CFLAR‐rs7558475 and current smoking . The interaction with the strongest statistical evidence was found between 5q14‐rs7707921 and alcohol consumption  in relation to ER– disease risk. The remaining two gene–environment interactions were also identified in relation to ER– breast cancer risk and were found between 3p21‐rs6796502 and age at menarche  and between 8q23‐rs13267382 and age at first full‐term pregnancy . While these results do not suggest any strong gene–environment interactions, our results may still be useful to inform experimental studies. These may in turn, shed light on the potential interactions observed.Investigating the most likely causal variants identified by fine‐mapping analyses may improve the power to detect gene–environment interactions. We assessed the interplay between 70 single nucleotide polymorphisms identified by genetic fine‐scale mapping of susceptibility loci and 11 epidemiological breast cancer risk factors in relation to breast cancer. Analyses were conducted on up to 58,573 subjects  from the Breast Cancer Association Consortium, in one of the largest studies of its kind. Analyses were carried out separately for estrogen receptor (ER) positive (ER+) and ER negative (ER–) disease. The Bayesian False Discovery Probability (BFDP) was computed to assess the noteworthiness of the results. Four potential gene–environment interactions were identified as noteworthy (BFDP < 0.80) when assuming a true prior interaction probability of 0.01. The strongest interaction result in relation to overall breast cancer risk was found between  What's new?Although it is widely acknowledged that genes and environment may interact to cooperatively modify breast cancer risk, no such interaction is known at the single nucleotide polymorphism (SNP) level. Here, the authors assessed the interplay of 70 SNPs with 11 known breast cancer risk factors in estrogen receptor‐positive and ‐negative disease. Weak interactions were found with individual SNPs and current smoking or alcohol consumption but no strong gene–environment interaction was identified. These data do not support the model of strong modification of genetic cancer risk by environmental factors. In 1968, MacMahon stated that “In no field are there more complex examples of the gene–environment relationship than in experimental cancer research.”loci that were previously identified in genome‐wide association studies (GWAS) were recently investigated further by genetic fine‐scale mapping in the framework of the Collaborative Oncological Gene‐Environment Study (COGS) using samples from studies participating in the Breast Cancer Association Consortium (BCAC). The SNPs identified in the fine‐mapping studies were further investigated in subsequent functional studies to identify potential causal associations. The consideration of causal variants may improve power to detect gene–environment interplay. However, if no interactions are detected, the weight of evidence against gene–environment interactions for the locus in question is strengthened. Additionally, new susceptibility alleles were identified from genotypes generated by imputation using the 1000 Genomes Project reference panel. Therefore, in this analyses, multiplicative gene–environment interaction in relation to breast cancer risk was assessed between 55 potentially causal as well as 15 newly identified SNP alleles, and the following 11 established epidemiological risk factors: age at menarche, oral contraceptive (OC) use, parity, age at first full‐term pregnancy (FTP), number of FTPs, breastfeeding, use of menopausal hormone therapy (MHT), body mass index (BMI), adult height, smoking and alcohol consumption. We also investigated interactions in relation to estrogen receptor (ER) specific breast cancer risk since different disease subtypes may arise through different pathways. The analyses reported in this article are based on the largest, currently available dataset with genetic data and extensive epidemiological information.Several breast cancer risk Data on subjects of European descent derived from 21 studies participating in the BCAC were pooled. A brief description of each study can be found in Supporting Information Table S1. There were 12 population‐based and 9 non‐population based studies, each contributing at least 200 cases and 200 controls with available SNP data and information on at least one epidemiological risk factor. Subjects were excluded from the gene–environment interaction analyses if they were male, of non‐European origin, a prevalent case or had missing data on age at diagnosis or age at interview, the epidemiological risk factor in question or any of the adjustment variables. Hence, the number of study subjects for each SNP‐risk factor pair varied with the availability of epidemiological data. Analyses were based on between 11,342 subjects  for effect modification by alcohol consumption and 58,573 subjects  for effect modification by number of FTPs. The set of study subjects that were included in at least one gene–environment interaction model comprised 30,000 cases and 34,501 controls. All studies were approved by the relevant ethics committees and informed consent was obtained from all participants.www.nature.com/icogs). With the aim of detecting causal variants, a number of loci known to confer breast cancer risk at the time of the design of the iCOGS array were further investigated using fine scale genetic mapping. To improve SNP density, imputation of the respective regions was performed using the March 2012 release of the 1000 Genomes as reference panel. The functional follow‐up work was not carried out centrally for all regions but divided between the different working groups of BCAC and thus the methods used varied somewhat.Genotyping was carried out using an Illumina iSelect array (iCOGS) in the framework of the COGS project  information at baseline was used, unless follow‐up information was available. Women who were 54 years or younger at reference were considered pre‐menopausal and women who were older than 54 years at reference were considered postmenopausal. Subjects who were smokers within 1 year before reference date or used MHT within 6 months before reference date were considered to be current smokers and current MHT users. For the case–control studies, BMI was calculated using usual adult weight or weight 1 year before reference , or weight around the age of 20 years . For the cohort studies , BMI was calculated using information from baseline or the latest available questionnaire before diagnosis, if available.Association analyses of SNP alleles and breast cancer risk were carried out using logistic regression models adjusted for age at reference, study and ethnicity. In all models used in this study, genotyped SNPs were treated as ordinal variables  and imputed SNPs as continuous variables.2), adult height (per 5 cm), current use of MHT in the form of estrogen and progesterone or estrogen only (yes or no), lifetime average alcohol intake (per 10 g/day), current smoking (yes or no) and pack‐years of smoking (per 10 pack‐years).The main effects of the epidemiological risk factors were also investigated using logistic regression models adjusted for reference age, study and self‐assessed ethnicity. Heterogeneity across studies was explored by means of Cochrane's Q‐test. The epidemiological variables used in this analyses were categorized as follows: age at menarche (per 2 years), ever use of OC (yes or no), ever parous (yes or no), number of FTPs for parous women , ever breastfed (yes or no), age at first FTP (per 5 years), adult BMI for pre‐ and postmenopausal women, respectively  breast cancer risk, using cases and controls. Furthermore, potentially differential gene–environment interaction according to ER status was assessed in case‐only analyses comparing ER– cases to ER+ cases. The ER‐specific models and the case‐only analyses were adjusted similarly as the interaction models for overall breast cancer risk. To elucidate the results of the interaction analyses, risk association between SNPs and breast cancer was investigated by stratifying on the epidemiological variables.Multiplicative gene–environment interaction was assessed by comparing logistic regression models with and without SNP‐risk factor interaction terms by means of the likelihood ratio test. All models on which this study is based were adjusted for study, reference age and ethnicity, so as to capture genetic population sub‐structure. An interaction term between the epidemiological variable and an indicator for population based study design was included to protect against bias due to the differing selection of study participants in non‐population based MHT was sub‐divided into estrogen only and combined (estrogen plus progestogen) therapy and investigated in relation to breast cancer risk using only post‐menopausal women. All statistical models involving MHT use were further adjusted for former MHT use and current use of the MHT preparation (estrogen only or combined) not included in the interaction term. Additionally, interactions of SNPs and BMI for postmenopausal women were assessed in never‐ and former users of MHT only. All risk analyses were carried out using SAS 9.2.2I. Heterogeneity was investigated for SNP‐risk factor pairs with an interaction p values below the Bonferroni corrected threshold of statistical significance for genetic main effects, computed by dividing the standard threshold of 0.05 by the number of SNPs (0.05/70 > 7 × 10−4). Interaction ORs were tested for heterogeneity across studies on basis of interaction p values in models of overall or ER specific breast cancer risk, although the latter on the condition that a heterogeneity p < 0.05 of ER+ versus ER– disease had been observed. Heterogeneity tests were conducted using the R package “rmeta” (version 2.2).Between‐study heterogeneity of the interaction odds ratio (OR) estimates was investigated using Cochrane's Q‐test and quantified by the ratio of true heterogeneity to the total observed variation, denoted p values below the Bonferroni‐corrected threshold given above (p < 7 × 10−4). The BFDP was computed for two different prior probabilities of this , under the assumption that the probability of observing a true interaction OR inside the interval 0.66–1.5 was 95%. As a complementary measure to the BFDP, we also computed the ABF, which approximates the ratio of the probability of the data given that the null hypothesis is true, to the probability of the data given that the alternative hypothesis is true. The null hypothesis in this case is that the coefficient of the interaction term in the logistic regression model is equal to zero.The Bayesian False Discovery Probability (BFDP) was computed to control the number of false‐positive findings and assess the noteworthiness of the results.The studies included in the gene–environment interaction analyses are listed in Table The associations between SNP alleles and breast cancer risk in the subset of BCAC studies with risk factor data available were consistent with earlier reports and can be found in Supporting Information Table S3.vs. ever having breastfed) were all factors that showed an increased risk of breast cancer. A reduction in risk was observed for older age at menarche, ever being parous, number of FTPs and high BMI for pre‐menopausal women. For current smoking and pack‐years of smoking, no significant association with breast cancer risk was detected.Main effects of the epidemiological variables on breast cancer risk across studies are presented in Supporting Information Figure 1. These analyses were carried out using only population‐based studies and the results were consistent with what has been reported earlier in the literature.p < 7 × 10−4 in relation to overall, ER+ or ER– breast cancer risk, as presented in Table The complete results from the interaction analyses, showing the risk association between SNPs and breast cancer across categories of the epidemiological variables, are presented in Supporting Information Table S4. We identified four SNP‐risk factor pairs with at least one interaction CFLAR‐rs7558475 and current smoking . This result was considered noteworthy (BFDP = 0.40) assuming a prior probability of true interaction of 0.01 and the approximated Bayes factor (ABF) = 0.007 indicated that the data were almost 140 times more likely given the alternative hypothesis than given the null. Breast cancer risk was reduced for current smokers carrying the minor allele (G)  compared to that of non‐smoker carriers  where no risk association was observed. When comparing ER– cases to ER+ cases, the results did not indicate any effect heterogeneity (phet = 0.48). There was no strong evidence of interaction, neither with respect to ER+ risk (pint = 0.0014) nor with respect to ER– risk (pint = 0.75).First evidence of an interaction in relation to overall disease risk was noted between the variant ATG10) gene, and alcohol consumption  in relation to ER– breast cancer. This result had the lowest BFDP = 0.33, and conditioning on the alternative, the data were about 200 times more likely as compared to conditioning on the null (ABF = 0.005). Carriers of the minor allele (T) of rs7707921 had an increased risk of ER– breast cancer if they consumed >20 g of alcohol per day , but not if they consumed <20 g of alcohol per day . A strong effect heterogeneity was detected when comparing ER– cases to ER+ cases (phet = 6.7 × 10−6). Together with the absence of interaction in relation to ER+ disease (pint = 0.79) and overall breast cancer risk (pint = 0.70), this indicated that the interaction might be specific to ER– disease.The most promising result of the gene–environment interaction analyses in terms of noteworthiness was considered noteworthy at the 0.01 probability level and was noted between the variant 5q14‐rs7707921 located in an intron of the autophagy related 10  which had BFDP = 0.49, and of which the ABF (ABF = 0.010) implied that the data were 100 times more likely under the alternative hypothesis than under the null. Carriers of the minor allele (A) of 3p21‐rs6796502 who experienced their menarche no later than the age of 11 years had a reduced risk of ER– breast cancer , whereas there was no association with disease risk of the genetic variant for women who had their menarche between the age of 12 and 13 years , or after the age of 14 years . While the observed interaction was in relation to ER– disease risk, no effect heterogeneity was detected when comparing ER– and ER+ cases (phet = 0.53) nor was there any indication of any interaction in relation to overall breast cancer risk (pint = 0.94). Hence, it is not possible to conclude that the observed interaction is specific for ER– disease.In addition, indications of two further interactions were noted in relation to ER– disease risk. One of these was between 3p21‐rs6796502 and age at menarche  in relation to ER– disease risk. This interaction had BFDP = 0.61 assuming a true, prior interaction probability of 0.01, and ABF = 0.016, indicating that the data are about 60 times more likely conditioning on the alternative than on the null. There was no interaction observed in relation to disease risk, when considering ER+ breast cancer (pint = 0.98), or overall breast disease risk (pint = 0.47), and no effect heterogeneity was found when comparing the risk of ER– and ER+ breast cancer (phet = 0.99). Our findings indicated a modest reduction in ER– breast cancer risk for minor allele (A) carriers who were aged 30 or above at their first FTP , whereas for women who had their first child at younger ages the allele had no effect on risk.Finally, an indication of a gene–environment interaction was found between 8q23‐rs13267382 and age at first FTP  assuming a true prior interaction probability of 0.01. One of the results was detected in relation to overall breast cancer risk, while the three remaining results appeared to be specific for ER– disease.From the analyses presented in this work, four SNP‐risk factor pairs were identified, for which CASP8 and FADD like apoptosis regulator (CFLAR) gene and current smoking (pint = 1.8 × 10−4). The protein product of CFLAR regulates apoptosis, thus it is possible that CFLAR genetic variants affect response to DNA damage caused by tobacco associated carcinogens and therefore modify breast cancer risk conferred by smoking. However, although rs7558475 is located in a CFLAR enhancer region, reports from recent functional studies and expression quantitative trait locus (eQTL) analyses did not provide any convincing evidence regarding functionality.The strongest gene–environment interaction in relation to overall breast cancer risk was noted between rs7558475 located in the ATG10) gene, and alcohol consumption (pint =1.9 × 10−5). Autophagy, which is considered a survival mechanism of the cell, may act as a tumor suppressor but also influence cell survival by promoting tumor growth, and has been suggested as a target in cancer therapy.ATG10‐rs7707921 does not coincide with any strong regulatory elements. The eQTL analyses carried out within the framework of BCAC showed a strong association between the T allele of rs7707921 and expression of the ribosomal protein S23 gene (RPS23) in breast tissue as well as a moderate association between the allele and expression of the ATPase, H+ transporting, lysosomal accessory protein 1‐like (ATP6AP1L) gene.RPS23 gene encodes a ribosomal protein and the ATP6AP1L is also protein coding but the genes have not yet been implicated in ER– breast cancer risk and their expression levels have not been assessed in relation to alcohol consumption or oxidative stress. Further work is thus needed to understand how the protein products of these genes could interact with alcohol consumption to modify the risk association of rs7707921 with ER– breast cancer.The strongest statistical evidence of interaction was found in relation to ER– breast cancer risk and was noted between an intron variant 5q14‐rs7707921 in the autophagy related 10 (pint = 1.8 × 10−4) in relation to ER– breast cancer. Our results suggest that the reduced risk of ER– breast tumors for carriers of the A‐allele are modified for women with late age at menarche ≥ 14 years. However, according to a recent functional study, the SNP is not located in the vicinity of any genes or enhancer regions in mammary cell lines, nor are there any significant results available from eQTL analyses.Furthermore, we found an indication of a possible interaction between 3p21‐rs6796502 and age at menarche (LINC00536) and age at first FTP (pint =2.6 × 10−4) suggests that the variant is associated with a reduced risk of ER– breast cancer with older age at first FTP, whereby the association was statistically significant for women who were at least 30 years of age at their first FTP. Overall, this variant was not reported to be associated with ER– disease risk,The interaction observed between the intron variant 8q23‐rs13267382 of the long intergenic non protein coding RNA 536 gene , the power was diminished due to the reduced sample size.This work is subject to a number of limitations. First, despite central harmonization of the data, substantial heterogeneity was observed in the risk estimates of the epidemiological risk factors across studies, which brought about the inclusion of a product term of study design and epidemiological variable in the interaction models, and the quantification of epidemiological main effects based on the population based studies. Second, the study population consisted predominantly of case‐control studies (only three cohort studies), which are known to be prone to selection bias and recall bias, as well as associated misclassification of risk factors. However, gene–environment interaction estimates were similar in the overall study population compared to the subset of population based studies (data not shown). Misclassification of epidemiological risk factors is known to reduce the power to detect interactions, rather than increasing the probability of false‐positive findings.However, this study also has several strengths. To begin with, the interaction analyses are based on the largest dataset presently available. The four indicated interactions were based on 11,337 subjects  in analyses with respect to alcohol consumption, and 19,427 subjects  for current smoking, as well as 43,513 subjects  in the analyses of age at menarche and 37,819 subjects  in the analyses of age at first FTP.Taken together, the results presented in this report are not in line with the existence of strong modification of the allelic effects on breast cancer risk by the epidemiological risk factors investigated. However, the results presented in this report contribute to the global body of knowledge on gene–environment interactions by generating hypotheses, thereby providing guidance for future functional studies and large scale replication studies.Supporting Information Figure 1.Click here for additional data file.Supporting Information Table 1.Click here for additional data file.Supporting Information Table 2.Click here for additional data file.Supporting Information Table 3.Click here for additional data file.Supporting Information Table 4.Click here for additional data file.


Breast cancer molecular prognostic tools that predict recurrence risk have mainly been established on endocrine-treated patients and thus are not optimal for the evaluation of benefit from endocrine therapy. The Stockholm tamoxifen (STO-3) trial which randomized postmenopausal node-negative patients to 2-year tamoxifen , versus no adjuvant treatment, provides a unique opportunity to evaluate long-term 20-year benefit of endocrine therapy within prognostic risk classes of the 70-gene prognosis signature that was developed on adjuvantly untreated patients.We assessed by Kaplan–Meier analysis 20-year breast cancer-specific survival (BCSS) and 10-year distant metastasis-free survival (DMFS) for 538 estrogen receptor (ER)-positive, STO-3 trial patients with retrospectively ascertained 70-gene prognosis classification. Multivariable analysis of long-term (20 years) BCSS by STO-3 trial arm in the 70-gene high-risk and low-risk subgroups was performed using Cox proportional hazard modeling adjusting for classical patient and tumor characteristics.p < 0.0001). Notably, there is equivalent tamoxifen benefit in both high (HR 0.42 (0.21–0.86), p = 0.018) and low (HR 0.46 (0.25–0.85), p = 0.013) 70-gene risk categories even after adjusting for clinico-pathological factors for BCSS. Limited tamoxifen exposure as given in the STO-3 trial provides persistent benefit for 10–15 years after diagnosis in a time-varying analysis. 10-year DMFS was 93 and 85% for low- and high-risk tamoxifen-treated, versus 83 and 70% for low- and high-risk untreated patients, respectively (log-rank p < 0.0001).Tamoxifen-treated, 70-gene low- and high-risk patients had 20-year BCSS of 90 and 83%, as compared to 80 and 65% for untreated patients, respectively  contains supplementary material, which is available to authorized users. Breast cancer is a diverse disease both in the sense of the metastatic potential of the primary tumor as well as time for metastasis to occur. The biological factors influencing the long-term risk of fatal breast cancer are unknown. It is, however, known that patients with newly diagnosed hormone receptor (HR)-positive breast cancer (ER− and/or progesterone (PR)-positive disease) have a continuous long-term risk for fatal breast cancer progression relative to stage-matched patients with newly diagnosed HR-negative cancer . EndocriGene expression signatures have helped us understand the inter-tumor heterogeneity between breast cancer tumors , 7, sepaGiven the pressing need to understand more about long-term breast cancer survival and endocrine therapy benefit, we evaluated long-term endocrine therapy benefit in women with 70-gene low- and high-risk prognosis signatures using a large Swedish clinical trial (STO-3) having complete long-term (20 years) follow-up of patients randomized to receive adjuvant tamoxifen versus not.The Stockholm Tamoxifen (STO-3) trial enrolled postmenopausal patients with lymph node-negative breast cancers with tumors less than or equal to 30 mm in diameter, randomized to 2 years of adjuvant tamoxifen (40 mg daily) versus no adjuvant treatment. Patients in the tamoxifen arm, who were relapse free after 2 years of tamoxifen and who re-consented, were further randomized to 3 additional years of tamoxifen or none. From the original randomized trial cohort, 808 patients had formalin-fixed paraffin-embedded (FFPE) tissue blocks of primary breast cancer tumor available for molecular analyses, and of these, 81 patients were excluded because there was insufficient invasive tumor present for analysis. The remaining 727-patient subset with FFPE material available is well balanced to the original STO-3 cohort with regard to tumor characteristics, such as tumor size, ER status, and treatment arm assignment . All patIn Sweden, all residents have a unique national registration number, which enables automatic linkage of various records of personal information from Regional and National registers of high validity and essentially complete coverage. Death due to breast cancer was assessed from the Swedish National Cause-of-Death Register with a reported accuracy of more than 96% from January 1, 1961 and onwards , 15. TheThe STO-3 trial was approved by the ethical committee at Karolinska Institutet, and participants provided oral consent.Gene expression data were independently generated using custom-designed arrays, Agilent Technologies , containing approximately 32.1K probes, representing approximately 21.5K unique genes from FFPE breast cancer tumor tissue. Approximately 90% (or 652 of 727 breast cancer tumors) passed the RNA quality check  and were used in the analysis. The 70-gene (MammaPrint) signature was performed according to standard protocols as previously described, including the use of 465 normalization genes and over 250 probes for hybridization and printing quality control. Patient tumor samples were classified into high or low risk by the 0.00 threshold in the MammaPrint index . The subgroup of ultralow tumors is defined by MammaPrint index > +0.355 –19.538 of the 652 tumors available for 70-gene evaluation were ER positive. Immunohistochemistry (IHC) was retrospectively done for ER, progesterone receptor [PR], human epidermal growth factor receptor 2 [HER2], and Ki-67 using DAKO Link48 Autostainer at the University of California Davis Medical Center (UCDMC). The antibodies used were ER , PR , HER2 , and Ki67 , with EnVision + detection, following standard recommended procedures and with per-run positive controls assessed by quantitative image analysis to ensure consistent run-to-run staining intensity .Tumor grade according to the Nottingham system was retrospectively assessed by one pathologist .The outcome of interest was death due to breast cancer, and analyses of long-term breast cancer-specific survival (20 year) by the 70-gene risk classification (high and low risk) were performed in patients with ER-positive tumors. Patient follow-up started at the date of primary breast cancer diagnosis and ended at the date of death, contralateral breast cancer diagnosis, emigration from Sweden , or end of study follow-up .For comparison with previous studies, we also performed 10-year analysis of distant metastasis-free survival. However, information on metastasis is less complete as compared to information on death. In our study, approximately 2%, i.e., 14 patients out of 727 patients, died from breast cancer but have missing information on metastasis. In patients with ER-positive disease and available gene expression information (538 patients) as included in this study, 11 patients who died from breast cancer had missing information on metastasis. For these 11 patients, date of death was used instead of the date of metastasis.Kaplan–Meier analyses were performed by STO-3 trial arm and 70-gene risk classification. The significance was assessed using the log-rank test.Multivariable analysis by the 70-gene risk classification was performed using Cox proportional hazard modeling adjusting for classical patient and tumor characteristics . Multivariable analysis for the ultralow 70-gene risk group by trial arm was not performed due to low sample size.Flexible parametric survival models were used to estimate hazard ratios over time since diagnosis. Breast cancer-specific death rates were modeled through flexible parametric survival models using a restricted cubic spline function for the baseline mortality rate , 21. TimThe proportional hazard assumption for the main exposure variable (70-gene risk classification) was assessed by including a time-dependent covariate in the model. No significant deviation was noted. Data preparation and analysis were done using SAS version 9.4, Stata version 14.2, and R version 3.4.0.Patients in the STO trial with ER-positive breast cancer disease and available 70-gene expression signature data, 538 patients in total, were included in our analysis. In Table p < 0.0001). For the 70-gene low-risk group, the 20-year breast cancer-specific survival with and without tamoxifen treatment was 90% (95% CI 84–94%) and 80.0% (95% CI 72–86%), respectively. For the 70-gene high-risk group, the 20-year breast cancer-specific survival with and without tamoxifen treatment was 83% (95% CI 72–90%) and 65% (95% CI 53–75%), respectively.Kaplan–Meier survival graphs for patients with and without tamoxifen are shown per trial arm and by the standard 70-gene high- and low-risk groups in Fig. 1S. A statistically significant difference in long-term (20 year) breast cancer-specific survival by STO-3 trial arm and 70-gene classification was observed . The benefit of tamoxifen was further investigated in the earlier defined ultralow-risk group of breast cancer patients with indolent disease and extremely good outcome [p = 0.39) in the ultralow-risk group for patients receiving tamoxifen therapy or not.The benefit of tamoxifen within each 70-gene risk group is shown in Fig.  outcome . No statp < 0.0001). For the 70-gene low-risk group, the 10-year distant metastasis-free survival with and without tamoxifen treatment was 93% (95% CI 88–96%) and 83% (95% CI 76–88%), respectively. For the 70-gene high-risk group, the 10-year distant metastasis-free survival with and without tamoxifen treatment was 85% (95% CI 75–91%) and 70% (95% CI 58–79%), respectively.In order to compare results to previous studies that evaluated endocrine treatment benefit in prognostic high- and low-risk subgroups up to 10 year after diagnosis, we also performed a 10-year analysis of distant metastasis-free survival by the 70-gene risk classification using Kaplan–Meier analysis . A statistically significant difference in 10-year distant metastasis-free survival was seen  breast cancer-specific survival by STO-3 trial arm in the 70-gene high-risk and the low-risk subgroups was performed using Cox proportional hazard modeling adjusting for classical patient and tumor characteristics . Interestingly, both patients classified as 70-gene high, as well as low risk notably benefited from tamoxifen treatment  impact of tamoxifen therapy versus not as the sole adjuvant therapy in women whose tumors were retroactively molecularly classified as either 70-gene high or low risk. The results demonstrate that there is a significant and comparable risk reduction benefit from tamoxifen in both groups, and that the survival benefit after 2 years of tamoxifen use (for one-third of patients in the tamoxifen arm after 5 years) continues for well over 10 years. These findings also confirm what has previously been shown, that the 70-gene classification is prognostic, and that women with low risk versus high risk have higher survival independent of treatment. In this study, adjuvant tamoxifen appeared to reduce risk of death by 50%, regardless of 70-gene high- or low-risk biology.It has been shown that breast cancer stage and grade do not appreciably affect the proportional risk reduction benefit from 5 years of adjuvant tamoxifen therapy ; this stMost prognostic tools have been shown to determine risk of recurrence only out to 10 years in a uniformly endocrine-treated population, making these tools less suitable to evaluate their ability to identify which patients might and to what extent benefit from endocrine therapy . This isInterestingly, this paper also likely confirms the additive benefit of chemotherapy, as risk for recurrence is more substantial in the first 5 years in the high-risk group as compared to the low-risk group. Even if the relative benefit of tamoxifen risk reduction is the same, the absolute risk of recurrence is higher in the high-risk group, where chemotherapy is known to exert its optimal effect . In the In order to advance the science of personalized medicine, diagnostics need to help us determine who will benefit and when. Women with ultralow-risk profiles have almost no risk and therefore benefit little if at all even from endocrine treatment. Women with biologically high-risk disease benefit from tamoxifen, but have high early residual risk supporting a decision to intercede with chemotherapy. Women with low- but not ultralow-risk disease, as well as those with high-risk disease, would be very well served if we had a robust marker of sensitivity to endocrine therapy and chemotherapy, to understand their long-term risk to die from breast cancer. That way, we could find ways to intercede for this group of women, and, as well, to determine for whom endocrine therapy is not sufficient. In order to more rapidly advance the field, we have to be able to identify those women at diagnosis and specifically focus more targeted interventions. Establishing the long-term benefit of endocrine therapy in prognostic subclasses as described here contributes to our ability to guide the use of adjuvant therapy in breast cancer.Supplementary material 1 (DOCX 108 kb)Below is the link to the electronic supplementary material.


Breast cancer survival is unacceptably low in many low-resource settings, including rural South Africa, where access to screening and treatment services is limited. To describe the context for implementing an early detection program, we assessed knowledge and attitudes toward breast cancer risk, early detection, and treatment.We conducted a cross-sectional survey among 243 women presenting to Hlokomela Clinic in Hoedspruit, South Africa, during April and May 2016. We used quantitative and qualitative analyses to determine levels of knowledge of risk factors, symptoms, and treatment of breast cancer, as well as experience with and attitudes toward detection and treatment methods.Thirty-one percent of women correctly identified at least six of 12 risk factors for breast cancer, and 53.1% identified breast lumps as an important symptom. Although > 97% of women stated that self–breast examination and early detection were highly important and that they would seek care for changes in their breasts, only 33.3% of women reported performing self–breast examination, and only 24.3% reported receiving a clinical breast examination. Age and education were not associated with knowledge, and level of knowledge did not predict care-seeking behaviors or attitudes.Although women demonstrated moderate levels of knowledge of breast cancer symptoms and risk factors and the importance of early detection, few women reported seeking services. These data demonstrate sufficient levels of knowledge and positive attitudes toward care seeking and suggest both a need and readiness for increased access to cost-effective services to facilitate early diagnosis and improved outcomes. Both incidence and mortality rates in LMICs have dramatically increased over the past few decades, and a majority of deaths resulting from breast cancer now occur in developing nations.2 In South Africa, breast cancer incidence has doubled in the past 20 years and now accounts for > 20% of all female cancers.4Breast cancer is the most commonly diagnosed cancer in women in both high- and low-resource settings.v 98.6%), and the age-standardized mortality rate for breast cancer in South Africa is 16.5 in 100,000, as compared with 14.1 in 100,000 in the United States.7Despite rapidly increasing incidence rates, early detection and treatment remain extremely limited in LMICs, and these countries face significantly higher mortality rates than high-income countries. The average 5-year survival in Africa is half of that in the United States . Participants were sampled consecutively; each woman age ≥ 18 years was approached for inclusion.Data collectors were members of the local community with experience in lay counseling and basic data collection, trained in both research methods and human research ethics and fluent in English, Xitsonga, and Northern Sotho (Sepedi). Date collectors collected written informed consent using a participant information sheet in the participant’s language of choice . Data collectors then verbally administered a five-page questionnaire in a quiet, private room. The five-part survey took approximately 10 minutes to administer and contained questions on demographic information, including age and level of education; personal and family histories of breast cancer; experience with breast cancer screening; knowledge of breast cancer risk and protective factors and symptoms; and knowledge of and attitudes toward breast cancer treatment. To assess knowledge of breast cancer risk and protective factors, participants were asked to state whether each of 12 factors increased the risk of breast cancer, decreased the risk of breast cancer, or had no impact . We assiDescriptive statistics are reported to describe the demographics of the study population. Percentages are reported for categorical variables including personal and family histories of breast cancer, screening and treatment histories, and knowledge of risk factors. We determined mean knowledge scores and categorized participants as having high or low knowledge on the basis of whether they were able to correctly identify ≥ 50% of the 12 risk or protective factors.Knowledge of symptoms and treatment and attitudes toward care seeking were assessed using qualitative methods. Qualitative analysis was conducted by coding and categorizing responses to open-ended questions. There were a total of three open-ended questions: “list any symptoms of breast cancer that you know of”; “if you think there is treatment available for breast cancer in South Africa, please explain what you understand that treatment to be”; and “please state any reason you can think of why you might not contact a doctor if you noticed changes in your breasts.” We categorized similar responses and reported totals for each symptom, treatment method, and reason for deferral that we identified.2 tests were used to determine associations between level of knowledge and self-reported action. All data analyses were conducted using STATA software , and tests of significance were two tailed at α = 0.05.One-way analysis of variance was used to compare mean knowledge scores between demographic groups. χWe interviewed a total of 243 black African women between the ages of 18 and 68 years, with a mean age of 38 years . A majority (59.0%) of respondents had an education level lower than grade 11, and 4% had a university or postgraduate degree . The selRespondents demonstrated moderate levels of knowledge with regard to breast cancer risk factors, symptoms, and treatment. Nearly one third of women (31.3%) were able to correctly classify six of 12 risk factors . Thirty-In comparison with symptoms and risk factors, respondents had lower knowledge of breast cancer treatment, with 38.7% stating that they were unaware of the methods of treatment, and 2.9% stating that breast cancer is not treatable. Less than one third (31.3%) of respondents stated that medicine or pills are used for treatment, although only 1.7% specified chemotherapy. Mastectomy (25.9%) and lumpectomy (9.1%) were the second and third most commonly identified treatment methods .Women in our population demonstrated strong positive attitudes toward care seeking, with > 97% of respondents stating that it was important to check their breasts regularly for breast cancer, that it was important to go to a physician or other care provider if they felt something abnormal in their breasts, and that they would be likely to go to a physician or other care provider should they notice changes in their breasts. A majority of women (67.1%) stated that they believed they would survive breast cancer if detection occurred early, whereas only 6.2% of women thought that they would be very likely to survive breast cancer if it was detected late. Women significantly overestimated their personal risk of breast cancer, with 47.7% responding that they were either very likely or somewhat likely to develop breast cancer in their lifetimes. The most commonly reported potential reason for not seeking care was fear of death or of having the breast cut off, although this was expressed by only 3.3% of respondents. Other potential reasons for not seeking care included lack of money, perceived poor quality of care at health facilities, long queues , and a belief that breast pain was not an important symptom. These reasons were only reported by a small minority of respondents .P = .43) or age (P = .10). Those with greater than grade 11 education did have a higher mean score for risk or protective factor identification (43.5% v 39.7% for those with ≤ grade 11 education), but this did not meet statistical significance (P = .20).In contrast to high levels of care-seeking intention, only 24.8% of women reported having ever received a clinical breast examination (CBE), and only 33.3% of women reported having ever conducted a self–breast examination SBE; . Increas8 Despite reported positive attitudes toward care seeking and higher levels of knowledge in comparison with those in other LMIC settings, our study identified an intention–action gap with respect to breast cancer care seeking in this population, indicating the need for increased access to early detection and treatment services.This study is the first to our knowledge to report data on knowledge, attitudes, and practices related to breast cancer in rural South Africa. Our findings generally echo those of similar studies conducted in urban and periurban settings in South Africa as well as other LMIC settings. Our results support findings from the Western Cape province that South African women perceive breast cancer to be both common and curable if detected early.9 Conversely, women in our study population demonstrated lower levels of knowledge of breast cancer symptoms than those surveyed in the Western Cape, as well as lower levels of SBE (33.3% v 65.0%) and CBE (24.8% v 62.0%).8 Although reported family and personal histories in our population were lower than those in previous South African studies, the relatively high proportion of women reporting knowledge of a family or community member with breast cancer (33.8%) suggests breast cancer prevalence rates similar to those seen in high-income countries.3Knowledge of breast cancer risk factors was significantly higher than knowledge levels reported in similar studies across Africa.10 Although women in both rural and urban or periurban settings in South Africa demonstrate an intention–action gap with regard to breast cancer care seeking, women in our study did not report the same justifications for delay in care seeking as their urban counterparts. Krombein and De Villiers8 found that the most commonly cited reasons for choosing not to seek care among women in the Western Cape included a fear of being diagnosed with breast cancer, insufficient knowledge, pain of the procedure, and cost. Although a small proportion of women in our population identified these same barriers, a vast majority of women did not report any reason for delay in seeking care. The comparatively high levels of knowledge and positive attitudes toward care seeking identified in our study suggest that structural barriers, including poor access to care, are responsible for limited breast care use in this population.In previous reports on LMICs, delays in the decision to seek care have been reported to be the result of cultural influences on the decision to act, including fatalism, fear of stigma, and preference for traditional healers.11 However, it is clear that, for a screening program to improve outcomes, an accessible treatment program must also be in place. There are several ways this could be achieved, again ranging from promising nonsurgical options such as ablative techniques to traditional treatments with surgery, chemotherapy, and/or radiation therapy.12 A similar paradigm, where alternative screening and treatment options are acceptable in a given context on the basis of available resources and capacities, has been put forth by the WHO for cervical cancer prevention.13 Thus, research is needed to provide an evidence base for alternative strategies to detect and treat breast cancer that may be better suited to low-resource settings. The present research will be used to inform further work by the authors on alternative screening options, including breast ultrasound, as well as nonsurgical treatment options for low-resource settings.In low-resource and economically transitioning countries, breast cancer control can be conceptualized as a spectrum of stages or implementation phases from CBE to advanced imaging, which may include mammography and breast magnetic resonance imaging. Although SBE and CBE may be the only feasible options in low-resource settings, when combined with education about the early signs and symptoms of breast cancer, these may be important tools to facilitate early detection.There are limitations to this study that must be considered when interpreting the results. First, the sample size was relatively small and may not be representative of all women in the rural setting, because women were enrolled while seeking care at a primary health care clinic. Our study site, Hlokomela Clinic, also uses a peer health education model, in which trained community members  disseminate health information throughout the community. Thus, the women in this population may be both more educated about breast health and more comfortable with seeking health care than the general population in rural South Africa. The relative homogeneity of our population (with > 95% of participants having ≤ high school education) meant that we were unable to identify variations by education level. Future research should aim to determine whether differences in primary versus high school education predict levels of knowledge in low-resource settings, as well as what roles socioeconomic status and access to health services play in determining knowledge, attitudes, and practices. As is the case in all cross-sectional surveys, our study is subject to both misclassification and social desirability bias. Data on family and personal histories as well as history of early detection practices were dependent on self-report and thus may have been under- or over-reported, which is the standard in this region and generally in LMICs where no formal medical data collection exists. Social desirability bias may have led to over-reporting of care-seeking intentions. The adaptation of our survey from English for a low-literacy, Tsonga- and Sepedi-speaking population may have also led to misclassification. Women were asked in the survey how likely they were to visit a physician. After completion of the survey, it became clear that women in the study population typically distinguish between physicians and other care providers . We were unable to assess familiarity with and history of screening ultrasound or mammogram, because of a translation error in the survey. Future research should seek to identify current practices with regard to these technologies in South Africa.Women in our study population demonstrated moderate levels of knowledge about breast cancer risk factors and symptoms, recognized the importance of early detection for breast cancer treatment, and demonstrated positive attitudes toward care seeking for breast cancer despite low access to care in the region. Our data suggest that implementation of an early detection and treatment program has a high likelihood of acceptability. Further research is needed on the feasibility and impact of such a program.


TL). While short TL generally is associated with increased cancer risk, its association with breast cancer risk is inconclusive. We suggest that working schedules might be an important factor in assessment of effects of TL on breast cancer risk. Moreover, telomere shortening might be a potential mechanism for night work‐related breast cancer. In this study, effects of shift work on TL and its association with breast cancer risk were investigated in a nested breast cancer case–control study of Norwegian nurses. TL was assessed by qPCR in DNA from 563 breast cancer patients and 619 controls. Here, we demonstrate that TL is affected by intensive night work schedules, as work with six consecutive night for a period of more than 5 years was associated with decreased telomere lengths . Furthermore, telomere shortening is associated with increased breast cancer risk in workers with long periods of consecutive night shifts. Thus, nurses with longer telomere lengths had a lower risk for breast cancer if they had worked more than four  or five  consecutive night shifts for a period of 5 years or more. These data suggest that telomere shortening is associated with the duration and intensity of night work and may be a contributing factor for breast cancer risk among female shift workers.Occupational factors such as shiftwork and especially night work that involves disruption of the circadian rhythm may contribute to increased breast cancer risk. Circadian disruption may also affect telomere length ( BRCA1 and BRCA2) genes, as well as genetic polymorphisms in multiple genes including ATM serine/threonine kinase (ATM) and genes in the tumor protein 53/MDM2 proto‐oncogene pathway are also associated with increased risk Breast cancer is the most common cancer in women worldwide. The etiology of the disease is complex and involves several known biological and lifestyle risk factors n nucleotide repeats, cap the ends of chromosomes and prevent chromosome shortening during replication. As telomeres are critically shortened, chromosome instability increases, and cellular senescence and apoptosis occur The mechanisms for the association between night work and increased cancer risk are largely unknown. Work schedules including work at night have been shown to affect telomere length (TL) Telomeres can be elongated by the nuclear enzyme complex telomerase which consists of telomerase reverse transcriptase (TERT), telomerase RNA component (TERC), and dyskerin TERT and TERC.We have recently assessed night shift work by duration and intensity of night work and found that female nurses that had worked for more than 5 years in schedules with more than six consecutive nights had an increased breast cancer risk This nested case–control study included Norwegian nurses graduated between 1914 and 1985. Study design, data collection, and recruitment of subjects were performed as previously described pm and 6 am. For each job, information on job duration, workplace, proportion of fulltime work, and work schedules  was collected. Information on number of consecutive night shifts (intensity) was obtained from all jobs that included either permanent night work or rotating night shifts. Our analyses focused on the combination of duration and intensity of night work which is a more accurate exposure metric than just duration of night shifts, and which has been associated with increased risk of breast cancer n consecutive nights” (n = 3–6), and four categories were defined. (1) never worked night shifts (reference group), (2) worked at night, however, never n consecutive night shifts, (3) worked n consecutive night shifts for <5 years, and (4) worked n consecutive night shifts for ≥5 years. Moreover, a metric focusing on the duration of night work only was used, and three categories were defined. (1) never night work (reference group), (2) 1–11 years of work including night shifts, and (3) ≥12 years of work including night shifts.Full details on the exposure assessment were described previously TERT (rs2736108) or in the proximity of TERC (rs12696304 and rs10936599) were chosen based on previously published literature showing a connection between the selected SNPs and variations in TL μL DNA on a 7900HT real‐time PCR system  or by pyrosequencing using Pyromark Q24 Advanced technology  according to the manufacturers’ instructions.DNA was extracted from the saliva samples using Oragene DNA isolation kit as described by the manufacturer (DNA Genotek Inc). Single nucleotide polymorphisms (SNPs) in FTH1) was used as reference gene. Primer sequences were as follows: Telomere forward primer 5′–CGGTTTGTTTGGGTTTGGGTTTGGGTTTGGGTTTGGGTT–3′, telomere reverse primer 5′–GGCTTGCCTTACCCTTACCCTTACCCTTACCCTTACCCT–3′, FTH1 forward primer, 5′‐GATGATGTGGCTTTGAAGAACTTTGCCA‐3′, FTH1 reverse primer, 5′‐CACCTCGTTGGTTCTGCAGCTTCATCA‐3′. Primer specificity was determined by melting point analysis. qPCR was performed using 1 ng template DNA in a total volume of 10 μL containing PerfeCTa SYBR Green Fastmix, ROX . Cycling conditions were as follows: 95°C, 2 min followed by 40 cycles of 95°C, 10 sec and 60°C, 45 sec. The standard curve was generated by performing serial dilutions of plasmid DNA containing a 10mer oligonucleotide with TTAGGG repeats and one copy of FTH1 sequence. pUC57 plasmid DNA  was added to each standard to maintain a constant amount of total DNA per reaction tube. Standard curves had r2 > 0.975. A master standard dilution was made to ensure minimal variation between different runs.Absolute TL was analyzed by qPCR using SYBR Green I technology essentially as previously described, with minor adjustments TL as outcome variable was analyzed using a linear mixed model with a random intercept for plates to take into account the plate variation on measured TLs. The data were ln‐transformed prior to analysis to ensure a more homogeneous residual variation in TLs between plates. Separate analyses were performed for the following combinations of exposure variables: (1) cancer status (case vs. control), (2) night work exposure metrics (reference = only day shift), (3) interaction terms between cancer status and night work, and (4) SNP variables.The odds ratios of breast cancer were analyzed using logistic regression. TL (ln‐transformed), night work exposure metrics, interaction terms between TL and night work, and SNP variables were considered as exposure variables.Four different genotype models were used to analyze the effect of SNPs on TL or on the odds ratio of getting cancer: free genotype model , recessive model (CC vs. CG/GG), dominant model (CC/CG vs. GG), and additive genotype model .The list of potential confounders tested included: alcohol consumption, parity, mother's age at first birth, duration of daily occupational exposure to X‐rays, hormonal treatment last 2 years before diagnosis, and occurrence of familiar breast cancer. For analysis of cancer risk, adjustments for age at cancer diagnosis (case) or age at year of diagnosis of the corresponding case, that is, age at recruitment (control) were included. In the analysis of TL as outcome, additional adjustments were made for age at the saliva test and number of years since cancer diagnosis. This variable allows for a possible more rapid change in TL after cancer diagnosis, and partially corrects for possible bias induced by the time delay from cancer diagnosis to the saliva sample collection in TL analyses. All possible combinations of adjustment variables were compared and the combination that minimized the AIC criterion was chosen. Final adjustments were performed for relevant confounding factors as further detailed in the respective table footnotes.chisq.test) or Mann–Whitney U‐test (wilcox.test) as appropriate. P ≤ 0.05 was considered significant.Statistical analyses were done using R (version 3.2.2). Linear mixed models and logistic regressions were analyzed, using the lme and glm functions, respectively. Characteristics of the study subjects were assessed by Chi‐square square (P < 0.001). As expected, some differences in the established risk factors, i.e., age, number of children, alcohol consumption, and hormone replacement therapy, were observed between cases and controls. However, these differences were not statistically significant.The demographics of cases and controls enrolled in the study are shown in Table P = 0.016) independent of their case‐control status, but not in those that worked <5 years with intensive consecutive night shifts.TLs were not significantly different in nurses that had worked night shifts compared with those that had worked only days. Thus, duration of night work independent of the intensity of night shifts did not influence TL. However, working many consecutive night shifts for at least 5 years was correlated with reduced TL independent of case–control status Table . While, P = 0.007, and E: −4.65, 95% CI: −9.49 to −0.96, P = 0.013), respectively (Table P = 0.075), based on 41 cases and 55 controls.Similar patterns were observed for the differences in TL between cases and controls for the different measures of night work duration and intensity. For the different duration categories , no significant differences in TL were observed between cases and controls. However, the combined adverse effect of long duration and high intensity of night work on TL was generally stronger in cases than in controls , . Nor, when only the duration of night work, and not the intensity of work, was evaluated. However, longer TLs were associated with decreased odds for breast cancer in nurses that had worked a minimum of four and five consecutive nights for at least 5 years , Table TL did not affect breast cancer risk when work schedules were not considered  were not associated with changes in TL, nor was any correlation found to breast cancer risk in this cohort (data not shown).We also examined the association between changes in TL and three polymorphisms in the TL is affected by several life style factors, and sleep deprivation and circadian disruption affect TL and telomerase activity Shift work has been classified as a probable carcinogen and is suggested as a risk factor for breast cancer These data suggest that telomere shortening may contribute to increased breast cancer risk in workers that have worked many years with several consecutive night works . Such shift systems may cause disruptions of circadian rhythms and disruptions of sleep patterns CLOCK genes TERT and TERC genes Telomerase activity oscillates with the circadian rhythm and is under control of For evaluation of the effects of night work on cancer risk, the duration of night work is generally utilized. Previous studies evaluating the association of breast cancer and night work differ in respect to classification of duration of night work, with limits set between 3.1 and 30 years, making comparison of reports difficult as differences in shift systems may affect the results In conclusion, this study demonstrates that telomere shortening is affected by work schedules and is correlated with long duration of work involving consecutive night shifts. Furthermore, reduced TL is associated with increased breast cancer risk in workers with long periods of consecutive night shifts. These data suggest that telomere shortening may be a contributing factor for breast cancer risk among workers with consecutive night work schedules.None declared.Figure S1. Changes in telomere lengths (kb) with increasing number of consecutive night shifts. Absolute telomere lengths were analyzed in DNA samples from nurses working 0, ≥3, ≥4, ≥5, and ≥6 consecutive night shifts for at least 5 years.Click here for additional data file.Table S1. Difference in telomere length (TL) between night work schedules, independent of case‐control status.Click here for additional data file.Table S2. Genotype frequencies of TERT and TERC polymorphisms among breast cancer cases and control subjects. Click here for additional data file.


Supplemental Digital Content is available in the text The present study aimed to investigate risk factors for early onset breast cancer that are related to lifestyle and psychological stress. A comparative case–control study was performed among patients from the Department of Breast Surgery in Shanghai Cancer Center of Fudan University. The information regarding risk factors associated with the development of early onset breast cancer was collected using a questionnaire in a face-to-face interview. The distribution of the risk factors associated with the development of early onset breast cancer between the patient group and the control group was analyzed with logistic regression. A total of 582 cases of young patients (≤40 years old) with breast cancer and 540 controls of young patients (≤40 years old) with benign breast disease were included in this study. The risk factors for breast cancer in young women include age at first birth , history of breast cancer in an immediate family member , history of genital surgery , active and passive smoking in daily life or the environment , weekly intake of soy products , use of household cooking oil , disharmonious marital status , frequent depression , and negative emotional experiences . Our study could provide the basis for risk assessment and preventive interventions for early onset breast cancer. Recently, the rate of breast cancer diagnosis has rapidly increased in young women in China, and the mortality rate among these young patients is higher than among those who are older. Statistics released by the International Agency for Research on Cancer have shown that patients younger than 40 years accounted for 12.56% of all cancer diagnoses in China in 2008. According to statistics of the Shanghai Center for Disease Control and Prevention, patients <40 years old accounted for 10% to 20% of the total cases of breast cancer in Shanghai from 1990 to 2007. The poor prognosis of early onset breast cancer has gradually attracted widespread international concern in recent years.,5The worldwide incidence of breast cancer in young patients shows an obvious upward trend in recent years. Based on the data of Surveillance, Epidemiology, and End Results, approximately 11% of breast cancer patients are 35 to 45 years old. Case–control studies from different regions of China have shown that the risk factors for breast cancer are mainly biological , psychological , and social  factors. Yan et al conducted a meta-analysis of nearly 10 years of Chinese literature to elucidate the relationship between psychological factors and breast cancer and showed that the development of breast cancer is the consequence of the integrated effect of multiple factors including biological, psychological, and social factors. Currently, research on risk factors for early onset breast cancer in China is lacking. Given the gradual increase in the incidence of early onset breast cancer, research investigating the lifestyle and status of young patients prior to disease onset is being performed to identify factors associated with early onset breast cancer. This study aimed to investigate the main physiological and psychological risk factors for breast cancer in young patients based on the biopsychosocial medical model and to explore the impact of lifestyle and psychological stress on the development of early onset breast cancer, thereby providing a basis for the development of relevant prevention strategies.Some countries with a high incidence of breast cancer have made significant progress identifying risk factors for breast cancer that are specific to certain regions and certain populations, which allows doctors to collect relevant information to quantitatively predict the risk of breast cancer for an individual woman.22.1The present study was approved by the Scientific and Ethical Committee of the Shanghai Cancer Center, Fudan University. Written informed consent was obtained from all participants. The individuals in the present study have given written informed consent to publish these details and data.2.2The present study took place in 1 cancer center in Shanghai between May 2013 and May 2015. Based on a convenient sampling strategy (nonprobability sampling), participants were screened and selected by the principal researcher according to inclusion and exclusion criteria. Patients younger than 40 years of age who had breast disease and who were admitted to the Department of Breast Surgery at Shanghai Cancer Center of Fudan University were included in this study. The patient group consisted of breast cancer patients, while the control group consisted of patients with benign breast disease.For the patient group, the inclusion criteria were as follows: pathological diagnosis of breast cancer, elementary education or higher, ≤40 years old, no past or current mental illness or unconsciousness, and agreement to participate in the study. The exclusion criteria were as follows: systemic metastasis and presence of arthritis, severe cardiovascular disease, diabetes, or brain dysfunction.For the control group , the inclusion criteria were as follows: agreement and ability to participate in the survey, elementary education or higher, ≤40 years old, no past or current mental illness or unconsciousness, and pathological diagnosis of benign breast disease. The exclusion criterion was as follows: presence of arthritis, severe cardiovascular disease, diabetes, or brain dysfunction.Eligible women were identified and approached by the researchers in our department. Then the researchers would explain details of the study to each patient, and ask for each patient's informed consent to participate in the study. If consent was given, the researchers would distribute the questionnaires to them and notify them that the questionnaires aimed to investigate the status of the patients before they were ill.2.3The present case–control study was designed to collect data regarding risk factors associated with early onset breast cancer and explored the impact of lifestyle and psychological stress on the development of early onset breast cancer. a self-designed structured questionnaire  was used to obtain information from cases and controls covering demographic factors, female reproductive factors, lifestyle factors, and psychological factors.According to Professor Engel's biopsychosocial model of modern medicine, which attributes the cause of a disease to integrated factors beyond a single biological agent and highlights the impact of psychological and social factors on human health,The demographic factors had 7 items and the female reproductive factors contained 9 items. The lifestyle factors contained 22 items covering 3 dimensions wherein smoking and drinking contained 6 items, living and working habits contained 11 items, and dining contained 5 items. and has been applied to the researches of the pathogenesis of tumor, insomnia and such physical and psychological illness. PSSG contained up to 44 items of 3 assessment levels including life events, emotional experience, and responses to living occurrences and moods. Life events contained such items as death of spouse/relatives, marriage problems (divorce/separation), changes in occupations, financial difficulty, and changes in personal health. Emotional experience contained negative emotion and positive emotion. Negative emotion included fear, worries, depression, nervousness, sorrow, helplessness, etc. Positive emotion included delightfulness, happiness, excitement, etc. Reponses to living occurrences and moods contained positive coping and negative coping. Positive coping included forgetting unhappy things as soon as possible, transferring negative factors into positive factors quickly, trying to find help, changing a different environment, being humorous to any problems, etc. Negative coping included being angry at others, losing temper, always crying, always drinking and smoking, etc. PSSG were believed to have good reliability and validity.The psychological factors were investigated by the “Psychosocial Stress Survey for Groups (PSSG)” questionnaire and 13 normal psychological items designed through literature and clinical experience. The “ PSSG” is based on Folkman's stress theorySeventeen medical information items were collected by researchers including height, weight, age of menarche, menopause, first birth, family history, etc.2.4t tests  and χ2 tests. Unconditional logistic regression model was used to analyze the significant risk factors of early onset breast cancer. Correlation power of all risk factors with breast cancer was evaluated by the odds ratio. The odds ratio represented the odds that an outcome would occur given a particular exposure, compared to the odds of the outcome occurring in the absence of that exposure.The data were input into SPSS 18.0 software. The indices in questionnaire were compared between the 2 groups using 3We contacted 891 young women in the patient group. A total of 582 patients consented and completed the questionnaire (65% acceptance). The most common reason for refusal provided was “not interested in it.” The majority (46%) did not provide a reason. Comparisons were made between 540 patients (60% acceptance) and the 362 refusers with regard to available data. The majority of the control group (51%) did not provide a reason.So from May 2013 to May 2015, a total of 582 patients who were ≤40 years old and who had breast cancer and 540 patients who were ≤40 years old and who had benign breast disease were included in this study.P > 0.05).Comparison of the demographic factors, reproductive factors, and lifestyle and psychological factors between the patient group and the control group is presented in Table P < 0.05)  Table . Women w4The present study is a case–control study of the risk factors associated with early onset breast cancer in China. Their cohort study in Shanghai showed that the risk of breast cancer in a woman with a history of breast cancer in an immediate family member was 1.74 times that of a woman with a negative family history, which was more significant for women ≤55 years of age. For young women, they should clearly know about their family history and be aware of their increased risk; then they could pay more attention to their health examination. And health professionals could provide these young women with related specialized information. Epidemiological studies have indicated that the history of reproductive disease increases the risk of breast cancer to varying degrees. The study by Schairer et al showed that those who underwent a hysterectomy alone were at a slightly increased risk of breast cancer. Studies by Cao et al and Ju et al also showed a positive correlation between a history of genital surgery and the incidence of breast cancer. The development of breast diseases is related to estrogen, and estrogen is closely related to breast cancer. Some ovarian diseases can cause abnormal secretion of estrogen. The instability of reproductive factors may be a complex research problem encountered in the study of risk factors for breast cancer. Therefore, regular screening should be provided for young women with a history of genital surgery, and they should be made aware of their increased risk.The logistic regression analysis in the present study showed that the risk of breast cancer in a young woman with a history of breast cancer in an immediate family member was 2.36 times that of a young woman with a negative family history. This finding is consistent with the study of Kilfoy et al. Studies have confirmed that secondhand smoke is harmful as soon as it is inhaled, and, thus, there is no safe exposure level. Canadian scholars have inferred the causal relationships between passive smoke exposure in nonsmoking young women and the development of breast cancer. Chen et al performed a meta-analysis of passive smoking among Chinese women and found a risk ratio for breast cancer of 1.67 (95% CI: 1.27–2.21) among women exposed to passive smoke. Our study also confirmed that frequent smoke exposure in daily life or at work increased a young woman's risk of breast cancer by 1.64 (95% CI: 1.19–2.25). As a preventable and controllable environmental risk factor, smoking has an important significance for the prevention of early onset breast cancer. Young women should be aware of this environmental factor, try to reduce their exposure to this indirect hazard, and maximize their chances to work and live in good environments.The harm to human health caused by smoking is indisputable. Although the rate of active smoking in Chinese women is not high, they are frequently exposed to passive smoking, which is also known as “environmental second-hand smoke.” and Woo et al, have shown that the regular intake of soy products protects against breast cancer. However, our study of young women showed opposite results. Because there are few studies of breast cancer risk among young patients consuming soy products, the results of this single study may not be applicable to all young women in the population. A prospective study would be a better experimental design to explore the correlation between breast cancer and consumption of soy products. Our study also found that using animal fat as a household cooking oil has a risk ratio for breast cancer of 2.04 (95% CI: 1.04–4.00). Animal oil contains more saturated fatty acids and cholesterol. Vegetable oil is the fat obtained from the extraction of the seeds and other parts of plants. Dai et al carried a large population-based case–control study; they found that intake of soybean oil might reduce the risk of breast cancer among women. Vitamin E and phytosterols are the phytochemicals that have been proven to restrain the growth and metastasis of breast cancer in cell culture and animal experiments. Moreover, soybean oil has a high density of essential fatty acids including linoleic and linolenic acid (mostly α-linolenic). The epidemiological evidence from other countries shows that olive oil may reduce the risk of breast cancer.,24 Research indicates that the major fatty acid composition of olive oil, which is octadecenoic acid, can block the generation of a protein that may stimulate the growth of breast cancer cells. These findings suggest that cooking oil factor and its interaction with body mechanism may play an important role in the etiology of breast cancer. The results of our study may provide a reference for young women in China to choose a cooking oil. But large-scale experimental researches on cooking oil are still lacking; a prospective experimental study could be better designed to explore the correlation between breast cancer and cooking oil.Studies of soy intake and the risk of breast cancer, including the meta-analyses by Liu et al,26; it may cause the body to activate human physiological systems in order to maintain stability. Gross et al followed subjects for 24 years to study the relationship between emotions and cancer, and the results showed a statistically significant difference in depression for women with breast cancer, and the level of anxiety also significantly increased the risk of breast cancer. A review by Butow et al found that some case–control studies had shown that emotional depression and alexithymia are strong predictors for the risk of breast cancer in young women. Possel et al also conducted a review focusing on the relationship between depression and the development of breast cancer; 12 of the 15 studies found positive associations between them. Few relevant studies from China are available. A survey by Wang et al of personality traits among breast cancer patients in Southwest China showed an unstable character among patients prior to the diagnosis, which mainly presented as depression, emotion repression, pessimism, and quick anger after stimulation. Our study showed that frequent depression and negative emotional experiences were associated with the development of early onset breast cancer, with risk ratios of 1.32 (95% CI: 1.00–1.75) and 1.15 (95% CI: 1.03–1.29), respectively, which are consistent with the finding that emotional repression increases the risk of breast cancer. The balance of neuroendocrine hormones in women is easily affected by psychological trauma, and long-term adverse emotional experiences may cause hyperplasia in mammary epithelial cells that leads to the development of cancer. Fast-paced urban life and social pressures push young women to pursue quick success without rest, which puts the body into a long-term stressed state that results in exhaustion, physical discomfort, mental depression, lowered self-regulation, and suppression of the body's immunity and endocrine balance. All of these elements may reduce the body's resistance to cancer-causing factors or enhance the body's susceptibility and, thus, may increase the risk of breast cancer. The 10-year follow-up survey of 18,932 women by Nielsen et al found that women working in fast-paced jobs had a higher risk of breast cancer than women working at a proper pace. The correlation of mental state and emotional experiences with breast cancer should draw more attention to young women. Young women should adjust their pace, relax, decompress, and experience positive emotions, which will improve their quality of life and reduce their possibility of illness.Psychological factors, including depression and stress, impair immune function, which, in turn, predisposes an individual to the development of cancer,35 A prospective study by Michael et al followed 84,334 women over a period of 7.6 years and found an increased risk of breast cancer among women reporting a negative life event compared to that among women without such an event. Specifically, negative events such as divorce/separation, death of a spouse, and bereavement showed the largest impacts. It is believed that the pathogenesis may be related to hormones or other mechanisms. A case–control study by Eskelinen and Ollonen showed that the score of negative life events and the level of personal pressure among breast cancer patients were significantly different from those who were healthy or had benign disease. Our study showed that the scores of negative life events for the young women in the 2 groups were significantly different, but only marital disharmony was identified in the logistic regression as being a risk factor, with a risk ratio of 1.16 (95% CI: 1.06–1.26). This is consistent with the results of previous studies, which also indicate that harmonious marriage is an important protective factor among young women. A good and stable marriage can promote human health and protect young women by improving their ability to deal with and adapt to life events, and a high-quality marriage requires joint efforts from both partners, so maintaining a harmonious marriage should be a priority.Negative life events and stressful events play an important role in the development of breast cancer.In summary, in the present case–control study, we found that besides age at first birth, history of breast cancer in an immediate family member, and history of genital surgery, lifestyle and psychological factors play an important role in the risk of breast cancer among young women. The present study was one of the few case–control studies of early onset breast cancer in China. It clarified the relationship of lifestyle factors and psychological factors with early onset breast cancer and indicated the importance of psychological factors in the prevention of early onset breast cancer.4.1The limitations of the present study include the recruitment and the convenient sample from 1 cancer center. And the numbers between case and control groups do not catch 1:1 match. Maybe they do not represent the majority of young breast cancer patients. Multiple testing can lead to significant findings due to chance.The authors would like to thank the women who participated in this research and shared their experiences. They would also like to thank Professor Jiayan Huang  for her suggestions on the present study.


The interaction between inherited mutated genes and environmental factors is believed to play a crucial role in cancer development. The main aim was to identify lifestyle-related risk factors for breast cancer among Jordanian women.A hospital-based multicenter case-control study was conducted in Jordan in 2016. Overall, 405 cases and 418 controls, in 3 large hospitals where cancer patients are treated, participated. The prevalence of individual and groups of cancer-related risk factors was estimated descriptively using percentages and odd ratios with their correlated 95% Confidence interval (CI). The predictors of the occurrence of breast cancer were determined using logistic regression to estimate unadjusted association and adjusted association.Women in the case group  were older than those in the control group . Physical activity (sufficiently active)  and fruit and vegetable intake  (OR=1.71 95% CI=1.25–2.35) were found to be associated with reduced breast cancer risk. However, calcium intake (>3 times a week)  was associated with increased risk of breast cancer.Lifestyle risk factors were identified, and certain modifications to lifestyle are needed. Women’s awareness of these factors should be raised through appropriate channels, as a priority of the health authorities. Increasing the amount of high-quality research in this area remains one of the best ways to fight breast cancer, reducing its incidence and associated morbidities. The interaction between inherited mutated genes and environmental factors is believed to play a crucial role in cancer development , 2. BaseTotal fruit and vegetable intake were associated with a reduction in the risk of breast cancer . A high What are the reproductive risk factors for breast cancer in Jordan related to dietary and lifestyle habits?What are the predictors of breast cancer occurrence among Jordanian women?This study aimed to answer the following specific research questions:A hospital-based multicenter case-control study design was used to explore and identify risk factors for breast cancer.The sample comprised two groups: case and control. Overall, 405 cases and 418 controls participated in the study that was conducted 2016. The case group comprised cancer patients who met the following inclusion criteria: 18 yr or older, confirmed breast cancer diagnosis as evident from histopathology reports, newly diagnosed within six months, knowing their cancer diagnosis, and physically able to complete a 15–30-min structured interview. The control group participants had no cancer and match the participants in the case group with regard to age (±5 yr), gender, and geographical area.The sample size was calculated based on the number of independent variables (m) in the logistic regression model. For medium-sized relationships between the independent variables and the dependent or outcome variable, 5% significance and 80% power, the sample size (N) should satisfy the following : N ≥ 10mThe DDS includes questions designed to elicit information about participants’ demographic characteristics: age, marital status, education, income, smoking, previous history of cancer. It also collects information about the patients’ general health, and on cancer diagnosis (confirmed histopathology report), stage, and other chronic medical conditions.2). Participants with BMI scores 18 to 25 were considered normal, but BMI scores from 25 to 29.9 were considered over-weight and of 30 and above as obese.Height and weight were measured for all participants and the body mass index (BMI) calculated: weight (Kg)/Height , gender , and geographical area, and having no known cancer. Patients in the case group were asked to suggest a possible control subject ; if this was not possible, the research assistant recruited controls from the visitors to other outpatient clinics. Participants in the control group were asked to sign the consent form then to complete the study questionnaire.Data was entered into SPSS . The prevalence of individual and groups of cancer-related risk factors was estimated descriptively using percentages, with 95% CI, across the entire sample and for key sub-groups. The statistical association of the presence of individual or groups of risk factors (yes/no) was analyzed using a two-group test, Pearson’s chi-square test for nominal variables. Predictors of the occurrence of breast cancer were determined using logistic regression to estimate unadjusted association (predictors considered separately) and adjusted association (predictors considered together) . FinallyP=0.004). Most of the women in both groups were married (case: 90.1%), control (93.5%)  were older than those in the control group . There was a significantly higher percentage of highly educated women in the case group (41.7%) than in control group (31.8%) ( (93.5%) .P-values were >0.05. However, increased intake of vegetables and fruit was associated with reduced risk of breast cancer . In addition, physical activity was inversely associated with the risk of breast cancer . An increased risk of breast cancer by 2.15 times was observed among women with a high total calcium intake, (>3 times a week) . Finally, the percentage of women practicing self-breast examination was significantly higher in the case group (29.9%) than the control group (20.6%) .All significant factors were further analyzed using a logistic regression model to conclude which factors could be the predictors of breast cancer occurrence . Of thesThe main findings of the study suggest the following: sufficient physical activity and optimal total fruit and vegetable intake are protective against breast cancer, high total intake of calcium supplement is a risk factor for breast cancer, and lifestyle-related risk factors vary from one geographical area to another and from culture to culture. Sufficient physical activity and optimal total fruit and vegetable intake are protective against breast cancer; this result supports previously published studies , 17–19. In regard to physical activities, the results varied and comparison was limited because of the use of different tools to measure the adequacy of physical activity , 20. MosFurther, physical activity may reduce the bulk of fat accumulation in the body associated with increased risk of breast cancer. Further research using a unified measurement tool is needed at national and international levels.P=0.970). However, this variation in the results might be because of different interaction between human genes and surrounding environmental factors , while smoking was not associated with breast cancer . HoweverThe results need to be understood in the light of the following limitations. First, selection and recall biases are inherent limitations of the case-control study design. Memorizing dietary habits, the type and amount of food taken are dependent on the subject’s ability to recall these details, which might differ from one person to another. In addition, patients in the case group may have become more aware of their dietary habits than those in the control group, because of their disease. Second, giving socially acceptable answers is a well-known limitation in the use of self-reporting questionnaires. Despite the limitations, this study sheds light on an area received little attention from Jordanian researchers, where most of the attention and care are directed to active cancer treatment.First, further research using robust design is needed to either confirm or contradict the current results and thus improve breast cancer prevention measures and practice. Second, more efforts are required to develop and validate unified measurement tools for dietary intake and physical activity to enable comparability of studies results from different parts of the world. Finally, healthcare providers are advised to educate their patients in general and patients at high risk in particular about healthy lifestyle habits and its role in reducing the risk of breast cancer.Lifestyle risk factors were identified, and certain modifications to lifestyle are needed. Women’s awareness of these factors should be raised through appropriate channels, as a priority of the health authorities. Increasing the amount of high-quality research in this area remains one of the best ways to fight breast cancer, reducing its incidence and associated morbidities.Ethical issues  have been completely observed by the authors.