We aimed to systematically review the evidence on adverse mental health outcomes in breast cancer survivors (≥1 year) compared with women with no history of cancer.Studies were identified by searching MEDLINE, PsycINFO, the Cumulative Index to Nursing and Allied Health Literature, and the Social Sciences Citation Index, and through backward citation tracking. Two researchers selected the studies, extracted data, and assessed the risk of bias.Sixty studies were included. Of 38 studies of depression, 33 observed more depression in breast cancer survivors; this was statistically significant in 19 studies overall, including six of seven where depression was ascertained clinically, three of four studies of antidepressants, and 13 of 31 that quantified depressive symptoms. Of 21 studies of anxiety, 17 observed more anxiety in breast cancer survivors, statistically significant in 11 studies overall, including two of four with clinical/prescription-based outcomes, and in eight of 17 of anxiety symptoms. Breast cancer survivors also had statistically significantly increased symptoms/frequency of neurocognitive dysfunction (18 of 24 studies), sexual dysfunctions (5 of 6 studies), sleep disturbance (5 of 5 studies), stress-related disorders/PTSD (2 of 3 studies), suicide (2 of 2 studies), somatisation (2 of 2 studies), and bipolar and obsessive-compulsive disorders (1 of 1 study each). Studies were heterogeneous in terms of participants’ characteristics, time since diagnosis, ascertainment of outcomes, and measures reported. Approximately one-half of the studies were at high risk of selection bias and confounding by socio-economic status.There is compelling evidence of an increased risk of anxiety, depression and suicide, and neurocognitive and sexual dysfunctions in breast cancer survivors compared with women with no prior cancer. This information can be used to support evidence-based prevention and management strategies. Further population-based and longitudinal research would help to better characterize these associations. Women with a history of breast cancer are the largest group of cancer survivors in high-income countries . In the A diagnosis of breast cancer is often overwhelmingly distressing . Women fTo our knowledge, no systematic review to date has summarized the evidence from studies comparing breast cancer survivors with a noncancer control group for a broad spectrum of adverse mental health outcomes. Therefore, the aim of this study was to identify and summarize the studies that have quantitatively compared mental health outcomes in breast cancer survivors (≥1 year) vs women who did not have cancer; we also assessed the quality of the evidence on this topic by applying objective quality assessment criteria.This review was registered in the International Prospective Register of Systematic Reviews (PROSPERO 2017: CRD42017056946) and followed the a priori methods outlined in the protocol (published elsewhere ). ResultThe predefined outcomes of interest were anxiety disorders; bipolar and related disorders; disruptive, impulse control, and conduct disorders; feeding and eating disorders; mood disorders; neurocognitive disorders; neurotic disorders; personality disorders; schizophrenia spectrum and other psychotic disorders; sexual dysfunctions of psychological nature; sleep wake disorders; somatoform disorders; substance-related disorders ; and trauma- and stressor-related disorders. We also considered eligible the studies providing data on self-injurious behavior . These categories were selected after systematically reviewing those listed in the Diagnostic and Statistical Manual of Mental Disorders, 5th edition  and in tPotentially eligible studies were identified in four databases: MEDLINE, PsycINFO, the Cumulative Index to Nursing and Allied Health Literature, and the Social Sciences Citation Index. A search expression tailored for each database was created including terms for the exposure (breast cancer), outcomes , and comparators  , clinically diagnosed or their symptomatology assessed through validated instruments, between adult female breast cancer survivors and a comparison group of women with no prior cancer. Female breast cancer survivors were defined as women with a history of breast cancer or in situ tumor for one year or longer. Studies with patients diagnosed with breast carcinomas in situ were included because despite of their excellent prognosis , they reThe eligibility of individual studies was assessed by two reviewers  who independently applied the predefined inclusion/exclusion criteria. Initial agreement between reviewers in the assessment of abstracts was 92.5% for HC/MM and 81.3% for HC/RH , and initial agreement in the full-text assessment was 95.9% (κ = 0.69) and 90.6% (κ = 0.54), respectively. All discordant assessments were discussed and successfully resolved.We systematically abstracted data on the characteristics of the study and study samples. We extracted quantitative data on the frequency  or severity (mean scores) of adverse mental health outcomes for each participant’s group or for the comparison between groups , as available, and the results of any hypothesis testing reported in the original studies. Prevalences from studies involving psychometric instruments were based on the cut-offs defined by the authors of the original studies. When two or more studies reported data on the same study population, we extracted data from the study with largest sample size, or if equal, the one providing more detailed outcome information. Data were extracted independently by two investigators  and discrepancies were resolved.The risk of bias in the included studies was assessed by two reviewers who independently evaluated domains previously identified as important in observational studies . The domP values for the comparison of mean scores from psychometric instruments between breast cancer survivors and women who did not have cancer were estimated with the independent samples t test; all tests were two-sided. To ensure comparability of the results across studies, we applied a type-1 error rate (α) of .05 when summarizing statistical significance even if studies themselves had provided results using a different statistical significance level. A quantitative synthesis of the results , as planned in the study protocol . When sufficient information was provided in the original studies, we calculated the prevalence ratio for each outcome  if this protocol , was notOf the 7517 individual publications identified, 729 studies were eligible for full-text evaluation, and 60  were ultTwenty-one eligible studies reported data for anxiety .Four longitudinal, population-based studies evaluated anxiety with clinical diagnoses (n = 2) or clinical diagnoses and anxiolytics prescription (n = 2); all used electronic health records data and pointed towards an increased risk in breast cancer survivors, but this was supported by strong statistical evidence in two studies only . The relSeventeen studies investigated symptoms of anxiety using scales . There wPrevalences of anxiety were generally less than 20% when electronic health records or anxiolytics were studied and in the range of 20% to 50% when scales were used . DetermiThirty-eight studies provided data on depression .Of seven studies that analyzed depression based on clinical diagnoses, six found strong evidence of an elevated risk among breast cancer survivors, with relative risk estimates ranging from 1.06 (95% CI = 1.00 to 1.12) to 2.04 (95% CI = 1.76 to 2.36) . All fouOf 31 studies that evaluated depressive symptoms with scales, 13 reported strong statistical evidence of higher severity of depressive symptoms among women who had breast cancer ; among tThe prevalence of depression in breast cancer survivors was highest when evaluated with self-reported instruments (with most estimates >30%) and lower for clinically diagnosed depression  to 60% (95% CI = 21% and 112%) higher risk than women in the comparison group .Twenty-four studies evaluated domains of neurocognitive function ; this waOf the 24 studies of neurocognitive dysfunction, 21 investigated the effect of being exposed to chemotherapy vs no chemotherapy; these studies consistently showed increased risk of neurocognitive impairments in breast cancer survivors exposed to chemotherapy. Three studies evaluated the effect of being exposed to hormone therapy in chemotherapy-naïve patients ,82,85; tSix studies, all involving convenience samples, reported data for sexual dysfunction . Five ofOther outcomes were infrequently studied, but five of five studies of sleep disturbance found a statistically significantly higher prevalence in breast cancer survivors, as did two of three studies of stress-related disorders, two of two studies of somatization, and the single studies identified with bipolar disorder and obsessive-compulsive outcomes .Approximately 50% of the studies were rated at high risk of selection bias, mostly because of the nonprobabilistic recruitment of participants  between long-term breast cancer survivors and women in the general population . The intThis study has several implications for clinical practice. It is important to raise awareness amongst health care professionals acting at various levels of the health care system of the increased risk of mental health symptoms among breast cancer survivors, in particular anxiety, depression, and neurocognitive and sexual dysfunctions. Screening for mental health disorders in some or all of the breast cancer survivor population may be warranted. Predictors of distress among breast cancer survivors include having perceived functioning limitations, fatigue, younger age, lower socioeconomic status, and psychiatric history, and modifiable factors such as vasomotor symptoms, pain, less social support, physical activity, and cigarette smoking . As suchOur review also identified areas for further research. There is a pressing need for studies evaluating clinically diagnosed adverse mental health outcomes in samples of women likely to represent the cohort of survivors in the general population and with sufficient numbers to allow effects to be detected. Further research is particularly needed to better characterize the trajectories of mental health outcomes over time, particularly of anxiety, depression, and neurocognitive dysfunction. The long-term risk of sleep disorders needs clarification, because breast cancer treatments such as chemotherapy and steroids have been suggested to be associated with impaired sleep ,131, posIn conclusion, women with a history of breast cancer appear to be at higher risk of a wide range of adverse mental health outcomes up to several years post diagnosis and treatment compared with women who did not have cancer. The evidence was particularly compelling for anxiety, depression and neurocognitive and sexual dysfunctions, and suicide, which were most often studied. However, there is a pressing need for more population-based research to better characterize the association between breast cancer history and mental health. Our results can be used to inform prevention and management strategies directed at tackling the burden of adverse mental health outcomes in breast cancer survivors.This work was supported by the Medical Research Council (MRC) and the Clinical Practice Research Datalink (CPRD) at the Medicines and Healthcare products Regulatory Agency (MHRA) (grant no. MR/M016234/1 to HC); the Bangerter Foundation and the Swiss Academy of Medical Sciences (grant no. TCR 14/17 to MM); and the Wellcome Trust and the Royal Society (grant no. 107731/Z/15/Z to KB).Department of Non-Communicable Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK (HC); Clinical Practice Research Datalink (CPRD), Medicines and Healthcare Products Regulatory Agency, London, UK (RW); Department of Emergency Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland (MM); Institute of Health Economics and Clinical Epidemiology, University Hospital of Cologne, Cologne, Germany (MM); Department of Non-Communicable Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK (RH); Department of Medicine, The Royal Marsden NHS Foundation Trust, London and Surrey, UK (SS); Department of Non-Communicable Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK (KB).The funders had no role in the design of the study; the collection, analysis, and interpretation of the data; the writing of the manuscript; and the decision to submit the manuscript for publication.Conflict of interest: Ms Williams reports that CPRD has financial relationships with its clients, including the London School of Hygiene and Tropical Medicine, in relation to providing access to research data and services outside the submitted work. Dr Stanway reports personal fees from Roche, Clinigen, Eli Lilly, and Novartis not related to this work. Dr Bhaskaran reports grants from Wellcome Trust, the Royal Society, Medical Research Council, and British Heart Foundation outside the submitted work. The other authors in this report have no conflict of interest to disclose.Acknowledgments: We thank Dr Maja Nikšić and Ms Ruoran Li for their help in interpreting the papers written in Serbian and Chinese, respectively.Supplementary DataClick here for additional data file.


Obesity is associated with increased risk of breast and other cancers. However, the complexity of the underlying mechanisms, together with the interplay of diet and physical activity—contributing to energy balance—and the role of adipose tissue, pose challenges to our understanding of the basis of this increased risk. Epidemiologic studies have documented a higher obesity prevalence in US black women compared to white women. Elucidation of the contribution of potential biological differences among racially distinct groups to their differences in breast cancer (BC) risk and mortality have been topics of considerable interest in recent years. The racial and ethnic variation in body fat distribution may account for at least part of the differences in breast cancer rates in these populations. Yet, while black women exhibit higher rates of obesity compared to white women, this does not translate directly into higher rates of BC. In fact, overall, BC in black women occurs with a lower incidence than BC in white women. Obesity is a known risk factor for postmenopausal breast cancer, and growing evidence suggests that abdominal obesity, also known as central obesity, may increase risk for triple negative breast cancer, which is more common in premenopausal women. The positive association of postmenopausal BC risk and specifically estrogen receptor (ER)-positive BC, is presumably due largely to accumulation of estrogen in the adipose tissue of the breast and other tissues. Of the two main types of adipose tissue—subcutaneous and visceral—visceral adipocytes are more active metabolically. Such adipose tissue harbors multiple molecular entities that promote carcinogenesis: endocrine molecules/hormones, immunologic factors, inflammatory cytokines, metabolic alterations, and other components of the microenvironment. Expression of these culpable entities is largely regulated by epigenetic mechanisms. The interrelationship between these entities and drivers of epigenetic alteration are critical to the regulation of pathways connecting obesity and cancer risk. Initiatives to counteract the carcinogenic effects of obesity have primarily involved modulation of energy balance by diet. However, targeting of specific molecular abnormalities characterizing adiposity offers an alternative approach to preventing cancer. Our goal in this review is to first discuss the major mechanisms contributing to the obesity-breast cancer link. We will also consider race, specifically black/white differences, as they relate to the association of obesity with breast cancer risk. Then we will enumerate strategies targeting these mechanisms to reduce BC risk, in large part by way of dietary interventions with potential to mitigate the cancer-promoting components of adiposity. The 2 .High adiposity  is a risk factor for several types of cancer, including breast cancer . The ass2) was associated with ER+ breast cancer and decreased risk of TNBC. Among premenopausal black women, higher BMI (> 30 kg/m2) was associated with decreased risk of ER+ breast cancer. When examining abdominal obesity, breast cancer risk also differed by menopausal status. For postmenopausal black women, a high waist-to-hip ratio (WHR) (>0.88 vs. ≤0.64 cm) was associated with increased risk for each tumor subtype , and a higher risk for TNBC tumors. In contrast, among premenopausal black women, high WHR (>0.88 vs. ≤0.64 cm) was only associated with increased risk of ER+ breast cancer  . This cot cancer . Other st cancer , 27; howt cancer .The Carolina Breast Cancer Study, which is contained within the AMBER Consortium, demonstrated an increased incidence of TNBC in premenopausal women. An association with obesity is suggested by the observation that women with a high compared to low WHR had a significantly higher risk of developing basal-type TNBC. This increased risk of TNBC in association with obesity applies to both pre- and postmenopausal black women , althougTo summarize, the relationship between adiposity and breast cancer risk is complex and varies depending upon several factors. Increased breast cancer risk in postmenopausal women is especially notable among those who are obese , as demoOn the one hand, early life obesity is protective against premenopausal breast cancer, whereas the scientific literature provides clear and consistent evidence linking high adult adiposity as a risk factor with postmenopausal breast cancer. Although the incidence of overall breast cancer is lower among black women compared to white women, black women have a higher incidence of ER- and TNBC tumors and their tumors tend to be of a higher grade than tumors in women from other racial and ethnic groups . The incObesity is associated with socioeconomic status (SES) in high-and-middle income countries . In highIntervention studies aimed at reducing the incidence of obesity can provide opportunities to decrease breast cancer risk, specifically post-menopausal breast cancer. The increase in obesity rates is associated with changes in the food and built environments which contribute to increased consumption of energy-dense foods and less physical activity. These changes result in a positive energy balance—the state in which energy intake exceeds energy expenditure—which, over time, can lead to obesity. Several studies have shown that reducing caloric intake and increasing physical activity may be protective against both pre- and post-menopausal breast cancer , 39. As The complex interplay of diet and physical activity, together with the role of adipose tissue, pose challenges to our understanding of the mechanisms by which obesity confers increased breast cancer risk. Furthermore, obesity is intertwined with social deprivation, environmental conditions, genetics, hormones, and epigenetic factors, all of which can impact breast cancer risk and the aggressiveness of breast cancer phenotypes. In this review we discuss obesity and diet-related biological mechanisms with the aim of identifying molecular and behavioral targets that can inform research into novel interventions to reduce breast cancer incidence and mortality. The focus of this review is on the relationship between obesity and postmenopausal breast cancer risk. Although it is an important topic, the interplay between adiposity and breast cancer survival is not addressed here.The increased adipose tissue that characterizes the state of obesity is not merely a passive reservoir to store lipids and energy, as once thought. Adipose tissue is biologically active, and is now considered to be an “endocrine organ,” given the multiple factors it produces that impact systemic energy metabolism, neuroendocrine function, and immune responses . These aIn obesity multiple metabolic changes are observed, including alterations in lipids, hyperglycemia and glucose intolerance, and insulin resistance/hyperinsulinemia , 41–43. Of note, all accumulations of adipose tissue, i.e., adipose depots, are not the same. The adipose depots that characterize obesity are complex and must be analyzed at a granular level in order to understand their effect on cancer risk. Excessive visceral deposits of adipose tissue, primarily in the abdomen, are considered to be the main culprits involved in disease causation , 48. SpeThese metabolic functions are intimately connected to the immune activities of adipose tissue . In addiThe dysfunctional milieu of obesity-associated adipose tissue has additional adverse immune effects, such as ectopic accumulation of lipids in non-adipose tissue, including tissues of the immune system: bone marrow and thymus . ObesityThe alterations in the immune system that are associated with obesity can predispose to development of 13 cancer types via a variety of mechanisms , 53, 55.2 (PGE2), an inflammatory factor, and hypoxia-inducible factor 1α (HIF-1 α) both participate in inducing aromatase production by adipose stromal cells (ASCs) (The increased incidence of estrogen-receptor-positive (ER+) breast cancer in obesity supports the role for estrogen, a steroid hormone, in breast carcinogenesis , bringins (ASCs) . Elevates (ASCs) , includis (ASCs) . This “os (ASCs) , 64, 65.At the molecular, mechanistic level, genetics, epigenetics, and microbiomics are likely involved in susceptibility to weight gain and obesity . These mBDNF, MC4R, NEGR, POMC)   gene, which was the topic of a recent systematic review that promulgated FTO gene as a possible mediator for the association between obesity and breast cancer (FTO gene encodes a dependent oxygenase related to 2-oxoglutarate that has a role in DNA demethylation but its molecular mechanism in obesity and metabolism has not been elucidated (FTO gene may influence the risk of breast cancer as well as obesity through expression of the homeobox transcription factor iriquois 3 (IRX3) gene. IRX3 is a developmental transcription factor that more recently has been implicated in regulating energy expenditure (Many gene variants have been found to be associated with obesity. Recent reviews highlight both the candidate gene approach utility for identifying monogenic obesity genes as well as genetic variants identified through Genome Wide Association Studies (GWAS), which implicate genes from several biological pathways in polygenic obesity –68. ThesR, POMC) –73, insu2, IRS1) , 74, adi2, IRS1)  and ener, MAP2K5 , 74, 76], MAP2K5 . Althoug, MAP2K5 , 78. Asst cancer . The FTOucidated . In theiucidated  suggesteenditure .With a great degree of complexity and flexibility, epigenetic mechanisms influence how genetic information is transcribed and translated into proteins, ultimately affecting health and disease, including the conditions of weight gain and obesity. In contrast to genetic modifications, which lead to a change in the base sequence of DNA, epigenetic changes are thought to be reversible and consist of chemical modifications to DNA  that occur in the absence of a change in the DNA sequence . EpigenePOMC) have also been found to be influenced by DNA methylation changes contributing to common obesity (PIM3 methylation (cg09349128), a gene involved in energy metabolism, mediated approximately 13% of the association between famine exposure and BMI.In mammals, the addition of methyl groups to DNA (methylation) occurs predominantly at cytosines adjacent to guanines (“CpG” sites) through DNA methyltransferases. Promoter DNA methylation disrupts the binding of transcription factors and attracts methyl-binding proteins that typically initiate chromatin compaction and gene silencing . Promote obesity . With th obesity . This st obesity . Investi obesity . They shESR1) gene hypermethylation, which may be involved in the development of breast cancer. Investigators hypothesized that BMI and estrogen-related reproductive risk factors may influence the methylation status of the ESR1 CpG loci in the normal breasts of healthy women. They found that ESR1 promoter methylation in women with a BMI ≥30 kg/m2 was higher than in the subgroups of women with BMI <25 kg/m2 or BMI 25–29 kg/m2 and was also higher in postmenopausal women compared with that in premenopausal women  coding a circulating lipoprotein lipase inhibitor (Angptl4), which resulted in an increase in triglyceride deposition in adipose tissue  that live inside and on the human body are referred to as the microbiome . Alteratividuals . Many meividuals . Backhedividuals . These re tissue . The mage tissue . Perhapse tissue .Microbial perturbations (dysbiosis) have been observed in breast cancer patients compared to healthy individuals , 105. HeSeveral observational studies found that adult weight loss was associated with decreased risk for postmenopausal breast cancer –109, altWeight loss, a state of negative energy balance, is believed to significantly influence postmenopausal breast cancer risk through alterations in several pathways including sex-steroid hormones, endocrine hormones, and inflammatory markers. Obesity-targeting weight loss interventions that include hypocaloric diets and/or exercise have been shown to significantly reduce total body weight, adipose tissue  and biomarkers associated with breast cancer risk . Here wep < 0.001), testosterone (p = 0.033), and SHBG (p < 0.001)  and free testosterone concentrations , 118. Fo< 0.001) . Researc< 0.001) , 118.p = 0.018) among women at increased risk for breast cancer , compared to the control group  composition. Several meta-analyses of weight loss randomized controlled trials (RCTs) examined the efficacy of low-carbohydrate (LC) vs. low-fat (LF) diets on weight change –143. OneFasting glucose and insulin may impact response to weight loss diets with different macronutrient composition. Researchers suggest that a LC diet may provide greater weight loss in overweight and obese women who are insulin resistant , 148; inFurthermore, it is possible that there is a differential weight loss response to diet composition and that biomarkers associated with breast cancer risk may mediate this association. For example, a LC vs. LF weight loss diet was associated with increased adiponectin concentrations in obese women; however, there were no correlations between weight loss and increased adiponectin . Other sAlthough our emphasis has been on weight loss as a remedy to obesity, other approaches are being tried. As previously discussed, increased physical activity has potential to decrease breast cancer risk, at least in part by reducing obesity . HoweverAnother agent showing benefits for weight management is liraglutide, a glucagon like peptide-1 (GLP-1) receptor agonist that is approved by the Food and Drug Administration (FDA) as an adjunct to diet and exercise for management of type 2 diabetes. A review of five randomized clinical trials showed that compared to placebo, liraglutide was associated with a higher proportion of patients achieving at least a 5-10% weight loss . The maiObesity has reached epidemic proportions in the United States and increasingly around the world. Undesirable health-related sequelae are expected to follow as the obese state is increasingly being observed in children and young adults. Obesity is physiologically complex, however, and we have discussed only a few of the endocrine, immunologic and molecular abnormalities that characterize this state. In addressing the need for reducing obesity we have concentrated on evidence derived from weight loss initiatives. However, other approaches are currently being undertaken. For example, physical activity as a major intervention, with or without accompanying diet directives, has potential to improve obesity-related metabolic parameters. Intermittent fasting approaches, including time-restricted feeding, are emerging weight loss strategies, which may also improve metabolic parameters. Bioactive food components such as omega-3-fatty acids are being studied as interventions to facilitate loss of weight. Finally, pharmacologic approaches, including agents such as metformin, need to be investigated in relation to their weight reducing efficacy.Breast cancer, the most common cancer in postmenopausal women in the U.S., is one of the malignant outcomes associated with chronic obesity. Thus, efforts to improve interventions to prevent breast cancer, along with other serious obesity-associated diseases, require a deeper understanding of the physiological basis of obesity as well as the development of interventions to reduce this high-risk state in the population.Despite the extensive research that has been ongoing into the multiple facets of obesity on general health and cancer in particular, huge gaps remain in our understanding of mechanisms and associations. Of immediate interest is the disconnect between obesity's positive association with postmenopausal ER-positive breast cancer and its inverse association with premenopausal ER-positive disease; what is the mechanistic basis for this difference? How do the duration and timing in the life cycle influence the chronic nature of obesity that appears to be linked to breast cancer? Additional gaps address the complex molecular mechanisms at the genetic and epigenetic levels which control expression of proteins that contribute to obesity. The integration of various omics data, including transcriptomics, proteomics, epigenomics, microbiomics, and metabolomics, may also assist in elucidating the link between obesity and cancer.The majority of the epidemiologic studies linking obesity to breast cancer used self-reported anthropometric measures  to assess risk. However, more meaningful assessments of body composition compartments , which capture known physiological and metabolic changes associated with breast cancer risk, need to be used in future studies. Also, one must not ignore the enormous effect the obesity epidemic is having on low SES populations, which in the future may potentially lead to associated chronic diseases, including cancer. Lastly, since the majority of the studies were conducted among Caucasian women, research is needed to understand the association between body fat distribution and specific breast cancer subtypes across various racial and ethnic groups.TA-C, SR, and BD each wrote sections of the manuscript and each reviewed and edited the manuscript for content and cohesion.TA-C, SR, and BD are employees of the National Cancer Institute, National Institutes of Health in Rockville, MD.


While numerous epidemiologic studies have found an association between higher serum 25-hydroxyvitamin D [25(OH)D] concentrations and lower breast cancer risk, few have assessed this association for concentrations >40 ng/ml.To investigate the relationship between 25(OH)D concentration and breast cancer risk across a broad range of 25(OH)D concentrations among women aged 55 years and older.Analyses used pooled data from two randomized clinical trials  and a prospective cohort (N = 1713) to examine a broad range of 25(OH)D concentrations. The outcome was diagnosis of breast cancer during the observation periods (median: 4.0 years). Three analyses were conducted: 1) Incidence rates were compared according to 25(OH)D concentration from <20 to ≥60 ng/ml (<50 to ≥150 nmol/L), 2) Kaplan-Meier plots were developed and 3) multivariate Cox regression was used to examine the association between 25(OH)D and breast cancer risk using multiple 25(OH)D measurements.P = 0.006). Second, Kaplan-Meier curves for concentrations of <20, 20–39, 40–59 and ≥60 ng/ml were significantly different (P = 0.02), with the highest proportion breast cancer-free in the ≥60 ng/ml group (99.3%) and the lowest proportion breast cancer-free in the <20 ng/ml group (96.8%). The proportion with breast cancer was 78% lower for ≥60 vs <20 ng/ml (P = 0.02). Third, multivariate Cox regression revealed that women with 25(OH)D concentrations ≥60 ng/ml had an 80% lower risk of breast cancer than women with concentrations <20 ng/ml , adjusting for age, BMI, smoking status, calcium supplement intake, and study of origin.Within the pooled cohort (N = 5038), 77 women were diagnosed with breast cancer . Results were similar for the three analyses. First, comparing incidence rates, there was an 82% lower incidence rate of breast cancer for women with 25(OH)D concentrations ≥60 vs <20 ng/ml D concentrations were associated with a dose-response decrease in breast cancer risk with concentrations ≥60 ng/ml being most protective. Breast cancer is the most common non-skin cancer in women . More thEpidemiologic studies by Gorham et al. ,4 and GaThe objective of this analysis was to investigate the relationship between 25(OH)D concentration and breast cancer risk across a broad range of 25(OH)D concentrations among women aged 55 years and older. Data from two randomized clinical trials (RCT) and a prospective cohort study were pooled: the 2007 Lappe et al. cohort D = 31 ng/ml, N = 1129) ,20, the Women in the 2007 Lappe et al. cohort (hereafter termed 2007 Lappe cohort) participated in a four year, population-based, double-blind, placebo-controlled trial of vitamin D and calcium supplementation in a 9-county area in Eastern Nebraska. Participants were randomly assigned to: 1) calcium plus vitamin D3 , 2) calcium , or 3) control . This trial was registered at clinicaltrials.gov as NCT00352170.In another study, women in the 2017 Lappe et al. cohort (hereafter termed 2017 Lappe cohort) participated in a four year, population-based, double-blind, placebo-controlled trial of vitamin D and calcium supplementation in a 31-county area in Eastern Nebraska. Participants were randomly assigned to: 1) intervention  or 2) control . This trial was registered at clinicaltrials.gov as NCT01052051.® Analyzer, Diasorin, Stillwater, MN for the 2017 cohort) at the Creighton University Osteoporosis Research Center Laboratory . The intra-assay coefficient of variation was 5% for IDS RIA and 5% for Liaison®. Additionally, the Creighton Laboratory participates in the Vitamin D External Quality Assessment Scheme (DEQAS) with findings on test samples regularly close to the international mean. Detailed descriptions of the Lappe trials and results of other outcomes can be found elsewhere [For both Lappe cohorts, inclusion criteria included women aged 55 years or older who were free of known cancer at enrollment and within the prior 10 years. As described previously –22, supplsewhere –22. All R2 values of 0.998 and 0.994 respectively). LC-MS/MS with dried blood spot cards has been validated against the radioimmunoassay method  [Women in the GrassrootsHealth cohort participated in a prospective population-based cohort study run by a non-profit public health research organization. Voluntary participants, who reside in 57 countries worldwide (91% in the United States or Canada) submitted home blood spot 25(OH)D test kits and completed online health questionnaires. There were no exclusion criteria nor any requirements related to 25(OH)D concentration or supplement intake dose. Participants included both genders and a wide range of ages; however, only female participants aged 55 years or older who were free of known cancer at enrollment and within the prior 10 years who completed at least two health assessments were included in this pooled analysis to match the inclusion criteria of the Lappe cohorts. As described previously , cancer rom 1.0) . All parOverall, this analysis included 1129 women from the 2007 Lappe cohort , 2196 women from the 2017 Lappe cohort , and 1713 women from the GrassrootsHealth cohort  .Demographic characteristics were summarized and comparisons between cohorts were performed using Kruskal-Wallis tests for age, BMI, calcium supplement intake (study and non-study combined for Lappe cohorts), and serum 25(OH)D. The chi-square test was used for smoking status. While data was collected for all types of cancer diagnoses, the outcome of interest for this current study was the diagnosis of breast cancer (invasive or in situ) during the observation periods. Age-adjusted breast cancer incidence rates were calculated using direct standardization to the 2010 US population .Three analyses were conducted to investigate the relationship between 25(OH)D concentration and breast cancer. First, breast cancer incidence rates and their 95% confidence intervals (95% CI) were calculated for successive 20 ng/ml strata of serum 25(OH)D concentration from <20 to ≥60 ng/ml using a moving average method  to assesSecond, Kaplan-Meier curves comparing the proportion of breast cancer-free participants by 25(OH)D group were developed to estimate breast cancer-free survival over time and account for varying lengths of follow-up. Four a priori categories of 25(OH)D were used: <20 ng/ml, 20–39 ng/ml, 40–59 ng/ml, and ≥60 ng/ml. The 20 ng/ml cut point is from the National Academy of Medicine  recommendation for bone health , the 40 www.r-project.org).Third, multivariate Cox regression was used to quantify the association between serum 25(OH)D and the risk of breast cancer after adjusting for the following breast cancer risk factors: age, BMI, smoking status, and calcium supplement intake. Indicator variables for study of origin were included to adjust for differences in study methods and demographics. Serum 25(OH)D concentration was assessed as a categorical variable , as was calcium supplement intake (<1000 mg/day vs ≥1000 mg/day) based on the NAM recommendation for bone health . Serum 2Baseline demographic characteristics of the pooled and individual cohorts are shown in During the observation periods, 77 women in the pooled cohort were diagnosed with breast cancer . The age-adjusted incidence rate of breast cancer was 512 cases per 100,000 person-years in the pooled cohort .P = 0.006).Within the pooled cohort, results were similar for the three analyses used to investigate the relationship between 25(OH)D concentration and breast cancer . First, breast cancer incidence rates according to 25(OH)D group are shown in P = 0.02), with the highest proportion breast cancer-free at 4 years in the ≥60 ng/ml group (99.3%) and the lowest proportion breast cancer-free in the <20 ng/ml group (96.8%). The proportion with breast cancer was 78% lower for ≥60 ng/ml vs <20 ng/ml (P = 0.02) in the Kaplan-Meier analysis.Second, Kaplan-Meier curves comparing the proportion of breast cancer-free participants by 25(OH)D group are shown in P = 0.03), adjusting for age, BMI, smoking status, calcium supplement intake, and study of origin (P = 0.02). Spline regression with 25(OH)D as a continuous variable revealed consistently lower risk of breast cancer with higher 25(OH)D concentration, with no evidence of increased risk in the higher 25(OH)D concentrations D concentration quartiles, baseline 25(OH)D concentration only, excluding non-US residents in the GrassrootsHealth cohort, and for each individual cohort. All revealed lower risk of breast cancer with higher 25(OH)D concentration.In this pooled cohort, 25(OH)D concentration was significantly inversely associated with breast cancer risk. All three analyses showed that women with 25(OH)D concentrations ≥60 ng/ml had significantly lower risk of breast cancer (~80%) compared to women with concentrations <20 ng/ml. There was a consistent decrease in breast cancer risk as 25(OH)D concentrations increased, with no evidence of increased risk in higher concentrations. Using a pooled cohort allowed for analysis across a wider range of serum 25(OH)D concentrations than any of the cohorts alone. While a novel approach, similar inclusion criteria were used for all three cohorts and analyses were adjusted for study of origin and breast cancer risk factors to account for differences in methodology and demographics.P<0.001) [The findings from this analysis support the previously reported inverse association between 25(OH)D and risk of breast cancer –18. AnotP<0.001) . The preThe Women’s Health Initiative (WHI) trial did not find an association between assigned vitamin D treatment group and breast cancer risk ; however2D3, binds to the vitamin D receptor (VDR) in normal breast epithelium and this complex regulates the cell cycle, promotes differentiation, increases cell-to-cell adhesion, protects cells from DNA damage, regulates cytokines, activates immune cells, and suppresses inflammation, all of which may act to reduce malignant transformations [2D3 [Vitamin D may play a number of roles in the prevention of breast cancer development and progression. The biologically active form of vitamin D, 1,25(OH)rmations . In brearmations . Additioons [2D3 –42. Studons [2D3  and detaons [2D3 . These mP = 0.02 for ≥60 vs <20 ng/ml). There was only one case of breast cancer diagnosed after one year among those with 25(OH)D concentrations ≥60 ng/ml. This woman’s diagnosis occurred 2 months into year two. Since there is a time delay between cancer initiation and diagnosis, many undiagnosed cancers that existed at enrollment would be diagnosed during the first year. Therefore, it is possible that analyses among women free of breast cancer at one year would better assess vitamin D’s specific role in prevention rather than prevention and tumor arrest combined.Whether our findings reflect prevention of the primary tumor or treatment of early stage, undiagnosed cancer by vitamin D is not clear. Of interest, the results for women who were followed and free of breast cancer at the end of the first year revealed a stronger association between 25(OH)D concentration and breast cancer risk , the effects of these risk factors did not reach statistical significance in this analysis. Since an inclusion criterion for these cohorts was age 55 years and older, the exclusion of younger women may have diminished the effect of age in this analysis. If younger women were included in this study we would expect to see a significant increase in breast cancer risk with age and possibly the effect of age-related changes in vitamin D metabolism. Also, information on dietary calcium intake was not available for the GrassrootsHealth cohort so this analysis only assessed supplemental calcium intake. However, it is possible that dietary calcium intake or total calcium intake would have been a significant predictor of breast cancer risk. Additionally, the small proportion of current smokers may have limited the ability of this study to detect an association between smoking status and breast cancer.Strengths of this analysis include using a wider range of 25(OH)D concentrations than most other studies and employing multiple analysis techniques with findings of a similar magnitude. Also, using serum 25(OH)D concentration is a better indicator of vitamin D status and statistically more powerful than using treatment group or intake amount because it captures the effect of multiple vitamin D input sources , overcomes the inherent bias of treatment compliance, and accounts for inter-individual variability in dose response . All thrLimitations of the analysis include the possible lack of generalizability to younger women and men. However, since other studies have found a significant association between higher 25(OH)D concentrations and lower breast cancer risk in younger women –13,18, wThe current NAM recommendation of 20 ng/ml (50 nmol/L) is based solely on bone health , yet it Focusing on primary prevention and implementing evidence-based interventions is needed to substantially decrease breast cancer incidence and associated mortality and economic costs. The national cost of female breast cancer in 2010 was estimated to be $16.5 billion . If wome


Studies with direct measures of body fat distribution are required to explore the association between central and general obesity to cancer risk in postmenopausal women. This study investigates the association between central obesity and general obesity to overall/site-specific cancer risk in postmenopausal women. The analysis included 4,679 Danish postmenopausal women. Body fat distribution was evaluated by whole-body dual-energy X-ray absorptiometry scanners. Cancer diagnoses were extracted from the Danish Cancer Registry and multivariable Cox regression models explored the association between cancer risk and central obesity after adjusting for BMI. Our results showed that high central obese women had a 50% increased risk of overall cancer relative to low central obese women . For site-specific cancers, central obesity was significantly associated with Respiratory , Gastrointestinal  and Female genital organs  cancer diagnoses. Sub-analyses stratified by smoking-habits found a significant association between central obesity and a cancer diagnosis for current  and former smokers . These analyses suggest that central obesity is associated with some cancers in postmenopausal women independent of BMI. A national health profile made by the Danish Health Authority showed that 51.5% of Danish women in the age range of 65–74 years were overweight or obese in 20172. The same trend of increasing obesity among the elderly is observed in the rest of the western world3.Obesity is an increasing problem in developed countries comprising a major global health challenge6. There is strong evidence that obesity, measured by BMI, is a risk factor for a variety of different cancers, including oesophagus, pancreas, liver, colorectum, breast  and ovary cancer6. It is estimated that almost 10% of cancer incidences in 2012 were due to overweight or obesity7. However, the current body of evidence relies almost exclusively on indirect anthropometric measures of obesity, e.g. body mass index (BMI), waist circumference (WC) and/or waist-to-hip ratio (WHR)8, which are associated with major limitations. In women, menopause initiates a shift of body fat towards a higher level of abdominal/visceral adiposity9, which is not captured by BMI. Moreover, anthropometric measures fail to differentiate between lean and fat mass10. Thus, studies with direct measures of body fat distribution are required to explore the association between body fat distribution and cancer risk in postmenopausal women. To this end, dual-energy X-ray absorptiometry (DXA) scanning is the gold standard for direct determination of whole-body and regional distribution of lean and fat mass, but only a few large-scale epidemiological studies have applied this method11.Several epidemiological studies have evaluated the link between obesity and cancer risk12.The present study explored the association between body fat distribution in postmenopausal women and cancer risk using data from the Prospective Epidemiological Risk Factor (PERF) study13.Here, DXA scans were available at baseline and data for cancer diagnoses along with death records for 5,855 Danish postmenopausal women were retrieved over a 12-year follow-up period. Accordingly, we examined the association between obesity and overall cancer risk in the postmenopausal women included in the PERF cohort. Obesity was measured both by BMI and trunk-to-peripheral fat ratio, to reflect overall and central obesity respectively. The principal objective was to explore the potential discrepancy between whole-body and regional obesity derived from DXA-scans adjusted for known risk factors for cancer and mediators of obesity. We further explored the association between obesity and site-specific cancer risk, and finally stratified our analyses by smoking habits as a potential moderating factor12. Women who previously participated in clinical prevention trials or had been screened for inclusion in randomized clinical prevention trials at the Center for Clinical and Basic Research (CCBR) were invited to participate in PERF. The characteristics obtained in the PERF cohort including lifespan and disease history are comparable with known distributions from elderly Danish women according to statistics Denmark14. The study was designed to obtain knowledge about the determinants of age-related diseases in elderly women and the participants are considered representative of postmenopausal Danish women.PERF is an observational, prospective cohort consisting of 5,855 Danish postmenopausal women12. The examination included a comprehensive medical workup along with an interview with a doctor or a nurse covering questions related to lifestyle, demographics, family disease history, reproduction, smoking history, alcohol consumption and level of education. All participants had their weight and height measured which allowed for calculation of BMI (kg/m2).The PERF baseline population was examined between 1999 and 2001 at CCBR located in either Ballerup or Aalborg (Denmark)15 and the Danish adult diabetes registry16 through a personal subject identification number (CPR-number). Cancer categories were classified according to WHOs international Classification of Diseases 10 (ICD10) . Co-morbidities at baseline were extracted from the Danish National Patient Register and the Danish adult diabetes registry.Participants of the study were matched to the Danish Cancer Registry, the National Danish Causes of Death Registry, the Danish National Patient Register17 and was calculated by division of fat mass in the trunk area with fat mass in arms and legs. DXA-scans were normalized into z-scores for analysis with the largest population as the reference (HOLOGIC QDR-4500). Before doing so it was insured that the three groups had the same age, weight and height distribution. Central obesity was normally distributed and DXA-scan measures of this cohort were consistent with reference values provided by T. Kelly et al.18. For analysis and comparison, the central obesity and BMI variables were divided into quartiles.Regional adiposity ) measures were performed with DXA scanners . Central obesity was defined as the trunk-to-peripheral fat ratioWomen with a diagnosis of solid cancer after baseline and women not present in the Danish Cancer Registry (non-cases) were included in the analysis. Women with only non-solid cancer or non-malignant tumours specified as benign tumours, non-melanoma skin cancer, hematologic cancer, desmoplasia and neoplasms of uncertain behaviour were excluded from the analysis. Lastly, women with a cancer diagnosis within the first 6 months after baseline were removed to reduce the risk of reverse causality Fig. . In the All continuous variables were normally distributed. Continuous and categorical baseline characteristics of women with and without a cancer diagnosis were compared using a t-test and a chi-squared test, respectively Table . A Cox r19.The time-scale of the model was age. Participants entered the analysis with their baseline age and exited with their age when they first got a cancer diagnosis at least 6 months after baseline. Non-cases exited the analysis with their censoring-age being the age at the end of the study (December 2012), the age when leaving Denmark or the age at death, whichever came first. Age was used as time-scale in the Cox analyses to ensure that the estimation was based on comparisons of individuals of the same age to prevent confounding by ageMultivariable Cox regression models stratified by smoking habits were done by classifying the participants into three groups: never, former and current smokers. To test for trends in the categorical obesity variables, study participants were assigned with the median value within their quartile and the resulting variable was fitted as a continuous variable in the regression models.Variance inflation factor (VIF) values were estimated for each regression model. None of the VIF values were larger than 3 indicating no existence of collinearity. All statistical analyses were performed using R (V.3.3.2) and the survival package (V.2.40.1). Level of statistical significance was 0.05.The PERF study protocol was approved by the Copenhagen County Scientific Ethics Committee (jr: KA 99070 gm). All participants in the present analysis provided written informed consent. All methods were carried out in accordance with the approved guidelines and regulations.Of the 4,679 women who were DXA-scanned in the PERF I study, 809 were diagnosed with cancer at least 6 months after baseline and 3870 women had no history of cancer (non-cases) Fig. .Table Previous history of disease for the women in the total cohort was distributed in the following way: 23% had a history of diseases of the circulatory system, 11% had a history of diseases of the respiratory system, 21% had a history of diseases of the digestive system and 25% had a history of diseases of the musculoskeletal system.To determine if body fat distribution was associated with cancer risk, both univariable and multivariable Cox regression analyses were conducted Table .In the univariable Cox regression, the DXA-derived measure of central obesity showed strong positive significant associations with overall cancer risk, whereas BMI was not associated significantly with cancer risk Table . In the To determine whether the results were applicable to all types of cancer, five multivariable Cox regression analyses with different site-specific cancers were performed. The cancer diagnoses were distributed between the five site-specific categories in the following way: GI: n = 223; respiratory: n = 122; FGO: n = 108; breast: n = 185; other: n = 171.For respiratory cancers, the results showed that the fourth quartile of central obesity was significantly associated with increased cancer risk when compared to the first quartile . For BMI both the third and fourth quartiles of BMI were significantly negatively associated with cancer risk compared to the first quartile . Only for FGO cancers, the same association was observed when comparing the fourth quartile of central obesity with the first quartile .In contrast, BMI was non-significant in both analyses Table . Trend aFor breast cancer, central obesity was not significantly associated with cancer risk, but here the fourth quartile of BMI was significantly associated with increased breast cancer risk when compared to the first quartile . In a test for trend, BMI was also significant in the analysis of breast cancer (p for trend = 0.01).Neither BMI or central obesity was associated with an increased risk of other cancers Table .To determine whether central obesity was independently associated with cancer risk regardless of smoking habits, the women were stratified into three groups; never smokers , former smokers  and current smokers . The prevalence of a solid cancer diagnosis at least 6 months after baseline within the three groups was distributed in the following way; never smokers: 18% (n = 333), former smokers: 24% (n = 272) and current smokers: 24% (n = 204).A multivariable Cox regression analysis adjusted for covariates revealed that the fourth quartile of central obesity was significantly associated with increased risk for overall cancer diagnosis in current smokers when compared to the first quartile of central obesity . In former smokers, the second, third and fourth quartiles of central obesity were all significantly associated with increased overall cancer risk   high central obesity was independently associated with increased risk of overall cancers, (ii) high central obese women had significantly increased risk of respiratory, GI and FGO cancer when compared to low central women and (iii) when stratifying the analysis by smoking habits, high central obesity was significantly associated with cancer risk in former and current smokers.These findings extend our understanding of the link between obesity and cancer and provide strong support for a positive association between central obesity and risk of some cancers in postmenopausal women. Furthermore, our findings underline the importance of including measures of body fat distribution in risk analyses, as obesity derived from BMI and body fat distribution describe two different obesity-types that have a different impact on risk.20. In alignment with our results, Wang et al. found a significant association between WC and increased risk of colorectal cancer in a cohort of 87,261 women21. For lung cancer, previous studies have shown an increased BMI to be a protective factor22. Reeves et al. found a 34% decreased risk of lung cancer for every 10 unit increase in BMI in a cohort of 1.2 million elderly women23. These results are consistent with our results which showed that an elevated BMI was inversely associated with respiratory cancer risk. In contrast, we found a significant positive association between high central obesity and respiratory cancers after adjusting for BMI and other cofounders. This suggests that while a high BMI is protective for respiratory cancer, high central obesity might be a risk factor. These results substantiate a recent meta-analysis, which concluded that central obesity, measured by WC and WHR, may play a role in the development of lung cancer24.Several studies have investigated the relationship between different cancer subtypes and anthropometric measures of obesity25. Other studies have also suggested that reduced oxidative DNA damage, which is inversely correlated to BMI, could explain the protective effect of a high BMI in lung cancer27. Nonetheless, further research is warranted to understand the associations between central obesity and general obesity to lung cancer.The biological mechanism behind the contradictory association between central obesity and general obesity to lung cancer remains poorly understood. Possible explanations could involve hyperinsulinemia and increased unbound estrogens, both of which have a stronger correlation to central obesity compared to general obesity28. In the Million Women Study, a 10 unit increase in BMI was associated with a four times higher likelihood for developing endometrial cancer23, which is in line with our results where central obesity is significantly associated with FGO cancer. Furthermore, in a study of 10,960 elderly women, Rohan et al. showed a strong positive association between both BMI and ratio of trunk fat mass to average of legs fat mass and breast cancer28. In this study, we also found a significant association between BMI and breast cancer, but central obesity did not show any significant association to breast cancer risk, though a similar trend for central obesity was observed. An explanation for the conflicting results might be the lower power in this study or that we in this study include both BMI and central obesity in the analysis whereas Rohan et al. perform separate analyses for the obesity measures.The link between obesity and hormone-associated cancers, such as breast, endometrial and ovarian cancer, is well established in postmenopausal women and thought to be mediated by increased concentrations of circulating sex hormones28. In line with this, we have previously seen, in a PERF subpopulation, that localization of fat mass was more important for atherosclerosis than general obesity29. Level of physical activity may also influence the accumulation of fat. In a recent study including 10,976 individuals from the general population30, cardiorespiratory fitness was found to be inversely associated with both central obesity and low-grade inflammation independent of BMI. Moreover, physical inactivity is an independent cause of the accumulation of visceral fat31 and regular exercise decreases central obesity and exerts anti-inflammatory effects32. Thus, high central obesity may reflect low fitness and low-grade inflammation, which are both associated with an increased risk of cancer33.Postmenopausal women tend to experience a re-distribution of body fat from a gynoid to an android pattern which has been linked to the metabolic syndrome and increased risk of cardiovascular diseases35. Furthermore, an association between lung cancer and BMI in former smokers has previously been shown36, though others have provided evidence that obesity may act as a protective factor against lung cancer37. In this study we found that high central obesity was significantly associated with increased risk of overall cancer in former and current smokers, but not in never smokers. We also found that the second quartile of BMI was inversely associated with overall cancer risk in former smokers. This substantiates the claim of stratification by smoking habits when assessing obesity and cancer risk13, and suggests that in former and current smokers general and central obesity reflect different risk.Smoking is also known to affect the body fat distribution resulting in smokers having a higher waist circumference compared to non-smoker28. This article adds to the knowledge about age-related diseases and postmenopausal obesity. Understanding the complex biology underlying the association between central obesity and menopause could, therefore, serve, not only as prevention strategies for cardiovascular diseases but also as cancer prevention strategies.As a whole, the results of this paper support the growing evidence that the distribution of body fat after menopause is as important as the fat mass itself when studying the risk of obesity-related diseases38.Limitations of this study include the number of cancer diagnoses, which was low when both sub-dividing for site-specific cancer and stratifying by smoking habits. Due to the small sample size, it was also impossible to subdivide the cancer-types even further by individual cancer sites. The data is restricted to postmenopausal Danish Caucasian women and may therefore not be generalizable to the general world population. The choice of variables to include in the analyses was restricted to the data present in the PERF study. The often-used measures WHR and WC were not recorded at baseline, why it was impossible to compare these measures with the central obesity measure from the DXA-scanning. Lastly, the study design does not allow an assessment of the causal role of central obesity in relation to cancer risk. The strength of this study includes the prospective design, the long follow up period and the access to the Danish health registries. Furthermore, the PERF cohort represents a limited number of cohorts where postmenopausal women are evaluated with DXA-scansIn conclusion, our study supports several relevant hypotheses. Firstly, we show that central obesity is independently associated with an increased risk of overall cancers. Secondly, we show that women with high central obesity have more than 50% increased risk of respiratory, GI and FGO cancers respectively compared to women with low central obesity. Lastly when stratifying the analysis by smoking habits high central obesity was significantly associated with cancer risk in former and current smokers. These results suggest that central obesity is at least partially independent of BMI and that different types of obesity have a diverse impact on health. This underlines that health strategies on keeping a healthy weight should be supplemented by recommendation on preventing central obesity, especially for women facing the menopause transition.Supplementary figure 1


To address the possible association between the use of metformin, other forms of antidiabetic medication (ADM) and statins with the incidence of breast cancer in women with type 2 diabetes (T2D).Data were collected from a Finnish nationwide diabetes database (FinDM). The study cohort consisted of women diagnosed with T2D in 1996–2011 in Finland. In full-cohort analysis, Poisson regression was used to estimate hazard ratios (HRs) in relation to use of metformin, insulin, other forms of oral ADM and statins. In nested case–control analysis, up to 20 controls were matched for age and duration of diabetes to each case of breast cancer. Conditional logistic regression was used to estimate HRs in relation to medication use and cumulative use of different forms of ADM, and statins.2300 women were diagnosed with breast cancer during follow-up. No difference in breast cancer incidence was observed between metformin users  or statin users  compared with non-users. In nested case–control analysis the results were similar. Use of insulin  was associated with a slightly increased incidence of breast cancer.No evidence of an association between the use of metformin or statins and the incidence of breast cancer in women with T2D was found. Among insulin users, a slightly higher incidence of breast cancer was observed.The online version of this article (10.1007/s10549-019-05185-0) contains supplementary material, which is available to authorized users. Breast cancer is globally the most common cancer among females in both developed and developing countries . Among aMetformin is commonly used as first-line oral medication for T2D. Over the years, it has been suggested that metformin may decrease breast cancer risk , but on Statins, i.e. 3-hydroxy-3-methylglutaryl-coenzyme A (HMG-CoA) reductase inhibitors, are some of the most commonly used cholesterol-lowering drugs in the world. Reducing levels of mevalonate with statins are associated with apoptosis of cancer cells , 13. LipIn this register-based, cohort and nested case–control study, we enriched the evidence base concerning the association between the use of metformin, other types of ADM, and statins, with the incidence of breast cancer in women with T2D. By virtue of the large and comprehensive Finnish nationwide registers available to us, some of the pitfalls in previous studies could be overcome in this one.In this article, we follow STROBE guidelines for reporting observational studies .A Finnish diabetes database (FinDM) has been created for epidemiological monitoring of diabetes in Finland . This daThe FinDM data were linked to the files of the Finnish Cancer Registry, which contain all cancer cases diagnosed in Finland since 1953 [The FinDM dataset contains data on approximately 240,000 women with T2D. In this study, we included women who were at least 40 years old and were newly diagnosed with T2D between the 1st of January 1996 and the 31st of December 2011. Women with prior breast cancer  and women with T2D who were diagnosed before 1996, and also women whose eligibility criteria would have been met only after 2011, were excluded. The final number of women with T2D in the cohort was about 140,000  metformin, (2) other types of oral ADM, (3) insulin and (4) statins. Details on Anatomical Therapeutic Chemical (ATC) codes of oral ADM and statins are listed in Supplementary Table. Exposure to a given medication was considered to begin a full year after its purchase date in order to avoid reverse causality problems. In the full-cohort analyses and in the nested case–control analyses, the study subjects were categorized as exposed to the drug from this moment onwards throughout the follow-up time. Additionally, cumulative use of metformin and statins, other forms of oral ADM and insulin were estimated by using defined daily doses (DDDs) purchased during the entire follow-up period (Jan. 1996–Dec. 2011).Follow-up of each patient started 365 days after diagnosis of T2D. It ended on the date of breast cancer diagnosis, death, or the end of study period (the 31st of December 2011), whichever occurred earliest.A nested case–control study within the cohort was conducted to evaluate the association between breast cancer and the cumulative use of the types of medication under study. This design, versus a full-cohort design, enables more straightforward calculation of the number of defined daily doses of medication used by each woman prior to their respective index date. For each case subject, up to 20 controls were selected without replacement from those women in the cohort who were alive and at risk of breast cancer at the date of breast cancer diagnosis of the case, and who were also matched for both age (date of birth ± 182 days) and duration of diabetes (± 182 days).In the full-cohort analysis, a Poisson regression model  was usedOur final study cohort consisted of 141,194 women diagnosed with T2D between 1996 and 2011 and at least 365 days after diabetes diagnosis  of breast cancer was highest in the group of women aged 60–69 years  for the amount of DDDs being 1200 or more when compared with no use at any time .In our study, no evidence of any association between metformin use and the incidence of breast cancer in either the full-cohort analysis or in the case–control analysis was found in women with T2D. A similar result was observed in connection with use of other forms of ADM and statins. However, insulin use was found to be associated with a slightly increased incidence of breast cancer in the full cohort as well as in the case–control analysis. Furthermore, increasing cumulative use of insulin was observed to be positively associated with the risk of breast cancer in a monotonic manner.Several epidemiological studies on breast cancer incidence and metformin use have been published before. In some of them, metformin use seems to be related to a lowered breast cancer incidence –26, at lThere are also several reviews and meta-analyses in which it has been concluded that statin use is not associated with the risk of breast cancer –42. In aMajor strengths of our study are the large sample size and the availability of reliable and comprehensive national registers. The patients’ details are entered into the diabetes register at the time of the first reimbursement for any form of ADM, and thus the data in the register concerning the date of diagnosis of diabetes are considered to be accurate. To our knowledge, this study is the first one in which the association between statin use and the incidence of breast cancer in women with T2D has been explored. Also, our study has involved one of the largest study populations in addressing the relationship between ADM and breast cancer incidence.A weakness of our study is that the FinDM database includes only information available in the registers. Therefore, we lack information on some known risk factors as regards the development of breast cancer, including body mass index (BMI), parity, use of contraceptives, use of hormone replacement therapy and family history. However, it is not known how these risk factors (apart from BMI) differ within ADM and statin users. Obesity is a common risk factor of both T2D and breast cancer. In the United Kingdom and the Netherlands, for example, metformin users have been found to have a higher BMI , 45. SomIn conclusion, we found no association between metformin or statin use and the incidence of breast cancer in women with T2D. However, insulin use  was found to be associated with an increased incidence of breast cancer.Below is the link to the electronic supplementary material.Supplementary material 1 (XLS 35 KB). Supplementary Table Details of Anatomical Therapeutic Chemical (ATC) codes and percentages of oral ADM and statins


An association of Lynch syndrome (LS) with breast cancer has been long suspected; however, there have been insufficient data to address this question for each of the LS genes individually.MLH1 (N = 65), MSH2 (N = 94), MSH6 (N = 140), or PMS2 (N = 124) identified via clinical multigene hereditary cancer testing. Standard incidence ratios (SIRs) of breast cancer were calculated by comparing breast cancer frequencies in our study population with those in the general population .We conducted a retrospective review of personal and family history in 423 women with pathogenic or likely pathogenic germ-line variants in MSH6 , 1.56–2.86) and PMS2  were associated with a statistically significant risk for breast cancer whereas no association was observed for MLH1  or MSH2 .When evaluating by gene, the age-standardized breast cancer risks for MSH6 and PMS2, are associated with an increased risk for breast cancer and should be considered when ordering genetic testing for individuals who have a personal and/or family history of breast cancer.Our data demonstrate that two LS genes,  MLH1, MSH2, MSH6, and PMS2, and 3′ deletions of EPCAM, a gene just upstream of MSH2, cause Lynch syndrome (LS). There is evidence that cancer risk depends on the affected gene. MLH1 and MSH2 are most commonly associated with a higher risk of colorectal cancer.1 Additionally, MSH2 has been associated with a higher risk for extracolonic cancers, and female MSH6 carriers may have the highest risk of endometrial cancer. While the LS tumor spectrum has been well established as including colon, endometrial, ovarian, stomach, small bowel, hepatobiliary tract, ureter/renal pelvis, pancreas, brain, and sebaceous neoplasms, the risks of other cancers, including breast, prostate, and adrenocortical tumors, are less clearly delineated.2Germ-line pathogenic variants (PVs) in the mismatch repair (MMR) genes 1 Screening for MMR deficiency by microsatellite instability and immunohistochemistry assays is often performed on colorectal and endometrial tumors to identify patients with LS. Although screening for MMR deficiency in breast tumors is currently not standard clinical practice, multiple studies have shown that breast cancers from women with LS are more likely to exhibit microsatellite instability and loss of one or more MMR proteins via immunohistochemistry, compared with sporadic breast cancers.14The MMR pathway is responsible for repairing single base pair mismatches and small insertions or deletions that occur when DNA polymerase attempts to replicate small repeat sequences. Pathogenic variants within the MMR genes result in errors in DNA repair, leading to an increased mutation load in MMR-deficient cells.16 Ascertainment bias may have affected results: many previous LS studies assessing breast cancer ascertained their study cohorts based on criteria heavily weighted toward colorectal cancer. As a result, many study cohorts consisted only of MLH1 and MSH2 carriers although some also included MSH6.23 A few studies have included all four MMR genes, but presented only a single combined breast cancer risk, likely due to a small number of MSH6 and PMS2 carriers.16 Thus, the lack of consistent association of breast cancer and LS in previous studies may reflect the genetic composition of the cohorts. While it has been suggested that breast cancer risk may vary by gene in LS, no one study has examined gene- and age-specific breast cancer risks for all four MMR genes. The aim of our study was to characterize breast cancer risks for each MMR gene in our group of women who were identified to have a PV via germ-line hereditary cancer panel testing for a variety of cancer-related indications.Clinical studies evaluating breast cancer risk in women with LS have been conflicting, with some showing up to a fourfold increased breast cancer risk and others reporting no increased risk.24 Combined EPCAM-MSH2 deletions were included in the MSH2 PV cohort. Individuals with a second PV in an MMR or another gene (excluding single PV in MUTYH) were excluded. A list of the multigene panels (with gene lists) included and PVs identified can be found in Supplementary Tables We retrospectively queried more than 50,000 women who had multigene hereditary cancer panel testing completed at GeneDx between 2013 and 2016, identifying 423 women with a single germ-line pathogenic variant or likely pathogenic variant (collectively referred to here as PV) in any of the four MMR genes. All sequence variants were classified based on the 2015 American College of Medical Genetics and Genomics/Association for Molecular Pathology guidelines for the interpretation of sequence variants.in situ. This study was approved by the Western Institutional Review Board, Puyallup, WA (WIRB 20162523).Demographic, clinical, and family history information was obtained from test requisition forms and accompanying clinical documents supplied by the ordering provider at the time of the test order. Pathology reports were not requested to confirm diagnoses. Subjects were limited to females over the age of 18. Breast cancer was defined as any invasive breast neoplasm or ductal carcinoma 26 Local realignment around insertion/deletion sites and regions with poor mapping quality was performed using the Genome Analysis Toolkit version 1.6 IndelRealigner.27 Variant calls were generated by the union of SAMtools version 0.1.18,28 Genome Analysis Toolkit UnifiedGenotyper,27 and a GeneDx-developed heuristic caller. Capillary sequencing  on a newly extracted DNA sample was used to confirm all variants with clinical or uncertain significance and to fill in sequence for regions with fewer than 15 reads by next-generation sequencing. Any potential variant position with coverage of fewer than 50 reads was reviewed by analysts and analyzed by capillary sequencing if unclear. Long-range polymerase chain reaction was used to distinguish variants in PMS2 from those in the PMS2 pseudogene PMS2CL. Deletion/duplication analysis was performed via custom-designed exon-targeted array comparative genomic hybridization (Agilent). Confirmation of copy-number changes detected on array comparative genomic hybridization was performed by multiple ligation-dependent probe amplification, repeat microarray analysis, or quantitative polymerase chain reaction using the Universal ProbeLibrary .Genomic DNA was isolated from whole blood using a QIAsymphony DNA kit, and from oral rinse using a QIAsymphony DSP Virus/Pathogen Midi Kit . Genomic DNA was enriched for the complete coding region and splice-site junctions of the genes of interest using custom SureSelect targeted capture . Next-generation sequencing and deletion/duplication analysis were performed for all coding regions as well as a portion of the 5′ untranslated region, 3′ untranslated region, and intronic regions for all genes on each panel, with the exception of EPCAM, for which only deletion/duplication analysis was performed. The products were sequenced on Illumina MiSeq or HiSeq instruments with paired-end reads . DNA sequence was mapped to a masked version of the published human genome build University of California–Santa Cruz hg19/GRCh37 reference sequence using BWA-Mem version 0.7.8.30 Corresponding 95% confidence intervals (95% CI) were calculated using the Poisson approximation distribution. SIRs for endometrial, colorectal, and ovarian cancer were also calculated using their respective incidence rates from SEER 18. All statistical analyses were conducted using RStudio 0.99.902.31 The Kaplan–Meier method was used to estimate cumulative risk and corresponding 95% CIs for breast cancers to age 60, stratified by MMR gene.32 Log-rank test was used to compare incidence rates between groups. All reported p values are two-tailed with a significance level of 0.05.Standardized incidence ratios (SIRs) for breast cancer were calculated for each gene as the number of observed cancers to the number of expected cancers based on breast cancer incidence in the general population. The expected number of cases was estimated for each 5-year age group from 20 to 85 as the time at risk multiplied by the reference population incidence rates. The population-based incidence rates were obtained using SEER*Stat statistical software from the Surveillance, Epidemiology, and End Results (SEER) 18 data, which includes 18 cancer registries representing 27.8% of the US population.MSH6, 33.1% (140/423); PMS2, 29.3% (124/423); MSH2, 22.2% (94/423); MLH1, 15.4% (65/423). The 423 women in our study harbored 241 unique PVs, the majority of which  were predicted to result in a truncated protein or a transcript subject to nonsense-mediated decay , while the rest were missense or small in-frame deletions  . The average age at time of genetic testing was 52.5 (±12.1) years  of the cohort, with 1.4% (6/423) reporting a history of more than one primary breast cancer. The average age at first breast cancer diagnosis was 50.2 years .Approximately half of the women with a MMR PV were referred for testing with either the Comprehensive Cancer Panel  or the Breast/Ovarian Cancer Panel , both of which contain genes related to breast cancer and LS . A diagnosis of breast cancer, irrespective of other personal cancer history, was reported more frequently in women with MSH6 or PMS2 PVs  compared to women with MLH1 or MSH2 PVs  (p < 0.001)  compared to women with PVs in MLH1 or MSH2  (p < 0.001)  Figure . Further) Figure .Figure 1MSH6 or PMS2 (average number of reported cancers per family = 1.46 and 1.52) whereas colon cancer was more commonly reported in family members of probands with a PV in MLH1 or MSH2 (2.62 and 2.12). The proportion of probands (excluding the seven relatives in our cohort) reporting a personal or family history of breast cancer but no colorectal, endometrial, or ovarian cancer was lower among those with MLH1 or MSH2 PVs  than among those with PVs in MSH6 or PMS2  (p < 0.001).The average numbers of reported breast, ovarian, endometrial, and colorectal cancers per family showed similar results to personal cancer histories Figure . Breast MSH6  and PMS2 . MLH1  and MSH2  were not found to be associated with breast cancer.Breast cancer risk was found to be approximately twofold higher  in our aggregate mismatch repair PV cohort compared to the general population  for MSH6, 16.1%  for MSH2, and 15.5%  for MLH1 PV carriers. MSH6 and PMS2 had a statistically significant greater cumulative incidence of breast cancer compared with MLH1 and MSH2 (p < 0.001).Cumulative incidence of breast cancer was calculated and illustrated via Kaplan–Meier analysis Figure . The cumn = 416) were evaluated to determine if they met Amsterdam II, Revised Bethesda Guidelines, and the National Comprehensive Cancer Network (NCCN) BRCA1/2 Testing Criteria  or MSH2  PVs, compared with MSH6 and PMS2, were more likely to meet Amsterdam II criteria. Women with MLH1 PVs most frequently met Revised Bethesda Guidelines . A higher proportion of women with MSH6  or PMS2  PVs met NCCN BRCA1/2 testing criteria compared to those with MLH1  or MSH2  PVs. Overall, our cohort of women with MMR PVs more commonly met NCCN BRCA1/2 testing criteria  than any of the established LS clinical or testing criteria .Unrelated probands , 11.1% (46/416) reported no personal or family history of these cancers. In the absence of large panel testing, many might not have been tested for the MMR genes. In addition, three women with breast cancer were found to be positive for a MMR gene PV only after having normal results on a smaller, high-risk breast panel.MSH6 and PMS2 PVs in our cohort, whereas no breast cancer association was observed for MLH1 or MSH2. PVs in MSH6 and PMS2 were found to confer 31.1% and 37.7% cumulative risks for breast cancer by the age of 60 while PVs in MLH1 or MSH2 were found to confer breast cancer risks close to the expected general population risk, 16.1% and 15.5%, respectively.We found a twofold and threefold increased risk of breast cancer for the women with MSH6 and PMS2 PV carriers, many previous studies evaluating breast cancer risk in association with the MMR genes are not suitable for direct comparison with our findings.16 In one retrospective study with a design more similar to ours, Engel et al.21 found an almost twofold increased breast cancer risk in a cohort of 1,107 women with PVs in the MMR genes . Although Engel’s study did not include any women with PMS2 PVs and included a smaller proportion of women with MSH6 PVs  than the current study (33.1%), our SIR of 1.96 for all four MMR genes was similar to theirs.Due to differences in study design, cohort ascertainment, and overall proportion of 36 As LS study cohorts in the literature have historically been ascertained using established clinical and/or testing criteria, resulting in overestimation of published CRC risks, we did not use CRC risks as a metric for comparison.37 The fact that the endometrial and ovarian SIRs in our cohort are consistent with previously published SIRs supports the validity of our approach.As a clinical laboratory, it was important to determine whether our calculated SIRs for breast cancer might be skewed if our referral population were higher risk than the general population. We therefore calculated SIRs for well-established female-specific LS-associated cancers  using the same cohort of 423 women with MMR PVs. In aggregate, the endometrial cancer risk was found to be 13-fold higher  while the ovarian cancer risk was eightfold higher  compared with the general population, consistent with published LS-associated endometrial (SIRs = 10–62) and ovarian (SIRs = 7–14) cancer risks.MSH6 and PMS2. Hegde et al.38 reported that MSH6 and PMS2 account for approximately 7–10% and <5%, respectively, of LS families. When applying Amsterdam II criteria to our cohort, consistent with Hedge et al., only 10.9% of women with MSH6 and 7.4% of PMS2 PVs would have been identified. The overall low proportion of women with MMR PVs meeting Amsterdam II Criteria (23.9%), compared with those meeting NCCN BRCA1/2 testing criteria (58.2%), underscores the need to continuously reconsider the criteria for which genes to test.Our findings suggest that the current LS clinical testing criteria may not be sufficiently sensitive, particularly for 39 To address these potential differences we conducted sensitivity analyses limited to those reported to be only Caucasian/European (non-Hispanic white) in our cohort using breast cancer SEER rates for non-Hispanic white females and found similar results (results not shown). Finally, given our retrospective study design, our estimates of cumulative survival may be overestimated because we may have differentially tested women with longer survival. It is also possible that the retrospective design and young average age at time of testing (52.1 years in this study) underestimates the cumulative incidence. To deal with this latter bias, we estimated cumulative incidence to age 60 only. Prospective validation of our findings will be needed to minimize these and other potential biases.This study has several limitations. First, the clinical information used in this study was limited to that provided with the testing sample. In addition, the study population consisted only of women considered candidates for genetic testing by their providers and may not be representative of all women with MMR PVs. As our overall testing cohort was comprised largely of women with a personal or family history of breast cancer, SIRs might be biased and will need to be confirmed in other studies. It is notable that the race/ethnicity distribution between this study cohort and the general population differs slightly among certain groups.MSH6 or PMS2 may benefit from increased breast cancer screening. Replication of our gene-specific breast cancer risks will be important to the future development of breast cancer management guidelines for female LS patients. In addition, further assessment of MMR deficiency in breast tumors may provide more information with which to evaluate the link between MMR genes and breast cancer. Finally, family studies of additional individuals with MMR PVs may also provide better breast cancer risk estimates.This study suggests that women with PVs in MSH6 or PMS2 are associated with a modest but statistically significant increased risk for breast cancer. Previously, the identification of a PV in MSH6 or PMS2 in a woman with breast cancer may have been considered an incidental finding. Here we show that PVs in MSH6 or PMS2 are associated with breast cancer and that these MMR genes should be considered when ordering a multigene panel for women with a personal or family history of breast cancer.In conclusion, our data demonstrate that PVs in Supplementary TablesSupplementary Figure 1