hospitals. Population-based controls (N = 1094) were randomly selected from primary care center lists within the catchment areas of the participant hospitals. ORs (95 % CI) were estimated using mixed-effects logistic regression models, using the recruitment center as a random effect term. Breast tumors were classified into hormone receptor positive (ER+ or PR+), HER2+ and triple negative (TN).Histologically confirmed incident cases of postmenopausal breast .Diabetes was not associated with the overall risk of breast cancer , and it was only linked to the risk of developing TN tumors: Among 91 women with TN tumors, 18.7 % were diabetic, while the corresponding figure among controls was 9.9 % . Regarding treatment, results showed that insulin use was more prevalent among diabetic cases (2.5 %) as compared to diabetic controls (0.7 %); OR 2.98; 95 % CI 1.26–7.01. They also showed that, among diabetics, the risk of developing HR+/HER2− tumors decreased with longer metformin use (ORThis study reinforces the need to correctly classify breast cancers when studying their association with diabetes. Given the low survival rates in women diagnosed with TN breast tumors and the potential impact of diabetes control on breast cancer prevention, more studies are needed to better characterize this association. Diabetes mellitus and cancer are two leading causes of death and disability worldwide. In Europe alone, by 2011 there were around 52.6 million people with diabetes, and 10 % of deaths in adults were attributed to this disease [Substantial evidence supports that type 2 diabetes is a risk factor for the development of numerous types of cancer, including those of the pancreas, liver, stomach, colorectum, kidney, bladder, postmenopausal breast and endometrium . Still, There is epidemiological evidence showing that the association between breast cancer and its risk factors vary according to the expression of tumor receptors. However, few previous reports have explored the possible role of diabetes on specific breast cancer subtypes . The objMCC is a population-based multicase–control study in Spain. Incidence cases of histologically confirmed breast tumors were recruited from 23 Spanish public hospitals from 2008 to 2013. Inclusion criteria required that cases had lived for at least 6 months in the same study area and were 20–85 years of age. Age- and region-matched population controls were randomly selected from primary care center lists. Response rates were 71 % for breast cancer and 72 % for controls, with no differences in the main socio-demographic variables among those who participated and those who refused to participate. All participants who agreed to participate signed an informed consent, and the study was formally approved by the corresponding ethics committee of each area. The MCC-Spain study also followed the Declaration of Helsinki and the Spanish Personal Data Protection Act of 1999.Both cases and controls were interviewed by trained personnel, collecting data on socio-demographic factors, health behaviors, gynecologic/obstetric history, preexisting medical conditions, treatments received and family history of cancer. Waist and hip circumferences were measured at the time of the interview.N = 1018) and their matched controls (N = 1243). We then excluded women with lack of information on diabetes status (N = 43 women) and, in order to reduce the probability of including type 1 diabetic individuals as exposed, women who had been diagnosed of diabetes before the age of 45 (N = 19 women). To allow for a minimum latency period and to avoid that the clinical conditions that lead to diabetes and cancer diagnosis could overlap, we also excluded women who had been diagnosed of diabetes ≤1 year before the diagnosis of cancer . Finally, to obtain effect estimators adjusted by BMI, we excluded 177 women with missing values, leading to a final sample of 916 cases/1094 controls. In a sensitivity analysis, we included these participants and imputed their BMI to check the consistency of our results (data not shown).In the present study, we initially included all cases of postmenopausal breast cancer  were censored to 1 year prior to the interview.Self-reported diabetic drugs were classified according to the Anatomical Therapeutic Chemical Classification System of the World Health Organization. Because the number of participants per subgroup was small, only two main categories are considered for this report: A10A  and A10B . In accordance with this, diabetic participants were classified into three groups if they had ever received this treatment for at least 1 year: (1) conservative therapy, (2) treatment with blood glucose-lowering drugs and (3) treatment with insulin (±anti-diabetic agents).Trained personnel reviewed all pathologic records and registered information regarding histological type and receptor status in breast cancer cases. Breast tumors were divided into groups according to the presence/absence of the estrogen receptor (ER), progesterone receptor (PR) or the human epidermal growth factor receptor (HER2) as follows: (1) hormone receptor-positive tumors (ER+ or PR+ with HER2−); (2) HER2+ tumors (independent of ER or PR) and (3) triple-negative (TN) tumors .Descriptive statistics of participant characteristics were calculated for both cases and controls by diabetes status Table . To evalTo explore whether the effects of diabetes, diabetes treatment or diabetes duration could differ by cancer subtype, multinomial logistic models were fitted, considering in each case the aforementioned subtypes of breast cancer. Heterogeneity of effects was tested using a Wald test comparing the coefficients obtained for the different subtypes.N = 1732). Third, we explored the results of including participants with missing values in BMI (N = 177) after performing multiple imputation on this variable. Fourth, we further adjusted models on diabetes treatment by diabetes duration. Finally, we evaluated whether the effect of diabetes varied across categories of BMI by introducing an interaction term between the independent variable and BMI (non-obese vs. obese). All sensitivity analyses gave similar results (data not shown in tables).As sensitivity analyses, we first adjusted all models for waist-to-hip circumference instead of BMI. Second, we further adjusted the models for tobacco and alcohol consumption, energy intake and physical exercise when this information was available (Table heterogeneity < 0.01), with a positive association encountered for TN tumors . Compared to non-diabetics, diabetic women under conservative management, as well as those under treatment with oral hypoglycemic agents, showed no overall increased risk of breast cancer, although, again, the results suggested a heterogeneous effect by tumor subtype. Conservative management was associated with a nonsignificant risk of HER2 tumors, while treatment with oral hypoglycemic agents alone showed a positive link with TN breast cancer. Diabetes treatment with insulin was associated with an overall increased risk of breast cancer .Table per year 0.89; 95 % CI 0.81–0.99). Duration of treatment with sulfonylurea was associated with a nonsignificant increased risk of breast cancer, after adjustment for insulin and metformin use . Although we could not evaluate the dose–response association between years of insulin glargine use and cancer risk due to a lack of power, we found that women who were receiving insulin glargine at the time of the interview had an increased risk of breast cancer when compared to women who had never received this drug .The last part of Table Interaction analyses revealed no effect modification of BMI on the association between diabetes or diabetes management and breast cancer risk.Our findings do not support an overall association between diabetes and breast cancer, although they suggest an increased risk of TN tumors in postmenopausal diabetic women. They also suggest that insulin use may increase the risk of breast cancer. Finally, results among diabetic patients indicate that the risk of developing HR+/HER2− tumors may decrease with longer metformin use, while the risk of TN tumors may increase with a longer duration of sulfonylurea use.Despite a number of meta-analyses linking diabetes and breast cancer incidence in postmenopausal women, results from three recently published large population-based studies have raised uncertainty. The first of these null studies retrospectively evaluated the risk of breast cancer in postmenopausal women using data from the Columbia Linked Health Database . The secDifferences in breast cancer risk factors by intrinsic subtypes are well documented, and some authors have suggested that TN tumors may be more strongly associated with insulin resistance . Our resThe biological mechanisms behind a potential increased risk of breast cancer in women with diabetes are unknown, although are probably related to alterations in circulating concentrations of insulin, insulin-like growth factors and endogenous sex hormones. Insulin and IGF-1 receptors are frequently expressed in breast cancer cells , with evMetformin is the most commonly used drug in patients with type 2 diabetes. Experimental studies have shown that this biguanide drug is capable of inhibiting the proliferation of breast cells . AdditioThe evidence on the association between metformin use and the risk of breast cancer has been mixed in epidemiologic studies –27. ResuA meta-analysis using data from 296,904 subjects in cohort studies found an increased risk of total cancer among participants using sulfonylureas when compared to non-sulfonylurea users . HoweverInsulin is a well-known growth factor with particularly strong mitogenic effects over cancer cells. According to our results, showing an increased prevalence of insulin use among cases than among controls, insulin treatment may increase the risk of breast cancer. However, because longer duration of insulin use among diabetics was not associated with breast cancer risk, this positive association cannot be easily explained based on the mitogenic effects of this drug and it can also reflect the influence of a longer duration of diabetes among insulin users.Results from a meta-analysis of observational studies have lately shown an overall increased risk of cancer in patients treated with insulin, although a nonsignificant increased risk of breast cancer  was reported . Data frAvailable data from in vitro experiments suggest that insulin glargine may have greater proliferative effects than human insulin in some breast cancer cell lines . This fiThis is the first population-based study that evaluates the association between diabetes and breast cancer in the Spanish population. Our main strength is that we have histologically confirmed incident cases and that we have classified tumors according to their receptor status. Very few studies have previously evaluated the association between diabetes and breast cancer by specific subtypes, and our results suggest the importance of this approach.Since our results are based on a case–control study, several methodological limitations may exist. First, diabetes history is self-reported and so it is subjected to recall bias. According to the International Diabetes Federation, around 35 % of the European diabetic population is unaware of having this condition . HoweverOur findings do not support an overall association between diabetes and breast cancer, but they provide some suggestive hypothesis for associations with particular tumor subtypes. Although our results should be interpreted with caution due to limitations in sample size, results suggest that diabetes may increase the risk of TN breast tumors. Given the low survival rates in women diagnosed with TN breast tumors, more studies are needed to better characterize this association.


High breast cancer mortality has been attributed to lack of public awareness, which leads to late diagnoses. As little is known about the level of knowledge and awareness of breast cancer in China, this study was designed to explore it among women in Eastern China.t-test, Pearson’s χ2 test, reliability analysis, exploratory factor analysis, univariate and multivariate logistic regression analyses were performed in the statistical analysis.We conducted a cross-sectional survey covering 122,058 females around Shandong, Hebei, Jiangsu and Tianjin, in Eastern China, using in-person interviews based on a self-designed structured questionnaire. Student’s α = 0.05) identified nine variables that predicted awareness of breast cancer: age , location , occupation , family history of breast cancer , household annual income , behavioral prevention score , no smoking , no drinking , overall life satisfaction .The results showed poor awareness of breast cancer among women aged 25–70 years in Eastern China. Only 18.6% of women were highly aware in the study, whereas 81.4% were poorly aware. Among all participants, family history of breast cancer was the best accepted risk factor for breast cancer (awareness rate 31.5%), followed by menarche at age before 12 (11.2%), no parity or late childbirth (13.9%), menopause at a late age (13.7%), high-fat diets (19.1%), long time drinking (19.5%) and long-term use of estrogen drugs (20.7%). Multivariate logistic regression analysis (Our study indicates insufficient awareness of breast cancer among women in Eastern China, and an urgent need for health education programs on this subject. Breast cancer is the leading cause of cancer death in women worldwide by far. About 1.67 million new cases were diagnosed, and 522,000 deaths from breast cancer occurred in 2012 . Based oBreast Cancer Facts & Figures 2013–2014 report, 5-year relative survival decreases with more advanced stage at diagnosis, at 99% for localized disease, 84% for regional disease, and 24% for distant-stage disease [Early diagnosis of breast cancer has been clearly shown to reduce mortality and improve survival –6. Combi disease . Larger  disease . Lucky t disease .Studies from developed countries showed that attitude and orientation of healthcare providers are important determinants of use of breast-screening programs , 18. ProTo plan critically needed breast cancer awareness and education programs that optimally address Chinese women, healthcare professionals and planners must know their current level of understanding. Therefore, we performed this cross-sectional survey in Eastern China to explore public awareness of breast cancer-related symptoms and risk factors.All participants were selected from an earlier epidemiological survey, funded by the Ministry of Health of the People’s Republic of China, of 122,058 women aged 25–70 years, from Shandong, Hebei, Jiangsu and Tianjin. The cross-sectional study used multi-stage stratified and cluster sampling methods. The target population covered women aged 25–70 years of the Han ethnic group, who had ≥ 2 cumulative years of local residence and ≥ 6 months of local residence at the time of survey. Long-term migrant workers, who had left their hometowns for work, were excluded from this study. Provinces in Eastern China where the Han ethnic group mainly resides, including Shandong, Jiangsu, Hebei and Tianjin, were selected for the survey. We then randomly selected counties or regions from each province, and randomly selected villages or communities from the selected counties or regions. Women who met the study requirements were then selected for the survey.This study was a cross-sectional epidemiological survey that included face-to-face interviews and breast examinations. Data were collected through in-person interviews based on a self-designed structured questionnaire. The questionnaire covered six areas gathered from participant interviews: (1) demographic characteristics such as age, marital status, education, occupation, etc.; (2) female physiological and reproductive factors: menstrual cycle history, childbearing history, etc.; (3) medical and family history, including breast-related diseases and family history of breast cancer; (4) dietary habits: frequency of the intake of various types of food; (5) lifestyle habits including smoking, alcohol intake, and psychological conditions ; (6) knowledge of risk factors for breast cancer, early signs and symptoms of disease . Except for the basic demographic information, all questions had multiple-choice responses , and the answer choices were categorized and quantified when possible. For all variables covered by the questionnaire, the answers were defined by strict criteria.This study was approved by the ethics committees of the Second Hospital of Shandong University and those at the collaborating institutions in each region and informed consent was obtained from all the study subjects. However, although all the official seals and signatures of committee members are available, this study has no ethics reference number. As a cross-sectional study, all interviews were completed over a 2-month period, July 15–Sept 15, 2008. Surveyors and physicians were recruited in each survey region before implementing this study. To ensure objectivity and authenticity, all participating investigators, and the physicians who perform physical examinations received strict and standardized professional training before beginning the project. A total of 77 physicians and 248 surveyors participated in the on-site survey process.Knowledge of breast cancer was assessed by requesting the respondents to answer 15 items included in the questionnaire on symptoms and risk factors of breast cancer  with 95% confidence intervals were also calculated. All data analyses were performed using SPSS13.0.The database was established using the software EpiData3.1. Statistical methods, including Student’s This epidemiological survey initially selected 147,538 women, of whom 124,758 were reached to complete the survey, giving a loss rate of 15.44%. Of the 124,758 women surveyed, 1037 subjects were younger than 25 years, and 1629 subjects were older than 70 years. A further 34 were excluded owing to unavailability of important information. Thus, 122,058 women were included in our final analysis.Table In our study, 22,740 women 18.6%) showed high awareness, and 99318 (81.4%) poor awareness. Table 8.6% showAmong the women who knew what breast cancer was, nearly half (48.5%) were aware that a lump in the breast was a symptom of breast cancer Figure . HoweverAs to breast screening and early detection awareness, 42178 of 122058 subjects (43.6%) had received breast examinations; including 26.5% who had ever carried out BSEs, 33.3% who received clinical breast examination, 17.5% who received breast ultrasound and 26.5% who received breast X-ray.Results for univariate analysis at α = 0.05 indicated that awareness and knowledge of breast cancer were related age, location , education status, occupation, marital status, household annual income, family history of breast cancer, drinking, smoking, overall life satisfaction and behavioral prevention score. Multivariate analysis of these factors (α = 0.05) identified age, location, occupation, family history of breast cancer, household annual income, behavioral prevention score, smoking and drinking habits, and overall life satisfaction to independently correlate with breast cancer awareness Table .Table 3P < 0.001), indicating that the correlation matrix was unlikely to be an identity matrix and was therefore suitable for factor analysis [Reliability and construct validity, and internal consistency reliability of the 15-item scale of knowledge about breast cancer and its subscales were assessed using reliability analysis ; the α-coefficient for the total scale was 0.910. The alpha coefficient >0.7 was considered acceptable for internal consistency reliability . Exploraanalysis .Our survey indicated that Chinese women tend to know about some lump-related symptoms of breast cancer, but generally had poor awareness of other breast cancer-related information including risk factors and some atypical symptoms. Only 18.6% of women surveyed showed high awareness, while other 81.4% were poorly aware.In this study, insufficient knowledge was mainly in two areas: symptoms of breast cancer other than lumps, and risk factors. Only 23.0% and 21.3%, respectively, recognized nipple discharge liquid and nipple retraction as signs of breast cancer. These results were in line with other studies, which also showed poor awareness of breast cancer symptoms. A large-scale, population-based survey involving various cancer types in the United Kingdom also showed poor awareness of early warning signs of cancer among British women . Grunfel−0.299, P < 0.000). As a result these women are more likely to be active learners and to access available information. Actually, some studies have shown that cancer awareness among older age groups was even worse [The results also indicated that the awareness and understanding of breast cancer is associated with age, occupation, educational level and family income. Women 25–35 years of age, with high education level and high annual family income tend to be more aware of this information. Generally, in China, younger women pay more attention to health care and tend to be better educated; our analysis showed collinearity between age and education . Similar findings have been reported in some other studies , 37, 38.P < 0.05), which indicates an effective interaction between awareness and screening. Although the investigators of the Shanghai study concluded that “intensive BSE instruction in the absence of mammography would be unlikely to reduce breast cancer mortality,” and the American Cancer Society no longer recommends that all women perform monthly BSE, most researchers agree that self-examination probably improves awareness and might play a part in nationwide programs for earlier-stage detection in China [Women who know more about breast cancer risk factors and mammography are more likely to receive breast cancer screening, which can lead to earlier diagnosis and treatment and improved survival. Our study found that the rate of detection of early-stage breast cancer was relatively low in eastern China—even lower than some survey results , 39. Ratin China –42. Thisin China .A limitation of this study is the lack of uniform standards and methods for measuring breast cancer-related knowledge. Here, we design a questionnaire of 15 questions to measure knowledge of breast cancer, which displayed high scale reliability .We will evaluate the scale’s reliability and validity in a future study.This study showed that most participants knew of breast cancer as a disease entity, but their awareness and understanding about the disease was very poor. As breast cancer incidence increases, a breast cancer awareness and education program is necessary and urgent, especially for women aged 35 years and older.


NFKB1 c.-798_-795delATTG (rs28362491), NFKBIA c.-949C>T (rs2233406), IL-8 c.-352A>T (rs4073), IL-10 c.-854T>C (rs1800871), TNF c.-418G>A (rs361525), and TNF c.-488G>A (rs1800629) polymorphisms with breast cancer risk in an East Chinese population.To explore the association of We conducted a case-control study including 975 study participants  and genotyped the polymorphisms employing polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Logistic regression was used to assess the association of the polymorphisms with breast cancer risk.NFKB1 polymorphism and TT genotype of IL-10 polymorphism significantly increased breast cancer risk . On the other hand, the TT genotype of IL-8 polymorphism, GA and AA genotypes of TNF c.-418G>A polymorphism, and GA genotype of TNF c.-488G>A polymorphism significantly reduced breast cancer risk . When stratified by menopausal status, the CT genotype of NFKBIA polymorphism significantly reduced the risk among pre-menopausal women , but not among post-menopausal women.We found that the ins/del and del/del genotypes of NFKB1, NFKBIA, IL-8, IL-10, and TNF polymorphisms could serve as useful predictive biomarkers for breast cancer risk among women in East China. BRCA1 and BRCA2, account for only less than 5% of the total breast cancer incidence (Breast cancer is the most frequent form of cancer and leading cause of cancer-related deaths among women around the world . The canNFKB1 c.-798_-795delATTG (rs28362491), NFKBIA c.-949C>T (rs2233406), IL-8 c.-352A>T (rs4073), IL-10 c.-854T>C (rs1800871), TNF c.-418G>A (rs361525), and TNF c.-488G>A (rs1800629) polymorphisms with breast cancer risk in East China. Since all these polymorphisms are located in the promoter region, they could affect the transcriptional activity of the gene, resulting in enhanced or reduced cDNA, and eventually protein levels, among their carriers (Single nucleotide polymorphisms (SNPs) have been extensively investigated for their associations with the risk of various cancers -11. As iTTG rs2832491, NFKcarriers . In addiTTG rs2832491, NFKA total of 1032 female study participants – 514 breast cancer patients and 518 controls without cancer were identified at the Jiujiang First People’s Hospital. 474 breast cancer patients and 501 female controls without cancer agreed to participate in the study. The participants were interviewed by trained professionals and data related to smoking, oral contraceptive use, and menopausal status were collected. The patients’ histopathological types and cancer grading were retrieved from their medical records. All the participants were Han Chinese. The study received approval from the Ethics of Human Research Board of Jiujiang First People’s Hospital. Informed consent was obtained from the participants before inclusion in the study.NFKB1 c.-798_-795delATTG (rs28362491), the PCR primers used were 5′-TGG GCA CAA GTC GTT TAT GA-3′ and 5′-CTG GAG CCG GTA GGG AAG-’3  technique and the genotypes were verified by direct sequencing of PCR products. For TTG rs2832491, theNFKBIA c.-949C>T (rs2233406) polymorphism, the forward primer was 5′-GGT CCT TAA GGT CCA ATC G-3′ and the reverse primer was 5′-GTT GTG GAT ACC TTG CAC TA-3′ (For AC TA-3′ . The annIL-8 c.-352A>T (rs4073) polymorphism, the forward primer was 5′-CCA TCA TGA TAG CAT CTG T-3′ and the reverse primer was 5′-CCA CAA TTT GGT GAA TTA TTA A-3′ (For IL-10 c.-854T>C (rs1800871) polymorphism, the forward primer was 5′-TGA GCA AAC TGA GGC ACA GAA AT-3′ and the reverse primer was 5′-GAC AAC ACT ACT AAG GCT CCT TTG GGA-3′ (For G GGA-3′ . The annTNF c.-418G>A (rs361525) polymorphism, the primers used were 5′-AAA CAG ACC ACA GAC CTG GTC-3′ and 5′-CTC ACA CTC CCC ATC CTC CCG GAT C-3′  polymorphism, the primers used were 5′-GAG GCA ATA GGT TTT GAG GGC CAT-3′ and 5′-GGG ACA CAC AAG CAT CAA G-3′  The differences in age, smoking habit, oral contraceptive use, menopausal status, and genotypic distribution between cases and controls were assessed using a χThere were no significant differences in mean age, smoking, oral contraceptives use, and menopausal status between patients and controls .NFKB1 ins/del and del/del genotypes, IL-8 TT genotype, IL-10 CC and TT genotypes, and TNF c.-418 and c.-488 GG and GA genotypes (TNF polymorphisms were in strong linkage disequilibrium (R2 = 0.819). All the genotypic distributions followed Hardy-Weinberg equilibrium.Significant differences between cases and controls were observed for enotypes . The twoNFKBIA polymorphism. NFKB1 c.-798_-795delATTG ins/del and del/del genotypes, and IL-10 c.-854 TT genotype were associated with increased breast cancer risk, while IL8 c.-352 TT genotype, TNF c.-418 GA and AA genotypes, and c.-488 GA genotype were significantly associated with a reduced risk  and ductal carcinoma in situ (DCIS), but not in invasive lobular carcinoma (ILC). IL10 variant genotype was associated with increased breast cancer risk in all three types of breast cancers. On the other hand, IL8 variant genotype and heterozygous genotypes of both TNF polymorphisms were associated with decreased risk of IDC but not of other types of breast cancer (t cancer .NFKB1 heterozygous genotype (in Grade 2 and 3 patients), NFKB1 variant genotype , NFKBIA variant genotype (in Grade 1 patients), IL10 heterozygous genotype (in Grade 1 patients), IL10 variant genotype , and TNF c.488 heterozygous genotype (in Grade 1 patients). Decreased risk associations were observed for IL8 heterozygous and variant genotypes, TNF c.418 heterozygous genotype, and TNF c.488 heterozygous genotype  (Increased risk associations were observed for atients) .This study established that the ins/del and del/del genotypes of NFKB1 polymorphism and TT genotype of IL-10 polymorphism significantly increased breast cancer risk, while the TT genotype of IL-8 polymorphism, GA and AA genotypes of TNF c.-418G>A polymorphism, and GA genotype of TNF c.-488G>A polymorphism significantly reduced breast cancer risk. Various lines of evidence have found that chronic inflammation was a risk factor for breast cancer development -18. InflNFKB1 and NFKBIA; IL-8 and IL-10; and TNF c.-418 and c.-488), menopausal status, histopathological type, and cancer grading. To our knowledge, this is the first study investigating the association between NFKB1 polymorphism and breast cancer risk although there are a few reports on its association with several other cancers. Our findings are in agreement with a study from East China that found that del/del genotype increased the risk of bladder cancer (NFKBIA polymorphism with the risk of breast cancer in any Asian population. Thus far, only one study has examined this association but it was conducted in a Caucasian population (NFKBIA polymorphism and breast cancer risk. For IL-8 polymorphism, one study conducted in East China showed no association with breast cancer risk (IL-10 polymorphism and breast cancer risk (TNF c.-418 and c.-488 polymorphisms, an Indian study (We analyzed not only the association of individual polymorphisms and breast cancer risk, but also the effects of combinations of functionally related polymorphisms (r cancer . Howeverr cancer  found thpulation . Similarcer risk . Our rescer risk . On the cer risk , which ian study , reportean study  reportedIn conclusion, our study provided evidence for the association of various inflammatory response gene polymorphisms with the risk of breast cancer in East China. The strengths of the present study are the reasonably large sample size and the detailed combination and stratification analyses performed. The limitations of the study are the small number of polymorphisms studied within each gene and the small sample sizes obtained by stratification according to menopausal status, histopathological type, and cancer grading, which might have led to misleading interpretation. Therefore, further studies by independent research groups are needed to confirm our findings.


Therefore, the ASBrS convened a panel of experts to develop a consensus statement on CPM. Initial literature review was performed and exchanged electronically by the panel, followed by an in-person meeting of the consensus group and polling of the membership of the ASBrS at the 2016 annual meeting. The consensus statement consists of two parts. This paper, part 1, outlines the data on the impact of CPM on cancer and noncancer outcomes, including risks of CPM and when CPM should be considered or discouraged. Part 2 outlines whether CPM utilization should be a quality measure, role of sentinel node biopsy for CPM, perspectives on CPM from patients and from providers in other countries, and counseling considerations for patients desiring CPM and includes a discussion template for providers to use with patients regarding CPM. The ASBrS Executive Committee reviewed and approved the statement. This consensus statement was developed to guide patient and physician discussion and should not affect insurance coverage.The consensus group agreed that CPM should be discouraged for an average-risk woman with unilateral breast cancer. However, patient’s values, goals, and preferences should be included to optimize shared decision making when discussing CPM. The final decision whether or not to proceed with CPM is a result of the balance between benefits and risks of CPM and patient preference.–10The consensus group recommends consideration of breast conservation for all patients who are appropriate candidates. Breast conservation is equivalent to mastectomy in survival outcome and has been the preferred treatment for early-stage breast cancer since the National Cancer Institute statement in 1991.6The panel recommends advocating for breast conservation for all appropriately eligible patients and considering neoadjuvant systemic therapy and/or oncoplastic approaches to facilitate breast conservation where possible.For women who elect or require mastectomy for management of their index breast cancer, the option of removing the contralateral breast is often discussed. Multiple factors should be considered including family history, patient age, comorbidities, and tumor prognosis, as well as the initial plan for surgery, systemic therapy, and radiotherapy. The surgical consultation should include a detailed discussion of local treatment options, the risk of developing a contralateral breast cancer (CBC) and distant cancer recurrence, the options for managing a CBC, and a clear recommendation for or against CPM. CPM is never an emergency and is never mandatory; even for patients at the highest risk of CBC, in the absence of disease, close surveillance is always a reasonable alternative to surgery.Among women with breast cancer, the absolute risk of developing a CBC exceeds that of the general population and is approximately 0.6 % per year in historic series.BRCA1/2 mutation carriers, studies have shown a 30–40 % risk of CBC at 10 years, and the risk appears to continue beyond 10 years.CHEK2, p53, PALB2, ATM, and NBN is less well studied, and at this time there is insufficient evidence to support an increased CBC risk for these mutations. Early studies of CHEK2 mutation carriers showed an increased risk for CBC, but future studies are warranted to verify this finding.14,Known factors contributing to the risk of developing CBC include individual patient factors  as well as treatment related to the index breast cancer . For known –25There is strong evidence that CPM reduces the relative risk of cancer in the contralateral breast by 90 to 95 %; however, breast cancer risk is not completely eliminated with CPM. The absolute risk of developing cancer on that side after CPM ranges from 0 to 1.5 %.20BRCA carriers.Risk of CBC for average-risk women with breast cancer is 0.1 to 0.6 % per year. CBC risk is higher for women diagnosed at a young age, those with a strong family history, and ,24–21,27–22,31,There are no prospective studies on the impact of CPM on overall survival (OS) and disease-free survival (DFS). In view of this, all published studies comparing OS and DFS for woman undergoing CPM with those not undergoing CPM have to be interpreted with caution, as they are retrospective and may contain known and unknown biases. Multiple retrospective studies have compared OS and DFS in women undergoing CPM compared to those not undergoing CPM. Some have shown a DFS benefit21BRCA carriers, retrospective studies have shown that patients who underwent CPM had better OS than BRCA carriers who did not undergo CPM.20,34,36,37For those patients at the highest CBC risk, such as BRCA carriers.CPM does not appear to be associated with a survival benefit, with the possible exception of Complications can be divided into categories based on time  and type . Early complications are dominated by surgical site issues such as tissue/skin flap necrosis, infection, bleeding, and standard surgical complications such as deep-vein thrombosis and anesthesia complications. Because reconstructive complications on the CPM side would not have occurred without the CPM, it is reasonable to consider the complications from the mastectomy and also any reconstructive complications  from both the immediate procedure and subsequent procedures required for completion of the reconstruction. Taking these together, complications are estimated to occur in 40–64 % over the entire course of a reconstruction, with an estimate of 52 % of patients having at least one unanticipated surgery in one series.38–CPM has been shown to have double the complication rate compared to unilateral mastectomy, regardless of whether reconstruction is performed or not, and complications occur almost equally on the affected and prophylactic sides.39CPM doubles the risk of surgical complications.CPM may negatively affect oncologic outcomes for patients who were never destined to develop a CBC. Surgical complications may delay the onset of adjuvant therapy, or may encourage patients to avoid therapy that would otherwise be recommended, such as radiotherapy. One study has shown that patients undergoing CPM had longer delays to adjuvant therapy then those patients undergoing unilateral mastectomy or lumpectomy.43Symmetry is a significant driver for CPM, especially for women with ptotic or large breasts. Satisfaction with breast appearance has been shown to be higher with bilateral mastectomy and implant reconstruction compared to unilateral mastectomy with implant reconstruction.–45,44,CPM has been associated with negative outcomes on quality of life associated with reconstructive surgery. Survey studies of patients who have undergone reconstruction have shown that up to 20–30 % of patients report that outcomes from their reconstruction such as the cosmetic appearance, numbness or tingling, and sexuality were worse than expected.45Bilateral reconstruction may provide improved cosmetic outcome.Average-risk women with unilateral breast cancer do not derive any oncologic benefit from CPM, and thus CPM should be discouraged.BRCA1/2, (2) a greater than 25 % lifetime risk of breast cancer primarily due to family history in the absence of deleterious mutations, or (3) a history of mantle radiation  before age 30.36,37From a risk perspective, CPM should be considered primarily for women at the highest risk for CBC, specifically those women with (1) deleterious mutations of CHEK2, PALB2, and CDH1, there is insufficient evidence regarding CBC risk to recommend for or against CPM in these patients, and therefore CPM can be considered.For patients with a strong family history without a known genetic mutation and patients with other breast cancer risk genes such as Symmetry is a significant driver for CPM, especially for those with ptotic or large breasts and unilateral breast malignancy. Plastic surgical consultation is highly recommended whenever mastectomy is required or chosen for management of the index cancer and the patient is interested in reconstruction. This consultation should involve a detailed discussion about what each reconstructive procedure involves, recovery time, the need for additional operations, and the risks associated with the procedure.Patients with more advanced disease, when timing of adjuvant oncologic therapy is critical and risk of recurrence from the primary tumor greatly outweighs potential risk of CBC, should not undergo CPM. Additionally, patients with comorbidities such as significant cardiac or pulmonary disease, chronic anticoagulation or steroid use, poorly controlled diabetes, poor wound healing, and liver failure should be discouraged from CPM because the surgical risks of the procedure likely outweigh any benefits.BRCA1/2 carrier.Documented Strong family history, but patient has not undergone genetic testing.History of mantle chest radiation before age 30 years.CPM can be considered for those at lower risk of CBCBRCA gene .Gene carrier of non-BRCA negative, no known BRCA family member.Strong family history, patient CPM may be considered for other reasonsTo limit contralateral breast surveillance .To improve reconstructed breast symmetry.To manage risk aversion.To manage extreme anxiety. CPM should be discouragedAverage-risk woman with unilateral breast cancer.Women with advanced index cancer .Women at high risk for surgical complications .BRCA negative with a family of BRCA-positive carriers.Woman tested BRCA carriers.Male breast cancer, including CPM should be considered for those at significant risk of CBC


Breast density has been established as a major risk factor for breast cancer. We have previously demonstrated that mammographic texture resemblance (MTR), recognizing the local texture patterns of the mammogram, is also a risk factor for breast cancer, independent of percent breast density. We examine if these findings generalize to another population.Texture patterns were recorded in digitalized pre-diagnosis (3.7 years) film mammograms of a nested case–control study within the Dutch screening program (S1) comprising of 245 breast cancers and 250 matched controls. The patterns were recognized in the same study using cross-validation to form resemblance scores associated with breast cancer. Texture patterns from S1 were examined in an independent nested case–control study within the Mayo Mammography Health Study cohort (S2) of 226 cases and 442 matched controls: mammograms on average 8.5 years prior to diagnosis, risk factor information and percent mammographic density (PD) estimated using Cumulus were available. MTR scores estimated from S1, S2 and S1 + S2  were evaluated in S2. MTR scores were analyzed as both quartiles and continuously for association with breast cancer using odds ratios (OR) and adjusting for known risk factors including age, body mass index (BMI), and hormone usage.P <0.001), which persisted after adjustment for PD. S2 showed an AUC of 0.63, 0.61, and 0.60 based on PD, MTR scores trained on S2, and MTR scores trained on S1, respectively. When adjusted for PD, MTR scores of S2 trained on S1 showed an association with breast cancer for the highest quartile alone: OR in quartiles of controls as reference; 1.04 (0.59 to 1.81); 0.95 (0.52 to 1.74); 1.84 (1.10 to 3.07) respectively. The combined continuous model with both PD and MTR scores based on S1 had an AUC of 0.66 ± 0.03.The mean ages of S1 and S2 were 58.0 ± 5.7 years and 55.2 ± 10.5 years, respectively. The MTR scores on S1 showed significant capability to discriminate cancers from controls (area under the operator characteristics curve (AUC) = 0.63 ± 0.02, The local texture patterns associated with breast cancer risk in S1 were also an independent risk factor in S2. Additional textures identified in S2 did not significantly improve risk segregation. Hence, the textural patterns that indicated elevated risk persisted under differences in X-ray technology, population demographics, follow-up time and geography. Mammographic density has beenRecently, qualifying an objective measure of density, based on quantitative calibrated imaging, measuring the volume percentage of fibroglandular tissue in raw digital mammograms has attracted attention, and beea priori clear how these disorganized structures will manifest in mammograms and how and whether these patterns can be separated from fibroglandular tissue of normal turnover. A very general approach, recording and recognizing structural components from mammograms of subjects with known outcome has shown very promising results[The underlying mechanisms of heterogeneity that relates to risk can be hypothesized to relate to increased turnover and thereby more disorganized growth of fibrous tissue. It is, however, not  results,11. The We examine whether structural components and textures were associated with breast cancer risk in two independent studies Two samples were included in the current study: Study 1 (S1) from the national Dutch screening program, and Study 2 (S2) from the Mayo Mammography Health Study cohort, a screening mammography cohort established at the Mayo Clinic. S1 was The Mayo Mammography Health Study (MMHS) cohort at the Mayo Clinic in Rochester, Minnesota (MN) was established to examine the association of breast density with breast cancer,15. The Both studies used digitized film mammograms. For S1, the right mediolateral view was digitized on a Vidar scanner  providing an image resolution of approximately 1,500 × 2,500 pixels on 12-bit grayscale and size 50 × 50 microns. In S2, four-view mammograms were digitized on the Array 2905 laser film digitizer  that similarly has 50 micrometer (limiting) pixel spacing with 12-bit grayscale bit depth.The breast region was manually outlined as a skin-air curve and a line separating breast tissue from the pectoral muscle. The projected area of the breast region was recorded.In S1, a trained radiologist estimated percent density (PD) on the right mediolateral oblique (MLO) view using a thresholding approach ignoringIn S2, PD was scored by a trained reader on the craniocaudal (CC) or top-down views of the contralateral breast to the cancer (and matched side for controls) using a similar approach as S1, Cumulus. The reaThe MTR scores,19 rely The MTR score was estimated on S1 using S1 as training data, but in a leave-two-subjects-out cross-validation fashion: when scMTR on S2 was scored using three different training algorithms: Training 1 (T1) used the S1 study as training data; Training 2 (T2) used the S2 study in a leave-two-out fashion as described for S1 above; Training 3 (T3) used the pooled S1 + S2 study in a leave-two-out fashion. The scoring using T1 was performed in Copenhagen and was blinded to outcome in S2. The MTR scores were transferred back to the Mayo Clinic for statistical analysis. Subsequently, case/control status was transferred to Copenhagen and T2 and T3 could be performed.Projected mammographic breast area was computed based on the pectoral muscle line and the skin-air boundary. Inside this region, the distribution (histogram) of image intensities was recorded.P <0.05.Data presented are expressed as mean ± standard deviation unless otherwise indicated. Group characteristics were compared using the nonparametric two-sided Wilcoxon signed rank test. Reported confidence intervals are based on 95%. All tests were two-sided and considered significant when A series of conditional logistic regression models with breast cancer as the outcome was fitted to each of the sets of training scores (T1 to T3). These models were adjusted for potential confounding variables: body mass index (BMI), menopause status, and postmenopausal hormone (PMH) use and percent density (PD). Odds ratios (OR) describe the association of the MTR scores with breast cancer, both as quartiles based on the control distribution and per one SD of each measure.The ability to discriminate case vs. control status was evaluated as an area under the receiver operator characteristic (ROC) curve (AUC). AUCs were compared using the Delong test. For S2, AUCs were calculated within matched sets in order to utilize the matched nature of the sample. This was done by comparison of predicted model risk scores for cases and controls within matched sets and tabulating how often the case is correctly identified as having a higher risk score. Bootstrapping was utilized to provide confidence intervals for AUCs in this case.Pearson correlation coefficients were used to summarize the association among different scores and PD measures. Kolmogorov-Smirnov tests were used to test differences in distribution of breast area and intensities.Participants in S1 were older, mean, 58.0 ± 5.7 years, range (49 to 81), than participants in S2  years). S2 had a longer time from mammogram to diagnosis than S1  vs. mean, 3.7 years, range (2.2 to 4.2), respectively). In S2, controls were well-matched to cases on the majority of characteristics . The mean intensities also differed in the two studies, P <0.0001. Figure The mean projected breast area was significantly smaller in S1, a mean of 164.8 ± 49.7 cmP <0.01) higher PD in the cases (22.3 ± 10.2%) than in the controls (19.7 ± 11.4%). Stratifying into screen-detected and interval cancers the density was higher (P <0.05) in those subsequently diagnosed as interval cancers (23.3 ± 1.0%) compared to screen-detected cancers (21.3 ± 0.9%) at the biannual screening visit. S2 similarly showed that cases had a higher mean density than controls .As reported previously, S1 showThe association between quartiles of PD and breast cancer is shown in Table The associations of MTR, for both quartiles and per SD, with breast cancer from all three training regimes are shown in Table P <0.001) whereas correlation with PD is low (R <0.25).Table Finally, a combined model Table , bottom In numerous studies, including S1 and S2, PD, adjusted for age, BMI, and PMH use, has been associated with breast cancer risk. In thisWe found comparable associations and discrimination using the MTR in two different populations: the North American cohort (S2) was younger and had a wider range of age than the Dutch cohort (S1). As density in general decreases with age, the visual appearance of textural patterns may also be hypothesized to change by age. In fact, it was shown earlier that density invariant texture patterns may significantly separate randomly selected groups of 30 women differing five years in age. HoweverThe mammographic technology also varied between the two studies, which used different film and digitizers. This serves as a potential source of noise in the recognition process of textures between studies. In Figure The North American cohort has a larger projected breast area than the Dutch cohort. BMI measurements are present for the North American cohort while BMI was not recorded in the Dutch cohort. Breast size as cup size has shown to be inversely related to breast density measured on a different Dutch population, a trendThe differences in percent dense tissue between S1 and S2 may be somewhat explained by the large proportion of interval cancers in S1, the hypothesized variation in BMI, the differences in age, potential differences in PMH usage, and the interrater variation.In S2 Table , cancersPMH use in the Dutch population was relatively low in the 1990s in the middle-aged population. Only 13 to 19% were current users with an average duration of two years. In compTime to diagnosis was considerably longer (8.6 years compared to 3.7 years) in the North American cohort S2. If patterns are stable and non-modifiable, the longer time window should only allow for more accurate outcome estimation, whereas if patterns change temporarily during the observation window, the longer time window could potentially contaminate prediction. As prediction is slightly (but insignificantly so) weakened in S2 one may hypothesize that texture patterns may potentially change over time, due to age, hormones, menopause, diet, and so on. Hence, it may be interesting to study the temporal variations of texture patterns in the individual.The MTR shows a slightly weaker (0.61 compared to 0.63) but still significant capability to discriminate cases from controls in S2 compared to S1. This may be due to closer matching in S2 taking time interval prior to cancer into account, and not just age as in S1. In both S1 and S2, PD and MTR both persist as risk factors, showing that texture may carry additional recognizable information.et al.[et al. did find larger associations with coarse scale features. Figure et al. above, MTR features have the capability to distinguish spatially varying features (the indication of a pattern may vary with its position within the breast) and to measure aspects that were not intended for by design, as they are selected based on visual recognition capability, and not the mathematical design of features. This could also contribute to the differences in these two studies.Measures such as fractal dimension have beeet al.. Of thesThe cause and appearance of textural features relating to breast cancer risk is potentially very complex. Tissue density has been suggested to relate to altered protein composition and accumulation in the tissue, which may result in cancer. This loIn fact, all three trainings of the MTR measure are highly correlated to each other, and at best weakly correlated to density. Also the MTR is associated with breast cancer, after adjustment for PD. This verifies the finding that MTRThe conclusions of the studies are limited to the demographics of the populations, including primary European populations. Furthermore, S1 was not matched or included risk factors other than age, and mammograms from the right side were always scored independently of the laterality of futurWe have shown that the mammographic texture resemblance, recorded in one study and examined in an independent cohort of different age distribution, geography, breast size distribution, X-ray and scanner technology, is a risk factor for breast cancer that is independent of percent density.Mads Nielsen has received grants from Nordic Bioscience A/S and holds shares in Biomediq A/S. Nico Karssemeijer holds shares in Matakina. Martin Lillholm holds shares in Biomediq A/S. Morten A Karsdal holds shares in Nordic Bioscience A/S. Celine M Vachon, Christopher G Scott, Konstantin Chernoff and Gopal Karemore declare that they have no competing interests.MN took part in the overall design, instructed on the MTR scoring, and was the main writer of the manuscript including the discussion. CV and CS collected the S2 data, conducted the statistical analysis and contributed substantially to the writing of the manuscript. KC and GK contributed to the design of the MTR scoring, implemented the MTR scoring, conducted the MTR scoring and the data handling in Copenhagen, contributed to the discussion, and critically revised the manuscript. NK supervised the collection of the S1 data, contributed to the design of the study and the discussion, and critically revised the manuscript. ML contributed to the design of the MTR scoring, the statistical analysis, and the discussion, and critically revised the manuscript. MK contributed to the design of the study, provided insight on breast biology, wrote sections of the manuscript, contributed to the discussion, and critically revised the manuscript. All authors read and approved the final version of the manuscript.