The aim of this study was to develop a measurement instrument for assessing knowledge of breast cancer and perceived risk of developing the disease (MARA).641 women with a mean age of 36.19 years (SD = 7.49) participated in the study. Data collection took place during 2019 and included sociodemographic data, data on history of cancer and breast cancer, perceived risk, and feelings of concern about developing breast cancer. Internal consistency, test–retest reliability, convergent validity, and structural validity were tested.r = 0.201–0.906), as well as strong evidence of validity in relation to a questionnaire on breast cancer knowledge (r = 0.131–0.434). In addition, the subscales were shown to have high discriminatory power in terms of the presence or absence of a history of cancer or breast cancer, perceived risk, and feelings of concern.The questionnaire items comprise 4 subscales: risk factors (9 items), signs and symptoms (9 items), perceived risk (6 items), barriers (7 items). A factor analysis revealed that the first two subscales had two dimensions each, whereas the other two subscales had one dimension each. Each subscale was shown to have adequate reliability (α = 0.74–0.92) and temporal stability (The MARA questionnaire represents a valid, reliable tool for assessing Spanish women’s knowledge, risks, perceptions, and barriers regarding breast cancer. A large proportion of the most prevalent conditions of our time are associated with unhealthy behaviors. Specifically, there is evidence to suggest that engaging in healthy behaviors contributes to the prevention of cancer .According to the health belief model (HBM), the following factors influence whether or not a person makes behavioral changes when faced with a potential risk of developing a condition: their perception of the severity of the condition, their susceptibility to the condition, the benefits that a change in behavior will have on prevention of the condition, and the perceived difficulties in implementing the recommended changes in behavior . In addiFor these reasons, the availability of a tool for assessing an individual’s perceived risk, ability to engage in preventive behaviors, and knowledge about a particular condition is essential so that disease prevention and health promotion strategies can be implemented to encourage healthy lifestyles. This is even more important when it comes to breast cancer, which is one of the main health problems affecting women around the world, and Spain is no exception. A number of behaviors that can be addressed and modified play a major role in the development of breast cancer .A recently published review explored the factors influencing women’s decisions to participate in breast cancer prevention programs, identifying the following: their perceived susceptibility to developing breast cancer, efforts required on their part to engage in healthy behaviors, their perceived competence, and their autonomy in carrying out the program, among others . These fSeveral tools are currently available for assessing a woman’s level of knowledge of breast cancer and her perceived risk of developing the disease , 9. ThesBeing able to assess the knowledge of risk factors related to breast cancer, signs and symptoms of breast cancer, perceived individual risk of developing breast cancer, the ability to engage in preventive behaviors, and barriers to breast cancer prevention can help healthcare workers to meet women’s needs in relation to breast cancer prevention and create targeted prevention plans. This would also help women to become aware of their own health status.As we were unable to identify any validated questionnaires in Spanish specifically assessing a combination of the aforementioned aspects, the objective of our study is to design and analyze the metric properties of the MARA questionnaire to assess levels of knowledge of breast cancer, the perceived risk of developing it, and perceived barriers to engaging in preventive behaviors.https://doi.org/10.7334/psicothema2016.209). A convenience sampling method was used. The eligibility criteria were (i) being at least the age of majority and (ii) not having been previously diagnosed with breast cancer.This validation study was carried out in 2019. Although there is no universal criterion, the usual recommendation is that each item should be answered by 5–10 individuals or include at least 200 observations . Women who were interested in participating were sent an informed consent form via email, which they then returned signed.Women and trusted individuals who had collaborated with the research team on previous studies were contacted via email, text message, and social media. In addition, after 2–3 weeks, the instrument was administered again (test–retest) to a total of 30 women randomly selected from among the participants. At both points in time, in order to fulfill the aforementioned objectives, the participants received by email or text message a link to the self-administered questionnaire using Google Forms, to be completed online. Responses were automatically sent to an email address created specifically for this study and accessible only to members of the research team. Participant data were anonymized using randomized alphanumeric coding. No personal data that could directly identify participants were requested. The provisions of Spanish Organic Law 3/2018, of the 5th of December, on Personal Data Protection and Guarantee of Digital Rights were observed at all times [REF].The MARA questionnaire was based on the b-CAS questionnaire , with thWith the permission of Professor Rakkapao, the b-CAS questionnaire was translated into Spanish following the back-translation procedure proposed by the World Health Organization . InitialIn the absence of a ‘gold standard’ instrument, the MARA questionnaire was administered along with questions written by Seven et al. . The queThe descriptive statistics of the items  were analyzed. The reliability of each scale was calculated using coefficient alpha for ordinal data  and McDoConstruct validity was assessed using exploratory factor analysis (EFA). The unweighted least squares (ULS) method was used to estimate the parameters in the EFA, and the optimal implementation of parallel analysis (OIPA) was used to determine the number of dimensions of each scale  and 0.434 , respectively. In turn, the breast cancer knowledge questionnaire showed a correlation of 0.394  with the non-specific signs and symptoms scale versus a correlation of 0.131  with the specific signs and symptoms scale. Finally, the perceived risk scale showed a correlation of 0.320  with the breast cancer knowledge questionnaire, whereas the barriers scale showed a correlation of − 0.230 .p < 0.001) on non-modifiable risk factors (d = 0.43), modifiable risk factors (d = 0.36), and all factors (d = 0.49) than women without university education. Women with a university education also displayed greater knowledge of non-specific signs and symptoms  and all signs and symptoms , but showed no difference in specific signs and symptoms . Finally, no differences were found regarding perceptions  or barriers  based on their level of education.Differences in modifiable risk factors are apparent, with women with a family history of cancer scoring significantly higher. Differences can also be identified on the barriers scale, with women with no history of breast cancer scoring significantly higher Table . FinallyThe MARA questionnaire for assessing knowledge of breast cancer, perceived risk of developing breast cancer, and perceived barriers regarding breast cancer prevention has been shown to have adequate psychometric properties for use in Spanish-speaking women. To the best of our knowledge, there is no tool available in Spanish that has the same characteristics as the MARA questionnaire. However, its content, structure, and psychometric properties are similar to those observed in questionnaires developed in other languages , 9, 11.The MARA questionnaire consists of four scales: risk factors, signs and symptoms, perceived risks, and perceived barriers. The risk factors scale displayed a two-dimensional structure, with two subscales: modifiable risk factors and non-modifiable risk factors. The signs and symptoms scale also exhibited a two-dimensional structure consisting of specific signs and symptoms—associated with breast cancer by the general population—and non-specific signs and symptoms—associated with other breast conditions by the general population. Both scales (risk factors and signs and symptoms) showed a strong correlation between their subscales, allowing a total score to be obtained. Both the perceived risks and the barriers scales exhibited an essentially one-dimensional structure. Along with the fact that all the scales showed strong correlations between one another, this demonstrates that the scales constitute a significant body of knowledge on breast cancer.Internal consistency was adequate for all scales, as shown by both Cronbach’s alpha and McDonald’s omega coefficients, ranging from 0.77 to 0.92. The scales also show adequate temporal stability in general . In termWith respect to the discriminatory power of the battery of questions, differences in the risk factors scale based on the presence or absence of a family history of cancer stand out, with women with a family history of cancer scoring significantly higher. In addition, when looking at the barriers scale, women with no history of breast cancer show significantly higher scores. These results are consistent with those observed in previous studies. In addition, several authors suggest that having loved ones with a history of cancer acts as a facilitator for the development of preventive attitudes  and behaThe MARA questionnaire has been shown to be effective in assessing knowledge of risk factors related to breast cancer, signs and symptoms of breast cancer, perceived individual risk of developing breast cancer, ability to engage in preventive behaviors, and barriers to breast cancer prevention. This information can help healthcare workers to meet women’s needs in relation to breast cancer prevention.On a personal level, possessing knowledge increases intentions to adopt healthy behaviors . SpecifiFailure to perceive the existence of a health problem may lead to a failure to take action to prevent or address said problem. When women are aware of the risk factors for breast cancer, they are better placed to perceive their actual risk of developing the disease . This caIn addition, identifying needs relating to the dimensions covered by the MARA allows these needs to be addressed and met, which can help women to take an active role not only in preventing the condition, but also in detecting it promptly. It should be borne in mind that prevention plans in Spain are standardized and their inclusion criteria are essentially based on women’s age and individual and family history of breast cancer. For example, women and immediate relatives of women who have not had breast cancer are included in prevention programs from the age of 50 onward, which does not appear reasonable given the multiple causes associated with this type of cancer. This is demonstrated in a study by Mukama et al. , which sOne limitation of our study is that the sample may not be representative. Culture and society determine behavior, so the items of the MARA should be reviewed before use in other Spanish-speaking regions, such as Hispanic America.However, our study also has a number of strengths. Confirming the psychometric properties of the MARA questionnaire has important clinical implications. Firstly, the MARA questionnaire can be used in healthcare and gynecological facilities to assess Spanish women’s knowledge, risks, perceptions, and barriers regarding breast cancer. Secondly, the independent measurement of these aspects facilitates the identification of specific individual needs so that professionals can better address them and take steps to develop effective interventions. Finally, the results of such an assessment may be used to inform educational and counseling interventions for addressing women’s misconceptions and improving their knowledge about breast cancer.The MARA questionnaire has adequate internal consistency and an adequate factor structure. It therefore represents a valid, reliable tool for assessing Spanish women’s knowledge, risks, perceptions, and barriers regarding breast cancer.


The mechanistic target of rapamycin (mTOR) pathway promoted by positive energy imbalance and insulin-like growth factors can be a mechanism by which obesity influences breast cancer risk. We evaluated the associations of body fatness with the risk of breast cancer varied with phosphorylated (p)-mTOR protein expression, an indication of the pathway activation.n = 715; 574 [80%] Black and 141 [20%] White) and non-cancer controls  were selected from the Women’s Circle of Health Study. Surgical tumor samples among the cases were immunostained for p-mTOR (Ser2448) and classified as p-mTOR-overexpressed, if the expression level ≥ 75th percentile, or p-mTOR-negative/low otherwise. Anthropometrics were measured by trained staff, and body composition was determined by bioelectrical impedance analysis. Odds ratios (ORs) of p-mTOR-overexpressed tumors and p-mTOR-negative/low tumors compared to controls were estimated using polytomous logistic regression. The differences in the associations by the p-mTOR expression status were assessed by tests for heterogeneity.Women with newly diagnosed breast cancer (P-heterogeneity < 0.05), although the OR estimates were not significant. For the measurement of central adiposity, cases with p-mTOR overexpressed tumors had a higher odds of being at the Q3  and Q4  of waist circumference (WC) compared to controls. Similarly, cases with p-mTOR overexpressed tumors had a higher odds of being at the Q3  and Q4  of WHR compared to controls. These associations of WC and waist-to-hip ratio (WHR) did not differ by tumor p-mTOR status .Cases with p-mTOR-overexpressed tumors, but not cases with p-mTOR-negative/low tumors, compared to controls were more likely to have higher body mass index (BMI), percent body fat, and fat mass index (Our findings suggest that in this population composed of predominately Black women, body fatness is associated with breast cancer differently for p-mTOR overexpression and p-mTOR negative/low expression. Whether mTOR plays a role in the obesity and breast cancer association warrants confirmation by prospective studies.The online version contains supplementary material available at 10.1186/s13058-021-01458-z. The underlying mechanisms between obesity and breast cancer development are not completely understood and may differ by cancer subtype and body size measurement. A widely accepted model is that, in postmenopausal women, obesity increases circulating estrogen levels through their aromatization in adipose tissue and promotes estrogen receptor–positive (ER+) breast cancer . This moMTOR, were associated with increased risk of breast cancer  Black and 141 [20%] White patients) and 1983 controls (1280 [64%] Black and 713 [36%] White women). The percentage of Black women in cases was higher than that in controls because WCHS focused on collecting tumor specimens in Black women in the later stage of the study. Among the cases, 644 had invasive breast cancer, and 71 had DCIS.We used p-mTOR to indicate mTOR pathway activation as the protein expression was positively correlated with BMI as well as key phosphorylated proteins in the upstream and downstream of the mTOR pathway, including p-AKT, p-p70S6K, and p-4EBP1 , 15. SecStained slides were digitally imaged at magnification × 20 using the Aperio ScanScope XT (Leica Biosystems) digital slide scanner system. Regions were identified and manually annotated to appropriately represent the heterogeneity of staining of each TMA core and to reduce irrelevant regions from image analysis calculations. The Aperio image analysis platform was used to develop quantitative image analysis algorithm macros for the quantification of IHC slides. A cytoplasmic algorithm was tailored to fine tune the cell feature detection using cellular, nuclear, and stain parameters, creating a specific algorithm macro for p-mTOR based on the cell compartment location of the target protein. The cytoplasmic algorithm analyzed DAB staining intensity and the percentage of cells containing stain within the cytoplasm compartment. The algorithm results provided total number of cells and percentage per scoring class . A histologic score (H-score) at the core level was calculated by the formula [1 × (% cells 1+) + 2 × (% cells 2+) + 3 × (% cells 3+)] × 100 . The corData on demographic characteristics, history of benign breast disease, reproductive and menstrual histories, family history of breast cancer in a first-degree relative, oral contraceptive use, and history of diabetes and its treatment were obtained by in-person interviews . Anthropt tests for continuous variables and χ2 tests for categorical variables. We performed polytomous  logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for p-mTOR overexpressed and for p-mTOR negative/low breast cancer in relation to the body fatness variables [2 (class II/III obesity) [r > 0.80), and WHR was modestly correlated with BMI, percent body fat, and fat mass index .Breast cancer cases with p-mTOR overexpressed tumors were defined as having p-mTOR expression levels above the 75th percentile level , and cases with p-mTOR negative/low tumors were those having expression levels below the 75th percentile. Because there is no standard definition for p-mTOR overexpression, we examined 2 additional cutoff points of p-mTOR expression levels: 25th percentile (H-score = 1) and 50th percentile (H-score = 20) for defining p-mTOR overexpressed tumors. Demographics and body fatness measurements were compared among p-mTOR overexpressed cases vs. controls and p-mTOR negative/low cases vs. controls using ariables . The modobesity) . WC, WHRWe compared the ORs of p-mTOR overexpressed tumors defined by the 3 cutoff points of p-mTOR expression  in association with body size . Patients who had p-mTOR negative/low tumors were more likely than controls to have BMI ≥ 30, larger WC, and higher WHR, but to a lesser extent compared to the differences between the cases with p-mTOR overexpressed tumors and controls. Compared with patients having p-mTOR negative/low tumors, patients with p-mTOR overexpressed tumors had higher BMI, larger WC, and more body fat, and their tumors were more likely to be ER+ (87.0% vs. 59.5%).Table P-heterogeneity = 0.011). There was an inverse association between BMI ≥ 35 and p-mTOR negative/low tumors . For the measurement of central adiposity, cases with p-mTOR overexpressed tumors had a higher odds of being at the Q3  and Q4  of WC compared to controls. Similarly, cases with p-mTOR overexpressed tumors had a higher odds of being at the Q3  and Q4  of WHR compared to controls. These associations of WC and WHR were not observed in cases with p-mTOR negative/low tumors compared to controls, although the associations did not differ by tumor p-mTOR status . In the subgroups, the association of BMI with p-mTOR overexpressed breast cancer appeared stronger in postmenopausal women (P-trend = 0.09) than premenopausal women (P-trend = 0.92) , but not those with ER– tumors. Also among women with ER+ tumors, larger (Q3 and Q4) vs. smaller (Q1) of WC and WHR were associated with increased risk of p-mTOR overexpressed tumors. Data among women with ER– tumors also suggest such associations, although the estimates were significant only for women in Q3 . Similar results were observed for ER+/PR+ and ER–/PR– tumors  WC and WHR compared to controls. Our findings suggest that mTOR pathway activation indicated by p-mTOR expression may be relevant to the association between body fatness and breast cancer risk. To our knowledge, this study is among the first to examine the associations between body fatness measurements and the risk of breast tumors with p-mTOR overexpression.N = 25). Our findings require replication with a larger sample of ER– tumors. If confirmed, our findings suggest that targeting the mTOR pathway using pharmacological approaches, such as metformin [Our stratified analyses on tumor ER status and menopausal status showed results consistent with our current understanding of obesity in association with breast cancer risk. If mTOR pathway activation is a mechanism by which body fatness influences breast cancer risk, the association of body fatness in relation to mTOR activation should be observed in postmenopausal women with ER+ tumors for obesity defined by high BMI, as the epidemiologic evidence indicates –5. In ouetformin , 27 and We observed an inverse association between BMI ≥ 35 vs. < 25 and p-mTOR-negative/low breast cancer overall and among women with ER– tumors. The association was comparable for both premenopausal and postmenopausal women (data not shown). Similarly, in the WCHS and AMBER Consortium, BMI ≥ 30 or 35 was associated with a lower risk of ER– or triple-negative breast cancer in postmenopausal women . The expWe acknowledge that the body fatness measurement in this study may not accurately reflect the specific adiposity compartments that are most relevant to mTOR pathway activation and breast cancer etiology. The body composition of participants was assessed by bioelectrical impedance analysis, and the method may have larger errors among those with lower vs. higher percent of body fat . BMI is The strengths of our study include rigorous and quantitative measurements of protein expression in breast tumors and multiple measurements of body fatness. We manually annotated the stained tissue to minimize influences from other tissue components, such as the stroma, and performed automated imaging analysis to derive objective scores. The continuous H-score has the flexibility to modify cutoffs for defining p-mTOR overexpression. In addition, body fatness was measured by trained staff who used a standardized protocol. The sample included a relatively large number of Black women, a population with high prevalence of obesity in general and central obesity  as well r = 0.26–0.31) and highly correlated with total phosphoprotein levels (r = 0.71), which is a summation of the three phosphoproteins  that was derived from expression levels of seven phosphoproteins in the pathway  that we evaluated in patients with breast cancer, p-mTOR has the strongest association in relation to body fatness . In addiSeveral other limitations of our study should be noted. First, as an inherent bias of case-control studies, body fatness was assessed after breast cancer diagnosis among cases. The observed associations might have been affected if the participants had changes in weight or body composition because of breast cancer development and treatment . StudiesIn this case-control study with a large proportion of Black women, we compared several body fatness measurements between cases with p-mTOR overexpressed tumors or p-mTOR negative/low tumors with non-cancer controls. We found that higher vs. lower levels of body fatness tended to be associated with p-mTOR overexpressed tumors, but not p-mTOR negative/low tumors. The associations stratified by tumor ER status and menopausal status are largely consistent with epidemiologic findings on body fatness and breast cancer risk. Our findings suggest that mTOR and its related signaling pathway is potentially an underlying mechanism by which body fatness influences breast cancer risk. The strength of the associations was modest (OR = 1.5–2.0), suggesting that the influence of obesity fatness on breast cancer risk is likely through multiple mechanisms. Our findings warrant further confirmation with studies of larger sample size, as statistical power in the current study may not be sufficient in detecting the heterogeneity of the associations between ER subtypes and estimating the risks within a subtype. A prospective study design is also necessary to confirm the associations.Additional file 1: Supplemental Table 1. Pearson correlation coefficients of the body fatness measurements. Supplemental Table 2. Odds ratios for p-mTOR-overexpressed breast cancer, with p-mTOR overexpression defined as above the 25th, 50th, and 75th percentile of the H-score, in association with BMI, WC, and WHR. Supplemental Table 3. Odds ratios for p-mTOR-overexpressed breast cancer in association with body size measurements by menopausal status. Supplemental Table 4. Odds ratios for p-mTOR-overexpressed breast cancer in association with body size measurements by race. Supplement Table 5. Odds ratios of breast cancer risk in relation to p-mTOR expression associated with body size measurements among invasive breast cancer cases and controls. Supplemental Table 6. Odds ratios of breast cancer risk in relation to p-mTOR expression associated with body size measurements in ER+/PR+ and ER–/PR– tumors. Supplemental Table 7. Pearson correlation coefficients (r) for phosphoprotein expression levels.


A paucity of research addresses breast cancer screening strategies for women at lower-than-average breast cancer risk. The aim of this study was to examine screening harms and benefits among women aged 50-74 years at lower-than-average breast cancer risk by breast density.Three well-established, validated Cancer Intervention and Surveillance Network models were used to estimate the lifetime benefits and harms of different screening scenarios, varying by screening interval . Breast cancer deaths averted, life-years and quality-adjusted life-years gained, false-positives, benign biopsies, and overdiagnosis were assessed by relative risk (RR) level  and breast density category, for US women born in 1970.Screening benefits decreased proportionally with decreasing risk and with lower breast density. False-positives, unnecessary biopsies, and the percentage overdiagnosis also varied substantially by breast density category; false-positives and unnecessary biopsies were highest in the heterogeneously dense category. For women with fatty or scattered fibroglandular breast density and a relative risk of no more than 0.85, the additional deaths averted and life-years gained were small with biennial vs triennial screening. For these groups, undergoing 4 additional screens  averted no more than 1 additional breast cancer death and gained no more than 16 life-years and no more than 10 quality-adjusted life-years per 1000 women but resulted in up to 232 more false-positives per 1000 women.Triennial screening from age 50 to 74 years may be a reasonable screening strategy for women with lower-than-average breast cancer risk and fatty or scattered fibroglandular breast density. There is general consensus that biennial screening from ages 50-74 years is effective in reducing breast cancer mortality and has a favorable balance between benefits and harms . Risk-baThe proportion of women at low risk in the population is substantial; for example, 34% of US women aged 40-74 years have a 5-year risk of developing breast cancer below 1.00% based on the Breast Cancer Surveillance Consortium (BCSC) risk model ,9. EstabBreast density has also received attention as an important factor that influences risk of developing breast cancer, as well as affecting the balance between benefits and harms of screening, because low breast density not only leads to a reduced risk for developing disease but also increases the sensitivity of mammography ,10,14. TWe used 3 well-established microsimulation models developed independently as part of the National Cancer Institute–funded Cancer Intervention and Surveillance Modeling Network consortium: model E , model Ghttp://www.bcsc-research.org) for sensitivity, specificity, and benign biopsy rate of digital mammography by age, breast density, and screening round (first vs subsequent). We modeled 16 subgroups of women, defined on the basis of combinations of risk levels  and invasive breast cancers detected. Benefits included breast cancer deaths averted, life-years gained, and quality-adjusted life-years (QALYs) gained. To calculate QALYs, we applied health-related quality-of-life utilities by age , and we We presented all outcomes by subgroups of risk and density for each strategy using the median  of the 3 models. Each outcome was compared with a reference value, defined as the model-specific results for biennial screening from age 50 to 74 years, all densities combined , and average risk (RR = 1). We evaluated the differences between screening scenarios by assessing the incremental benefits and incremental harms by dividing the incremental harm by the incremental benefits.We performed sensitivity analyses on varying utility values for undergoing screening and additional workup and on varying specificity by risk   detected in the average-risk (RR = 1) extremely dense group and decreased with decreasing risk and density in all 3 models to 39 (range = 33-52) in the lowest risk-density category  . The treThe absolute numbers of lifetime benefits decreased with decreasing risk and with decreasing density in all 3 models. For women with lower-than-average risk and fatty breasts, screening led to fewer benefits (breast cancer deaths averted and life-years gained) than for women at average risk and/or with denser breasts . The finThe number of false-positives were relatively stable over risk given our model assumptions . The numThe relationship between overdiagnosis and density varied across models: in model E, overdiagnosis increased with increasing density; in model W, overdiagnosis was highest in the 2 middle categories; and in model GE, overdiagnosis slightly decreased with increasing density . When ovThe ratio between harms and benefits showed diversity across models and measures  incremental benefits  are small for biennial screening from age 50 to 74 years compared with triennial screening. This is reflected in the higher ratio between additional false-positives and additional life-years gained in the low-risk and low-density subgroups when going from triennial to biennial screening than in the average-risk population, indicating that there are (relatively) more harms relative to benefits in these subgroups than in the average-risk population.The models consistently found that the benefits of screening decrease with decreasing risk, whereas the number of false-positives and unnecessary biopsies are mostly stable over categories of low risk. The latter was due to our assumption that mammography performance was unaffected by risk. The benefits also decreased with decreasing density, although the decrease in benefits was not so steep when comparing the highest density category to the next category, indicating that elevated risk among women with high density is a more important determinant of absolute screening benefits than high breast density. With regard to harms, false-positives and unnecessary biopsies were highest in the heterogeneously dense category, whereas the trends in overdiagnosis across density categories varied across models.These results are useful for informing guidelines and for clinical practice. Because the conditions that result in lower-than-average risk are common, primary care providers could use these results in shared decision-making discussions with women. Most risk factors that lead to a decreased risk are not easily modifiable, but they are relatively straightforward to ascertain. If a subgroup of women can be identified to be at low risk, these women can relatively safely decrease their screening intensity from biennial to triennial.We acknowledge that breast density is not known in women who have never been screened and is therefore difficult to use to tailor the interval of screening among low-risk women. However, it is possible to tailor the screening interval after a first mammogram based on density, especially because mandated standard reporting of breast density to women after a mammogram has become increasingly more common in the United States. Importantly, the measurement of breast density has become more reliable with automated density measures and has similar accuracy in predicting breast cancers .Strengths of this study include consideration of breast density; evaluation of a comprehensive set of outcomes for benefits and harms; and the use of 3 well-established, validated models . One of Our study also had some limitations. Most importantly, we assumed that the relative risk only influenced the onset of breast cancer and was constant over age. Thus, our models assumed that the age distribution of cancers was similar to the average population reported in SEER and was just proportionately lower. We also assumed that the screening performance and the distribution of tumors in terms of estrogen receptors and HER2 are the same for lower-than-average risk women as that for average-risk women. It would be useful to reassess our results when there are additional data on disease biology and screening performance by risk level. Second, we modeled digital mammography screening. Several studies have suggested that the introduction of tomosynthesis in the United States has led to a reduction in recall rates ,42, so tDespite the substantial differences between models on these key assumptions, models come to the same conclusion regarding the incremental benefits and harms of biennial vs triennial screening in low-risk women.Overall, our collaborative modeling study showed that triennial screening from ages 50 to 74 years can be considered for women who have fatty or scattered fibroglandular breast density and average or low risk of developing breast cancer and for women with very low risk at any density level. By undergoing more intense screening, these women are subjected to more harms, with only small added benefits. The results contribute to the growing body of evidence that tailored screening has many advantages over age-based guidelines for average populations . It willhttps://www.bcsc-research.org/about/work-acknowledgement.This work was supported by the National Cancer Institute at the National Institutes of Health . Data collection for model inputs from the Breast Cancer Surveillance Consortium (BCSC) was supported by the National Cancer Institute grant P01 CA154292 and grant U54 CA163303. The collection of BCSC cancer and vital status data used in this study was supported in part by several state public health departments and cancer registries throughout the United States. For a full description of these sources, please see Role of the funders: The funders had no role in the design of the study; the collection, analysis, and interpretation of the data; the writing of the manuscript; or the decision to submit the manuscript for publication.Disclosures: Dr Kerlikowske reports unpaid consulting with Grail on the STRIVE study. The other authors have no disclosures.Acknowledgment: The authors thank Isabelle Lefebvre for data processing and analysis.Author contributions: Conception and design: NTvR, CBS, OA, KK, JSM, DLM, BLS, NKS, HJdK, ATD, ANAT; Data analysis and interpretation: NTvR, CBS, JHM, OA, JJvdB, KK, JSM, DLM, BLS, NKS, HJdK, ATD, ANAT; Funding acquisition: KK, JSM, DLM, BLS, ATD, ANAT; Writing-original draft: NTvR; Writing-review&editing: CBS, JHM, OA, JJvdB, KK, JSM, DLM, BLS, NKS, HJdK, ATD, ANAT.n.vanravesteyn@erasmusmc.nl).Input and output data from the models are available by sending a request to the corresponding author of this study (e-mail: djaa218_Supplementary_DataClick here for additional data file.


Glucocorticoids could theoretically decrease breast cancer risk through their anti-inflammatory effects or increase risk through immunosuppression. However, epidemiological evidence is limited regarding the associations between glucocorticoid use and breast cancer risk.We investigated the association between systemic glucocorticoid use and breast cancer incidence in the E3N cohort, which includes 98,995 women with information on various characteristics collected from repeated questionnaires complemented with drug reimbursement data available from 2004. Women with at least two reimbursements of systemic glucocorticoids in any previous 3-month period since January 1, 2004, were defined as exposed. We considered exposure as a time-varying parameter, and we used multivariable Cox regression models to estimate hazard ratios (HRs) of breast cancer. We performed a competing risk analysis using a cause-specific hazard approach to study the heterogeneity by tumour subtype/stage/grade.insitu = 1.34 (1.01–1.78); HRinvasive = 0.86 (0.76–0.97); Phomogeneity = 0.01]. Regarding the risk of invasive breast cancer, glucocorticoid exposure was inversely associated with oestrogen receptor (ER)-positive breast cancer ; it was also inversely associated with the risk of stage 1 or stage 2 tumours but positively associated with the risk of stage 3/4 breast cancers .Among 62,512 postmenopausal women (median age at inclusion of 63 years old), 2864 developed breast cancer during a median follow-up of 9 years (between years 2004 and 2014). Compared with non-exposure, glucocorticoid exposure was not associated with overall breast cancer risk [HR = 0.94 (0.85–1.05)]; however, it was associated with a higher risk of in situ breast cancer and a lower risk of invasive breast cancer [HRThis study suggests that the association between systemic glucocorticoid use and breast cancer risk may differ by tumour subtype and stage.The online version contains supplementary material available at 10.1186/s12916-021-02004-6. Synthetic glucocorticoids, drugs that are structurally and pharmacologically similar to the endogenous hormone cortisol, are used to treat a wide range of diseases, most often chronic diseases such as rheumatologic disorders, autoimmune diseases, allergies, or respiratory diseases . GlucocoTo advance knowledge on the role of glucocorticoids on breast cancer development, we evaluated the associations between systemic glucocorticoid use and breast cancer incidence, overall and by breast cancer subtype, in the E3N  cohort.The E3N study is an ongoing prospective cohort, which initially aimed to investigate the relationship between lifestyle, diet, hormones, environment, and female cancers . In 1990n = 1529) and were therefore excluded. Thus, our study population included 62,512 E3N postmenopausal women.Follow-up started on July 1, 2004 (study baseline) and ended at the date of diagnosis of any cancer , the latest completed questionnaire, or November 17, 2014 (the date at which the last considered E3N questionnaire was sent to participants), whichever occurred first. The selection of the study population has been already described previously . In brieMost breast cancer cases were self-reported in the questionnaires or, to a lesser extent, spontaneously reported by participants’ next of kin or identified from the cause of death data. Among self-reported cases for which we could obtain medical information , less than 5% were not confirmed by the medical information obtained, and these false-positive self-reports were considered as non-cases. Due to the low proportion of false-positive self-reports, self-reported cases for which we could not obtain medical information were considered as true cases. Pathology reports, which were obtained for 95% of the incident cases identified in the entire cohort, were used to extract information on tumour characteristics such as invasiveness status (in situ/invasive/unknown), oestrogen receptor (ER) status (ER-positive/ER-negative/unknown), progesterone receptor (PR) status (PR-positive/PR-negative/unknown), human epidermal growth factor receptor 2 (HER2) status (HER2-positive/HER2-negative/unknown), histological subtype , grade (from 1 to 3 or unknown), and stage (from 1 to 4 or unknown).We considered all deliveries of systemic glucocorticoids  since January 1, 2004. The following data were extracted for each glucocorticoid delivery: date of purchase, active ingredient, number of pills/phials per package, and route of administration.We defined “recurrent” users as women with at least two reimbursements of the drug of interest during any previous 3-month period since January 1, 2004. Other women were considered as never/occasional users and served as the reference category. We classified exposure among recurrent users according to the following characteristics: type of glucocorticoid (active ingredient), route of administration, time since the first or the last use, age at first use, and cumulative number of reimbursements. The date of last use was calculated as the date of last purchase + the number of pills/phials contained in the last reimbursed box. Women with glucocorticoid reimbursements between January 1, 2004, and April 1, 2004, were likely to have begun their treatment before the availability of reimbursement data, and in that case, the cumulative number of reimbursements, age at first use, and time since the first use might be left-truncated. Thus, unless they could be assigned to the highest category of number of reimbursements/time since first use or the lowest category of age at first use, we assigned these women to an “unknown” category.Variables considered as potential confounders are listed in Table We used multivariable Cox regression models with age as the time scale and stratified by birth cohort (in 5-year categories) to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association of recurrent glucocorticoid use  with breast cancer risk, overall and by breast cancer subtype. We considered exposure, other factors issued from the reimbursement database, and covariates updated during follow-up as time-varying parameters. Thus, for a given drug, participants contributed follow-up as unexposed until purchasing the drug for the second time in a 3-month period. The cumulative number of reimbursements, age at first use, and time since the first/last use were also updated during follow-up.We systematically included in the multivariable models the following covariates: educational level, recent mammogram, and established risk factors for breast cancer . The number of consultations with the doctor during the preceding 6 months and recurrent use of proton pump inhibitors modified the HR of certain breast cancer subtypes associated with exposure to glucocorticoids by at least 0.05 point and were therefore included in the final multivariable models. None of the other factors tested as potential confounding factors  was included in the final models. The categories used are displayed in Table We lagged by 6 months all variables coming from the reimbursement database  to allow a period of latency and to minimize reverse causation bias due to any early breast cancer symptoms . The resWe evaluated the effect modification by age, BMI, MHT use, comorbidities, and other drugs  by including cross-product interaction terms in the Cox models.We performed a competing risk analysis using the cause-specific hazards approach to study the heterogeneity by tumour subtype/stage/grade , 18. We We conducted a sensitivity analysis in which women with no reimbursement of glucocorticoids served as the reference category . Then, we repeated the analyses with exposed women defined as women with at least three reimbursements (women with less than three reimbursements served as the reference category). We also used a 2-year exposure lag instead of the 6-month lag. To assess the potential impact of surveillance bias, we restricted our analyses (i) to women who self-reported having had a mammogram performed during the previous follow-up cycle and (ii) to women with at least one medical consultation during the preceding 6 months.All tests of statistical significance were two-sided, and significance was set at .05. We performed all analyses using the SAS software, version 9.4 .During a median follow-up time of 9 years, 2864 breast cancer cases were diagnosed  among the 62,512 participants. Among the invasive cases, 2260 had information on ER status (1952 ER-positive and 308 ER-negative), 2206 on PR status (1459 PR-positive and 747 PR-negative), 2029 on HER2 status (244 HER2-positive and 1785 HER2-negative), 2326 on histological subtype , 2236 on grade , and 2273 on stage . Among the 62,512 participants, 30% had never been exposed, 42% had been occasionally exposed, and 28% had been recurrently exposed to systemic glucocorticoids during follow-up. Among the recurrent users, the most frequently reimbursed glucocorticoids were prednisone , prednisolone (30%), betamethasone (13%), and cortivazol (10%). Less than 8% of reimbursements were for dexamethasone, methylprednisolone, hydrocortisone, or triamcinolone.Compared to never/occasional users, recurrent glucocorticoid users were older, had a higher BMI, had a more frequent medical follow-up, were more likely to have ever used MHT, and had more frequent histories of arthrosis, asthma, chronic bronchitis, or hay fever as well as recurrent exposure to nonsteroidal anti-inflammatory drugs, paracetamol, proton pump inhibitors, and anti-arthritics Table .Phomogeneity < 0.01), with a positive association of glucocorticoid use with the risk of in situ breast cancer [HR = 1.34 (1.01–1.78)] and an inverse association with the risk of invasive breast cancer [HR = 0.86 (0.76–0.97)].The age-adjusted HR of breast cancer associated with having recurrently been exposed to glucocorticoids, compared with having never/occasionally been exposed, was 0.98 (95% CI 0.89–1.09). The multivariable HR was 0.94 (95% CI 0.85–1.05)  and ER status (Phomogeneity = 0.03) were found ; HRstage2 = 0.67 (0.52–0.86)] and a higher risk of stage 3/4 breast cancer [HRstage3 or 4 = 1.49 (1.02–2.20)]. The lower risk of invasive breast cancer was only found for ER+ breast cancer . The breast cancer-glucocorticoid association did not differ by other breast cancer characteristics . No statistically significant heterogeneity/trend of invasive breast cancer risk according to the type of glucocorticoid, route of administration, time since first/last use, or age at first use was found , n exposed cases = 908] . The assHowever, our results, suggesting a lower risk of invasive breast cancer among glucocorticoids users, especially for ER+ tumours, are supported by experimental models showing that the expression of the glucocorticoid receptor was correlated with improved breast cancer prognosis especially for ER+ tumours and that activation of the glucocorticoid receptor may reduce oestrogen-induced cell proliferation in ER+ breast cancer , 20. IndOther mechanisms which could lead to a decreased breast cancer risk include the effects of glucocorticoids on angiogenesis , or the The higher risk of stage 3/4 breast cancers with glucocorticoid exposure is in line with other previous experiments showing that the glucocorticoid receptor was overexpressed in metastatic breast cancer and might be a strong inducer of epithelial-to-mesenchymal transition . A recenAlthough in line with some experimental studies, the mechanistic interpretation of our epidemiological findings is unclear. In particular, the potential dual effects of glucocorticoids on breast cancer development according to tumour stage have never been evaluated in previous experimental studies. The mechanisms underlying the potential impact of glucocorticoids according to tumour stage should be explored in experimental studies, and our results replicated in larger epidemiological studies with information on breast cancer subtypes/stages. If our results are confirmed, this will have to be taken into account in the risk-benefit assessment of glucocorticoid prescriptions made by clinicians and/or in recommending mammographic control before initiating glucocorticoid treatment. It is important to mention that glucocorticoids are occasionally used among breast cancer patients to reduce chemotherapy-induced side effects such as nausea or lack of appetite. Thus, further studies should also consider the potential impact on breast cancer metastasis of such use.The main strengths of this study included its prospective design and the use of information from a drug reimbursement database to identify glucocorticoid exposure, which avoids differential recall bias between cases and non-cases. In addition, the exhaustive data on glucocorticoid reimbursements allowed us to consider precise information on exposure (including the number of reimbursements and timing of use). However, we lacked data regarding the compliance/adherence to the dispensed treatment, but defining users as women with at least two reimbursements during a 3-month period makes it likely that they took the drug. Since data on glucocorticoid reimbursements were combined with self-reported data on lifestyle, reproductive, and medical factors, we were able to take into account potential confounders. Surveillance bias could arise due to more frequent medical consultations or more frequent mammographic screening for women prescribed glucocorticoids and thus increased likelihood of being diagnosed with breast cancer . We addressed that bias by adjusting our models for a recent mammogram and the number of recent medical consultations. As sensitivity analyses, we also restricted our analyses to women with a recent mammogram or to women with at least one medical consultation during the preceding 6 months. These additional restrictions were not in favour of surveillance bias since the results remained unchanged. However, residual confounding by medical surveillance issues cannot be excluded. We were also able to stratify the analyses according to breast cancer subtype and to examine interactions of glucocorticoid use with breast cancer risk factors, comorbidities, and other drugs. However, the power to detect differences was limited because of the low number of cases in some categories and the number of advanced-stage cases was too small to separate stage 3 and stage 4 breast cancers. It is also possible that our results are due to chance, and they must be interpreted carefully. In addition, while some autoimmune diseases were associated with breast cancer risk , we wereIn this large cohort of postmenopausal women, glucocorticoid exposure was associated with a lower risk of invasive breast cancer that was restricted to ER+ and to stage 1 or 2 tumours and with a higher risk of in situ and stage 3/4 breast cancers.These results are novel and suggest that tumour molecular subtype and stage are important to consider when evaluating the associations between glucocorticoid use and breast cancer risk. In-depth experimental and epidemiological researches are needed to better understand the potential impact of glucocorticoids on breast cancer risk.Additional file 1: Use of systemic glucocorticoids and risk of breast cancer in a prospective cohort of postmenopausal women: Supplementary Tables S1-S3 and Supplementary Figures S1-S3. Table S1. Associations of glucocorticoid recurrent use with in situ breast cancer risk, according to characteristics of use. Table S2. Associations of glucocorticoid recurrent and occasional use with breast cancer risk, compared to never use. Table S3. Associations of glucocorticoid recurrent use with breast cancer risk, compared to never/occasional use, overall and by breast cancer subtype, among women with at least one medical consultation during the preceding 6 months. Figure S1. Associations of glucocorticoid recurrent use with invasive breast cancer risk, compared to never/occasional use, in strata of selected factors, comorbidities and recurrent use of other drugs. Figure S2. Associations of glucocorticoid recurrent use with breast cancer risk, compared to never/occasional use, overall and by breast cancer subtype, with exposure and other covariates coming from the reimbursement database lagged by 2 years. Figure S3. Associations of glucocorticoid recurrent use with breast cancer risk, compared to never/occasional use, overall and by breast cancer subtype, among women with a recent mammogram.


XRCC5) and 6 (XRCC6) are critical for DNA repair. Few studies have assessed their association with breast cancer risk, and related gene‐environment interactions remain poorly understood. This study aimed to determine the influence of XRCC5/6 polymorphisms on breast cancer risk, and their interactions with cigarette smoking, alcohol consumption, and sleep satisfaction.X‐ray repair cross‐complementary 5  and related 95% confidence intervals (95% CI) were assessed using unconditional logistic regression models. Gene‐environment interactions were analyzed using logistic regression with multiplicative interaction models.The study included 1039 patients with breast cancer and 1040 controls. Four single‐nucleotide polymorphisms of XRCC5 rs16855458 was associated with increased breast cancer risk in the co‐dominant (ptrend = 0.003) and dominant  genetic models after Bonferroni correction. The CG + GG genotype of XRCC6 rs2267437 was associated with an increased risk of estrogen receptor‐negative/progesterone receptor‐negative (ER−/PR−) breast cancer  after Bonferroni correction. Moreover, an antagonistic interaction between XRCC5 rs16855458 and alcohol consumption (pinteraction = 0.017), and a synergistic interaction between XRCC6 rs2267437 and sleep satisfaction were associated with breast cancer risk (pinteraction = 0.0497). However, these interactions became insignificant after Bonferroni correction.XRCC5 rs16855458 was associated with breast cancer risk, and XRCC6 rs2267437 was associated with the risk of ER−/PR− breast cancer. Breast cancer risk associated with XRCC5 and XRCC6 polymorphisms might vary according to alcohol consumption and sleep satisfaction, respectively, and merit further investigation. XRCC5 rs16855458 was associated with breast cancer risk, and XRCC6 rs2267437 was associated with the risk of ER−/PR− breast cancer. Breast cancer risk associated with XRCC5 and XRCC6 polymorphisms might vary according to alcohol consumption and sleep satisfaction, respectively, and merit further investigation. XRCC5/6 polymorphisms correlate with susceptibility to develop various malignant tumors.XRCC5 rs16855458 and rs9288516 have potential biological functions as they cause changes in the binding sites of transcription factors, and correlate with risk for hepatocellular carcinoma,XRCC6 rs2267437 and XRCC5 rs3835 were correlated with breast cancer risk in European women.XRCC5/6 polymorphisms and breast cancer susceptibility in Chinese women, and available results have been inconsistent. For example, a study conducted in Taiwan found that XRCC5 rs3835 was not linked to breast cancer susceptibility,XRCC1 and smoking in the etiology of breast cancer.XRCC5/6 polymorphisms and carcinogenesis‐related environmental factors, especially in Chinese mainland populations. Relevant investigations will contribute to breast cancer risk assessment and the development of intervention strategies.Cells under the influence of endogenous and exogenous factors in vivo sustain a large number of DNA‐damaging events daily.XRCC5/6 polymorphisms on breast cancer susceptibility among Chinese women and their potential interactions with smoking, alcohol consumption, and sleep satisfaction.The present study aimed to clarify the effects of 22.1The study participants have been previously described.2.2Demographic information and lifestyle habits of the participants were obtained using a structured questionnaire as described previously.2.3https://www.ncbi.nlm.nih.gov/snp/). rs3835, rs828907, rs16855458, and rs9288516 of XRCC5,XRCC6Fasting blood samples were collected into EDTA Vacutainers (Becton Dickinson and Co.) and stored at −80°C after sedimentation. DNA was extracted using the Wizard Genomic DNA Purification Kit . Single‐nucleotide polymorphisms (SNPs) were selected based on their reported association with cancer risk, and with a minor allelic frequency (MAF) >5% according to the 1000 Genomes project (2.4χ2 tests. A population representative was detected using Hardy–Weinberg equilibrium (HWE) in the control group. Associations between co‐dominant (wild‐type homozygous vs. heterozygous vs. mutant homozygous) and dominant (wild‐type homozygous vs. heterozygous and mutant homozygous) models of genetic variants and breast cancer were assessed using unconditional logistic regression. Odds ratios (OR) with 95% confidence interval (95% CI) were estimated after adjustment for age, body mass index (BMI), menstrual status, and family history of breast cancer. Trends were tested by considering the categorical genotypes as continuous variables in co‐dominant inheritance profiles. Gene‐environment interactions were assessed using logistic regression including multiplicative interaction models. Sleep satisfaction was defined as “dissatisfied” versus “satisfied,” and the dominant model with the homozygous common genotypes was adopted as the reference to facilitate the interaction analysis. The Bonferroni correction was employed for multiple testing and the significant p value was set at 0.0083 (0.05/6) for testing the six loci. All data were statistically analyzed using SPSS 23.0 (IBM Corp.).Differences in demographic and lifestyle data between the case and control groups were assessed by 33.1Table 3.2XRCC5/6 SNP genotypes and their adjusted effects on breast cancer risk. All SNPs followed the Hardy–Weinberg equilibrium (p > 0.05). Logistic regression analyses showed that XRCC5 rs16855458 was associated with increased breast cancer risk in the co‐dominant genetic model (ptrend = 0.003), and the dominant genetic model  after the Bonferroni correction. The other five SNPs were not significantly associated with breast cancer risk.Table 3.3XRCC5/6 and the risk of ER+/PR+, ER−/PR− breast cancer. The CG + GG genotype of XRCC6 rs2267437 was associated with an increased risk of ER−/PR− breast cancer  after Bonferroni correction. Increased ER+/PR+ breast cancer risk in the co‐dominant genetic model of XRCC5 rs16855458 after Bonferroni correction was observed (ptrend = 0.008). The AA genotype of XRCC5 rs16855458 was associated with an increased risk of both ER+/PR+ and ER−/PR− breast cancer , but not after Bonferroni correction. The other SNPs were not significantly associated with ER+/PR+ or ER−/PR− breast cancer risk.Among the 1039 cases, 918 88.4%) cases had explicit joint ER and PR statuses. Overall, 614 (59.1%) cases were ER+/PR+, 212 (20.4%) were ER−/PR−, 77 (7.4%) were ER+/PR−, and 15 (1.4%) cases were ER−/PR+. Due to the limited number of ER+/PR− and ER−/PR+ cases, they were excluded from further analysis. Table % cases h3.4XRCC5 and XRCC6) SNPs and smoking, alcohol consumption, and sleep satisfaction on breast cancer risk were analyzed. An antagonistic interaction was found between XRCC5 rs16855458 and alcohol consumption (pinteraction = 0.017). Compared with nondrinkers carrying the rs16855458 CC genotype, risk for breast cancer was increased in nondrinkers harboring the CA + AA genotype  and drinkers with the CC genotype , but not in drinkers with CA + AA genotype . The XRCC6 rs2267437 genotype synergistically interacted with sleep satisfaction (pinteraction = 0.0497). Compared with satisfied sleepers carrying the rs2267437 CC genotype, breast cancer risk increased in dissatisfied sleepers harboring the CG + GG genotype . However, these interactions became insignificant after the Bonferroni correction. The other SNPs evaluated did not show significant interactions with smoking, alcohol consumption, or sleep satisfaction , a tumor suppressor involved in homologous recombination pathways of DNA repair, was associated with the risk of hormone receptor‐negative breast cancer.XRCC4, another essential gene in the NHEJ pathway, were found to be associated with PR− breast cancer risk.XRCC5 rs16855458. However, the AA genotype of XRCC5 rs16855458 was associated with an increased risk of both ER+/PR+ and ER−/PR− breast cancer. Therefore, the relationship between XRCC5 rs16855458 and breast cancer risk by different hormone receptor states needs to be further explored. Furthermore, the CG + GG genotype of XRCC6 rs2267437 was found to be associated with an increased risk of ER−/PR− breast cancer even after Bonferroni correction, but not with ER+/PR+ breast cancer. This finding demonstrates that this relationship might be genuine rather than a false positive. Polymorphisms of XRCC6 rs2267437 were related to Ku70 protein expression, which was an essential protein in the NHEJ pathway of DNA double‐strand break.XRCC6 rs2267437 variation and ER+/PR+ breast cancer risk is still unclear and further investigation is required.Several studies showed that DNA repair defects are associated with hormone receptor‐negative breast cancers. For example, the breast cancer susceptibility gene 1  status data, this study only analyzed the correlation between XRCC5/6 polymorphisms and the risk of breast cancer by different hormone receptor states, but not molecular subtypes. Nonetheless, the findings of this study are a good complement to the existing knowledge. In the future, better‐designed studies with larger samples, systematically selected SNPs, and molecular subtypes’ information are needed to further clarify the effects of gene‐environment interactions on the occurrence of breast cancer.This study has several limitations. The hospital‐based, case‐control design might hold an inherent selection bias. Also, only a few SNPs were selected for analysis, in particular only four variants of 5XRCC5 rs16855458 is associated with breast cancer risk among Chinese women, and that XRCC6 rs2267437 is associated with the risk of ER−/PR− breast cancer. Moreover, potential interactions between XRCC5 rs16855458 and alcohol consumption, and between XRCC6 rs2267437 and sleep satisfaction were identified in relation to breast cancer risk. Despite that interactions became insignificant after conservative multiple‐comparison correction (Bonferroni correction), these results provide novel evidence for risk assessment and individual intervention for breast cancer in Chinese women.This study provides new evidence that All authors declare no conflict of interest.


The results of our study indicated that longitudinal weight gain increases cancer risk, whereas being highly physically active during adulthood could decrease cancer risk in men. Further, women were observed to be less prone to lifestyle-related risk factors than men. The results emphasize the role of weight maintenance and high-intensity physical activity throughout the lifespan, especially in men with Lynch syndrome.Lifestyle modifies cancer risk in the general public. How lifestyle modifies cancer risk in individuals carrying the inherited pathogenic gene variants in DNA mismatch repair genes (Lynch syndrome) remains understudied. We conducted a retrospective study with cancer register data to investigate associations between body weight, physical activity, and cancer risk among Finnish Lynch syndrome carriers  self-reported their adulthood body weight and PA at 10-year intervals. Overall cancer risk and colorectal cancer (CRC) risk was analyzed separately for men and women with respect to longitudinal and near-term changes in body weight and PA using extended Cox regression models. The longitudinal weight change was associated with an increased risk of all cancers  and CRC  in men. The near-term weight change was associated with a lower CRC risk in women . Furthermore, 77.6% of the participants retained their PA category over time. Men in the high-activity group had a reduced longitudinal cancer risk of 63%  compared to men in the low-activity group. PA in adulthood was not associated with cancer risk among women. These results emphasize the role of weight maintenance and high-intensity PA throughout the lifespan in cancer prevention, particularly in men with LS.Lynch syndrome (LS) increases cancer risk. There is considerable individual variation in LS cancer occurrence, which may be moderated by lifestyle factors, such as body weight and physical activity (PA). The potential associations of lifestyle and cancer risk in LS are understudied. We conducted a retrospective study with cancer register data to investigate associations between body weight, PA, and cancer risk among Finnish LS carriers. The participants ( Individpulation . HoweverThere is strong evidence derived from the general population that increased physical activity and reduced body adiposity are associated with decreased cancer risk ,10,11,12MLH1 are found in a major proportion of Finnish LS families [path_MMR men and women. We modeled the recalled levels of weight and physical activity as time-dependent variables in the relative risk model.In this study, we hypothesized that the interplay between genetic factors and lifestyle is associated with variable cancer risk in a distinct high-risk population. Two founder mutations in families ,19,20, wpath_MMR variants, cancer history, and lifestyle and socioeconomic characteristics are presented in Descriptive data on MLH1, 25.6% for MLH1 other than ex 16, 16.3% for MSH2, 10.3% for MSH6, and 0.4% for PMS2.Almost half of the men (47.0%) and women (49.0%) had had one or more cancers prior to lifestyle data collection. The most common cancer was CRC, with a higher prevalence in men (88.1%) compared to women (63.1%). The mean age at the first cancer incidence was 45.9 years in men and 48.6 years in women, and 45.6 years and 48.4 years at the age of the first CRC, respectively. MMR-gene variant frequencies for the entire study population were 47.3% for Healthy participants were more often working, whereas participants with cancer were more often retired. Women with cancer had a lower level of education and they were more commonly living alone compared to their healthy counterparts. Self-rated health status and fitness, as well as current physical activity level, was in general better among participants who had not had cancer. In addition, other lifestyle variables were moderately similar among participants with and without cancer.A change in longitudinal weight throughout the lifespan, calculated per one-kg weight increase, was associated with a 2% increased risk of cancers in men , whereas no such association was observed in women. Moreover, near-term weight change had no impact on the risk of all cancers in either sex.Longitudinal weight gain increased the CRC risk by 3% in men only . Among women, near-term weight gain within the 10-year interval before cancer diagnosis was associated with a 4% decreased risk of CRC . No associations between near-term weight gain and CRC risk were observed in men.The associations between physical activity and cancer risks are presented in Men in the high activity group were found to have a reduced longitudinal cancer risk of 63%  compared to men in the low activity group. There were no longitudinal associations between physical activity and cancer risk observed in women. In the near-term, participating in physical activity had no impact on cancer risk in either men or women.There was no association between physical activity and the risk of CRC.path_MMR carriers to elucidate the associations between changes in adult body weight, physical activity, and cancer risk. Our results suggest that associations between lifestyle and cancer risk differ between men and women and may vary during the course of life. We found that an overall increase in total body weight throughout the lifespan slightly elevated the risk of cancers, including CRC, in men. We also observed that men who continued to participate in more intensive physical activities over their adult life were at lower risk of all cancers.We conducted a retrospective study with longitudinal data collection and cancer register data among Finnish path_MMR carriers of the current study, participants increased their body weight during their adult years, and 61% of men and 55% of women were overweight or obese. Obesity and overweight may be more harmful for men, as we found that a trend of body weight accumulation during adult years was associated with an increased cancer risk in men but not in women. This is in agreement with other reports which have investigated weight accumulation in relation to the risk of LS cancer [In Western societies, body weight typically accumulates during the adult lifespan and growing levels of obesity predispose individuals to multiple health complications. Obesity is acknowledged as one of the most important risk factors of non-communicable diseases ,21,22. IS cancer ,24.Unfortunately, in most of the studies, including ours, a lifelong change in body composition could only be determined by changes in body weight. However, aging is not only associated with an increase in body weight that is related to fat accumulation but also to changes in body composition . BeginniIntriguingly, we also found that near-term weight increase had a CRC-protective effect in women. To speculate, it is possible that hormonal factors might have influenced the risk estimates. The primary source of endogenous estrogen in post-menopausal women has been suggested to be adipose tissue ,33. Therpath_MLH1 and path_MSH2 regular vigorous leisure time physical activity over a year prior to cancer diagnosis decreased CRC risk by 38% when compared to those who did not indulge in any such activity. Although we did not observe associations between physical activity and cancer risk in the near-term like Kamiza et al. (2015) [Our results suggest that performing more vigorous guided physical activity exhibit a cancer-preventive effect in men, as those who continued at higher levels of physical activity were at a 63% lower cancer risk when compared to less active men performing non-guided physical activity. To date, we are aware of only two previous studies that have assessed the impact of physical activity on LS cancer risk ,14. Both. (2015) , similarpath_MMR carriers (57% women). As in our study, they modeled longitudinal and near-term changes in physical activity separately. Unlike our study, Dashti et al. (2018) [Further, the study by Dashti et al. (2018)  comprise. (2018)  did not . (2018)  found hipath_MMR women, which may be due to differences in physical activity behavior between men and women, including the intensity and type of physical activity, as well as the timing of physical activity exposure in life. For example, throughout the follow-up, female participants mainly reported participating more frequently in guided leisure time physical activity than men, who reported performing competitive sports more often , which can be used to improve motivational support for healthy lifestyle maintenance or lifestyle changes.As described previously, the association of decreased cancer risk and healthy lifestyle in the general population has been observed in large population-based studies. Since the influence of healthy behaviour on decreased cancer risk was observed in our study with a limited number of participants, it could be possible that the effect of the modifiable behavioral risk factors—physical activity and body weight—is emphasised in path_MMR carriers. We also chose to model the change in cancer risk in the near-term setting (during the age-period of cancer or censoring) as it could be more accurate than longitudinal change, which could be influenced by poor recall. We also used time-dependent covariate values, which allow us to account for changes in predictor values over time.A major strength of the current study is that the study cohort comprised participants who had undergone comprehensive screenings of LS-predisposing mutations, with ascertainment utilizing Amsterdam and Bethesda clinical criteria and cascade testing, and those who had been offered colonoscopy surveillance at 2–3-year intervals. Our body weight and physical activity data collection encompassed the entire adult lifespan and was carefully analyzed by considering potential time-varying risks, sex differences, and potential confounders regarding cancer incidence. The observation period was initiated from the age of 20 years, instead of birth, to avoid the detection of changes in body weight which were merely due to natural growth and maturation. In doing so, we were also able to exclude the time-period when cancer incidence tends to be extremely low even among However, there are also several limitations. Weight and physical activity were assessed using self-recall instruments. Even though a recent study found that cross-sectional self-reported measurements of BMI were reasonably close to recent direct measurements , the recpath_MMR who were registered in the Finnish Lynch Syndrome Research Registry  and provided consent for research-related contacts. LSRFi is a nation-wide research registry (est. 1982) operating in Jyväskylä and Helsinki that organizes surveillance and cancer prevention for LS families. Currently, the registry consists of clinical and family history data of over 300 LS families and over 1700 pathogenic variant carriers under frequent surveillance. Individuals were identified in the registry before the genetic testing became available, based on clinical criteria (Amsterdam and Bethesda criteria) [path_MMR variants (classes 4 and 5 by InSiGHT criteria) [The study cohort included those carriers of riteria) ,47, and riteria)  were elipath_MMR carriers who had remained cancer free until data collection.Age, sex, and all cancer diagnoses with the cancer type and date of each diagnosis, mutation status, and family cancer history were confirmed from hospital medical records and national cancer registries upon recording in the LSRFi. With regard to analyses, participants in the cancer group were required to have at least one past cancer diagnosis in the medical registries although he/she could have been healthy at the time of data collection. The healthy group included only path_MMR carriers whose addresses were available in LSRFi in December 2016 and July 2020. Of them, 480 (response rate 46.2%) returned the questionnaire. However, 15 participants did not carry the path_MMR variant and therefore they did not fulfil the eligibility criteria and were excluded from the study. Then, the final study sample included 465 participants.Questionnaires for anthropometric, socioeconomic, and lifestyle data collection were sent to 1038 adult The education level was categorized according to the Finnish schooling system into four categories: basic education (including elementary or comprehensive school), upper secondary education , polytechnic degree, and university degree. Occupational status included the categories of worker or employee, retiree (including both disability and old age pensioners), and other . Marital status was categorized as living alone or married/cohabitating.Self-rated health and physical fitness were collected using standard five-scale questions. Due to the low number of responses in a few categories, answers were re-categorized into poor , average, and good  for statistical analysis.The level of alcohol consumption was identified by two questions assessing the frequency of alcohol use and the number of alcohol portions consumed per occasion. One portion refers to 10–14 g alcohol, which one may obtain, for example, from a single serving of 0.33 liters of beer or a similar light alcoholic beverage, from 12 cL of wine, or from 4 cL of spirits. Furthermore, the subjects’ smoking status was defined as never smoker if they reported being non-smokers and having never been a smoker, or smoked <100 cigarettes during their entire life; as former smoker if they reported currently being non-smokers but were regular smokers in the past; or as current smoker if they reported being current and regular smokers. Participants were also asked whether or not they used any anti-inflammatory drugs regularly during the surveyed time period (yes/no). Current leisure-time physical activity was assessed via the seven-option scale question ,50. The 2). Participants were categorized into four BMI groups—underweight (BMI < 18.5), normal weight (BMI 18.5–24.9), overweight (BMI 25–29.9), and obese (BMI ≥ 30)—according to the WHO classifications. Measuring tape was sent with the questionnaire to examine the waist circumference, along with written instructions. Waist circumference was measured without clothing in a standing position, 2 cm above the umbilicus.Anthropometrics were self-measured. Participants were asked to report their height and to measure their body weight before breakfast and without clothes. If weight could not be measured, participants were asked to fill in the last weight measurement known. BMI was calculated as weight in kilograms divided by the height squared in meters  longitudinal and (2) near-term settings. We used age as the time variable and determined cancer status at the end of follow-up. Thus, follow-up time extended from study entry at the age of 20 years to exit-age due to cancer diagnosis (event) or remaining free of cancer (censored). As we used time-dependent measurements of weight and physical activity, we utilized the counting process approach  for the path_MMR were particularly susceptible to lifestyle exposures that may be either protective or hazard increasing. We found that weight gain in adulthood increased the risk of cancer in men, whereas participating in more intense physical activity across the lifespan may have a cancer-preventive effect. According to our results, women were not as prone to lifestyle-related risk factors. The sex-based difference in the associations could be explained by differences in weight gain, which was smaller in women, and by sex-related factors modifying body composition over time. Taken together, our results emphasize the importance of weight maintenance and high-intensity physical activity throughout the lifespan in cancer prevention in men with path_MMR. The results of our study could be used in developing a cancer risk quantification methodology based on the consideration of various risk factors that are modifiable by the individuals themselves.To conclude, our results suggest that men with


Bisphenol A (BPA) is an endocrine disruptor that it is present in numerous products of daily use. The aim of this study was to assess the potential association of serum BPA concentrations and the risk of incident breast and prostate cancer in a sub-cohort of the Spanish European Prospective Investigation into Cancer and Nutrition (EPIC).We designed a case-cohort study within the EPIC-Spain cohort. Study population consisted on 4812 participants from 4 EPIC-Spain centers . BPA exposure was assessed by means of chemical analyses of serum samples collected at recruitment. Borgan II weighted Cox regression was used to estimate hazard ratios.p = 0.022), 37% increase for tertile 2 (p = 0.034) and 31% increase for tertile 3 (p = 0.072) was observed with respect to values bellow the limit of detection. No significant association was observed between BPA levels and breast cancer risk.Median follow-up time in our study was 16.9 years. BPA geometric mean serum values of cases and sub-cohort were 1.12 ng/ml vs 1.10 ng/ml respectively for breast cancer and 1.33 ng/ml vs 1.29 ng/ml respectively for prostate cancer. When categorizing BPA into tertiles, a 40% increase in risk of prostate cancer for tertile 1 (We found a similar percentage of detection of BPA among cases and sub-cohort from our population, and no association with breast cancer risk was observed. However, we found a higher risk of prostate cancer for the increase in serum BPA levels. Further investigation is needed to understand the influence of BPA in prostate cancer risk.The online version contains supplementary material available at 10.1186/s12940-021-00779-y. Cancer incidence is increasing worldwide with 18.1 million new cancer cases and 9.6 million cancer deaths in 2018 . Some riBPA is considered a non-persistent chemical, i.e., as it is degraded in the organism and there is evidence that BPA acts as an endocrine disruptor with estrogenic effects in the rodent mammary gland –27. MoreThe present study aims to assess the potential association of serum BPA concentrations and the risk of incident breast and prostate cancer in a sub-cohort of the Spanish European Prospective Investigation into Cancer and Nutrition (EPIC).We designed a case-cohort study within the EPIC-Spain cohort. EPIC is a prospective multi-centric cohort study planned to investigate the relationship between diet, lifestyles and cancer. It involves 23 research centers in 10 European countries, including five Spanish centers: Asturias, Granada, Murcia, Navarra and Gipuzkoa . Study pThe EPIC-Spain included 41,446 participants (62% women) aged 29–69 years enrolled between 1992 and 1996 in five provinces of Spain. Participants were recruited mostly among blood donors (about 60%) and the study population covered a broad range of socioeconomic and educational levels. Furthermore, they signed an informed consent and the study was approved by Ethics Committee of the Bellvitge Hospital (Barcelona). EPIC study populations and data collection were explained elsewhere [Study population in the present study consisted of 3690 sub-cohort participants, 547 breast cancer cases and 575 prostate cancer cases from four EPIC-Spain centers  with available data on BPA exposure. Participants selected for the sub-cohort included, by design, an overlap of 57 breast cancer cases and 111 prostate cancer cases  and age (quintiles), excluding persons with cancer at recruitment. In our sub-cohort, 79.6% of the participants provided a fasting blood sample at recruitment and 85.6% of them were extracted between 6 am and 11 am. However, we can generalize and assume most of our samples were taken during the mornings and in fasting conditions.Follow-up time began at EPIC recruitment and cancer cases were defined as participants with a diagnosis of breast or prostate cancer (i.e. ICD10 codes C50 and C61 respectively) during the study period. Incident cancer cases are identified by linkage with the Population Cancer Registries. Incidence date was determined by the date of cancer diagnosis and prevalent cases were excluded (participants with a cancer diagnosis prior to recruitment). Dates of end of follow-up for cases identification were: 31/12/2012 for Granada, 31/12/2013 for Murcia, 31/12/2011 for Navarra and 30/12/2013 for Gipuzkoa. For sub-cohort participants, the end of follow-up date was the lowest among date of diagnosis, date of death, date of loss of follow-up or the center-specific end-of-follow-up, whatever happened first.Vital status and date of death of participants in our sub-cohort was determined by linking EPIC data base with the National and regional Registries, IND , INE  and regional mortality register until 30/12/2013 (maximum date of identification of incident cases).Information on lifestyle and other health-related factors was obtained by an interviewer-administered questionnaire at baseline. All interviewers had received appropriate training for this task.2, 25- < 30 kg/m2, ≥30 kg/m2. Educational level was classified according to five categories: none, primary school, secondary school, technical or vocational training and university degree. Smoking status was summarised in three categories: never smoked, former smoker and current smoker. Alcohol consumption at recruitment in grams per day was categorized as no drinker (0 g/day), drinker (≤30 g/d in men and ≤ 20 g/d in women) and heavy drinker (> 30 g/d in men and > 20 g/d in women). Information on the domains of physical activity was compiled taking seasonal variation into account. A simple four-level physical activity index  was derived and validated by combining recreational and household activity [Measurements of height, weight, and hip and waist circumferences were taken at recruitment using standardised procedures . The queactivity . ReproduBlood samples were drawn from each participant at recruitment, which were subsequently centrifuged, and aliquots of plasma, serum, red blood cells and buffy coat in 0.5 mL straws were stored in liquid nitrogen (− 196 °C).BPA levels were quantified in serum samples using two of 0.5 mL straws, in an adaptation of a previously-validated methodology . In briehttps://www.medinadiscovery.com/, which has been assessed and certified for the standards of ISO 9001:2015, and routinely performs internal and external quality control analyses. In addition, the present analyses are encompassed in the activities of our research group within the The Human Biomonitoring Initiative .Chemical analyses were performed at Centro de Excelencia en Investigación de Medicamentos Innovadores en Andalucía MEDINA  were calculated for cases and sub-cohort and according to center, sex, age group, educational level, body mass index, physical activity and alcohol consumption and smoker status. Statistical differences were assessed through the Mann-Whitney or Kruskall-Wallis tests.Time to cancer event were modelled by means of Borgan II weighted Cox proportional hazard models , stratifIn our study, median follow-up time was 17 years. We had 547 cases of breast cancer and 575 prostate cancer cases and 3690 sub-cohort participants (1918 women and 1772 men). Table Among breast cancer patients, there were more smokers (18.1% vs 10.3%) than in the sub-cohort. Regarding physical activity, the sub-cohort had more participants in the “very high” classification than the cases: 58.7% vs 50.3% respectively. Other significant differences were observed in education level, BMI, menopausal status, number of pregnancies, breastfeeding and oral contractive use comparing breast cancer cases and sub-cohort participants (Table p = 0.754)  between smoker . However, there were no significant differences when observing other variables, neither those concerning women reproducibility , neither in logarithmic model  . Moreover, when categorizing BPA in tertiles we observed an increased risk of prostate cancer in model C: a 40% increase in risk of prostate cancer for tertile 1 , 37% increase for tertile 2  and 31% increase for tertile 3  was observed with respect to values bellow the limit of detection (p-trend = 0.069)  were no significant differences in blood BPA levels between breast cases and controls were found (p = 0.42) [In our study, 70% of the population had detectable BPA values and its concentrations were similar among cancer cases and sub-cohort participants which is comparable to an epidemiological study in Korea ( = 0.42) .n = 1000 participants) [n = 575) [n = 264) [Our results show no association for BPA serum concentrations and risk of incident breast cancer despite BPA is considered an ED with carcinogenic potential –33. Thescipants) . In the n = 575) . Howevern = 575) , 47–49. n = 264) . Mammogrn = 60) showed a much higher concentration of BPA in the urine of those patients in comparison with the control group [Regarding prostate cancer, we found a significant non-linear association with risk of prostate cancer when we categorized serum BPA in tertiles, as individuals with serum BPA levels in the 1st and 2nd tertile showed a 40 and 37% increased risk of prostate cancer respectively. In this regard, a case control study conducted in men with prostate cancer  (percentage above the limit of detection (LOD) and geometric mean (GM) with 95% confidence interval) by sociodemographic and life style characteristics in breast cancer cases and sub-cohort. Table S2. Serum BPA levels (ng/ml) (percentage above the limit of detection (LOD) and geometric mean (GM) with 95% confidence interval) by sociodemographic and life style characteristics in prostate cancer cases and sub-cohort.