The associations between vitamin D receptor (VDR) gene polymorphisms and breast cancer risk were comprehensively investigated to clarify issues that remain controversial.Fok1, poly-A repeat, Bsm1, Taq1 or Apa1 polymorphisms of the VDR gene and breast cancer risk. Summary odds ratios and 95% confidence intervals (CI) were estimated based on a fixed-effect model (FEM) or random-effect model (REM), depending on the absence or presence of significant heterogeneity. A total of 39 studies met the inclusion criteria. A meta-analysis of high-quality studies showed that the Fok1 polymorphism of the VDR gene was associated with an increased risk of breast cancer . No significant associations were observed between the other polymorphisms and breast cancer risk. No positive results were detected by pooling the results of all relevant studies.An electronic search was conducted of several databases, including PubMed, the Cochrane library, Web of Science, EMBASE, CBM and CNKI, for papers that describe the association between Fok1 polymorphism of the VDR gene was closely associated with breast cancer risk.A meta-analysis of high-quality studies demonstrated that the  As vitamin D exerts its activity by binding to the VDR, the finding that normal breast epithelial cells Laboratories investigations and epidemiological studies have suggested that the level of vitamin D, and the expression of the vitamin D receptor (VDR), might be associated with an increased risk of breast cancer 2D uptake and can therefore be considered as latent disease risk variants. A series of characterized VDR gene polymorphisms, including Fok1 (rs2228570) Bsm1 (rs1544410) Taq1 (rs731236) Apa1 (rs7975232) VDR gene polymorphisms, we performed a meta-analysis of 39 existing studies to clarify the relationship between genetic variations in VDR and the risk of breast cancer.The gene that encodes VDR maps to the long arm of chromosome 12 (12q12-14), and harbors approximately 200 single nucleotide polymorphisms (SNPs). Some are linked to differences in 1-25(OH)st, 2013. Publications with the following search words in the titles, abstract or key words of the original studies were included: ‘vitamin D receptor’, ‘VDR’, ‘Fok1’, ‘Poly A’, ‘Bsm1’, ‘Taq1’, ‘Apa1’, ‘polymorphism’ or ‘variant’ or ‘mutation’ coupled with the term ‘breast cancer’. Additional studies that were not captured by the database search were identified by reviewing the bibliographies of relevant articles.A comprehensive literature search of numerous databases, including PubMed, the Cochrane library, Web of Science, EMBASE, CBM (China Biology Medicine) and CNKI , was conducted up until December 21VDR gene polymorphisms  and breast cancer risk; (2) cases of breast cancer were confirmed by medical records or linkage with population-based tumor registries; (3) the numbers of case and control groups for each genotype were reported or the relevant data was available, and adequate data was provided to calculate the odds ratio (OR); and (4) publications in both English and Chinese were included.All identified studies were reviewed independently by two investigators. The following criteria were used for a publication to be included in the meta-analysis: (1) any study published as an original study that evaluated the association between VDR gene were reported using restriction fragment length polymorphism (RFLP) nomenclature for the major and minor alleles, as follows: Fok1 (rs2228570) alleles C = F and T = f; Bsm1 (rs1544410) alleles G = b and A = B; Taq1 (rs731236) alleles T = T, and C = t; and Apa1 (rs7975232) A = A and C = a. The allele counts were calculated from the genotype counts when needed.Two investigators conducted the search, extracted and tabulated all the relevant data independently. If a study was referenced more than once, the most complete and newly released study was used. If one article reported two or more different case-control studies, it was considered as two or more studies, respectively. Data extracted from each study were as followings: name of the first author, publication year, ethnic origin of the studied population, numbers of case and controls, and the genotype frequency of the polymorphisms. To maintain consistency with the previously published literature, SNPs of the The quality of studies was assessed according to the STrengthening the REporting of Genetic Association Studies (STREGA) criteria VDR gene and the risk of breast cancer were assessed for the contrast between two groups of homozygotes , the recessive , dominant  and allelic  models by calculating the pooled OR and its 95% confidence interval (CI). The pooled ORs were obtained using either the fixed-effects (Mantel-Haenszel’ method) model Q statistic and was quantified using the 2I statistic 2 statistic (I2>50%) indicated significant heterogeneity existed across studies.The strengths of the associations between five polymorphisms of the A Sensitivity analysis was performed to evaluate the key studies that had substantial impacts on between-study heterogeneity levels by removing the individual studies sequentially. To further explore the cause of heterogeneity, a meta-regression was performed, which included covariates such as ethnicity and sample size of the studies. If the origin of heterogeneity was found, subgroup analyses were conducted according to the origin. All statistical analyses, except the meta-regression, were performed using RevMan version 5.1.6 software . The meta-regression procedure was conducted using STATA statistical software .The possibility of publication bias was assessed using Begger’s linear regression and funnel plots. An asymmetrical funnel plot suggested a possible publication bias.Fok1, poly-A, Bsm1, Taq1 or Apa1 polymorphisms of VDR gene and breast cancer risk. Among these studies, 22 studies Fok1 polymorphism with breast cancer, including 16,353 cases and 21,881 controls, while seven studies Bsm1 polymorphism, 25 studies Taq1 polymorphism included 6,940 cases and 8,267 controls. For the Apa1 polymorphism, 11 studies were included VDR gene and breast cancer risk. The general characteristics of the selected studies are summarized in A flow chart of the literature search is shown in ff genotype on risk of breast cancer   . No signp = 0.12 , S2, S3.Four of the seven studies complied with the STREGA criteria Bsm1, Taq1 or Apa1 polymorphisms and breast cancer risk. Twelve high-quality studies did not show a significant association between the Bsm1 polymorphism and breast cancer risk Taq1 and Apa1 polymorphisms, and therefore meta-analyses were not performed by pooling the results of high-quality studies alone.For all relevant studies, the pooled results did not illustrate any significant correlation between To detect the origin of study heterogeneity, the random effects meta-regression method was used Fok1 polymorphism was symmetrical . The funnel plot for the recessive model of metrical . The othVDR polymorphisms play in the pathogenesis of breast cancer have been investigated across the world. Many studies have been carried out to investigate the relationship between VDR gene polymorphisms and the risk of breast cancer Fok1, Bsm1, Taq1 and Apa1) and contained relevant studies that were published before October 2008 VDR polymorphisms and breast cancer risk, but no definitive quantitative results were obtained Fok1, poly-A, Bsm1, Taq1 and Apa1 polymorphisms and breast cancer risk. This is the most comprehensive meta-analysis to data, to the best of our knowledge.Vitamin D regulates a variety of independent biological processes including bone metabolism, the innate immune response, cell proliferation and cell differentiation ff genotype were responsive to the increased risk of breast cancer compared to patients with Ff or FF genotypes. The overall data from all genetic models did not demonstrated that there was a significant association between the poly-A repeat, Bsm1, Taq1 and Apa1 polymorphisms and breast cancer risk. A sensitivity analysis was performed by removing the individual studies sequentially, and the overall genetic effects were consistent with those of the corresponding sensitivity analyses for the poly-A, Bsm1, Taq1 and Apa1 variants. These findings further indicated the robustness of the lack of association between these four polymorphisms and breast cancer risk.This meta-analysis included data from 39 relevant studies. The meta-analysis of high-quality studies showed that individuals with homozygous Fok1 polymorphism and Bsm1, Taq1 and Apa1 polymorphisms Fok1 can be considered as an independent marker within the VDR gene. The effect of this SNP on breast cancer is plausible, given that the presence of the f allele in the 5′-promoter region of the VDR gene results in a protein that is three amino acids longer protein that the wild-type, and which is less transcriptionally active Fok1 polymorphism with breast cancer did not identify any evidence for a significant association, McKay et al. found a positive statistically significant association between ff genotype and the increased risk of breast cancer by pooling six studies  ff genotype carriers  ff genotype was significantly associated with risk of breast cancer, in accordance with previous reports No linkage disequilibrium was shown between the VDR gene which is strongly linked with Bsm1, Apa1 and Taq1 has an important impact on VDR mRNA stability LL genotype (long/long) confers susceptibility to breast cancer risk compared with the SS genotype LL genotype is significantly associated with high-grade breast cancer in northern Indians  S alleles The poly-A repeat in the 3′-untranslated region of the Bsm1 polymorphism is located at the 3′ end of the VDR gene. It does not appear to change the nature of the translated VDR protein VDR mRNA stability Bsm1, Taq1 and Apa1 polymorphisms are all in the same linkage disequilibrium block. These polymorphisms have been widely investigated, but with differing results. Consistent with a previous meta-analysis, our finding showed no significant association of these three genetic variations with breast cancer risk. Several studies have been performed to examine the VDR haplotypes Bsm1(B/b), Apa1(A/a), Taq1(T/t) and a poly-A repeat(S/L), but they failed to find significant association between any haplotype and breast cancer risk baTL has been reported to increase the risk of breast cancer The VDR polymorphisms with breast cancer survival, but their results were also inconsistence. An analysis conducted among 111 Swedish breast cancer patients younger than 37 years of age found a trend towards a higher survival rate, especially among those estrogen receptor-positive tamoxifen-treated patients that were homozygous for the rare Taq1 allele Taq1 homozygous genotype had a 2.8-fold increase in the probability of death from breast cancer compared to homozygous carriers with the common allele  A few studies have investigated the association of VDR gene polymorphism in Fok1 and an increased risk of breast cancer. The obvious evidence of between-study heterogeneity in this meta-analysis should be discussed. Although a meta-regression procedure that included two covariates was performed, the origin of the heterogeneity among the studies was not found. The heterogeneity might have been due to other factors, such as diversity in the population characteristics , genotyping methods and study design. Previous studies have shown that the ethnic (genetic) background, gene-gene or gene-environment interactions and life-style  might play a major role in the increased risk of breast cancer in association with genetic variations. Our meta-analysis was based on estimates without adjusting the data for these factors, which is another potential limitation of this study.Our meta-analysis illustrates strong evidence for the association between a Fok1 polymorphism in the VDR gene is significantly associated with an increased risk of developing breast cancer. Furthermore, individuals that were homozygous for the minor allele genotype of Fok1 were more likely to develop breast cancer. No correlations were found between the poly-A variation, Bsm1, Taq1 and Apa1 polymorphisms in the VDR gene and the risk of breast cancer in this study.In conclusion, this comprehensive meta-analysis of high-quality studies provides substantial evidence that the Figure S1Forest plots of association of Fok1 polymorphism with breast cancer (ff vs. FF).(TIF)Click here for additional data file.Figure S2Forest plots of association of Fok1 polymorphism with breast cancer (ff+Ff vs. FF).(TIF)Click here for additional data file.Figure S3Forest plots of association of Fok1 polymorphism with breast cancer (f vs. F).(TIF)Click here for additional data file.Table S1Characteristics of studies included in this meta-analysis between the Fok1 polymorphism in the vitamin D receptor gene and breast cancer.(DOCX)Click here for additional data file.Table S2Characteristics of studies included in this meta-analysis between the poly-A polymorphism in the vitamin D receptor gene and breast cancer.(DOCX)Click here for additional data file.Table S3Characteristics of studies included in this meta-analysis between the Bsm1 polymorphism in the vitamin D receptor gene and breast cancer.(DOCX)Click here for additional data file.Table S4Characteristics of studies included in this meta-analysis between the Taq1 polymorphism in the vitamin D receptor gene and breast cancer.(DOCX)Click here for additional data file.Table S5Characteristics of studies included in this meta-analysis between the Apa1 polymorphism in the vitamin D receptor gene and breast cancer.(DOCX)Click here for additional data file.Appendix S1PRISMA Checklist.(DOC)Click here for additional data file.


TOX3 (rs4784227) in a case-control study with a total of 702 breast cancer cases and 794 healthy-controls. In addition, we also evaluated the multiple interactions among genetic variants, risk factors, and tumor subtypes. Associations of genotypes with breast cancer risk was evaluated using multivariate logistic regression to estimate odds ratios (OR) and their 95% confidence intervals (95% CI). The results indicated that both polymorphisms were significantly associated with the risk of breast cancer, with per allele OR = 1.35, (95%CI = 1.17–1.57) for rs2046210 and per allele OR = 1.24 (95%CI = 1.06–1.45) for rs4784227. Furthermore, in subgroup stratified analyses, we observed that the T allele of rs4784227 was significantly associated with elevated OR among postmenopausal populations  but not in premenopausal populations, with the heterogeneity P value of P = 0.064. These findings suggest that the genetic variants at chromosome 6q25 and in the TOX3 gene may play important roles in breast cancer development in a Chinese population and the underlying biological mechanisms need to be further elucidated.Recent genome-wide association studies (GWAS) have identified a series of new genetic susceptibility loci for breast cancer (BC). However, the correlations between these variants and breast cancer are still not clear. In order to explore the role of breast cancer susceptibility variants in a Southeast Chinese population, we genotyped two common SNPs at chromosome 6q25 (rs2046210) and in  Breast cancer is one of the most common malignancies worldwide, ranking first in incidence and second in mortality among all cancers diagnosed in women. For the year 2014, it is estimated in the United States that approximately 232,670 female patients would be diagnosed with breast cancer and 40,000 would die from it TOX3 gene were highlighted for their potential biological contribution to the development of breast cancer. SNP rs2046210 is located 180 kb upstream of estrogen receptor 1(ESR1) and downstream of C6orf97. The ESR1 gene is of particular interest in breast carcinogenesis as it encodes estrogen receptor α (ERα). ERα regulates estrogen signal transduction and plays an important role in breast cancer TOX3 gene is located at chromosome 16q12.1 TOX3 regulates calcium dependent transcription through the interaction with the cAMP response element binding protein TOX3 is mainly expressed in the brain In the past few years, several genome-wide association studies (GWAS) have identified a number of novel genetic susceptibility variants and loci which were independently associated with elevated risk of breast cancer Studies by Zheng et al. This study was a hospital-based case-control study that included 702 breast cancer patients and 794 healthy controls. All participants were genetically unrelated Chinese from Fuzhou City and its surrounding regions. Patients were consecutively recruited from the Fujian Medical University Union Hospital, Fujian, China, between June 2009 and March 2014. All BC cases were histopathologically confirmed without restriction of histological type or age. Healthy controls were frequency-matched to the BC patients by age (±5 years) and randomly selected from persons undergoing routine health examinations in the same hospital. Each participant was interviewed face-to-face by trained interviewers to gather information on demographic data, menstrual history, reproductive and breastfeeding history, previous benign breast disease history, environmental exposure history and family history of breast cancer. In addition, approximately 3 ml of venous blood was collected from each subject. Written informed consent was obtained from all participants via an institutional consent form. The study and this consent procedure were approved by the Ethics Committee of Fujian Medical University Union Hospital. The clinicopathological data of BC patients were obtained from medical records. The ER and PR status were determined by an immunohistochemical method evaluating the percentage of cancer cell nuclear staining, and the percentage of staining cells ≥10% was considered positive.Genomic DNA was extracted from the EDTA anti-coagulated whole blood using a commercially available kit according to the manufacturer's protocol . Genotyping for the two selected SNPs was performed with a custom-by-design 2×48-Plex SNPscan Kit . The kit was developed according to patented SNP genotyping technology by Genesky Biotechnologies Inc., which was based on double ligation and multiplex fluorescence PCR. Primers and probes were designed and synthesized by Invitrogen . Sample DNA were ligated and amplified by PCR according to the manufacturer's recommendations. The resulting data were analyzed with an ABI3730XL sequencer and GeneMapper 4.0 Software . To ensure quality-control, genotyping was performed without knowledge of case or control status of the subjects, and approximately equal numbers of case and control samples were assayed on each 96-well plate with two blank controls. In addition, a 5% random sample of cases and controls were genotyped twice, and the concordance rate was 100%. Genotyping failed in only one breast cancer case due to DNA quality or quantity, and the average call rate for all SNPs was higher than 99%.2 test  or Student's t-test (for continuous variables). The Hardy-Weinberg equilibrium (HWE) was evaluated by a goodness-of-fit χ2 test to compare the observed genotype frequencies with the ones in controls. Associations among genotypes, tumor subtypes and breast cancer risk were estimated by computing odds ratios (ORs) and 95% confidence intervals (CIs) from multivariate logistic regression with adjustment for age, BMI, age at menarche, age at first live birth, menopausal status and family history of breast cancer. All statistical tests were two-sided, and a P-value of <0.05 was considered statistically significant.Statistical analyses were performed with Statistical Package for the Social Sciences  for Windows . Differences between cases and controls in demographic characteristics, risk factors and genotype frequencies were evaluated by using χP>0.05). However, compared with healthy-controls, breast cancer patients tend to have an earlier age at menarche, an earlier age at first live birth and a higher proportion of family history of breast cancer (P<0.05). Among 701 breast cancer cases, 479 (68.3%) cases were ER positive and 442 (63.1%) were PR positive.The selected characteristics compared between breast cancer and healthy-control cases are summarized in P = 0.49 for rs2046210 and P = 0.94 for rs4784227. In the single locus analyses, both polymorphisms achieved significant differences in the genotype distribution between cases and controls, with per allele OR = 1.35 (95%CI = 1.17–1.57) for rs2046210 and per allele OR = 1.24 (95%CI = 1.06–1.45) for rs4784227. Multivariate logistic regression analyses also revealed that, for rs2046210, the GA or AA carriers were at higher risk of BC compared with the GG homozygotes . Similarly for rs4784227, in the dominant model, a significantly increased risk was observed in the CT+TT genotype, as compared to the CC genotype , indicating the CT or TT carriers were associated with an altered risk of breast cancer compared with the CC homozygotes. In addition, the associations for variant genotypes in the two polymorphisms were both dose-independent, P trend<0.001 for rs2046210 and P trend = 0.009 for rs4784227.The allele and genotype distribution of rs2046210 and rs4784227 in cases and controls are shown in P value (P = 0.064) for heterogeneity testing was observed between different menopausal subgroups, indicating rs4784227 potentially elevates a significant breast cancer risk in postmenopausal populations when compared with premenopausal populations. No significant positive associations and heterogeneity were observed in the age, age at menarche and age at first live birth subgroups.To further evaluate the suggestive association between two polymorphisms and breast cancer risk, we performed subgroup stratified analyses according to different epidemiological characters and tumor subtypes. As shown in P = 1.19×10−6).The combined effects of the two polymorphisms are shown in TOX3 gene were significantly associated with increased BC risk.In the present case-control study, we investigated the associations of two candidate SNPs and the risk of breast cancer in a Southeast Chinese population. We found that both rs2046210 at 6q25 and rs4784227 in the Zheng et al. ESR1 gene. ESR1 encodes receptor α which is activated by the hormone estrogen. Breast cancer is one of the hormone dependent malignancies and cumulative exposure to sex hormones has been suggested to be linked to the development of BC In vitro experiments have also proven that activating ESR1 mutations were shown to result in continued responsiveness to anti-estrogen therapies The SNP rs2046210 lies 180 kb upstream of the ESR1, researchers hypothesize that it was the polymorphism itself or the causal variants in LD that might regulate ESR1 gene expression and contribute to be elevated susceptibility to breast cancer. Another SNP, rs9397435 (2.9 kb away from rs2046210) has been identified to confer BC risk to Asian, European and African populations in fine-mapping studies ESR1, thus the potential functional mechanism of this polymorphism still requires consideration and further investigation.Since the contiguous relations between rs2046210 and TOX3 gene and in the evolutionarily-conserved portion of an intron in the LOC643714 gene. This SNP has been implicated to be a functional genetic risk variant for breast cancer in various in vitro experiments. Long et al. FOXA1 and ESR1 in a cancer-cell specific manner, modulating the affinity of chromatin for FOXA1 and resulting in allele-specific gene expression The SNP rs4784227 is located 18.4 kb upstream of the In our study, we confirmed rs4784227 as a BC susceptibility locus among a Southeast Chinese population. Further stratified analyses suggested that positive association was stronger in ER/PR positive than in ER/PR negative breast cancer which was consistent with previous data FGFR2) and methionine synthase reductase (MTRR) were indicated to elevate individual susceptibility in postmenopausal breast cancer FGFR2 gene was identified to impact carcinogenesis through cellular signal transduction MTRR gene mainly influenced folate metabolism and played important roles in DNA methylation and synthesis It is well established that endogenous estrogen in postmenopausal women is mainly produced by adipose tissue through the variation from androgen in the aromatase activity In conclusions, the present study confirmed that SNP rs2046210 and rs4784227 contributed to increased breast cancer susceptibility among a Southeast Chinese population. Moreover, our data provided additional evidence for the correlations among genetic variants, risk factors and tumor molecular subtypes. One main limitation of this study was that the sample size was still not large enough which can impact on the precision and accuracy of results, some epidemiological characteristics were also unable to be conducted in the stratified analyses. Meanwhile the functions of these two SNPs remain still unclear. Therefore, it is necessary that future larger ethnic-matched studies should be warranted and further investigations into potential biological mechanisms of these two polymorphisms are also needed.


Women with breast cancer are at increased risk of second malignancy (SM). However, the impact of race and the hormone receptor (HR) status of the primary breast tumor on risk of SM are not known. The purpose of this study is to analyze the incidence of SM in women with a history of breast cancer according to race and HR status.In the surveillance, epidemiology, and end results database, multiple primary standardized incidence ratio sessions were used to compare the incidence of SM in women with a history breast cancer to the cancer incidence in the general population. Analyses of SM by age, race, and hormone-receptor status were performed using the absolute excess risk (AER) and observed/expected (O/E) ratio.Younger black women (under the age of 50) were at greater risk of SM with an AER = 76.03  compared to younger white women who had an AER = 38.59 . Older black women (50 years and older) had at an increased risk of SM with an AER = 42.26  compared to older white women who had an AER = 11.56 . Second breast malignancy is the predominant SM in both black and white women. Women with hormone-receptor (HR)-negative breast cancer had higher risk of SMs with an AER = 43.53  compared to women with HR-positive disease with an AER = 21.43 . In HR-negative women, younger black women had an AER = 96.46 , younger white women had an AER = 66 , older black women had an AER = 58.58 , and older white women had an AER = 20.88 .Black breast cancer survivors and women with HR-negative breast cancer are at increased risk of SM, which deserves further evaluation to understand the biological and clinical basis for this increased risk. Women with breast cancer are at increased risk of second malignancies (SM) compared to the general population  database. We evaluated the risk based on age, race, and HR status.The results reported in this study are based on the following SEER database: Incidence—SEER 9 Regs Research Data, Nov 2014 Sub (1973–2012) <Katrina/Rita Population Adjustment >—linked to county attributes—Total U.S., 1969–2013 Counties, National Cancer Institute, DCCPS, Surveillance Research Program, Surveillance Systems Branch, released April 2015, based on the November 2014 submission. This database covers approximately 9.4 % of the US population (based on 2010 census) and the geographic areas and years covered are: San Francisco-Oakland SMSA—1973+; Connecticut—1973+; Detroit (Metropolitan)—1973+; Hawaii—1973+; Iowa—1973+; New Mexico—1973+; Seattle (Puget Sound)—1974+; Utah—1973+; and Atlanta (Metropolitan)—1975+.Multiple primary standardized incidence ratios (MP-SIR) sessions were generated to compare incidence of SM in the SEER cohort of patients previously diagnosed with breast cancer to the incidence of cancer in the general population. The general population was matched by race and age.The first primary diagnosis of breast cancer was used and patients were excluded if the diagnosis was obtained solely based on death certificate or autopsy report or if there was no microscopic confirmation of diagnosis. Patients with carcinoma in situ were also excluded. Patients were observed from the diagnosis of breast cancer until the diagnosis of another cancer or death. For the analyses based on hormone receptors (HR), women for whom the summary results of estrogen and/or progesterone receptors were coded as positive or negative in the database were selected. Women whose breast cancer was coded as ER and PR borderline, undetermined, or unknown were excluded. Women with ER-positive or PR-positive cancer were analyzed together as HR-positive disease. For the race analyses, the SEER variables white and black were selected, and other or unknown races were excluded. The terms younger (Y) women and older (O) women in this manuscript refer to women under age 50 and 50 years or older, respectively. The risk of SM are reported for younger white (YW), younger black (YB), older white (OW), and older black (OB). Due to the limited data on HER2 status in the SEER database, the impact of this variable on the risk of SM was not examined.SEER* Stat 8.2.1, released on 4/08/2015, was used to analyze the observed to expected (O/E) risk of secondary cancers in patients with a first breast cancer diagnosis. The observed incidence is the actual count of events experienced for this subset of patients. The expected incidence is the number of events expected for this subset of general population of women matched by race and age. The O/E risk is the observed count divided by the expected count. The absolute excess risk (AER) is the excess cancer (beyond the expected amount) per 10,000 persons per year. The formula for excess risk is: (Observed count—Expected count) × 10,000/person years at risk. The mean age at exposure is the mean age, in years, at diagnosis of the first cancer among individuals in this subset of the cohort, and the mean age at event is the mean age, in years, at the time of experiencing the SM. 95 % confidence intervals (CI) are reported and the P value is <0.05 if the CIs do not overlap 1.Women with a first diagnosis of breast cancer have a significant increased risk of SM at all sites with higher risk in younger women.Younger women  had 16,492 new SM , and the mean age at time of SM was 54.6 years. In contrast, older women  had 58,378 SM , and the mean age at time of SM was 74.4 years.Younger women had 8696 new second breast malignancy (SBM) , and the mean age of SBM was 52.4 while older women had 19.175 SBM  and the mean age of SBC was 72.8.For younger women, the AER was significant for solid tumors (41.91), SBM (33.49), ovarian (2.39), respiratory system (2.29), leukemia (1.11), uterine (1.05), skin (0.61), endocrine cancers (0.57), urinary systems (0.4), soft tissue (0.39), pancreas (0.28), and bone/joint (0.08). For OW, the AER was significant for solid tumors (17.32), SBM (14.45), gynecologic (3.17), skin (0.48), endocrine cancers (0.51), urinary systems (0.4), soft tissue (0.27), and bone/joint (0.08).BW women with a first diagnosis of breast cancer had an increased risk of SM compared with WW women regardless of age. YB women  had 1897 new SM  and the mean age at time of SM was 52.0 years; YW women  had 13,390 new SM  and the mean age at time of SM was 55.1 years. OB women  had 3818 new SM  and the mean age at time of SM was 52.0 years; OW women  had 51,548 new SCs  and the mean age at time of SCs was 74.7 years , YB women had 743 new NBSM  and the mean age at time of SM was 55.2; YW women had 6508 NBSM  and the mean age at time of SCs was 57.38. OB women had 2439 NBSC  and the mean age at time of SMs was 73.20; OW women had 34,819 NBSM  and the mean age at time of SCs was 75.4.Women with HR-negative breast cancer had higher risk of SM. Women with HR-negative disease N = 65,593) had 7442 new SM  while women with HR-positive disease  had 27,328 new SM   had 370 new SM , YW women  had 1485 SM , OB women (N = 3578) had 590 new SM , and OW women  had 3520 SM .In women with HR-positive disease, YB women (N = 5782) had 476 new SC , YW women (N = 3829) had 1485 SC , OB women  had 1380 new SM , and OW women  had 20,547 SC . The risk of breast cancer as a second event (BCSE) after a first diagnosis of non-breast cancer was evaluated. Having reciprocal increased risk supports the presence of shared etiology for both cancers. Black women  had 1508 new breast cancers as a second event  while the risk was not elevated in white women when all sites of first cancers are grouped together.In black women, the risk of SBM was elevated in women with non-basal/non-squamous skin cancer , ovarian cancer , thyroid cancer , and lymphoma .In white women, the risk of SBM was elevated in women with soft tissue cancer , non-basal/non-squamous skin cancer , thyroid , and lymphoma , but not ovarian cancer.To our knowledge, this is the first detailed report demonstrating an increased risk of SM in patients with primary breast cancer based on race, and HR status of breast cancer. The risk of SM was higher in black women than white women for both SBM and NBSM. This higher risk of SM in black women and HR-negative women might be related to underlying genetic variation in DNA repair. In a population-based, multi-ethnic series of female breast cancer patients <65 years at diagnosis who were enrolled at the Northern California site of the Breast Cancer Family Registry, the BRCA1 mutation frequency was 16.7 % in black women diagnosed under age 35 versus 7.2 % in non-Hispanic white patients without Ashkenazi Jewish ancestry. Women with triple-negative breast cancer have higher frequency of BRCA1/2 mutation as well. The potential for higher frequency of impaired DNA repair mechanisms in black women and in HR-negative women .The strength of the SEER database for statistical analysis is the long-term follow-up of large numbers of women with breast cancer, the availability of data on hormone receptor status and race, and the high quality of the database itself. The SEER Program is viewed as the standard for quality among cancer registries around the world. Each SEER program registry must meet specifically defined data quality goals on an ongoing basis (However, the SEER registry is limited in that it does not report data on the use of adjuvant systemic therapy. Thus, the role of these therapies in the risk of SM cannot be elucidated and is a limitation of the current analyses. Data pertaining to HR status within SEER dates back only to 1990, limiting the number of women with complete HR status. In addition, comorbidities and additional risk factors known to influence cancer incidence, such as body mass index, tobacco or alcohol consumption, physical activity, use of exogenous hormones, diet, and medications or supplements were not controlled-for in this analysis because the SEER database does not capture this information. Other limitations of the SEER Curtis  that migTesting for genetic predisposition to inherited cancer syndromes is evolving rapidly (Tung et al. Furthermore, with the increasing use of germline panel testing for inherited cancer syndromes, there is a clinical need for correlation between genotype and phenotype. We recommend that large databases such as SEER consider collecting data on BRCA1 and BRCA2 and other inherited cancer predisposition genes, since the large clinical information available in SEER provides an excellent opportunity for a better understanding of the risk of SM based on specific DNA repair genes.The search for biological surrogate markers to identify tumors with abnormalities in DNA repair is underway (Watkins et al.


Energy-related indicators, including physical activity, energy intake, body mass index (BMI) and adult weight change, have been linked to breast cancer risk. Very few studies of these associations have been conducted among black women, therefore we used the Nashville Breast Health Study (NBHS) to determine whether similar effects were seen in black and white women. The NBHS is a population-based case-control study of breast cancer among women age 25 to 75 years conducted between 2001 and 2010 in and around the Nashville Metropolitan area. Telephone interviews and self-administered food frequency questionnaires were completed with 2,614 incident breast cancer cases ascertained through hospitals and the statewide cancer registry, and 2,306 controls selected using random digit dialing. Among premenopausal white and black women, there was little effect of adult exercise or other energy-related indicators on breast cancer risk, regardless of tumor estrogen receptor (ER) status. The beneficial effect of adult exercise on postmenopausal breast cancer appeared to be comparable between white and black women ; however, among black women the reduction was limited to those with ER-positive disease. White and black women should be encouraged to engage in more physical activity to reduce their risk of postmenopausal breast cancer. Energy-related indicators, including physical activity, energy intake, body mass index (BMI) and adult weight change, have been linked to breast cancer risk. Increased physical activity has been associated with reduced breast cancer –7, whichAside from studies of BMI , 24–30, Detailed methods of this population-based case-control study conducted in and around the Nashville Metropolitan area appear elsewhere . Briefly2) was based on self-reported current height and weight one year prior to the interview. Weight change since age 18 was the difference in weight one year prior to the interview and self-reported weight at age 18 or about the time the subject may have graduated from high school. Adult exercise, occupational activity and weight change since age 18 were categorized as none (none or weight loss for weight change), and the remaining group of women were divided using tertiles among the controls for the main effects. Energy intake was categorized as quartiles among the controls for main effects. BMI was categorized using standard definitions of underweight/normal weight (<25), overweight (25–29.9), obese (30.0–34.9) and severely obese (≥35) for main effects. The referent group for the main effects was the lowest category for all energy-related indicators which for adult exercise was 0 MET hours per day reflecting the highest percentage of subjects. For most of the joint effects of energy-related indicators, the lower two of the four categories were collapsed; however, for adult exercise the upper two of the four categories were collapsed. The referent group for the joint effects was the highest category of adult exercise combined with the lowest category of energy intake or BMI or weight change. We also examined the main effects by tumor estrogen receptor (ER) status, available from pathology records for 70% of cases, using the same reference groups as the main effects, but collapsing the categories to form tertiles rather than quartiles.Trained interviewers conducted telephone interviews to ascertain information on demographic characteristics, suspected breast cancer risk factors, and energy-related indicators including adult exercise, occupational activity, current weight and height, and weight at age 18. Food frequency questionnaires validated in a similar Southern U.S. population  were admDifferences between cases and controls for demographic characteristics and breast cancer risk factors were assessed using t-tests and chi-square tests. Analyses are presented separately by race and menopausal status since the hypothesized effects of energy-related indicators on breast cancer may differ by these factors. Unconditional or polynomial logistic regression was used to estimate the odds ratio of breast cancer associated with the main and joint effects of energy-related indicators while controlling for potential confounding factors . Interac2  and black women whose BMI was >30.0 kg/m2  were at increased risk of premenopausal breast cancer. For postmenopausal women, there was a similar reduction in odds of breast cancer associated with adult exercise and occupational activity among both white  and black   women. Neither energy intake nor BMI was related to postmenopausal breast cancer. Weight change during adulthood was not related to pre- or postmenopausal breast cancer regardless of race.When we analyzed these associations by tumor ER status, the increased premenopausal breast cancer risk associated with energy intake in black women was more pronounced for ER negative than for ER positive cancer. In contrast, the reduction in risk of postmenopausal breast cancer associated with adult exercise and occupational activity in white and black women was more pronounced, although not significantly, among women with ER positive than ER negative cancer  .Our finding of a reduced risk of breast cancer associated with adult exercise in the past 10 years among postmenopausal women, but not among premenopausal women, is in agreement with previous studies conducted among white women –6, 8–9. Overall there was a suggested increase in premenopausal breast cancer among black women associated with increased energy intake, which was significant for women with ER negative tumors, but not for women with ER positive tumors. To our knowledge, this is the first time this association has been examined jointly by race, menopausal status and hormone receptor status. This finding partially agrees with Zhang et al.  who repoContrary to most previous studies , 29–30, We did not see an association between adult weight change and pre- or postmenopausal breast cancer. Adult weight gain has been linked to an increased risk of postmenopausal breast cancer , 46–47, Unlike previous studies, we did not identify any differences in breast cancer risk associated with physical activity by BMI –2, 5, orLimitations of our study included self-report of physical activity, energy intake, current weight and height, and recall of weight at age 18 which are prone to misclassification. In addition, we were unable to collect other energy-related indicators such as waist-hip ratio and percent body fat, and our definition of weight change was based on a very wide range. Nor did we collect data on activities of daily living and housework which would have allowed us to sum physical activity for a more complete definition of total physical activity . Our faiOur study is one of the largest to investigate the joint effect of energy-related indicators on premenopausal and postmenopausal breast cancer among white and black women, separately. We adjusted for known breast cancer risk factors and stratified by race and menopausal status.Our results indicate the effect of adult exercise on postmenopausal breast cancer risk is comparable in white and black women. White and black women should be encouraged to engage in more physical activity to reduce their risk of postmenopausal breast cancer.S1 Table(DOCX)Click here for additional data file.


Background. The incidence of breast cancer in RA patients remains controversial. Thus we performed a meta-analysis to investigate the impact of RA on breast cancer. Methods. Published literature was available from PubMed, Embase, and Cochrane Library. Pooled standardized incidence rate (SIR) was computed by random-effect model analysis. Results. We identified 16 separate studies in the present study, in which the number of patients ranged from 458 to 84,475. We did not find the increased cancer risk in RA patients . However, subgroup analysis showed that breast cancer risk in RA patients was positively different in Caucasians  and non-Caucasians , respectively. In subgroup analysis by style, a reduced incidence was found in hospital-based case subjects . Similarly, subgroup analysis for adjusted factors indicated that in A3 (age and sex) and A4  the risk was decreased . Conclusions. The meta-analysis revealed no increased breast cancer risk in RA patients. However, in the subgroup analysis, the risk of breast cancer is increased in non-Caucasians patients with RA while it decreased in Caucasian population, hospital-based case subjects, and A3 group. Such relationship may provide preference for risk of breast cancer in different population. Rheumatoid arthritis is a common type of autoimmune disease characterized by synovitis and joint destruction, which could lower the quality of life and life expectancy. With the improvement of treatment, the survival of RA patients has been increased. Recently, it has been reported that many comorbidities may arise during the RA disease course. Among these comorbidities, cancer is an attractive issue. Recently, many studies have analyzed the association between RA and breast cancer. Abnormal regulations of the host's immune surveillance are considered as cause of development of tumors . Immune This meta-analysis was conducted with reference to the following standard guidelines . RelevanA recruited study had to meet the following criteria: (1) it was a cohort study; (2) sample size was not less than 100 patients; (3) the study offered necessary information like standardized incidence rate (SIR) and its 95% confidence interval (CI) of breast cancer in RA patients.The exclusion criteria were as follows: (1) conference abstracts, case reports, and review articles; (2) not cohort studies; (3) not control subjects; (4) duplicate reports or unclear data description. If the same cohort study appeared in other publications, only the latest article was selected into our study.Information was carefully extracted from these recruited publications independently by two of the authors (by Guo Tian and Jia-Ning Liang), including author, year of publication, country, calendar period, total number of RA patients, person-year of follow-up, sources of patients, observed/expected, and standardized incidence rate (SIR) with its 95% CI. If original necessary data were unavailable in relevant articles, a request was sent to the author for additional data.An independent literature search was performed (by Guo Tian and Jia-Ning Liang) with the same method. The contents of abstracts were checked independently by two investigators (Guo Tian and Zhuo-Yun Wang) to decide whether they were available for inclusion. References in the studies were reviewed (by Guo Tian and Zhuo-Yun Wang) to identify additional studies. When discrepancies occurred, a third investigator (Dian Zhou) made further assessment and a final decision was made by the majority of the votes. The Newcastle-Ottawa quality assessment scale was implemented to assess the quality of the methodology in the included studies. This scale comprising eight questions with nine possible points was reviewed by a star system according to the selection populations, comparability of groups, and outcome. The qualities of the recruited studies were evaluated and examined by two reviewers (Guo Tian and Jia-Ning Liang), respectively.Q statistic [I2 = 100% × (Q − df)/Q [Q statistic (P < 0.10) suggested heterogeneity across studies, and then the result of the random-effect model was selected. If not, the result of the fixed effect model was selected. Additionally, publication bias was investigated with the funnel plot and Egger's linear regression test [In the meta-analysis, we used SIR with its 95% CI to combine these pieces of data. Heterogeneity assumption in studies was checked with the ion test . All theCharacteristics of studies eligible for the current meta-analysis appeared in With regard to cohort studies, 83% were of high quality (NOS score > 6), with an average NOS score of 6.2. The quality ratings of each study according to NOS criteria are listed in Q-test of heterogeneity was not significant and then the original SIRs were pooled by means of the random-effect models . We did not detect the increased cancer risk in RA patients . Subgroup analysis was performed by ethnics. It showed that breast cancer risk in RA patients was positively different in Caucasians and non-Caucasians . And publication bias was observed in population-based group but not in hospital-based group . Also, A1  and A3 revealed no publication bias except A2 group .We conducted a sensitivity analysis in each group to assess the stability of this meta-analysis. When any single study was removed, the relevant pooled SIRs were not radically changed. It well suggested the stability of the meta-analysis. Funnel plot asymmetry was evaluated by the method of Egger's linear regression test. The result showed that there was a significant publication bias in the total population while not existing in Caucasians and non-Caucasians, respectively  regulates many genes for immune response, cell adhesion, differentiation, and proliferation. NF-κB dysregulation may be associated with both inflammatory diseases and immune deficiencies like RA and several cancers including breast cancer [α genotypes with breast cancer [Recently, emerging studies have suggested that genetic polymorphism may play an important role both in the RA and in breast cancer. Li et al.  conductet cancer . In addit cancer  and somet cancer  has beent cancer .In subgroup analysis by style, although a reduced incidence was found in hospital-based case subjects in 6 cohort studies, the use of them might have led to selection bias because those suffering from mild RA would have made them more inclined to be away from hospitals. Nevertheless, this selection bias was minimized in the remaining population-based cohort studies.Within stratified analysis for adjusted factors, it seems that the decreased age- and sex-specific incidence may be potential factors to decrease the risk. For breast cancer with the increased SIR, an early age  of RA diagnosis was a risk factor . Even anThe present meta-analysis has several limitations. First, the sample size of non-Caucasians was relatively small, result of which may be partly biased, and thus the analysis may have insufficient statistical power to obtain a more real SIR and its 95% CI. Second, publication bias among included studies was identified while not detected when stratified by ethnicities. It is possible that some studies were not included in this analysis or some unpublished studies with null results were not found. Third, a more precise analysis could be conducted, if individual data including cultural factors, age, menopausal status, smoking, and other environmental factors may account for the ethnic difference between them. Fourth, a relatively high level of heterogeneity showed the instability of the result, which could come from the data sources.In conclusion, the present study indicates that the breast cancer risk is not increased in overall RA patients. Nevertheless, increased risk of breast cancer is observed in non-Caucasians patients with RA while decreased risk is detected in Caucasian population, hospital-based case subjects, and A3 group. Although breast cancer risk prediction remains imperfect, this might provide preference for risk of breast cancer in different population. However, potential mechanism between RA and breast cancer risk is still unclear. Therefore, the conclusion should be interpreted with caution and more large-scale studies are warranted to confirm the results in the future.


Haplotype analysis showed that FTO TAC haplotype (rs9939609-rs1477196-rs1121980) had significant reduced breast cancer risk  compared with TGC haplotype. But we failed to find any association between FTO polymorphisms and breast cancer survival. These findings suggest that variants in FTO gene may influence breast cancer susceptibility.Recently, several studies have reported associations between fat mass and obesity-associated (FTO) gene mutations and cancer susceptibility. But little is known about their association with risk and survival of breast cancer in Chinese population. The aim of this study is to examine whether cancer-related FTO polymorphisms are associated with risk and survival of breast cancer and BMI levels in controls in a Chinese population. We genotyped six FTO polymorphisms in a case-control study, including 537 breast cancer cases and 537 controls. FTO rs1477196 AA genotype had significant decreased breast cancer risk  compared to GG genotype, and this association was only found in women with BMI < 24 kg/m Although breast cancer mortality rates have declined in recent years owing to increased awareness, early detection, and better treatment options, it is still the most common cancer and the leading cause of cancer-related death among females in the world . In ChinPotential risk factors, including age, reproductive factors, personal or family history of breast disease, genetic predisposition, and environmental factors, may be involved in the pathogenesis of breast cancer . Early rTo explore the role of FTO polymorphisms in breast cancer development and progress, we performed a case-control study to assess the associations of six cancer-related FTO polymorphisms  with breast cancer risk and prognosis and BMI levels in healthy controls in Chinese population.Newly pathologically confirmed female breast cancer cases were consecutively recruited between 2008 and 2014 from the Third Affiliated Hospital of Zhengzhou University. A total of 537 eligible breast cancer cases completed in-person interviews with response rate of 91.5%. At the same time, 537 healthy controls who frequency matched to cases by age (5-year-age groups) and without a history of cancer were randomly selected from the same hospital with response rate of 90.1%. At enrollment, all participants signed a written informed consent form and then were interviewed by trained interviewers using structured questionnaire, including demographic characteristics (age and education), reproductive variables , medical information , and family history of breast cancer. Height and weight were also measured to calculate body mass index (BMI). Fasting peripheral blood samples were also collected from each subject at enrollment. All patients were followed up regularly (every 6 months) until death or the end of follow-up. This study was approved by the Ethics Committee of the Third Affiliated Hospital of Zhengzhou University.http://www.hapmap.org database, we found that rs9939609 tags rs17817449 and rs8050136 with r2 > 0.95 in population of Chinese Han in Beijing (CHB). So we selected 6 SNPs , all of which were located in the intron region of FTO gene, for genotyping with possible association with susceptibility and prognosis of breast cancer [There are total 8 SNPs  in FTO gene that reported to be associated with cancer risk . After st cancer . Genomic t-test were used to evaluate the case-control differences in the distribution of the selected characteristics, including age, education, age at menarche, menopause status, ever breastfeeding, family history of breast cancer, and BMI. Odd ratios (ORs) and 95% confidence intervals (CIs) of FTO SNPs and breast cancer risk were calculated by unconditional logistic regression models, using the most common genotype as the referent group. The linkage disequilibrium between loci in the FTO gene and the deviation of allele frequencies from Hardy-Weinberg equilibrium in healthy controls were assessed by HaploView version 4.2 [P value of 0.05 was considered statistically significant.We used SAS software version 9.3  for statistical analyses. Chi-square test andsion 4.2 , 22. We The distributions of selected characteristics of the study subjects are shown in P > 0.05). Two SNPs in FTO gene were significantly associated with risk of breast cancer. Specifically, AA genotype of rs1477196 was associated with significant decreased risk of breast cancer  compared with the GG genotype; subjects with the AA genotype of rs16953002 had significant increased cancer risk  compared with those who carry the GG genotype. These associations were remained statistically significant after further adjustment for age, age at menarche, BMI, ever breastfeeding, and education . Further stratified analysis by BMI level (<24 kg/m2 and ≥24 kg/m2) showed that the effect of rs1477196 was statistically significant only in people with BMI < 24 kg/m2  (Frequencies of the 6 SNPs in FTO gene are shown in 22–0.76) .D′ = 1.0, r2 = 0.07–0.78). The associations between FTO haplotypes and breast cancer risk were shown in Haplotype analysis showed that rs9939609, rs1477196, and rs1121980 were in linkage disequilibrium  of rs1477196 had lower BMI than those carrying the GG genotype (23.82 ± 3.60 kg/m2), but it did not reach statistical significance.Finally, we investigated the associations between the FTO SNPs and BMI in healthy controls. Results showed that subjects carrying the mutant genotypes  and TAC haplotype (rs9939609-rs1477196-rs1121980) in FTO gene were significantly associated with breast cancer risk. FTO gene located in chromosome 16q12.2. FTO protein is one homolog in the AlkB family proteins which also acts as a DNA-demethylase . Mutatiointron 1 . Thus, oP < 0.001), and this effect had significant interaction with physical activity (P = 0.004). Specifically, the rs1477196 C allele was associated with obesity in the low-activity group  but not in the high-activity group (P = 0.11). Another study done among early onset and severe obesity cases in a western Spain population also found that AA genotype of rs1477196 conferred decreased risk of obesity , and a block containing the rs1477196/rs17817449/rs9939609 haplotype had an increased risk of obesity  [2 after stratification by BMI levels.Rs1477196 located in intron 1 of FTO gene. A few studies have examined the effect of the rs1477196 variant on obesity and breast cancer risk. Rampersaud et al.  investig41–3.04) . A case-D′ = 1.0) in our study. FTO rs9939609 has been reported to be associated with obesity in many other papers [Besides, TAC haplotype (rs9939609-rs1477196-rs1121980) had significant reduced breast cancer risk compared with TGC haplotype, which may be mainly driven by individual SNP rs1477196, which was in linkage disequilibrium with rs9939609  , but tilThe essential strength of our study is the detailed review of cancer diagnosis , which minimized the potential disease misclassification. However, limitations of our study cannot be ignored. First, potential selection bias of controls might occur because of the hospital-based study design. Second, Berkson's bias could not be ruled out because obesity is more frequent amongst hospitalized patients than that in the general population, which may underestimate the real association in our study. Third, the relatively small sample size may reduce the power to explore subgroups analysis. Fourth, lack of information on physical activity may have interaction with the identified mutations.Overall, our results suggest that genetic variations in FTO gene may play roles in breast cancer pathogenesis in women. However, further researches are required to replicate our results in other populations and functional analyses are needed to elucidate the exact role of these genomic variations in the development of breast cancer.


The objective of this study was to develop a rating tool for policy makers to prioritize breast cancer interventions in low- and middle- income countries (LMICs), based on a simple multi-criteria decision analysis (MCDA) approach. The definition and identification of criteria play a key role in MCDA, and our rating tool could be used as part of a broader priority setting exercise in a local setting. This tool may contribute to a more transparent priority-setting process and fairer decision-making in future breast cancer policy development.First, an expert panel (n = 5) discussed key considerations for tool development. A literature review followed to inventory all relevant criteria and construct an initial set of criteria. A Delphi study was then performed and questionnaires used to discuss a final list of criteria with clear definitions and potential scoring scales. For this Delphi study, multiple breast cancer policy and priority-setting experts from different LMICs were selected and invited by the World Health Organization. Fifteen international experts participated in all three Delphi rounds to assess and evaluate each criterion.This study resulted in a preliminary rating tool for assessing breast cancer interventions in LMICs. The tool consists of 10 carefully crafted criteria , with clear definitions and potential scoring scales.This study describes the development of a rating tool to assess breast cancer interventions in LMICs. Our tool can offer supporting knowledge for the use or development of rating tools as part of a broader (MCDA based) priority setting exercise in local settings. Further steps for improving the tool are proposed and should lead to its useful adoption in LMICs. As the second most common cancer in the world and the most common cancer in women, breast cancer is an important health problem globally . AlthougCost-effectiveness analyses (CEAs), based on the maximization of health benefits, have often been used for the selection of breast cancer control strategies. To provide an evidence base for the cost-effectiveness of breast cancer interventions in LMICs, a consortium of the WHO, Erasmus University Rotterdam, the Radboud University Nijmegen Medical Center, and the Susan G. Komen for the Cure Foundation initiated an international study in 2010 . Such CEMulti Criteria Decision Analysis (MCDA) is a well-accepted framework that can simultaneously assess multiple criteria for priority setting of interventions . DiffereSeveral studies have shown the potential of MCDA in prioritizing health interventions, however, it has not yet been applied for the selection of breast cancer control interventions -23. ReceThe objective of this study is to develop a rating tool to assess breast cancer interventions along the continuum of care, within the context of the overarching breast cancer CEA project . The ratTo develop the rating tool we established an expert panel (n = 5) of breast cancer and priority-setting experts from WHO and the Radboud University Nijmegen Medical Centre. The expert panel consisted of two health economists, a scientific researcher, a public health specialist and a student on health technology assessment. Three of the experts are co-authors of this article . A detailed overview of the considerations made by the expert panel in the development of the rating tool is provided as additional information , and absence of any relevant interest in the personal declaration of interest form. Twenty-nine experts with expertise in priority setting or breast cancer policies in LMICs were involved, ensuring methodological as well as substantive quality. Experts were identified by approaching authors of relevant articles and by snowball sampling. Among the experts there were epidemiologists, cancer survivors, pathologists, guideline-developers, public health specialists, radiotherapists, surgeons, researchers, managers, strategists and ethicists.In this round, the list with criteria based on the performed literature study was presented to the participants. The participants were asked to score the criteria on five-point Likert scales, according to whether they agreed that interventions scoring high on the criterion should be more prioritized . The experts could give comments on the list and mention whether important criteria were missing. In addition, the definitions and scoring scales of the criteria were presented and participants were asked to provide comments. Likert scales were chosen for this first round because this method is reviewed as acceptable for a Delphi study and is simple and easy to perform .This second round showed the scores and comments given in the first round, together with the adaptations to which they had led. Subsequently, participants were asked whether they agreed on the adaptations and if they could clarify their answers.Based on the proportion of participants agreeing on the adaptations made after the first round and on the comments provided, some final changes were made to the criteria list. These final criteria and their definitions and scoring scales were shown to the participants, who were asked whether they agreed that this final list contained the most relevant criteria for the prioritization of breast cancer interventions. Furthermore, participants were asked to divide 100 points over the criteria according to their relative importance for the evaluation of breast cancer interventions.The analysis of the answers was both quantitative and qualitative. After the first Delphi round, mean and median scores on the Likert scales for “the importance” of criteria were calculated. The second round resulted in a percentage of participants who agreed with the suggested adaptations. After the third round, the mean and median weights given according to the importance of criteria were calculated. All participant comments were quantitatively analyzed.The literature search on criteria resulted in a total of 33 criteria Figure . After tOut of 72 experts who were asked, 29 were willing to participate. Of these, 17 were experts on priority setting, and 12 were experts on breast cancer policies. The first questionnaire was completed by 23 participants, the second questionnaire by 19 participants, and the third questionnaire by 15 participants. Reasons for not completing a questionnaire were private circumstances and disagreement with the aim of this research (n = 1). Most participants, however, gave no reason.Based on the results of the first round, two criteria (‘Severity of breast cancer’ and ‘Age’) and one of the components (‘The time until the effect emerges’) were suggested for removal; two of the components were suggested to be combined with two criteria; and all the other components were suggested for separation into different criteria. Also, a new criterion was suggested , two definitions were refined, and four scoring scales were adapted. These adaptations led to a list of 10 criteria. For all criteria, except for the criterion ‘Effectiveness’, there was divergence in Likert scale scores. The average and median Likert scale values and most important comments on the criteria are shown in Table Based on the results of the second round, the new suggested criterion  was removed again because participants argued that political will would also depend on the results of interventions on the other criteria; political will changes too often; and MCDA aims at a more fair priority-setting process while political will might even be clearly unfair. Two criteria  were separated into two different criteria ; two criteria were combined ; and some small refinements to most of the definitions and scoring scales were made. An overview of the changes made in the criteria list is shown in Figure All participants agreed that the list after the second round covered the most relevant criteria for the prioritization of breast cancer interventions. Three participants mentioned, however, that some criteria might be still overlapping. As one participant noted: “Doing the relative weighting exercise above, I realized that some criteria are overlapping and it was difficult to assess independent relative weights to them; for example, ‘effectiveness’ and ‘quality of the evidence’ are inseparable whereas we would not perhaps say something is effective if the quality of the evidence is weak”. There were also doubts about ‘cost-effectiveness’ being covered by the ‘affordability’ and ‘effectiveness’ and about ‘safety’ being covered by ‘effectiveness’ and ‘geographical coverage’ being covered by ‘effectiveness’. The criterion ‘geographical coverage’ was rated relatively low in its importance for the evaluation of breast cancer interventions, followed by ‘safety’ and ‘affordability’, respectively. The importance of the criterion ‘Effectiveness’ was rated highest Table .This study describes the development of a rating tool to measure the impact of breast cancer interventions based on multiple criteria in LMICs. Ten criteria, including definitions and potential scoring scales, have been indicated. The results of this study show that effectiveness, quality of the evidence, magnitude of individual health impact, acceptability, cost-effectiveness, technical complexity, affordability, safety, geographical coverage, and accessibility seem to be important principles in the selection of breast cancer control strategies. Although selecting and defining interventions and criteria for breast cancer control is context specific, we think that this rating tool can be a starting point for local policy makers as part of a broader, MCDA based, priority setting process.The tool could be used as part of the integrated MCDA and accountability for reasonableness (A4R) approach for priority setting, recently proposed by Baltussen et al.  Figure . This neAn important next step in the local use of the rating tool is to investigate how the tool and its components are understood in LMICs in a pilot study. Users of the tool could for example select relevant stakeholders  and establish a consultation panel (step 1). These stakeholders could discuss the interventions, criteria, the attitude of decision-makers against the criteria and scoring scales using democratic elements  (step 2). After the collection of all relevant  evidence, the users could use our tool as an input for a performance matrix (step 3), and then interpret and deliberate on the results of this matrix (step 4 and 5). Users should be well informed and plan enough time for this process, and should try to ensure that the tool is perceived as a simple and legitimate way to frame policy discussions in a more rapid and balanced manner. The potential of this tool could also be investigated for other cancers.Our study has a number of limitations. First, prior to the Delphi study, the expert panel made a selection of 9 criteria out of 33 criteria. This selection was based on overlap between criteria and whether criteria would be appropriate for the selection of breast cancer interventions. However, there is no certainty that personal preferences did not lead to bias in this selection.Second, we used Delphi studies to define a list with core criteria including definitions and scoring scales. The Delphi method ensures participant anonymity and provides enough time to properly consider one’s own answers and those of others. However, the Delphi questionnaire may not allow for adequate elaboration on difficult concepts such as equity and social welfare. Also, Delphi questionnaires can be relatively time consuming, which may have partly caused 14 participants to withdraw from this study. We do not expect that these withdrawals biased the results because they varied in gender and type of expert and the number of comments remained high in each questionnaire.Third, the wide variety of comments and views of the participants made us aware of the difficulties in developing a clear, consensus-based, non-overlapping criteria list and scoring scales. There are many possible compositions and definitions of criteria -33. BesiThe difficulty of avoiding overlap between criteria may be explained by a lack of a broader theory on the relationship between criteria. Some disagreement between participants remained until the end of the process, and some overlap was still suspected in the final criteria list. These potential overlaps will need attention in the further development of this tool because criteria should preferentially be independent from each other ,42. EspeThe tool also has some practical limitations that one should be aware of. First, the tool does not provide guidance to convert the performance matrix into a final prioritization of interventions. This tool stops at rating interventions after which a choice should be made based on a democratic learning process Figure . This toSecond, the proposed rating tool is based on decision-maker values and preferences while the views of other stakeholder groups are also considered important in priority setting exercises. Different stakeholder groups are likely to have different preferences for criteria ,44. ThisThird, there are limitations to the collection of information, and it may sometimes be difficult to assess interventions on certain criteria. This is however a problem across the field of health priority setting and we recommend to be transparent on the available evidence and its quality. A sensitivity analysis may help to give insight in the uncertainty of the scoring performances of intervention options. In this way, quality of evidence is not used as a single criterion but as an uncertainty factor per criterion per intervention .This study describes the development of a rating tool to assess the impact of breast cancer interventions on multiple criteria. This tool may be a starting point for local decision makers that would like to conduct multi criteria decision analysis to set priorities for breast cancer control.The authors declare that they have no competing interests. The views expressed in this paper are those of the authors, and the funding organization has had no influence on them.KV and SZ made substantial contributions to the conception and design of the study, acquisition of data, and analysis and interpretation of data. They also participated in the expert panel and drafted the manuscript. JL contributed to the design and methodology of the study and participated in the expert panel. NT assisted in the design of the study and has been involved in revising the manuscript critically for important intellectual content. All authors have read and approved the final manuscript.Key considerations for the development of the rating tool. In this additional file we elucidate on the key considerations made for development of the rating tool.Click here for file


Breast cancer incidence in Japanese women has more than tripled over the past two decades. We have previously shown that this marked increase is mostly due to an increase in the estrogen receptor (ER)-positive, HER2-negative subtype. We conducted a case–control study; ER-positive, HER2-negative breast cancer patients who were diagnosed since 2011 and women without disease were recruited. Environmental factors, serum levels of testosterone and 25-hydroxyvitamin D, and common genetic variants reported as predictors of ER-positive breast cancer or found in Asian women were evaluated between patients and controls in pre- and postmenopausal women. To identify important risk predictors, risk prediction models were created by logistic regression models. In premenopausal women, two environmental factors  and four genetic variants  were considered to be risk predictors, whereas three environmental factors , serum levels of testosterone and 25-hydroxyvitamin D, and two genetic variants (TOX3-rs3803662 and ESR1-rs2046210) were identified as risk predictors. Inclusion of common genetic variants and serum hormone measurements as well as environmental factors improved risk assessment models. The decline in the birthrate according to recent changes of lifestyle might be the main cause of the recent notable increase in the incidence of ER-positive breast cancer in Japanese women. We have previously shown that this marked increase in breast cancer incidence is mostly due to an increase in the estrogen receptor (ER)-positive, HER2-negative subtype [Breast cancer is the most common cancer in Japanese women as well as in women worldwide. Its incidence in Japanese women has more than tripled over the past two decades , a lower number of pregnancies (P = 0.003), nulliparity (P = 0.004), a history of never breastfeeding (P = 0.001), and presence of a family history of breast cancer (P = 0.034) were observed in patients compared to controls (Table P < 0.001), body mass index (BMI) ≥ 25 kg/m2 (P < 0.001), older age at menarche (P < 0.001), a history of never breastfeeding (P = 0.009), presence of hyperlipidemia (P < 0.001), and presence of diabetes mellitus (P = 0.029) were found in postmenopausal patients compared to control women  were significantly higher in patients than in controls in both pre- and postmenopausal women (P = 0.004), rs2046210 (P < 0.001), rs4784227 (P = 0.049), and rs4973768 (P = 0.043) in premenopausal women, and risk allele frequencies of rs2046210 (P < 0.001) and rs4784227 (P = 0.044) in postmenopausal women were significantly higher in patients compared with those in controls (Table P = 0.001 in the dominant model), ESR1-rs2046210 , 8q24-rs13281615 , and SLC4A7-rs4973768 , showed significant association with increased risk of ER-positive breast cancer (Table P = 0.031 in the recessive model) and ESR1-rs2046210 , showed a significant association with increased risk of ER-positive breast cancer in postmenopausal women  curves with the area under the curves (AUCs) for three different models. One model took into account environmental factors only, the second model included both environmental factors and endogenous hormones, and the third model included all factors including genetic factors Figure . The risThe best risk prediction models with the most effective risk factors were established using the backward stepwise selection method. Finally, the following factors were included in the best risk prediction models: a history of breastfeeding, a history of benign breast disease, CT+TT at TOX3-rs3803662, CT+TT at ESR1-rs2046210, GG at 8q24-rs13281615, and TT at SLC4A7-rs4973768 for premenopausal women with an AUC of 0.762 Table , and BMITo identify important risk predictors, we created risk prediction models for ER-positive, HER2-negative breast cancer in Japanese women. In this study, all of the patients were newly diagnosed since 2011, and control women were recruited in 2015. Because both patients and controls who participated in this study were recently diagnosed or recruited, this study is able to reflect the recent notable increase of incidence of ER-positive breast cancer in Japanese women. Moreover, the quality of this study has been much improved compared with our previous study , becausehttp://www.mhlw.go.jp/english/database/db-hw/FY2010/live_births.html). The decline in the birthrate according to recent changes of lifestyle might be the main cause of the recent notable increase in the incidence of ER-positive breast cancer in Japanese women [A history of never breastfeeding, and a positive history of benign breast disease were identified as environmental risk factors for premenopausal women, while a history of never breastfeeding, higher BMI, and the presence of hyperlipidemia were environmental risk factors for postmenopausal women in our analysis. These environmental factors are established risk factors for breast cancer . A histose women .In addition to environmental predictors, we demonstrated that higher serum testosterone levels and lower serum 25-hydroxyvitamin D levels were observed in both pre- and postmenopausal breast cancer patients compared to those in controls, and these two factors are included in our best risk prediction model for postmenopausal women. We and others previously reported the association of serum testosterone levels with increased risk of ER-positive breast cancer , 18, 19.Two genetic variants, TOX3-rs3803662 and ESR1-rs2046210, are included in our best risk prediction models for both pre- and postmenopausal women, and 8q24-rs13281615 and SLC4A7-rs4973768 are included for premenopausal women only. Previous studies reported that rs3803662 were associated with ER-positive breast cancer risk , and thaThere are several limitations to this study. First, this is a case–control study, and therefore some self-reported lifestyle factors may have been uncertain. However, our study might reflect the recent marked increase in the incidence of ER-positive breast cancer, because all of the patients and controls who participated in this study were very recently diagnosed. Second, this study was non-age matched. Third, smoking and alcohol intake, which are considered as environmental risk factors, could not be analyzed, because of difficulties of evaluation and lack of reliability. Fourth, we recruited control women who visited Hokkaido Cancer Society for breast cancer screening. Because Hokkaido is located in the northern part of Japan, backgrounds and environmental factors might not be completely similar to those of the common population of Japanese women.In conclusion, we created risk prediction models for ER-positive, HER2-negative breast cancer for pre- and postmenopausal Japanese women to identify important risk predictors. Our results suggest that the decline in the birthrate might be the main cause of the recent notable increase in the incidence of ER-positive breast cancer in Japanese women. Inclusion of common genetic variants and serum hormone measurements as well as environmental factors might improve risk assessment models.The study population comprised 253 consecutive Japanese women  aged 40 years or older with ER-positive, HER2-negative breast cancer, both invasive and non-invasive cancers, which were newly diagnosed at Hokkaido University Hospital and Kumamoto University Hospital between January 2011 and December 2014, and 905 control Japanese women  who visited Hokkaido Cancer Society for breast cancer screening consecutively between January and October 2015 and confirmed to be without disease, giving a 1:3 case: control ratio in premenopausal women and a 1:4 case: control ratio in postmenopausal women. Women aged 80 years or older were excluded, because very old women rarely undergo a breast cancer screening. The protocol of this study was approved by the Institutional review committees and conformed to the guidelines of the 1996 Declaration of Helsinki. Family history of breast cancer was defined as positive if first and/or second-degree relatives had had breast cancer. Blood samples from patients were taken before treatment. ER status of the breast cancer tissues was assessed by immunohistochemistry, and tumors with ≥ 1% positive cells were considered positive. Patients with HER2-positive tumors were excluded from this study. Postmenopause was defined as the existence of amenorrhea for more than one year together with low serum levels of estradiol. Women with high levels of serum estradiol were considered premenopausal regardless of whether they had experienced amenorrhea for more than one year.g for 10 min at 15°C, and the separated sera were stored at −80°C. Concentrations of testosterone and 25-hydroxyvitamin D, which are recently-reported predictive factors and able to evaluate commonly, were measured by commercially available immunoassays. Serum testosterone levels were measured by electro-chemiluminescence immunoassay using Ecrusis Testosterone . Serum levels of 25-hydroxyvitamin D were measured by direct radioimmunoassay using 25-Hydroxyvitamin D 125I RIA Kit . The concentrations of the two factors were stratified using a cut-off for categorized evaluation; the median was used for testosterone, and a threshold of vitamin D deficiency (20 ng/mL) was used for 25-hydroxyvitamin D levels [Blood samples were centrifuged at 1300 D levels .Genomic DNA was extracted from the blood samples with a QIAamp DNA blood mini kit . Nine genetic variants reported as risk predictors for ER-positive breast cancer or found in Asian women were analyzed: TOX3-rs3803662 , 26, 29,t-test, and categorical variables were analyzed by the Chi-squared test. Odds ratios with 95% confidence intervals were calculated to assess the strength of influence of each SNP on breast cancer risk using logistic regression models after adjustment for age. A co-dominant model, a dominant model, and a recessive model of risk alleles were established, and the SNPs showing a significant association with risk were selected in multivariate analyses. Allele frequencies of all the nine SNPs in controls were verified to be in line with Hardy–Weinberg equilibrium by the Chi-squared test. Multivariate binary logistic regression analyses were performed for environmental factors only, environmental factors and endogenous factors, and all factors including SNPs. ROC curves were generated with the AUC for the three models to evaluate the models with different variables. Finally, the best model with an ROC curve calculated by the essential factors was generated using the backward stepwise selection method. All statistical analyses were carried out using IBM SPSS Statistics 22.0 . P values of < 0.05 were considered statistically significant.Differences in continuous variables between patients and controls were evaluated by Student’s