P < 5 × 10−8 with BW were used to construct (1) a 41-SNP instrumental variable (IV) for univariable MR after removing SNPs with pleiotropic associations with other breast cancer risk factors and (2) a 49-SNP IV for multivariable MR after filtering SNPs for data availability. BW predicted by the 41-SNP IV was not associated with overall breast cancer risk in inverse-variance weighted (IVW) univariable MR analysis of genetic association data from 122,977 breast cancer cases and 105,974 controls . Sensitivity analyses using four alternative methods and three alternative IVs, including an IV with 59 of the 60 BW-associated SNPs, yielded similar results. Multivariable MR adjusting for the effects of the 49-SNP IV on birth length, adult height, adult body mass index, age at menarche, and age at menopause using IVW and MR-Egger methods provided estimates consistent with univariable analyses. Results were also similar when all analyses were repeated after restricting to estrogen receptor-positive or -negative breast cancer cases. Point estimates of the odds ratios from most analyses performed indicated an inverse relationship between genetically-predicted BW and breast cancer, but we are unable to rule out an association between the non-genetically-determined component of BW and breast cancer. Thus, genetically-predicted higher BW was not associated with an increased risk of breast cancer in adult life in our MR study.Observational studies suggest that higher birth weight (BW) is associated with increased risk of breast cancer in adult life. We conducted a two-sample Mendelian randomisation (MR) study to assess whether this association is causal. Sixty independent single nucleotide polymorphisms (SNPs) known to be associated at The online version of this article (10.1007/s10654-019-00485-7) contains supplementary material, which is available to authorized users. The hypothesis that the risk of developing breast cancer in adulthood may be increased by factors that first act in utero—in particular by fetal exposure to higher levels of maternal estrogen—was first proposed in 1990 –6. When Mendelian randomisation (MR) is a form of instrumental variable (IV) analysis that uses genetic instruments or single nucleotide polymorphisms (SNPs) associated with an exposure of interest to infer a causal relationship (or lack thereof) between this exposure and an outcome. Since SNPs are randomly allocated at conception, an MR study may be thought of as being analogous to a randomised controlled trial of the effects of the exposure on the outcome, making such a study less susceptible to classical confounding. However, MR is a valid tool for causal inference only if three assumptions hold: 1) SNPs used as part of the IV are associated with the exposure, (2) these SNPs are not associated with known or unknown confounders for the outcome, and (3) given these confounders, the SNPs affect the outcome only through the exposure of interest and not via other pathways. Here, we report the result of an MR analysis that aimed to investigate the relationship between birth weight as the exposure and susceptibility to breast cancer as the outcome. A genome-wide association meta-analysis of over 150,000 individuals has previously identified 60 independent SNP loci that are associated with birth weight (BW) and genetic association data for 59 of these loci are available from a separate meta-analysis of breast cancer susceptibility that included over 225,000 women , 30. We  SNPs useP < 5 × 10−8) associations for BW at 60 independent loci were previously reported by Horikoshi et al. . The signs of the beta coefficients for each SNP across all summary data sets were aligned to the BW-increasing allele .In summary, breast cancer data were available for 59 of the 60 BW-associated lead SNPs. When considering these two data sets together with the seven additional “risk factor” data sets, 54 BW loci had results listed across all data sets , Cook’s distance, and stepwise downward “model selection” consistently identified five SNPs with large effects on breast cancer that had an undue influence on the overall results (Supplementary Table 6). The stepwise downward approach suggested that an additional (sixth) SNP also contributed to the observed heterogeneity, while studentised residuals identified three of the five SNPs as outliers (Supplementary Table 6). Removing the five SNPs and repeating the standard IVW method using the remaining 36 SNPs that represented a more homogeneous genetic instrument for BW yielded an OR of 0.92 . Further reducing the potential impact of pleiotropy at the cost of losing power by using the 24-SNP IV constructed after removal of all SNPs associated at P < 9.2 × 10−4 (instead of P < 5 × 10−8) with at least one of seven putative breast cancer risk factors did not significantly change the primary IVW MR result . Results specific to ER-positive and ER-negative breast cancer are presented in Fig. MR analysis of the 49-SNP IV for BW simultaneously adjusting for the genetically predicted effects of these SNPs on birth length, adult height, adult BMI, age at menarche, and age at menopause using the weighted regression-based framework provided estimates for the association between BW and overall breast cancer risk that were consistent with the univariable results  to date [P < 5 × 10−8 with BW and at P < 6 × 10−8 with adult height in the data sets that we used . We did not use MR to assess the independent effect of birth length on adult breast cancer risk due to the availability of just two SNPs both of which are strongly pleiotropic and the consequent potential for unreliable estimates with such a genetic instrument. We could not include age at first birth and number of children ever born in our multivariable MR analyses since the publicly-available summary genetic association statistics for these two phenotypes were restricted to P-values only. However, only two BW SNPs were associated with age at first birth (rs12823128 and rs7742369) and no SNP was associated with number of children ever born at P < 9.2 × 10−4 . We removed these two SNPs in constructing our 24-SNP IV for univariable MR analysis, which yielded estimates consistent with the other univariable and multivariable MR analyses. Given this result and the lack of strong associations between the other birth weight SNPs and age at first birth and number of children ever born, not being able to adjust for these two putative breast cancer risk factors in our multivariable MR is highly unlikely to have substantially altered the overall conclusion from our MR study.A few observational studies suggest that the association between higher BW and increased future breast cancer risk is confined to premenopausal women but combined analyses of these studies show that this association does not differ by menopausal status , 8. ER-n to date . Both SNP < 0.05 level, they did uniformly indicate that the effect (if any) of higher BW on adult breast cancer might be protective  and IGF1R (rs7402982) that encode IGF-1 and its receptor, respectively, were associated with birth weight at P < 5 × 10−8 and with adult height in women at P < 6 × 10−4 (Supplementary Tables 2 and 3). However, neither SNP was associated with overall or ER-positive or ER-negative breast cancer risks at P < 0.05 although the alleles that increased BW also conferred breast cancer risk . Thus, while there is an association between SNPs in the core IGF-1 signalling genes and BW, our data do not provide any evidence that higher BW as predicted by these two IGF pathway SNPs is associated with adult breast cancer risk. While data on the association between BW and breast cancer risk in non-European populations is scarce, it is also worth noting here that a small study from China failed to show any association [It has been suggested that insulin-like growth factor (IGF) signalling is one potential pathway linking increased BW to breast cancer risk in later life . Haematoociation .In conclusion, the association between higher BW and increased risk of developing breast cancer in adulthood has been identified in several observational studies published over the last three decades. Revisiting this association using a comprehensive set of recently-developed MR methods and the largest available genomic data sets provides no evidence to suggest that genetically-predicted higher BW is associated with increased breast cancer risk in adult life. A key unanswered question is whether the association between higher BW and increased breast cancer risk seen in observational studies is largely due to the BW-increasing effect of non-genetic factors such as maternal hormones and nutrition and we are unable to rule out an association between the non-genetically-determined component of BW and breast cancer.Supplementary material 1 (DOCX 334 kb)Supplementary material 2 (XLSX 44 kb)Below is the link to the electronic supplementary material.


Background: Breast cancer rates have been increasing worldwide, particularly among young women, suggesting important interactions between genes and health behaviors. At the same time, mobile technology, including smartphones applications (apps), has emerged as a new tool for delivering healthcare and health-related services. As of 2018, there were nearly 600 publicly available breast cancer apps designed to provide disease and treatment information, to manage disease, and to raise overall awareness. However, the extent to which apps are incorporated into breast cancer prevention research is unknown. Therefore, the objective of this review was to determine how mobile applications are being used for breast cancer prevention among women across the cancer control continuum.Methods: Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched PubMed and Web of Science Core Collection databases using the keywords breast cancer, smartphone, mobile application, and phone app. Full-length journal articles available in English that addressed the research question were included. We categorized articles by prevention type  and phase of research , and identified common themes and gaps.Results: Our search yielded 82 studies (69 unique) that used apps in breast cancer prevention research across 20 countries. Approximately half of the named apps were publicly available. The majority (73%) of studies targeted tertiary prevention; 15% targeted secondary and 13% targeted primary prevention. Apps were used across all phases of research with the predominant phase being feasibility in tertiary prevention (34%), effectiveness in secondary prevention (63%), and development (30%) and effectiveness (30%) in primary prevention. Common uses included assessing outcomes relevant to clinical care coordination, quality of life, increasing self-efficacy and screening behaviors, and tracking and managing health behaviors.Conclusions: We identified the following gaps: few effectiveness studies in tertiary prevention, minimal use of apps for breast cancer etiology or early detection, and few interventions in those at average risk of breast cancer. These findings suggest that while mobile apps can inform breast cancer prevention across the continuum, more work is needed to incorporate apps into primary prevention. Breast cancer rates have been increasing worldwide, particularly among young women . Such raAt the same time, mobile technologies, including smartphone applications (hereafter referred to as apps), have emerged as new tools for delivering healthcare and health-related services in the field of cancer and particularly breast cancer. In fact, nearly half of all cancer apps are targeted toward breast cancer . A recenGiven that the use of apps for breast cancer prevention is still in the early stages of adoption, the authors agreed that a systematic review with a broad research scope was warranted. Therefore, we performed a systematic review to answer the question: how are mobile apps being used for breast cancer prevention research across the cancer control continuum, including tertiary, secondary, and primary prevention, in women? Since the use of apps in research is relatively new, we also sought to identify at what phases of the research process mobile apps were being used for breast cancer research, including protocol, development, feasibility, pilot, effectiveness, and measurement studies. In addition to the systematic review, we sought to find common themes and gaps across the body of literature.In order to conduct this systematic review, we utilized the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines . We systn = 82), we flagged those studies that had multiple publications reporting outcomes across different stages of research  but were using the same underlying cohort (n = 23).Records were screened in Endnote and included if they were published as an original research article in English. The primary reviewer [RH] then reviewed the full-text article for relevance to the study question. Articles were excluded if study participants were providers or caregivers; if breast cancer prevention was not an explicit goal or implication of the research; if the article did not include a mobile application or only discussed that the research could be potentially adapted into a mobile application; or if the smartphone was examined as a carcinogen. We also excluded books or book chapters, meeting abstracts, non-empirical records , non-English records, and records where the full-text were unavailable. When inclusion was unclear, authors LH and JAM independently reviewed the articles and then all authors discussed until a consensus was met. LH and JAM also reviewed 20% of excluded articles for accuracy. In one case where we could not reach consensus, we contacted the corresponding author for clarification. Among all studies that were eligible for qualitative analysis , mobile application name (where applicable), and study objectives and/or outcomes . We categorized studies by prevention type based on whether they were targeting a secondary cancer event and/or morbidity/mortality (tertiary), early diagnosis and treatment (secondary), or disease prevention (primary). We assigned articles to only one prevention type category. We also categorized studies by research phase based on the study outcome(s). Studies categorized as Development included those collecting information on participant interest and preferences for a mobile application that was not yet produced. Based on features outlined by Orsmond and Cohn , we catea priori hypotheses regarding common themes and gaps in the literature, we comprehensively reviewed unique studies by cancer prevention type to identify common themes and gaps. We then extracted mobile app details and categorized app use by prevention type and the availability of the app in the Apple and/or Android app store.Our initial analysis tabulated all articles eligible for qualitative analysis by cancer prevention type and by research phase. We then estimated the number of articles published by year. We used the subset of unique studies and tabulated the number of publications by country and continent. Lastly, void of n = 52) were tertiary, 12% (n = 8) were secondary, and 13% (n = 9) were primary.We identified 199 records through our search, excluding duplicate records . Of thesAs displayed in The number of studies using apps for breast cancer prevention research increased rapidly over the last 10 years . The earThe majority of mobile apps used for breast cancer prevention research addressed tertiary prevention. We identified 63 studies (53 unique)  and the We identified two common themes for the use of mobile health apps in tertiary breast cancer prevention: clinical care coordination and health related quality of life during and after a breast cancer diagnosis. Cancer care coordination studies focused on the support and communication between the breast cancer patient and the physician , 66, 68,In addition to the two main themes identified, we also found that tertiary prevention apps were used to improve measurement and provide real-time data for assessment and prediction. For example, Timmerman et al. subjectively measured fatigue in 18 cancer survivors by administering the Visual Analog Scale on a smartphone 3 times per day . In addiThe vast majority of the apps we identified for clinical care coordination were not named in the study or publicly available, but rather developed for each specific study. In contrast, studies using apps to improve health related quality of life were more readily available for public use in the Apple and/or Android app store .We identified 9 studies (8 unique) that used apps for secondary breast cancer prevention in the following phases: development (37.5%), feasibility (25%), pilot (12.5%), and effectiveness (62.5%); with three articles reporting on multiple study phases see .We identified only one theme in the studies of secondary prevention; with one exception , all stuTwo developmental studies used apps to innovate breast cancer detection strategies. The SmartIHC-Analyzer mobile app automates scoring of Ki-67 protein, a hallmark for assessing cell proliferation rate during cancer progression . The PixWith one exception , none ofWe identified 10 articles (9 unique) that focused on the use of mobile apps for primary breast cancer prevention see . The artWe identified three common themes for the use of mobile health apps in primary breast cancer prevention: knowledge and adherence to screening guidelines, the targeting of high-risk populations, and the incorporation of theoretical frameworks. Primary prevention studies focused on apps that increased breast cancer prevention knowledge and adherence to breast cancer guidelines and surveillance , 83–85. BRCA mutation carriers , self-efficacy (with a distinction between active and passive information seeking), and user-friendly scheduling tools. For example, literacy and self-efficacy were important in a study among college women that applied a family-based life course approach to breast cancer prevention . Given cWith regard to app availability, 4 studies used publicly-available apps  77, 79,, 84. OthThis systematic review summarizes the emerging literature for breast cancer prevention research using mobile apps. While we found studies across the cancer control continuum, the majority of studies used mobile apps to target tertiary prevention, particularly clinical care coordination and health-related quality of life for breast cancer survivors, as well as to improve the measurement and assessment of symptoms, behaviors, and risk. Fewer mobile apps were used for secondary and primary prevention where outcomes were related to increasing self-efficacy and screening behaviors and tracking and managing health behaviors. The studies reviewed spanned all phases of research in diverse populations in nearly 20 countries. The use of apps in breast cancer research has been increasing since 2010, a trend that will likely continue. Given the ubiquity of smartphones and global burden of breast cancer, there is potential for mobile apps to impact breast cancer trends across the globe.Previous reviews have explored the use of cancer apps, but were not systematically conducted , specifiGiven that breast cancer is the most commonly diagnosed cancer in women globally  and therWhile a greater proportion of secondary prevention studies were at the effectiveness stage, we found mixed evidence that apps could modify breast cancer screening behaviors, especially among at-risk populations. Lee et al. showed that a mobile phone-app based intervention, in combination with health navigator services, could effectively improve breast cancer knowledge and readiness for mammography . GinsberThe majority of primary prevention studies were aimed at improving the transfer of knowledge and adherence to existing cancer prevention guidelines among women at high risk for breast cancer; however, less research has been conducted with populations at average risk, or on modifiable risk factors to prevent breast cancer. Targeted prevention to high-risk populations is logical given that with limited resources and competing disease risk, resources should be allocated to those who will benefit most. However, if maintaining healthy weight, diet and physical activity can reduce cancer incidence by 26% , then apAs of early 2019, there were over 5.1 billion mobile phone subscribers and this number is growing given the average annual percent increase of 2.9% . One couGiven our review, we highlight the following opportunities and/or recommendations with regard to the use of apps across the breast cancer control continuum:Research is needed to understand the effectiveness of mobile apps for breast cancer primary prevention in women at average risk, but especially in young women. The incidence of invasive breast cancer in young women (age 25–39 years) has risen in the US with an annual percent change of 2.7% for white non-Hispanic women and 3.1% for black non-Hispanic women from 1976 to 2009 . Many bede novo app development. Popular apps carry the benefit of having a strong infrastructure given that software is routinely updated, designs are improved, and new features are added  and tertiary prevention (continuing cancer care) were not readily available. Even for primary prevention, Cohen et al. found that over 200 potential users from 68 countries outside of the US tried to access the SNAP for BRCA app, but potential users could not download the app as it required a study code . Withoutre added . HoweverResearchers should capitalize on the opportunity apps provide to collect information on exposures and outcomes of interest that have traditionally been difficult to measure. Not only does mobile app technology allow researchers to obtain repeat real-time data, mobile data measurement and collection reduces in-person study staff assistance, while not fully replacing study staff. Study staff will likely remain essential, especially for study implementation in low-middle income and hard to reach populations .This review is not without limitations. First, the advent of mobile apps is relatively recent and research in this area is rapidly changing. As a result, articles may have been missed that were not indexed with the search terms selected. To counteract this possibility, we broadened our search to include the full-text rather than just MeSH or keywords. Second, our review may also be missing studies that addressed breast cancer risk factors, such as obesity, but do not make an explicit reference to breast cancer. This likely deflated the number of articles identified as primary prevention; however, a more exhaustive review of all mobile apps being used for breast cancer risk factors was beyond the scope of this study. Finally, we included two databases in our search strategy, so gray literature and clinical trials with unpublished findings were not included.The use of mobile apps for breast cancer prevention research is rapidly growing. Our systematic review suggests that while some gaps identified in previous reviews have already been addressed, new challenges have emerged. For mobile app interventions to have a global impact across the cancer control continuum, researchers will need to continue to invest in primary and secondary prevention research studies, as well as studies that are farther along in the research phase, in order to demonstrate the potential impact on outcomes relevant to breast cancer.LH and JM conceptualized the study and all authors  formulated the study design. RH managed the literature search and reviewed all articles and LH and JM independently reviewed a subset of articles. All authors drafted the initial manuscript, reviewed and revised the final manuscript for critical and important intellectual content, approved the final manuscript, and agree to be accountable for all aspects of the work.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


This study analyzes the association of excessive energy intake and caloric restriction with breast cancer (BC) risk taking into account the individual energy needs of Spanish women. We conducted a multicenter matched case-control study where 973 pairs completed lifestyle and food frequency questionnaires. Expected caloric intake was predicted from a linear regression model in controls, including calories consumed as dependent variable, basal metabolic rate as an offset and physical activity as explanatory. Overeating and caloric restriction were defined taking into account the 99% confidence interval of the predicted value. The association with BC risk, overall and by pathologic subtype, was evaluated using conditional and multinomial logistic regression models. While premenopausal women that consumed few calories (>20% below predicted) had lower BC risk , postmenopausal women with an excessive intake (≥40% above predicted) showed an increased risk . For every 20% increase in relative (observed/predicted) caloric intake the risk of hormone receptor positive (p-trend < 0.001) and HER2+ (p-trend = 0.015) tumours increased 13%, being this figure 7% for triple negative tumours. While high energy intake increases BC risk, caloric restriction could be protective. Moderate caloric restriction, in combination with regular physical activity, could be a good strategy for BC prevention. Compared to European levels, rates in Spain in 2015 are somewhere in the middle, with an age-standardised rate of 88.3 cases3. However, the evidence from epidemiological studies is less consistent8. Suggested biological mechanisms for the beneficial effects of caloric restriction include decreased circulating levels of growth factors, anabolic hormones, and cytokines. This in turn leads to a reduction in growth factor signaling, vascular perturbations, and inflammation. Caloric restriction is also involved in lower oxidative stress and free radical-induced DNA damage, better DNA repair processes, improved apoptosis of damaged cells, enhanced autophagy and protection from the damaging effects of toxic and genotoxic agents10.The role of energy intake on breast cancer risk has been studied in both experimental and observational studies. According to the International Agency for Research on Cancer, there is sufficient evidence from experimental animal studies indicating that limiting body-weight gain by caloric restriction has a preventive effect on cancer of the mammary gland12. Instead, a positive energy balance, characterized by excessive energy intake  in relation to energy expenditure 6, rather than high energy intake per se, may be the etiologically relevant factor in breast cancer risk. This positive balance over a prolonged period, results in excess of body fat and, consequently, contributes to increased postmenopausal breast cancer risk13. Although only a few epidemiologic studies have explored the three components of energy balance  simultaneously, all of them detected an increased risk for breast cancer among women with the least favorable energy balance profile: high-energy intake, high body mass index (BMI) and low physical activity18.On the other hand, high-energy intake has not been consistently associated with increased breast cancer risk in human studies19. Basal metabolic rate is defined as the energy required for maintaining the body’s vital functions under resting conditions, and represents 45 to 70 percent of daily total energy expenditure. This rate is determined by the individual’s age, gender, body size, and body composition19. It would be very interesting to explore the association between excess or deficit of caloric intake and breast cancer risk taking into account the basal metabolic rate of each individual. So, the main aim of this study is to investigate the association between relative caloric intake, as a function of daily total energetic expenditure and body size, and the risk of breast cancer in Spanish women. Secondary aims include evaluating whether this association differs by menopausal status, specific risk profile, and/or tumour pathologic subtype.However, beyond physical activity, a more comprehensive measure of energy expenditure is the daily total energy expenditure. This measure combines three basic components: basal metabolic rate, energy expenditure through physical activity, and the metabolic response to foodhttp://www.geicam.org/), recruited 1017 women with histologically confirmed incident breast cancer being treated at 23 hospitals, in 9 Spanish regions. To be eligible for the study participants had to reside in one of the hospitals´ catchment area, be between 18–70 years old and be able to complete the epidemiological questionnaire. Each patient (case) was matched with a healthy woman (control) usually selected by the patient  of a similar age (±5 years) and residing in the same city. Patients´ blood-relatives were not eligible.Between 2006 and 2011, GEICAM, the Spanish Breast Cancer Group . Cases completed the questionnaire within 3 months after diagnosis of breast cancer. When questions referred to a specific time period for cases , the corresponding control was asked about the same calendar period. The questionnaires were reviewed by trained interviewers at each center, clarifying any questions participants had. Data entry and quality control were performed at the GEICAM headquarters. The accuracy of the information recorded in the database was checked by randomly selecting and reviewing 10% of the questionnaires.Data collected for each participant included age, educational level, height and weight, menopausal status, age at menarche, number of children, age at first birth, use of hormone replacement therapy (HRT), previous diagnosis of benign breast diseases, family history of breast cancer, physical activity during the year previous to diagnosis, smoking status, and diet. Based on highest educational level achieved, participants were classified into 3 categories: no formal education - up to first grade; primary education - vocational training; and university graduate or higher. BMI was calculated based on participant´s weight one year before the interview and height.22. The 117-item FFQ has been adapted to and validated in different Spanish adult populations23, and covered eating habits during the preceding 5 years. Patients had nine options to describe how frequently they consumed each food item, ranging from “never or less than once per month” to “six or more times per day”. Responses were converted to mean daily intake in grams by multiplying consumption frequency by the nutrient content of the portion size specified in the FFQ. Finally, total intake of each nutrient and total energy intake –in kcals/day- were computed for each participant.For dietary assessment, cases and controls completed a validated semiquantitative food frequency questionnaire (FFQ) similar to the Harvard questionnaire20, and therefore, possible confounders in the present study. These patterns were identified grouping the EpiGEICAM FFQ items, excluding alcoholic beverages, into 26 inter-correlated food groups that were log-transformed and centered. Subsequently, Principal Components Analysis without rotation of the variance-covariance matrix was applied. We then calculated the adherence score to Western, Prudent and Mediterranean dietary patterns as a linear combination of the weights of each food group (pattern loadings) in the previously mentioned study20, and the log-transformed centered food group consumption reported by the participants. Adherence scores were classified into quartiles based on controls´ score distribution.From these data we also calculated level of adherence to the Western, Prudent and Mediterranean dietary patterns. Western dietary pattern  and Mediterranean dietary pattern  were already associated with breast cancer risk in a previous EpiGeicam study21, in the present study we decided to adjust for overall physical activity during the year previous to the breast cancer diagnosis in cases or during the year prior to interview in controls.A detailed questionnaire collected a history of physical activity from recreational, occupational, and household activities, as well as an overall assessment of physical activity considering all these domains using 5 categories: sedentary , lightly active , moderately active , active , very active . Due to the protective effect of physical activity on breast cancer risk previously detected in these womenet al.24. These equations take into account individual´s age, weight, height, gender, and race/ethnicity. An online basal metabolic rate prediction tool is also available . Next, we built a linear regression model based on data from the control group to estimate the number of calories expected, according to women’s basal metabolic rate and physical activity as follows: the amount of calories consumed by women in the control group was the dependent variable, the basal metabolic rate was included as an offset in the model and physical activity level was included as explanatory variable. From this model, we predicted the expected caloric intake per participant, and its 99% confidence interval . Afterwards, we constructed a new variable  as follows: The reference category  included participants whose caloric intake (observed) was within the range defined by the 99% confidence interval of their expected caloric intake. Overeating was defined as a relative caloric intake exceeding the upper limit (UL) of that interval (observed > UL_expected) and, in turn, undereating was defined as a relative caloric intake under the lower limit (LL) of that range interval (observed < LL_expected). Relative intake was subsequently categorized taking into account the percentiles 20 and 80 of the distribution in controls, into 5 categories: evident undereating (observed/LL_expected intake ≤0.80), moderate undereating (observed/LL_expected intake >0.80 with observed intake < LL_expected), normal intake (observed > LL_expected & observed < UL_expected), moderate overeating (observed/UL_expected intake >1 and ≤1.40) and evident overeating (observed/UL_expected intake >1.40).Relative caloric intake was our main variable of interest as a potential predictor of breast cancer risk. Its creation consists of several steps detailed below. First, we calculated the basal metabolic rate using the predictive equations derived from meta-regression equations of 47 studies developed by Sabounchi 25. Patients were classified as follows: patients with hormone receptor positive (HR+) tumours , patients with HER2+ tumours (regardless of ER/PR status), or patients with triple negative (TN) tumours . Controls were the reference category.Our primary aim was to evaluate the potential association between relative caloric intake and a diagnosis of histologically confirmed invasive breast cancer. Thus, the values for the main outcome variable were Case vs. Control. Our secondary aim was similar, but exploring the link between caloric intake and the different pathologic breast cancer subtypes. Thus, we created a second dependent variable based on tumour classification according to estrogen receptor (ER), progesterone receptor (PR), and the human epidermal growth factor receptor 2 (HER2) status according to a simplified version of the St Gallen international consensusParticipants’ characteristics were described using counts and percentages for categorical variables and means and standard deviations for continuous variables. To check the significance of case-control differences we used Pearson Chi-square tests and Student’s t-tests, respectively.Our primary aim, the potential association between relative caloric intake and breast cancer risk, was assessed using conditional logistic regression models. Linear trends were tested by entering the independent variable, relative caloric intake, as a continuous term. We adjusted for potential confounders: educational level, BMI one year prior to the interview, menopausal status (these last two variables were included in the models with the corresponding interaction term), smoking status, age at first birth (with a category of nulliparous), age at menarche, history of benign breast disease, family history of breast cancer, HRT use, physical activity, and level of adherence to Western and Mediterranean dietary patterns. Additionally, we evaluated the potential effect modification of menopause on the predictive variable by including an interaction term between relative caloric intake and menopausal status. Finally, the increase in breast cancer risk per every 20% rise in relative caloric intake was also assessed by category of other explanatory variables.Our secondary aim, to test whether the association of interest varied across pathological subtypes, was assessed using multinomial logistic regression models with pathological subtype as the dependent variable. Models were fully adjusted as described above including also age and recruiting area. Heterogeneity of effects for the different cancer subtypes was tested using the Wald statistic.Finally, given the matching nature of our data, we used Multiple Imputation by Chained Equations to impute missing values for overall physical activity during the previous year (8.0%), HRT use (4.9%), age at menarche (0.6%), age at first birth (4.7%), smoking (0.3%), weight (2.6%) and height (8.4%). Imputation models included these variables as well as the following confounding variables with complete information: case-control status, age, parity, menopausal status, educational level, caloric intake, and previous chronic diseases. Five imputed datasets were created using STATA´s multiple imputation procedure.All statistical analyses were performed by using STATA/MP 14.0 software.The global participation rate was 82% (75% in cases and 90% in controls). Of the 1017 case-control pairs recruited, 44 were excluded due to implausible caloric intake values at least in one of each member . Thus, the current analyses are based on 973 case-control participant pairs. Compared with controls, cases had lower educational level, higher proportion of postmenopausal overweight women, slightly higher age at menarche, higher frequency of previous benign breast diseases, more relatives with breast cancer, higher caloric intake and more adherence to the Western dietary pattern. The average excess of calories consumed in relation to predicted calories  was 296 calories in cases and 178 calories in controls . No differences were seen between pre and postmenopausal women (p-heterogeneity = 0.734).Table Next, we examined the association between caloric intake and breast cancer risk by pathological subtype Table . There wFigure The present study analyzes the association between breast cancer risk and women’s relative caloric intake  according to participants’ physical activity and basal metabolic rate. Our results suggest that restricted caloric intake offers a protective effect against breast cancer, especially in premenopausal women, whereas excessive caloric consumption increases breast cancer risk. The latter effect is observed mainly among postmenopausal women and women reporting low adherence to the Mediterranean diet. A positive association between relative caloric intake and breast cancer was observed in all pathologic subtypes, though the association failed to reach statistical significance among women with TN tumours due, most likely, to a limited number of cases.18. Third, because physiological pathways and metabolic effects of calories vary by source  we adjusted our models for quartile levels of adherence to the Mediterranean and Western dietary patterns, both associated with breast cancer risk and previously identified among our participants20. All the possible combinations of these two variables allowed us to capture (and adjust for) the broad diversity of food consumption patterns found across Spain. Fourth, regarding breast cancer subtypes, as far as we are aware of, this is the first study exploring the association between caloric intake and breast cancer risk considering HER2 status separately. Finally, the large sample of premenopausal participants allowed for a fully adjusted exploration of the effect of caloric consumption on this group.This study has several strengths. First, this is a multicenter study carried out in 9 Spanish regions located throughout the second largest country in Europe. Second, to our knowledge, this is the first epidemiological study to date that explores the effect of caloric deficit or excessive caloric consumption according to the individual energy requirements of each woman based on her basal metabolic rate and physical activity performed. Previous studies have examined the joint effect of energy intake, physical activity, and body size; however, their analyses were stratified by those three components23, there is evidence that overweight or obese individuals tend to underestimate their weight and caloric intake and to overestimate their physical activity26. To minimize this bias, we performed sensitivity analyses to test whether the effect of caloric intake was consistent across four categories of BMI . The resulting associations were very similar to those reported here, with no evidence of heterogeneity (data not shown). Therefore, we believe that this potential bias, is very likely non-differential, and thus, our reported associations would, in any case, underestimate the real ones. Further, although we collected very detailed information on recreational physical activity21 we forewent this information in favor of categories of overall physical activity to estimate the expected caloric consumption. We made this decision because leisure physical activity does not realistically capture the amount of exercise performed by women in this context, especially in the case of less educated women27. However, when sensitivity analyses were performed with the subgroup of women with complete information on metabolic equivalents (MET-h/week) from leisure physical activities, the results were no different from those reported here (data not shown). On the other hand, the fact of having selected friends, partners or not blood-relatives as controls of breast cancer cases could entail a greater similarity in lifestyles, including dietary habits among cases and controls. However, if this bias exists, it would imply an underestimation of the effects studied, and so, the associations reported here would underestimate the real ones. Being a case-control study, another limitation to take into account is that all information  in cases was collected after diagnosis. This may have caused differential recall between cases and controls that could have skewed the results. However, this differential bias could be minimized because women were not aware of the specific hypothesis we investigated and we used a well-structured and validated instrument for dietary assessment with a wide temporal window (5 years prior to the diagnosis of the corresponding case) thus expecting similar misclassification errors in cases and controls. Regarding pathologic subtypes, we had an insufficient number of cases with TN tumours to achieve statistical power to test heterogeneity, since TN tumours are relatively uncommon in our patient population28. Finally, even though most established risk factors were taken into account, residual confounding cannot be ruled out.Several limitations should be considered when interpreting our findings. First, the explanatory variables of interest are based on self-reported data, thus subject to recall bias. In particular, even though the FFQ used showed a satisfactory validity and reproducibility3. Some observational epidemiological studies provide additional evidence that caloric restriction provides humans certain protection against cancer9. In fact, recent clinical intervention trials have demonstrated that some metabolic and molecular adaptations observed in experimental animals also take place in humans in response to caloric restriction29. Short-term studies with overweight and obese subjects have shown that caloric restriction may reduce circulating concentrations of inflammatory markers such as C-reactive protein, tumour necrosis factor-α and interleukin-6, improve insulin sensitivity, increase serum concentrations of insulin-like growth factor binding protein (IGFBP)-1 and IGFBP-2, increase circulating levels of adiponectin, and reduce leptin and the leptin-to-adiponectin ratio30. In addition, caloric restriction affects multiple processes involved in the pathogenesis of cancer including a reduction of oxidative stress and free radical-induced DNA damage, an enhancement of DNA repair processes, an increase in removal of damaged cells through apoptosis, an enhancement in autophagy and protection from the damaging effects of toxic agents10.Our results show that women who consumed fewer than 80% of the calories expected based on their physical activity and basal metabolic rate, had lower breast cancer risk. There is sufficient evidence based on animal models that limiting body weight gain by caloric restriction prevents cancer of the mammary gland30. In premenopausal participants of a randomized trial, Harvie and colleagues observed that both intermittent and continuous caloric restriction during 6 months resulted in weight loss in 107 overweight or obese women together with improvements in several cancer risk markers31. Among the metabolic effects of this voluntary weight loss, several studies have demonstrated a substantial reduction in biomarkers of estrogen stimulation and inflammation, among both premenopausal and postmenopausal women32. However, we observed that postmenopausal women in our study had to consume substantially fewer calories than predicted to reduce their breast cancer risk. Thus, we conclude that postmenopausal women would need a stricter hypocaloric diet to reduce their body fat and, hence, their estrogen exposure through aromatization of adrenal androgens.The protective effect of caloric restriction has been observed in both our premenopausal and postmenopausal participants. Previous observational studies have shown that weight loss through caloric restriction reduces the risk of postmenopausal breast cancer12. Excessive caloric intake results in weight gain and body fatness which, in turns, is strongly associated with postmenopausal breast cancer risk. However, greater body fatness before the menopause seems to protect against premenopausal breast cancer13. To take into account the possible differential effect of obesity in pre and postmenopausal women, all models were adjusted by the interaction term between both variables. Nevertheless, in our study, the association between obesity and breast cancer was not significant among premenopausal women  = 0.95–1.02). Interestingly, although breast cancer risk associated with excessive caloric intake was significantly higher among postmenopausal women, the risk for every 20% increase in relative caloric consumption was practically the same in both groups. It should be borne in mind that body fatness is the result of maintained energy disbalance in the past, and from that perspective, overeating in premenopausal women will translate into higher BMI in the future, possibly after menopause. Taking this consideration into account, our results do not contradict, but are in agreement with what is already known based on BMI. From a public health point of view, they emphasize the importance of reducing excessive caloric intake before menopause. On the other hand, because total caloric intake is highly related to body size and physical activity, it is difficult to assess the independent effect of caloric intake on breast cancer risk. Two previous cohort studies found that women with the most unfavorable balance profile  had increased premenopausal17 and postmenopausal14 breast cancer risk. Results further confirmed by two case-control studies18. Whereas Mallin and co-authors observed that the profile characterized by high energy intake and low physical activity was associated with a higher breast cancer risk among postmenopausal women16, Zhang and colleagues found a 60%-70% increased risk associated with high energy intake only among premenopausal women18.Although most case-control and prospective studies have found a positive association between high energy intake and breast cancer risk, others have notet al., in a case control study of women enrolled in the Breast Cancer Family Registry, found that the association between high energy intake and breast cancer risk was only significant in women with HR+ tumours18. In addition, some experimental studies with mice have shown that caloric restriction may reduce the risk of HER2+ breast cancer33, decreases metastatic burden in TN breast cancer patients34, or slow tumour growth regardless of tumour subtype35.In our study, relative caloric intake seemed to have a similar effect on the risk of all pathologic subtypes of breast cancer, suggesting that there must be biological mechanisms, other than those related to the hormonal pathway, influencing this association. Zhang 36. According to this approach, what contributes to obesity and related diseases is not the number of calories in specific foods but rather the amount and type of carbohydrates these foods contain. Foods that are highly processed, and mostly comprised of rapidly absorbable sugars and starches, may be of greatest concern. Such carbohydrates, not typical of the Mediterranean diet, may induce neurohormonal alterations that lead to “eating more” and “moving less”36. In contrast, Bray et al.37 found that, given equal numbers of extra calories, weight gain was lower with a low protein diet compared with a normal protein diet. Whereas calories alone contributed to body fat increase, protein intake contributed to changes in energy expenditure and storage of lean body mass, but not to an increase in body fat37.The breast cancer risk associated with excessive caloric consumption was higher in women with low adherence to the Mediterranean dietary pattern. This result is in line with the qualitative approach by Lucan and colleagues38, that the prevalence of overweight and obese women has also increased progressively (54.6% in 2014)39, and that the consumption and variety of fast food has spread widely in recent years in Spanish households40, individual and public health strategies should be implemented especially in high-risk women. Moderate caloric restriction in combination with regular physical activity could have beneficial effects on health. Future prospective studies are needed to confirm these results in other populations and to elucidate the mechanisms underlying them.In summary, we found that women with a high relative caloric intake, i.e., above the expected intake according to physical activity and body size, presented increased breast cancer risk, with caloric restriction showing a protective effect. This association was observed in both premenopausal and postmenopausal women and across all pathologic breast cancer subtypes. Given that the prevalence of sedentarism is increasing in Spain (44% reported never exercised or played sports in the 2013 Eurobarometer Survey)


Little is known about the risk of developing various cancers according to occupation and occupational physical activity.Using nationwide clinical inpatient data (1984‐2017) in Japan, we undertook a multicentered, matched case‐control study with regard to the risk of developing various cancers according to occupation and using patients admitted with fractures as controls. Using standardized national occupation and industrial classifications, we first identified the longest‐held job for each patient. Using sales workers as the reference group, odds ratios (ORs) and 95% confidence intervals (CIs) were estimated by conditional logistic regression, adjusted for age, admission period, and the admitting hospital, with smoking, alcohol consumption, and lifestyle diseases as covariates. The risk of high and low occupational physical activity was also estimated.Across all occupations, a reduced risk for all common cancers among males was observed among those occupations associated with high physical activities, such as agriculture. People in these occupations tended to show a lower risk for most cancers, including, for example, prostate cancer  and lung cancer . For females, the breast cancer risk was low in women engaged in agriculture  and in those occupations with high levels of occupational physical activity .This study revealed differences in cancer risk among diverse occupations in Japan. Specifically, those occupations associated with high levels of physical activity may be associated with a decreased risk of cancer. The study revealed differences in cancer risk among diverse occupations in Japan. Specifically, those occupations associated with high levels of physical activity may be associated with a decreased risk of cancer. Using nationwide, multicenter inpatient data, including individual‐level clinical data and occupational information, we examined the risk of cancer associated with each occupation.1.11.1.1We used the Inpatient Clinico‐Occupational Database of Rosai Hospital Group (ICOD‐R), provided by the Japan Organization of Occupational Health and Safety (JOHAS), an independent administrative agency in Japan. Rosai Hospitals now comprise 33 hospitals, located from Hokkaido to Kyushu, in both rural and urban areas in Japan. The database contains medical chart information overseen by physicians, including a clinical history and diagnosis of current and past diseases, pathological information, treatments, and the outcome for every inpatient. The diagnoses are coded according to the International Statistical Classification of Diseases and Related Health Problems, 9th Revision (ICD‐9) or 10th Revision (ICD‐10). The ICOD‐R also includes an occupational history (current and past three jobs), information on lifestyle such as smoking and alcohol habits, and a history of lifestyle‐related diseases using interviews and questionnaires completed at the time of admission. Detailed occupational histories were coded using 3‐digit codes of the standardized national classification, the Japan Standard Occupational Classification and Japan Standard Industrial Classification, corresponding to the International Standard Industrial Classification and International Standard Occupational Classification. Written informed consent was obtained before patients completed questionnaires, and trained registrars were in charge of registering the data. Registrars are “health information managers”, qualified people in Japan. This is quite a unique feature of the database in Japan. The profiles of the inpatients are nationally representative because the Rosai Hospital Group has grown to cover all occupations since the establishment of the Rosai Hospital Group by the Ministry of Labour of Japan in 1949.2The study was approved by the ethics committees of The University of Tokyo (No. 10891) and Kanto Rosai Hospital (No 2018‐11).2.1We obtained an anonymous dataset extracted from ICOD‐R with the permission of JOHAS, which included admissions to hospital between 1984 and 2017. We conducted a multicenter, hospital‐based matched case‐control study. With respect to selection cases and controls, we randomly sampled one control for each cancer case from cases of fractures of the arms and legs , matched for age, sex, period of admission date, and admitting hospital.The cancer cases were difined by those patients with an inital diagnosis of cancer coded by ICD‐9 or ICD‐10. The cancer sites were selected according to national statistics in Japan,2.2To evaluate the odds ratio of each occupation, we chose the longest‐held job of each patient from their occupational history.We also analyzed several additional categories. The occupational groups with high or low levels of OPA were defined based on information on their accelerometer‐derived occupational activities, modified by the National Health and Nutrition Examination Survey of 2003‐2004 (NHANES).2.3P‐values were two‐sided. All analyses were conducted using STATA/MP15.0 (Stata Corp LP).Conditional regression analysis was used for the estimation of odd ratios (ORs), with 95% confidence intervals (95% CIs), for each occupational category in relation to the risk for each cancer. The sales workers group was selected as a reference category in accordance with a previous study.3The total number of inpatient cases registered in the ICOD‐R from 1984 to 2017 comprised 6 526 387. Of these, completed data were available for 6 309 852 cases, which included birthday, sex, ICD‐9, or ICD‐10 code, history of smoking and alcohol consumption. Of these cases, 4 186 750 were first‐time admissions of the initial admission cases, while occupational information was available for 1 843 672 cases. Cancers for the 57 913 cases included prostate, breast, kidney, ureter, bladder, esophagus, stomach, liver, pancreas, colon and lung. The demographics of each cancer are shown in Table The average age of breast cancer patients was the lowest of all cancer sites .Table Agriculture was significantly associated with reduced risks for most cancers in males Table . In thisAs a whole in males, an overall reduced risk for all cancers was associated with those occupations related to high OPA. In females, a reduced risk for breast cancer showed a similar tendency: an association with occupations characterized by high OPA.44.1In general, workers are engaged in their jobs for about 40 hours per week, which means that they spend one‐fourth of their time in job‐related activities. Moreover, many Japanese companies have conventionally adopted the lifetime employment system: a promise by a company to an employee that they will have a job for their whole working life, as is customary in Japanese society. Therefore, most workers’ lifetime physical activity in Japan can be defined by an OPA.In Japan, one of the main changes observed in the employment sector in recent years has been the decline in the proportion of the population working in agriculture. In comparison, the proportion of workers engaged in the tertiary sector, including sales and services, is increasing rapidly. As a result, physical activity derived from an occupation has tended to diminish. Such major changes have been observed from the late twentieth century onwards, and have coincided with the growth of the welfare state and the increasing urbanization of the population.Another important change has been the increase in female labor in the workplace. Women have been released from a life of domestic servitude in the home and have become increasingly engaged in the workforce.Such factors outlined above may have strongly influenced the occupational factors associated with national cancer incidence and mortality in Japan.4.2Previous studies indicated that agricultural workers represent a unique population, possibly due to differences in lifestyle or their exposure to risky environmental hazards. Such workers deal with many potential hazards that include pesticides, chemical and biological agents, and the operation of heavy equipment. However, a lower prevalence of smoking plus high occupational activity has been reportedIn a previous large Canadian cohort study linked with cancer registry records, hazard ratios of the agriculture sector for lung, colon, bladder, kidney and liver cancers were found to be significantly lower than for other occupational workers.Farmers tend to not have an occupational retirement age since they are limited by physical strength and health, even though the normal time for retirement in Japan is between 60 and 65 years. In our study, although farmers were somewhat older than those employed in other occupations, the risk was significantly lower for all sites of cancer than that of other occupations. This difference explains how a risk‐reductive process may exist in the agricultural sector.In Japan in the middle of the twentieth century, about 18 million people were employed in agriculture, then one of the largest occupational groups. Since the economic significance of the agricultural sector has declined in parallel with an increase in the service sector, the proportion of people employed in this sector decreased to 6.3 million by the end of the last century.4.3In this study, we found significant associations between high levels of OPA and the risk of common cancers in males. This suggests that OPA may have some impact on the risk of developing cancer.The present study is in agreement with previous studies reporting an association between high physical activity  and cancer occurrence.It has also been reported that only recreational physical but not occupational activity diminished the cancer risk.In this study, the physical activity health paradox was not observed since the high OPA group showed low rates of obesity and a low risk of cancer. One may speculate that the effect of a low percentage of obesity due to high OPA may cause a reduction in risk rather than being an unhealthy result due to a specific OPA. The interwoven complexity of physical activity, obesity, and cellular pathways in cancer is yet to be disentangled. However, it is plausible that sedentary behavior may contribute to carcinogenesis.4.4As far as we are aware, we are the first to investigate the association between occupations, especially OPA, and the risk of developing common cancers  in Japan. This study is also one of the largest studies on the risk of developing cancer reported in the country. The particular strengths of this study include accurate diagnoses, which were directly extracted from medical charts in contrast to the less accurate diagnoses from claims data as done in other studies.Helicobacter pylori in stomach cancer, hepatitis virus in liver cancer) or socioeconomic status （ie, amount of income, educational attainment） could not be evaluated due to the limitations of the data. In addition, our data were not designed to detect occupational exposure to carcinogens or the high risks associated with specific occupational situations.However, despite this, several limitations may still exist. First, the content of ICOD‐R may have been flawed. Other factors relevant to the study, such as the presence of pathogenic organisms (ie, Because ICOD‐R is not a relevant population‐based database, the hospital‐based case‐controls we used may have had a selection bias. In addition, one‐third of the missing information within an occupation may amplify any selection bias even though all available factors were included as covariates in statistics. This problem arose because the return of occupational data from patients was not enforced because of concerns about the protection of patients’ privacy. This has the effect of making any selection bias stronger and may have affected results that were insignificant for each occupational risk in females. An information bias existed in terms of misclassifications in occupational categories because data recall was from disease onset. Confirmation of this can be found in a previous study since occupational profiles in this database are nationally representative.Second, a screening bias existed within the results. Though, medical checkup systems are widespread and covered on a national basis by medical insurance in Japan, disparities still exist in terms of opportunities for undergoing a medical examination among occupations and residential areas. Agriculture workers tend to work in self‐owned businesses and live in rural areas, so that the chance of diagnosing carcinoma is likely lower than for other occupations. We could not adjust such an inequality in the chance to undergo screening even though adjustments for areas were undertaken.Finally, evaluating occupational risk using the longest‐held job may have led to a biased influence. The identified occupations used in this study were those in which individuals were mainly engaged in throughout their lifetime. On this point, this is a more accurate assessment of occupational risk than choosing the occupation of the patient at the time of death.More detailed studies in future will evaluate the occupational aspects of cancer causal relationships in an increasingly statistical manner.5We have documented occupational inequalities in the risk of developing various cancers in Japanese workers. High levels of occupational physical activity are associated with a decreased risk of various cancers in men and decreased breast cancer in women. Further research on occupational physical activity and cancer risk in another large population may lead to an improvement in the health of the general population.None.Rena Kaneko: Funding acquisition, conceptualization, resources, formal analysis, writing—original draft, review and editing. Masayoshi Zaitsu: Review and editing. Yuzuru Sato: Funding acquisition, review and editing. Yasuki Kobayashi: Funding acquisition, supervision, review and editing.This study involved a retrospective analysis of data that had already been obtained through a national survey. As we did not use any personally identifiable information based on existing regulations in Japan, personal informed consent was not required.


ERCC1 rs11615 polymorphism and breast cancer risk, there is still no consensus on it. We conducted the current meta-analysis of all eligible articles to reach a much more explicit conclusion on this ambiguous association. A total of seven studies involving 2354 breast cancer cases and 2193 controls were elaborately selected for this analysis from the Embase, EBSCO, PubMed, WanFang, and China National Knowledge Infrastructure (CNKI) databases. Pooled odds ratios (ORs) and their 95% confidence intervals (CIs) were estimated in our meta-analysis. We found that the ERCC1 rs11615 polymorphism was significantly associated with breast cancer risk under all genetic models. When excluded, the studies that deviated from Hardy–Weinberg equilibrium (HWE), the pooled results of what remained significantly increase the risk of breast cancer under the allele model , heterozygote model , and dominant model . This increased breast cancer risk was found in Asian population as well as under the heterozygote model  and dominant model . Our results suggest that the ERCC1 rs11615 polymorphism is associated with breast cancer susceptibility, and in particular, this increased risk of breast cancer existence in Asian population.Excision repair cross-complementation group 1 (ERCC1), a DNA repair protein, is vital for maintaining genomic fidelity and integrity. Despite the fact that a mounting body of case–control studies has concentrated on investigating the association of the  Breast cancer is one of the most common malignancies in females and it alone accounts for 25% of all the cancer cases as well as 15% of cancer deaths amongst females ,4, we arERCC1 gene polymorphisms were associated with reduced mRNA and protein expression levels in various types of carcinomatosis [Excision repair cross-complementation group 1 (ERCC1) is a critical DNA repair protein and is involved in several distinct DNA-damage repair pathways, including nucleotide excision repair (NER), base excision repair (BER), interstrand cross-link (ICL) repair, and recombinational DNA repair , in the omatosis . The immERCC1 gene polymorphisms and the risks of several types of cancer such as lung cancer, adult glioma, colorectal cancers, bladder cancer, and head and neck carcinomas have been reported [ERCC1 rs3212986 gene polymorphism suffer a higher risk of breast cancer [ERCC1 rs11615 gene polymorphism and breast cancer risk have produced mutually contradictory results [ERCC1 rs11615 polymorphism on breast cancer risk.A number of epidemiological studies and meta-analyses of the association between reported . In addit cancer . Several results . Thus, wERCC1’ or ‘354 T>C’ or ‘G19007A’ or ‘rs11615’. All the relevant studies were retrieved for screening of the abstracts, full-text reports, and references by two investigators independently. Authors were contacted to obtain relevant data not present in the original articles. There was no language restriction on the search and selection of the articles.We searched for relevant articles published in the Embase, EBSCO, PubMed, WanFang, and China National Knowledge Infrastructure (CNKI) databases up to December 2017, using the following terms: ‘breast carcinoma’ or ‘breast cancer’ or ‘breast neoplasm’ AND ‘polymorphism’ or ‘genetic variant’ or ‘single-nucleotide polymorphism’ (‘SNP’) AND ‘ERCC1 rs11615 polymorphism and breast cancer risk; (ii) the study was an independent case–control study for humans; and (iii) genotype frequencies of case and control groups were stated in the article or could be obtained by contacting the authors. We excluded reviews, conference papers, and other studies that were published in abstracts only. When publications had obvious overlapping data in terms of the study participants, we kept only the study with the largest sample size.An article was included in our meta-analysis if it met the following selection criteria: (i) the study evaluated the association between the A standardized form was used for information collection from each retrieved study by two investigators independently. We collected information on the first author’s name, year of publication, ethnicity , country, total number of cases and controls, genotyping method, the distribution of genotypes in cases and control subjects, evidence of Hardy–Weinberg equilibrium (HWE) in the control group, and association with breast cancer. During the data extraction, there was an open discussion amongst all the investigators for reaching a final consensus regarding discrepancies.ERCC1 rs11615 polymorphism and breast cancer risk in the allele model (T compared with C), homozygous model (TT compared with CC), heterozygous model (TC compared with CC), recessive model (TT compared with TC + CC), and dominant model (TC + TT compared with CC); P<0.05 was considered significant. We assessed HWE in control subjects of each study by the χ2 test  [P<0.05) violation of HWE [Q statistic based on a standard Chi-square test with a P<0.10 [2I values that manifested the definite extent of between-study heterogeneity [P-value of heterogeneity tests was no more than 0.10 [P<0.05 being considered significant publication bias [All statistical analyses were performed using STATA version 12.0 software . Pooled odds ratios (ORs) with their 95% confidence intervals (CIs) were used to estimate the association between the ry 2018)  and evaln of HWE . The staa P<0.10  and I2 vogeneity . A randohan 0.10 ; otherwihan 0.10 . Furtherion bias .ERCC1 rs11615 polymorphism and breast cancer risk were included in our study, encompassing 2354 cases and 2193 controls.A total of 475 publications were preliminarily identified after systematically searching the aforementioned databases based on our search strategy using different search term combinations. All articles were scrutinized carefully by reading the full texts, and the studies that conformed to the selection criteria stringently as mentioned above were selected for this meta-analysis. The detailed selection process is shown in The characteristics of the eligible studies are shown in ERCC1 rs11615 polymorphism and increased breast cancer risk in all genetic models: the allele model , homozygous model , heterozygote model , recessive model , and dominant model  , heterozygote model  and dominant model   . The nex P=0.01) .P=0.025), heterozygote model , and dominant model   and dominant model   populations, while no subgroup analysis of the Caucasian population and Mexican-mestizo population was conducted, for each of which there was only study amongst the eligible studies. The stratified analysis showed an increased breast cancer risk in Asian populations based on the allele model  . We also P=0.03) .ERCC1 rs11615 and breast cancer risk, when including the studies that were deviant from HWE or not. In addition, when the data were stratified by menopausal status, there was no significant difference in the risk of breast cancer.Subgroup analysis of different genotyping methods  for only one study) showed no relationship between To observe the impact of each single study on the pooled OR, sensitivity analysis was performed by removing each study sequentially. In each case, the overall outcomes for the different genetic models showed no statistically significant changes, suggesting that this meta-analysis has good stability and reliability .Q-test and 2I statistics. Substantial heterogeneity (P<0.10) was found, whereas no 2Ivalues were more than 75%. Thus, a model was applied to synthesize the data . We found no evidence of publication bias, and the results showed no instability through sensitivity analysis, convincing us of the reliability of the current meta-analysis. However, we took notice of deviations from HWE in the studies we included by Yang et al. [P=0.02, P=0.007, and P=0.01, respectively), which further confirmed the significant role played by ERCC1 rs11615 in breast cancer susceptibility. The obvious alteration of P-values and estimates of effect size previously ascertained in all the genetic models could be due to reduced sample size, given that the two excluded studies accounted for 27.18% of individuals [Our pooled study demonstrated a clear increase in breast cancer risk associated with the g et al.  and Pongg et al. . Genotypg et al. ,45, whicg et al.  and Pongg et al. , we ran ividuals .ERCC1 rs11615 polymorphism was associated with an increased risk of breast cancer in Asian populations. Unfortunately, there are no ample studies of Mexican-mestizo and Caucasian populations included in this meta-analysis. As a consequence, it is still too early to tell the role that the ERCC1 rs11615 polymorphism plays in breast cancer risk variation in different ethnic backgrounds. Extremely large-scale single studies of different ethnicities are now necessary to draw a more precise conclusion about the specific significant association suggested by our intriguing finding. In addition, breast cancer is heterogeneous; De Waard et al. [ERCC1 rs11615 polymorphism in premenopausal and postmenopausal females. However, we did not find any difference between premenopausal and postmenopausal females in breast cancer susceptibility associated with ERCC1 rs11615, contrary to the results by Lee et al. [ERCC1 rs11615 polymorphism in relation to menopausal status has not been widely and thoroughly investigated and may be a promising area for breast cancer research.In further subgroup analysis by ethnicity, the d et al. ,48 showee et al.  and He ee et al. . To dateERCC1 rs11615 polymorphism to breast cancer risk due to the insufficient number of studies. Second, the existence of heterogeneity in some models may generate false positive signals, while it could also lead to false negatives for some potential associations. We failed to discover any notable source of heterogeneity when we executed meta-regression analysis based on year, ethnicity, genotyping methods, and HWE in the control group (data not shown). Finally, compared with individual SNP loci, haplotypes may increase associations with disease. A study by Nexo et al. [ERCC1 have strong or moderate linkage disequilibrium in Asian and European populations [ERCC1 rs11615, and Romanowicz et al. [ERCC1 rs3212961 have 10.61-times the risk of developing breast cancer. Thus, certain haplotypes may increase the strength of an individual polymorphism and lead to significant enrichment of essential biological functions. Unfortunately, no article in the present meta-analysis analyzed the frequency distributions of haplotypes except the one by Nexo et al. [ERCC1 haplotypes are imperative.Some limitations in the present meta-analysis should be noted. First, having only a total of seven papers, and even fewer after grouping, may limit the statistical power and result in some genuine associations being undetected. As previously described, it is unreasonable to state that there is a definite racial difference in the contribution of the o et al.  found tho et al. . The SNPulations  and may z et al.  concludeo et al. . FurtherERCC1 rs11615 polymorphism significantly increases the risk of breast cancer. This significant association is observed in Asian populations, but more studies are necessary to determine if there is such an association in other races. Taking all our findings together, the increased risk of breast cancer under the heterozygote model and dominant model persisted, revealing that the TC genotype plays a crucial role in determining breast cancer risk. Well-designed case–control studies with larger sample sizes and examining populations from across the world are essential for the exploration of the association between breast cancer risk and ERCC1 gene polymorphisms, other DNA repair gene polymorphisms, and even the relevant haplotypes.In conclusion, our meta-analysis does demonstrate that the


Metabolic syndrome (MetS) and cancer are major public health problems worldwide. The relationship between MetS and cancer death is of great interest. We examined the predictive value of MetS for cancer mortality in Japan.Study participants included 4495 men and 7028 women aged 18–90 years who were registered between 1992 and 1995 as part of the Jichi Medical School Cohort Study. We used a definition of MetS modified for the Japanese population. The primary outcome was cancer mortality. Additionally, the relationship between MetS and cancer-type specific mortality was examined. Analyses were conducted with Cox’s regression models adjusted for age, smoking status, alcohol drinking status, marital status, educational attainment, physical activity, occupational category, and menopausal status (only in women).During a mean follow-up of 18.5 years, 473 men and 297 women died from cancer. MetS was positively associated with cancer mortality in women , but not in men . Additionally, MetS was associated with a high risk of colorectal  and breast  cancer deaths in women.MetS was a significant predictor of cancer mortality in women.The online version of this article (10.1186/s13098-018-0398-2) contains supplementary material, which is available to authorized users. Metabolic syndrome (MetS) is a disease characterized by a cluster of high blood glucose, dyslipidemia, obesity, and hypertension . MetS isCancer remains a major cause of death worldwide, with 14.1 million new cases and 8.2 million deaths from cancer occurring annually . Each coWe herein investigated the relationship between MetS and cancer mortality in a general Japanese population.The present study was a serial prospective population-based cohort analysis using data from the Jichi Medical School (JMS) Cohort Study. The research design of the JMS Cohort Study and some descriptive data have been reported in detail elsewhere . The stuThe JMS Cohort Study conducted follow-up surveys until 31 December 2013. We obtained death certificates from public health centers with the permission of the Agency of General Affairs and the Ministry of Health, Labour and Welfare. Each municipal government collected annual data on participant relocation. In Japan, the registries of residency and deaths are established by law and doctors are trained to describe in standard format.2. Trained interviewers used a standardized questionnaire to obtain data, including smoking habit , alcohol drinking habit , medical history , marital status (yes or no), educational attainment (the age at completion of education), physical activity  was calculated as weight (kg)/height (m)ionnaire ), occupaionnaire –21. Occuionnaire . Systoliionnaire .Information on the causes of death were determined by death certificates and coded using the International Classification of Diseases 10th revision (ICD-10). The primary endpoint was total cancer deaths (C00–C97), and secondary outcomes were lung (C33–34), stomach (C16), colon (C18), rectum (C19–20), liver (C22), gallbladder (C23), prostate (C61), and breast (C50) cancer deaths.2 is consistent with a WC of ≥ 85 cm in men and ≥ 90 cm in women in Japan [2 and the presence of two or more of the following: (i) SBP and/or DBP ≥ 130/85 mmHg or the use of antihypertensive medication; (ii) TG ≥ 1.69 mmol/L (150 mg/dL) and/or HDL-C < 1.03 mmol/L (40 mg/dL) and/or the use of antihyperlipidemic medication; and (iii) fasting PG ≥ 6.1 mmol/L (110 mg/dL) (with a fasting duration of at least 3 h) or casual PG  ≥ 7.8 mmol/L (140 mg/dL) and/or the use of antidiabetic medication.We applied the modified Japanese MetS definition using BMI instead of waist circumference (WC) because only approximately 20% of all participants in the JMS Cohort Study had WC measured, and BMI ≥ 25 kg/min Japan . MetS wa2 test. To elucidate the relationship between MetS and cancer mortality, a Cox’s proportional hazards regression model was constructed to estimate multivariate-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for cancer mortality to the number of metabolic risk factors, the obesity category (BMI ≥ 25 kg/m2 or < 25 kg/m2), and MetS by sex, adjusting for age, smoking status , alcohol drinking status , marital status (yes or no), educational attainment , physical activity , occupation category , and menopausal status (pre or post) only in women at baseline. These covariates are commonly adjusted for in cancer risk. However, tests for linear trend across the number of metabolic risk factors were conducted by including an ordinal scoring in the models to examine a dose–response association between MetS component and cancer mortality. The proportional hazards assumption for the model was checked by examining the log-negative-log plot of the survival function for participants with and without MetS, and the number of MetS components against time to death/follow-up time. These curves help in identifying non-proportionality patterns in hazard function such as crossing of the curves, convergent, or divergent. Additionally, we conducted Cox’s regression analysis by age ≥ 65 years or < 65 years and estimated multivariate adjusted HRs for cancer mortality to each metabolic risk factor, and for cancer-type specific mortality associated with MetS by sex. We performed sensitivity analyses by excluding participants who were younger than 40 years at baseline to minimize the influence of a younger generation. The threshold for significance was P < 0.05. All statistical analyses were conducted using IBM SPSS version 25.0 .Summary statistics were used to compare the characteristics of participants with and without MetS using the Mann–Whitney U test and χThe baseline characteristics of subjects with and without MetS are summarized for both the sexes in Table Figure Figure Table Table Sensitivity analyses performed by excluding participants who were younger than 40 years at baseline were consistent with the primary findings. These analyses are described in Additional file In the present study, we demonstrated that MetS was associated with increased cancer deaths in women, particularly those younger than 65 years, over a mean follow-up duration of 18.5 years. The predictive value for cancer mortality increased with a higher number of MetS components. The results of the present study are important because the predictive value of MetS for cancer mortality in Japan has not been previously proven.Only four recent cohort studies have reported a relationship between MetS and cancer mortality –17. ProsThe present study also showed that the linear association between increases in the number of MetS components and cancer deaths, and the pathology of obesity is key in MetS because the presence of obesity affected the relationship between the number of MetS components and cancer mortality, whereas the absence of obesity did not. Previous studies also reported a dose–response relationship between MetS components and cancer mortality –16 as weMetS was positively associated with the risk of colorectal and breast cancer deaths in women. However, the number of cancer-type specific deaths was small. Previous cohort studies reported that MetS was positively associated with cancer mortality in the gastrointestinal system , particuWhile many definitions of MetS have been used worldwide, such as the NCEP , 33 and There was no significant difference in smoking between participants with and without MetS in both sexes. However, men with MetS smoked more ≥ 21 cigarettes per day than men without MetS . Current smoker in women may have less impact on MetS than in men because women had lower current smoker than men. There was no significant difference in alcohol drinking between participants with and without MetS in men, while women with MetS were significantly lower alcohol drinkers than women without MetS. One of the reasons may be that light to moderate alcohol consumption decreased the incidence of diabetes . The treThe mechanisms responsible for the relationship between MetS and an increased risk of cancer death remain unclear; however, potential factors include obesity, insulin resistance, and the insulin-like growth factor (IGF) system . Obesity2 correlates highly well with a WC of ≥ 85 cm in men and ≥ 90 cm in Japan [The present study has several potential limitations. The measurement of MetS was based on a single measurement only at baseline, which made it impossible to evaluate the effect of changes in metabolic risk factors over time on cancer mortality. Furthermore, we defined obesity of MetS using BMI instead of WC. Although WC and BMI can produce slight differences in the diagnostic performance and pathological meaning of MetS, BMI ≥ 25 kg/min Japan . In addiThe present results suggest that MetS is a significant predictor of cancer death in women. Furthermore, there is a dose–response association between an increasing number of MetS components and cancer mortality. These findings implied that subjects with MetS may need to prevention and management of cancer. Further studies are needed to confirm the influence of MetS on the risk of cancer.Additional file 1: Table S1. Multivariate analysis of cancer mortality with metabolic syndrome by sex, excluding participants <40 years. Table S2. Multivariate analysis of cancer mortality with the NCEP-ATP III and IDF by sex. Figure S1. The log-negative-log plot of the survival function for the number of metabolic syndrome components against time to death/follow-up time. Figure S2. The log-negative-log plot of the survival function for participants with and without metabolic syndrome against time to death/follow-up time.


Environmental and genetic factors play an important role in the etiology of breast cancer. Several small blood-based DNA methylation studies have reported risk associations with methylation at individual CpGs and average methylation levels; however, these findings require validation in larger prospective cohort studies. To investigate the role of blood DNA methylation on breast cancer risk, we conducted a meta-analysis of four prospective cohort studies, including a total of 1663 incident cases and 1885 controls, the largest study of blood DNA methylation and breast cancer risk to date.q value) was used to account for multiple testing.We assessed associations with methylation at 365,145 CpGs present in the HumanMethylation450 (HM450K) Beadchip, after excluding CpGs that did not pass quality controls in all studies. Each of the four cohorts estimated odds ratios (ORs) and 95% confidence intervals (CI) for the association between each individual CpG and breast cancer risk. In addition, each study assessed the association between average methylation measures and breast cancer risk, adjusted and unadjusted for cell-type composition. Study-specific ORs were combined using fixed-effect meta-analysis with inverse variance weights. Stratified analyses were conducted by age at diagnosis , estrogen receptor (ER) status (+/−), and time since blood collection . The false discovery rate . In addition, higher average methylation level was not associated with risk of breast cancer . We found no evidence of modification of this association by age at diagnosis (P = 0.17), ER status (P = 0.88), time since blood collection (P = 0.98), or CpG location (P = 0.98).The average age at blood draw ranged from 52.2 to 62.2 years across the four cohorts. Median follow-up time ranged from 6.6 to 8.4 years. The methylation measured at individual CpGs was not associated with breast cancer risk  contains supplementary material, which is available to authorized users. There are many well-established environmental and genetic factors associated with breast cancer risk but whether DNA methylation measured in blood is associated with breast cancer risk remains to be determined. The rationale for such an association is that blood DNA methylation levels could be a surrogate for breast tissue methylation –4, repreBRCA1 and RASSF1A gene promoters, and hypermethylation of the body of the ATM gene were more common in breast cancer cases [RPTOR, cg00736299 in MGRN1, and cg27466532 in RAPSN to be more commonly hypomethylated in breast cancer cases [Evidence for an association between blood-based DNA methylation and breast cancer risk is inconsistent . A recener cases , 15–21. er cases , althouger cases –25. A neer cases  reporteder cases . This gler cases , 29. Thier cases  and the er cases , reporteer cases .In this study, we examined the association between DNA methylation in blood and breast cancer risk in the largest to-date study, involving 1663 incident invasive breast cancer cases and 1885 controls combined from four prospective cohort studies.We combined results from four prospective studies: the MCCS , EPIC-Itminfi Bioconductor package [preprocessIllumina function. Subset-quantile within array normalization (SWAN) was performed to correct for type I and II probe bias [P value > 0.01. Also, each study excluded CpGs with a P value > 0.01 in more than 20% of the samples, and CpGs labeled as cross-reactive [Three of the cohorts  measured DNA methylation using the Illumina Infinium HumanMethylation450 BeadChip (HM450K) array while PLCO used the MethylationEPIC BeadChip, which includes 90% of the sites in the HM450K array . The fou package . Data weobe bias . Each streactive , 37, or P values. Statistical significance was defined by a false discovery rate (FDR)-adjusted P value, or q value, less than 0.05, which means that 5% of significant tests  were expected to be false positives. Heterogeneity in the odds ratio across studies or subgroups was assessed using the I2 statistic and the P value for the Cochran’s Q statistic.The four studies individually performed conditional  or unconditional (PLCO) logistic regression to estimate the odds ratio (OR) and associated standard error (SE) per one standard deviation increase in methylation for each of the 365,145 CpG probes, adjusting where appropriate for the matching variables specific to each study , and SE for probe k, θ the K × K correlation matrix of the K probes among controls, Φ the K × K diagonal matrix with the SEs along the diagonal and w a column vector of values equal to 1. We then report exp(βavg) as the average OR and calculate the 95% confidence interval under normality assumption and P values using the Wald test.To assess enrichment at specific genomic regions, we considered the average of the ORs for the CpGs located in those regions. We defined the average log (OR), Each of the four studies also performed adjusted logistic regression to assess the association between a one standard deviation increase in global DNA methylation and the risk of breast cancer. Global methylation was defined for each study participant as the average methylation level across all 365,145 CpGs. In addition, we computed average measures in CpG islands, CpG shores, CpG shelves, and “open sea,” as well as at regulatory regions defined using the UCSC classification  . CpG sitAll analyses were conducted using the R software, version 3.4.1.The characteristics of the 1663 cases and 1885 controls included in the meta-analysis are described in Table q > 0.59) overall, or after stratification by age , ER status (ER+/−), stage (early/late), or time since blood collection  (data not shown). To account for possible subclinical effects from occult disease at the time of blood collection, we also investigated risk associations < 2 years versus ≥ 2 years since blood draw. We observed putative associations within 2 years of blood draw with cg00899463  and cg07145930 , but there was substantial heterogeneity across studies for both CpGs (I2 = 100%), with each association driven by a single study.We found no evidence of association between blood DNA methylation measured at individual CpG sites and breast cancer risk . Overall, methylation at the promoter region of BRCA1 was not associated with breast cancer risk (P = 0.88); of the 26 CpGs in this region that we examined, pooled ORs were consistent in direction with previous reports for 14, with cg20185525 having the largest OR . With respect to gene RASSF1A, 43 CpGs were in its promoter region but only 7 of them were associated with breast cancer risk in the direction previously reported. Overall, there was no association with the promoter region of RASSF1A overall (enrichment P = 0.061). Of the 9 CpG sites located in the body of ATM, only two were associated with breast cancer risk in the direction previously reported and there was no enrichment (P = 0.26). Previously identified CpGs in RPTOR (cg06418238), MGRN1 (cg00736299) and RAPSN (cg27466532) were not associated with breast cancer risk .We next focused on CpGs and genes reported to be associated with breast cancer risk in previous studies. Of the 250 CpGs reported by Xu et al. , 205 werP = 0.26; P for study heterogeneity = 0.86; I2 = 0%; Fig. P = 0.92) after adjustment . When analyses were restricted to subjects with a family history of breast cancer (108 cases and 107 controls), no significant association was observed. In addition, the assays used in the aforementioned studies were mostly based on targeted regions, for which a single measurement of methylation for an entire genomic region is obtained, and not genome-wide array-based assays, as in our study, for which methylation measurements are performed at individual CpG sites. However, we conducted enrichment tests and still did not observe associations. Similar results were observed for RASSF1A, despite previously reported associations [ studies , 20, but studies , 18, 21.ciations , 42–44.ATM to be associated with breast cancer risk [ATM were statistically significantly associated with breast cancer risk in our study. However, the HM450 assay used in our analysis is gene-centered, with a special focus on gene promoters, and has less coverage of other areas of the genome, particularly repetitive elements. Our analysis included only nine CpG sites in the body of ATM so that we could not thoroughly assess gene-body methylation.A few studies have reported hypermethylation of repetitive elements within the body of cer risk , 15. NonRPTOR, cg00736299 in MGRN1, and cg27466532 in RAPSN that were recently reported to be associated with breast cancer risk [Previous findings for cg06418238 in cer risk  were notcer risk , and thiA previous analysis of the Sister Study reported a methylation signature for breast cancer consisting of 250 differentially methylated CpG sites in blood identified in a prospective study of 298 cases and 612 cancer-free women . We founThere was no association between global DNA methylation and breast cancer risk in our meta-analysis. Previously, two of the cohorts  included in our study reported significant associations with breast cancer risk , 30. HowPrevious studies that assessed associations between global DNA methylation and breast cancer risk have reached mixed conclusions. Global methylation  was measured using different methods, at different genomic locations , and various populations and study designs (retrospective versus prospective) were used, which makes it difficult to compare results. Several studies have also suggested that blood global hypomethylation is associated with increased cancer risk in general , 45–47, Our analysis has several strengths. First, it is the largest evaluation to date of blood DNA methylation and breast cancer risk. The large sample allowed us not only to investigate new associations, but also to test associations previously reported by smaller studies. Another important aspect of our analysis is the prospective design of all the studies included, which avoids the influence of reverse causation (methylation changes due to the presence of cancer), as well as potential effects on blood methylation of treatment given prior to blood collection. Our analysis also has some limitations. First, we had limited statistical power to detect small effects of methylation on breast cancer risk, despite having a sample size which was larger than that of previous studies which reported significant associations. Another limitation is that we restricted the analysis to sites in the Illumina HM450 BeadChip, which accounts for less than 2% of the 28 million CpG sites in the genome . This arIn summary, we found no evidence in this meta-analysis of four prospective cohort studies that DNA methylation measured in blood is associated with substantial variation in breast cancer risk. Larger studies may be required to determine if modest to weak associations exist between blood DNA methylation and breast cancer risk. Studies with greater methylation coverage of the genome may also have the potential to uncover novel associations.Additional file 1: Description of the four prospective studies. Also, a figure with the results of the association between average methylation and breast cancer, adding published data from the NOWAC study. (DOCX 126 kb)