N = 207) and risk of breast cancer among predominantly premenopausal women of the Nurses’ Health Study II using conditional logistic regression  and multivariable analyses evaluating all metabolites jointly. Eleven metabolites were associated with breast cancer risk . Seven metabolites remained associated after adjustment for established risk factors  and were selected by at least one multivariable modeling approach: higher levels of 2-aminohippuric acid, kynurenic acid, piperine , DMGV and phenylacetylglutamine were associated with lower breast cancer risk  = 0.84 (0.77–0.92)) while higher levels of creatine and C40:7 phosphatidylethanolamine (PE) plasmalogen were associated with increased breast cancer risk  = 1.11 (1.01–1.22)). Five amino acids and amino acid-related metabolites  were inversely associated, while one amino acid and a phospholipid  were positively associated with breast cancer risk among predominately premenopausal women, independent of established breast cancer risk factors.Known modifiable risk factors account for a small fraction of premenopausal breast cancers. We investigated associations between pre-diagnostic circulating amino acid and amino acid-related metabolites ( Known modifiable risk factors are estimated to account for only around one-third of postmenopausal breast cancers4, and an even smaller fraction of premenopausal cancers5. Thus, new strategies are needed for the identification of modifiable risk factors, especially for premenopausal breast cancers.Breast cancer is the most common malignancy among women in the United States, with more than 250,000 cases diagnosed each year6. In breast cancer, metabolomics has proven useful for tumor biology characterization, predicting treatment response, anticipating recurrence, and estimating prognosis7.Metabolites are small molecules that are produced and consumed by cellular metabolism. The study of the complete collection of metabolites, called metabolomics, provides a direct signature of cellular activity in the body and has emerged as a powerful tool for the diagnosis, characterization, and prediction of disease. Metabolomic methods have uncovered biomarkers for a wide variety of cancers including colorectal, gastric, pancreatic, liver, ovarian, breast, urinary, esophageal, and lung10, prostate12, liver13, colorectal14, ovarian16, endometrial17, and breast cancer22. For breast cancer, studies have used both targeted23 and untargeted22 methods to discover metabolomic risk factors associated with diet23, body mass index (BMI)21, microbiota metabolism20, lipid, amino acid, and other metabolic pathways22. While several studies stratified results by estrogen receptor (ER) status23, no prospective metabolomic breast cancer studies have investigated differential effects by menopausal status.More recently, prospective epidemiological studies have used metabolomics to identify metabolite risk factors for several cancers including pancreaticIn this study, we assessed the association of over 200 prospectively measured circulating amino acid and amino acid-related metabolites with risk of breast cancer among the predominantly premenopausal women (1057 cases and 1057 matched controls) of the Nurses’ Health Study II (NHSII).1057 cases and 1057 matched controls were included in this study ; 2-aminohippuric acid: 0.85 (0.77–0.93); C40:7 PE: plasmalogen: 1.11 (1.01–1.22); asparagine: 1.10 (1.00–1.22)) and when we restricted to premenopausal women . Significant interactions with BMI were observed for several additional metabolites that were not significant overall; for example C36:4 DAG/TAG fragment (high BMI: OR (95% CI) = 0.92 (0.80–1.06); normal BMI: OR (95% CI) = 1.21 (1.06–1.37); p-interaction = 0.005), serine (high BMI: OR (95% CI) = 1.19 (1.04–1.38); normal BMI: OR (95% CI) = 0.93 (0.83–1.05); p-interaction = 0.008), and proline betaine (high BMI: OR (95% CI) = 0.82 (0.72–0.94); normal BMI: OR (95% CI) = 1.04 (0.92–1.17); p-interaction = 0.017).Among the 11 selected metabolites, only DMGV showed effect modification by BMI with stronger associations among women with high BMI  = 0.82 (0.70–0.97); normal BMI: OR (95% CI) = 0.94 (0.83–1.06); p-heterogeneity = 0.03). Three additional metabolites were suggestively different by ER status: betaine (ER− tumors: OR (95% CI) = 0.89 (0.73–1.09); ER+ tumors: OR (95% CI) = 1.07 (0.96–1.20); p-heterogeneity = 0.02), 4-acetamidobutanate (ER− tumors: OR (95% CI) = 0.89 (0.72–1.09); ER+ tumors: OR (95% CI) = 0.97 (0.87–1.08); p-heterogeneity = 0.03), and histidine (ER− tumors: OR (95% CI) = 1.06 (0.87–1.29); ER+ tumors: OR (95% CI) = 1.01 (0.91–1.13); p-heterogeneity = 0.05).Of the 11 selected metabolites, we only observed stronger associations with risk of ER- tumors in the adjusted model , metoprolol  was nominally significantly associated with risk of breast cancer . Women with detectable metoprolol levels had a 23% higher risk  of breast cancer compared to women with undetectable metoprolol. However, among women with measured metoprolol, higher levels were associated with lower risk . The remaining metabolites with high missingness were not associated with risk of breast cancer.In an exploratory analysis including metabolites with >10% missing values  in all three simple (without adjustment for risk factors) multivariable models, Lasso, Elastic Net, and Random Forests . These associations remained significant after further adjustment for risk factors  with the exception of N2,N2-dimethylguanosine in Random Forests (p = 0.05) and piperine in Elastic Net .The inverse association of piperine with risk of breast cancer met the threshold for statistical significance  within NHSII, a cohort of predominantly premenopausal women. Higher levels of six metabolites, 2-aminohippuric acid, DMGV, kynurenic acid, N2, N2-dimethylguanosine, phenylacetyl glutamine, and piperine, were associated with lower breast cancer risk while higher levels of asparagine, creatine, and three lipids, C20:1 LPC, C34:3 PC plasmalogen, C40:7 PE plasmalogen, were associated with increased breast cancer risk. Inverse associations between 2-aminohippuric acid, DMGV, kynurenic acid, phenylacetyl glutamine and piperine, and the positive associations with creatine and C40:7 PE plasmalogen remained statistically significant after adjusting for established risk factors and were selected by at least one multivariable modeling approach . Notably, associations between 2-aminohippuric acid, piperine, and kynurenic acid remained significant even after multiple testing correction. None of the metabolites showed effect modification by BMI, except DMGV. None of the metabolites showed heterogeneity by ER status, except asparagine.26. Piperine also inhibits tumorigenesis, tumor angiogenesis, cancer cell proliferation, cancer cell migration and invasion, and enhances apoptosis and autophagy27. Experimental and cell line studies identified anti-breast cancer specific mechanisms of action, including decreased matrix metalloproteinase 9 (MMP-9) and MMP-13 expression, induced apoptosis through activation of caspase-3 and inhibition of human epidermal growth factor receptor 2 (HER2) gene expression28. Synergetic effects of piperine and chemotherapy drugs , hormone therapy drugs (tamoxifen), radiotherapy, TRAIL-based and nano-delivery-based therapy drugs  were observed28. Notably, piperine inhibited growth and motility29, and enhanced efficacy of TRAIL-based therapy30 in triple-negative breast cancer cells, the most aggressive breast cancer subtype. In a previous study of the associations of diet-related metabolites and breast cancer risk within the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer screening trial , piperine was found to be modestly correlated with liquor consumption (correlation = 0.16) and similar to our study, inversely associated with breast cancer risk ), after adjusting for BMI and other potential confounders23. Similarly, piperine was associated with lower risk of breast cancer (OR per 1 SD increase = 0.94 (0.89–0.99), p = 0.01) in the SU.VI.MAX cohort 20. Notably, PLCO women were postmenopausal while the SU.VI.MAX cohort included premenopausal and postmenopausal women at the time of blood collection suggesting that the association between piperine and breast cancer may be independent of menopausal status.Piperine is a polyphenol responsible for the pungency of black and long pepper and exhibits a wide range of properties: anti-diabetic, anti-inflammatory, immunomodulatory, reduction of insulin resistance, and enhanced drug bioavailability32. Plasma DMGV is positively associated with incident coronary artery disease, cardiovascular mortality, nonalcoholic fatty acid liver disease, and type II diabetes34. Circulating DMGV is directly correlated with resistance to the metabolic benefits of exercise35. Consumption of vegetables and red wine are associated with lower circulating DMGV, while sugar-sweetened beverage consumption is associated with higher circulating DMGV36. DMGV was associated with lower breast cancer risk in our study. The association between DMGV and breast cancer risk has not been previously assessed in prospective cohort studies. However, this metabolite was correlated with liver fat in the offspring cohort of the Framingham Heart Study 33. In addition, in the same study, baseline DMGV levels were associated with higher risk of type 2 diabetes, with replication of this association in the Malmo Diet and Cancer study and the Jackson Heart Study33. Large prospective studies are required to validate the association between DMGV and breast cancer risk. If replicated, experimental studies will be needed to understand the complex relationship between DMGV, diet, physical activity, CVD, type II diabetes, and breast cancer. Of note is that this analysis was in predominantly premenopausal women, among whom adiposity is also inversely associated with risk of breast cancer for reasons that are still not fully understood37.Dimethylguanadino valeric acid (DMGV), an organic keto acid, is the product of transamination of asymmetric dimethylarginine (ADMA), which inhibits nitric oxide signaling that is crucial to endothelial function—excess ADMA is associated with increased risk of cardiovascular disease38) that constitute 15–20% of all phospholipids in cell membranes39. Plasmalogens have head groups that are usually either phosphatidylcholine  or ethanolamine , and are characterized by an ether bond to an alkenyl group in the sn-1 position while the sn-2 position is usually occupied by polyunsaturated fatty acids39. Certain cancers exhibit altered plasmalogen levels: circulating plasmalogens are depressed in pancreatic cancer patients40 and increased in gastric carcinoma patients41 compared to healthy controls. Our study identified two plasmalogens, C34:3 PC plasmalogen and C40:7 PE plasmalogen, associated with increased risk of breast cancer. The fatty acid component of specific lipids may also reflect dietary or metabolic processes; notably C40:7 PE plasmalogen is highly unsaturated but the position of the double bonds cannot be determined in this metabolomics assay. Among 74 women with breast cancer, the levels of the majority of measured phospholipids  were higher in tumor tissue when compared to normal breast tissue samples38. Similar trends were observed in another study comparing tumor to normal tissue in 257 participants with breast cancer, and these lipids were correlated with cancer progression and patient survival42. Contrary to our findings, in the European Prospective Investigation into Cancer (EPIC) cohort, PC plasmalogens, including C34:3 PC plasmalogen, were inversely associated with risk of breast cancer19. However, neither study stratified their results by menopausal status, thus making a direct comparison difficult. Additional studies are needed to evaluate how plasmalogens are associated with risk of breast cancer and if this relationship is modulated by menopausal status.Although the measurement platform used here was optimized to measure amino acids and related metabolites, not lipids, our analysis included a small number of lipids and identified a few significant associations. Plasmalogens are a subclass of phospholipids . High levels of glutamine were associated with increased risk  and this association persisted among the subgroup of premenopausal women (p for interaction = 0.003)52. Notably, elevated expression of asparagine synthetase correlates with lung metastasis in breast cancer patients53. Furthermore, in vitro breast cancer studies show asparagine bioavailability promotes invasion and metastasis and that this effect is prevented by limiting asparagine bioavailability53. In a nested case-control study within the EPIC cohort (n = 1624 cases), asparagine was inversely associated with breast cancer risk , in contrast to the direction of association in our study18. However, the EPIC study participants were overwhelmingly (> 70%) postmenopausal at the time of blood collection, in contrast to our population with 80% premenopausal women. Differences in the menopausal status may partially explain the observed opposite directions of association between asparagine and breast cancer risk.Our study identified three amino acid derivatives associated with breast cancer risk. High levels of phenylacetylglutamine were associated with decreased breast cancer risk while high levels of asparagine and creatine were associated with increased risk. Phenylacetylglutamine is formed from phenylacetate and glutamine and is found as a normal constituent of human urine54 and have significantly lower muscular creatine levels than meat eaters55. Creatine is broken down to creatinine in a first-order reaction, the rate of which decreases with age and decreased muscle mass56. Creatine/creatinine metabolism plays an important role in energy metabolism in skeletal muscle tissue, and thus disturbances in this pathway are associated with many muscle diseases, whether as a cause or consequence57. To the best of our knowledge, no previous work has reported a link between creatine and breast cancer risk. However, the association we observed in this analysis is consistent with the positive association between red meat and risk of breast cancer among premenopausal women in the NHSII cohort58.Creatine is obtained from meat consumption and synthesized endogenously from arginine, glycine, and methionine. Most creatine is found in skeletal muscle, and a significant amount is also found in the brain. Omnivores obtain roughly 50% of their daily creatine from meat and 50% is biosynthesized, while vegetarians biosynthesize most of their creatine59, but little is known about its biological function. Both kynurenic acid and 2-aminohippuric acid are part of the kynurenine branch of the tryptophan pathway, an essential amino acid and a precursor to many biologically active metabolites61. Studies of the function of kynurenic acid suggest pleiotropic roles in disease. On the one hand, kynurenic acid has been shown to have anti-inflammatory and anti-ulcerative properties in animal models, as well as antioxidative properties in vitro in human cells62. On the other hand, circulating kynurenic acid was associated with increased risk of insulin resistance63. Kynurenic acid acts as both an anti-inflammatory and immunosuppressive factor which in turn allows tumor proliferation64. Tryptophan metabolism plays an important role in tumor progression and malignancy with several cancers expressing tryptophan-degrading enzymes such as IDO166. However, the direct role of kynurenic acid remains unclear, with both proliferative and antiproliferative effects on human glioblastoma cells, an antiproliferative effect on human colon adenocarcinoma cells, and decreased DNA synthesis and inhibited migration in both cell types62. Neither kynurenic acid nor 2-aminohippuric acid have been previously associated with breast cancer risk.Kynurenic acid and 2-aminohippuric acid are benzenoids inversely associated with breast cancer risk in our study. 2-amminohippuric acid is a glycine conjugate of anthranilic acid and can be synthesized in the liver67, solid tumors68, incident type II diabetes69, and all-cause mortality70. Elevated levels of N2,N2-dimethylguanosine were found in patients with acute leukemia and breast cancer71. Elevated circulating levels of this metabolite are associated with lower risk of breast cancer in our study.N2,N2-dimethylguanosine (DMGU) is a purine nucleoside and a primary degradation product of transport RNA. Elevated circulating DMGU levels may indicate cellular stress and is associated with several diseases, including pulmonary arterial hypertension34 but both metabolites are inversely associated with risk. The Mediterranean diet was positively associated with C40:7 PE plasmalogen72 though this metabolite was positively associated with risk. Further, physical activity is inversely associated with creatine and positively associated with asparagine73 though we observed positive associations with breast cancer risk for both metabolites. This work supports the fact that these metabolites are potentially modifiable, however the complex relationships with breast cancer risk preclude clear recommendations and more investigation is required.Importantly, there are several studies suggesting lifestyle and dietary changes may impact circulating levels of the here identified metabolites; however, the relationships are complex and warrant further study. For example, vegetables intake was positively associated with piperine (manuscript in preparation) and inversely associated with DMGV74 . Our cohort consisted of registered nurses, a group that are not representative of the general population , however there is no evidence suggesting that breast carcinogenesis is different in this group of women. Additionally, our cohort also included predominantly Caucasian women. However, while the prevalence of risk factors often differs across population subgroups, many breast cancer risk factors have been documented to operate similarly across ethnic groups, as would be expected from a common underlying biology88. Nonetheless, it is crucial that future studies conduct similar analyses in racially and ethnically diverse cohorts. While we had reasonable power in most of our analyses, we had limited power among ER negative tumors. Lastly, the uniqueness of our data measured among predominantly premenopausal women make replication studies challenging. We conducted this analysis in a hypothesis generating framework and hope that other cohorts will follow and analyze metabolomics data stratifying by menopausal status.Our study has several strengths and limitations. Notably, we conducted a prospective analysis of amino acid and amino acid-related metabolomics and risk of breast cancer among a large number of predominantly premenopausal women. We had detailed information on sample collection characteristics and risk factors, which we included in our statistical approaches. Although metabolomics was measured at only one point in time, the identified metabolites are reasonably stable over timeIn summary, we identified eleven metabolites associated with risk of breast cancer among premenopausal women. Seven metabolites remained associated after adjustment for established risk factors and were selected by at least one multivariable modeling approach: higher levels of 2-aminohippuric acid, kynurenic acid, piperine, DMGV and phenylacetylglutamine were associated with lower breast cancer risk while higher levels of creatine and C40:7 PE plasmalogen were associated with increased breast cancer risk. Additional prospective cohort studies are needed to assess these associations considering menopausal status. If these findings are validated, experimental studies are warranted to understand the underlying biological mechanisms driving changes in metabolite levels.In 1989, 116,429 female registered nurses aged 25–42 y returned a mailed questionnaire and were enrolled in the NHSII. Participants have been followed biennially since 1989 with questionnaires collecting information on reproductive history, lifestyle factors, diet, medication use, and new disease diagnoses.89. Of these, 18,521 women who had not used oral contraceptives, been pregnant or breastfed in the previous 6 months provided samples timed within the menstrual cycle, targeting the early follicular (days 3–5 of the cycle) and mid-luteal (7–9 days prior to expected start of next cycle) phases. The remaining women donated a single untimed sample. Follicular plasma was separated and frozen by the participants and returned with the luteal sample; samples were collected and shipped overnight to our laboratory where we processed and archived aliquots of white blood cell, red blood cell, and plasma in liquid nitrogen freezers (≤−130 °C). Follow-up in the blood subcohort is high (96% in 2011).In 1996–1999, 29,611 NHSII participants aged 32–54 y contributed blood samples, as previously describedThe study protocol was approved by the institutional review boards of the Brigham and Women’s Hospital and Harvard T.H. Chan School of Public Health, and those of participating registries as required. The return of the self-administered questionnaire and blood sample was considered to imply consent.n = 780) were diagnosed between 1999 and 2011. Breast cancer cases were reported by the participant, which were confirmed by medical record reviews (n = 1015) or verbally by the nurse (n = 42). Given the high confirmation rate by medical record for breast cancer in this cohort (99%), all cases are included in this analysis.Cases of breast cancer were identified after blood collection among women who had no reported cancer (other than nonmelanoma skin). Thousand and fifty-seven cases (invasive cases One control was matched per case by the following factors: age (+/− 2 y), menopausal status and postmenopausal hormone therapy (HT) use at blood collection and diagnosis , and month (+/− 1 month), time of day (+/− 2 h), fasting status at blood collection , race/ethnicity  and luteal day .90, immunohistochemical results for ER and PR, read manually by a study pathologist, were included for cases with available tumor tissue included in tissue microarrays.Data on breast cancer risk factors, including anthropometric measures, reproductive history, and lifestyle factors, were collected from questionnaires administered biennially and at the time of blood collections. Case characteristics, including invasive vs. in situ, histologic grade, estrogen and progesterone receptor , were extracted from pathology reports. As previously described92. Pooled plasma reference samples were included every 20 samples and results were standardized using the ratio of the value of the sample to the value of the nearest pooled reference multiplied by the median of all reference values for the metabolite. Samples were run together, with matched case-control pairs (as sets) distributed randomly within the batch, and the order of the case and controls within each pair randomly assigned. Therefore, the case and its control were always directly adjacent to each other in the analytic run, thereby limiting variability in platform performance across matched case–control pairs. In addition, 238 quality control (QC) samples, to which the laboratory was blinded, were also profiled. These were randomly distributed among the participants’ samples.Plasma metabolites were profiled at the Broad Institute of MIT and Harvard  using a liquid chromatography tandem mass spectrometry (LC-MS) method designed to measure polar metabolites such as amino acids, amino acids derivatives, dipeptides, and other cationic metabolites as described previouslyg, 4 °C), and the supernatants were injected directly onto a 150 × 2 mm, 3 µm Atlantis HILIC column . The column was eluted isocratically at a flow rate of 250 µL/min with 5% mobile phase A (10 mM ammonium formate and 0.1% formic acid in water) for 0.5 min followed by a linear gradient to 40% mobile phase B (acetonitrile with 0.1% formic acid) over 10 min. MS analyses were carried out using electrospray ionization in the positive ion mode using full scan analysis over 70–800 m/z at 70,000 resolution and 3 Hz data acquisition rate. Other MS settings were: sheath gas 40, sweep gas 2, spray voltage 3.5 kV, capillary temperature 350 °C, S-lens RF 40, heater temperature 300 °C, microscans 1, automatic gain control target 1e6, and maximum ion time 250 ms. Metabolite identities were confirmed using authentic reference standards or reference samples.Hydrophilic interaction liquid chromatography (HILIC) analyses of water soluble metabolites in the positive ionization mode were conducted using an LC-MS system comprised of a Shimadzu Nexera X2 U-HPLC  coupled to a Q Exactive mass spectrometer . Metabolites were extracted from plasma (10 µL) using 90 µL of acetonitrile/methanol/formic acid (74.9:24.9:0.2 v/v/v) containing stable isotope-labeled internal standards . The samples were centrifuged . All metabolites (N = 226) included here exhibited good reproducibility within person over 1-2 years74. Two hundred and six metabolites had no missing values among participant samples. One metabolite had <10% missing values and 19 metabolites had ≥10% missing values. Most of the metabolites (N = 191) had a coefficient of variation (CV) < 25% and an intraclass correlation coefficient (ICC) > 0.4 among blinded QC samples. Twenty-five metabolites had CV ≥ 25%, five had ICCs ≤ 0.4, and five metabolites had CV ≥ 25% and ICC ≤ 0.4.In total, 259 known metabolites were measured in this study. Metabolites not passing our previously conducted processing delay pilot studyN = 1). Metabolites with >10% missing values (N = 19) were excluded from the main analysis and evaluated in an exploratory analysis. Association of metabolite levels with breast cancer risk was assessed in metabolite-by-metabolite models and in multivariable analyses that included all metabolites simultaneously.Metabolite levels were natural logarithm transformed and standardized prior to statistical analysis. Missing values were imputed by one half the lowest observed value per metabolite, for metabolites with <10% missing values . In a simple model, each metabolite was included without adjustment for other factors. In an adjusted model, the following additional factors were included: BMI at age 18, weight change from age 18 to time of blood draw, age at menarche, parity and age at first birth, family history of breast cancer, diagnosis of benign breast disease, physical activity, alcohol consumption, exogenous hormone use and breastfeeding history. Odds ratios (OR) and 95% confidence intervals (95% CI) were estimated for a one-unit (one standard deviation) increase in the log-transformed and standardized metabolites levels.2 [635 cases and 578 controls]; ≥25 kg/m2 [422 cases and 479 controls]) and ER status . In a sensitivity analysis, we observed similar results between conditional logistic regression and unconditional logistic regression adjusting for the matching factors. Thus, stratified analyses were conducted using unconditional logistic regression, additionally adjusting for the matching factors. To test for effect modifications by BMI and heterogeneity by ER status, we included cross-product terms of the metabolite with potential effect modifier in conditional logistic models and report the p-value for that interaction. As ER status represents a case characteristic, we assigned each control the ER status of its matched case.We performed analyses restricting to premenopausal women at blood collection (838 cases and 838 controls), and analyses stratified by BMI  to estimate the significance level of the association.p-value for each metabolite was obtained from a permutation test in which the case/control labels were permuted within each matched stratum. A p-value for each metabolite was calculated as the proportion of permutations (out of 250) in which the magnitude of the coefficient under label permutation was at least as large as the regression coefficient in the observed dataset. Analyses were carried out using the R library clogitL193.Multivariable analyses evaluating the joint association of the 207 metabolites with breast cancer risk were based on (1) conditional logistic regression with lasso penalty (“Lasso”), (2) conditional logistic regression with an elastic net penalty (“Elastic Net”), and (3) random forests. In the Lasso and Elastic Net analyses, a minimally adjusted model included only the set of 207 metabolites, whereas a fully adjusted model further adjusted for the risk factors noted above. In each analysis, the optimal values of the regularization parameter(s) were estimated as that which minimizes the average deviance in the left-out partitions, in a 10-fold cross validation procedure. A mtry corresponding to the number of variables randomly sampled as candidates at each split was set to the square root of the total number of covariates in the model. Each classifier was an aggregate of 5000 trees. A p-value for each metabolite was obtained from a permutation test as described above in which the case/control labels were randomly permuted 100 times. Analyses were carried out using the R library random forests94.Random forests analyses included a minimally adjusted model that included the 207 metabolites and matching factors. A fully adjusted model also included the additional risk factors noted above. In all analyses, the parameter q-value procedure95. Metabolites that satisfied a p-value less than 0.05 and corresponding q-value less than 0.20 in the minimally adjusted model were discussed as primary findings.To adjust for multiple testing in the conditional logistic regression and the multivariable models we estimated the positive FDR based on the p-value < 0.05 and q-value < 0.20 in at least one of the four models  with minimal adjustment were considered as statistically significant. An exception was made for metabolites that did not meet a p-value threshold < 0.05 in the conditional logistic regression: four metabolites that met the threshold for statistical significance in Lasso only but had high raw p-values (>0.3) in the conditional logistic regression were excluded .Criterion for statistical significance: metabolites that met a A metabolite score was estimated for each participant as a linear combination of all metabolites that met the threshold for statistical significance. The coefficients associated with each metabolite were estimated in a conditional logistic regression model with the Lasso penalty that included all metabolites simultaneously and with full adjustment for all potential confounders.96 version 3.6.3 and SAS version 9.4. All statistical tests were two-sided.Analyses were caried out using RFurther information on research design is available in the Supplementary InformationReporting Summary


Racial disparities in breast cancer present a vexing and complex challenge for public health. A diverse array of factors contributes to disparities in breast cancer incidence and outcomes, and, thus far, efforts to improve racial equity have yielded mixed results. Systems theory offers a model that is well-suited to addressing complex issues. In particular, the concept of a systemic leverage point offers a clue that may assist researchers, policymakers, and interventionists in formulating innovative and comprehensive approaches to eliminating racial disparities in breast cancer. Naming systemic racism as a fundamental cause of disparities, we use systems theory to identify residential segregation as a key leverage point and a driver of racial inequities across the social, economic, and environmental determinants of health. We call on researchers, policymakers, and interventionists to use a systems-informed, community-based participatory approach, aimed at harnessing the power of place, to engage directly with community stakeholders in coordinating efforts to prevent breast cancer, and work toward eliminating disparities in communities of color. This approach differs from traditional intervention paradigms, which seek to isolate factors in a linear causal chain resulting in a single health outcome, in that it works from the assumptions that multiple interrelated causes can exert a multiplicative influence over and above the sum of their effects, that numerous outcomes are likely to trace back to the same interrelated set of causes, and that disruptions in one subsystem will likely not change outcomes. Focus is therefore shifted from finding a single cause to finding those subsystems, or nodes in the network of related causes, that mediate the relationships between numerous other subsystems and the outcome(s) of interest. Those component subsystems that are necessary for the maintenance of systemic equilibrium can be understood as leverage points [There are significant racial disparities in breast cancer incidence, care, and outcomes, with Black women experiencing higher incidence of aggressive breast cancer subtypes, lower quality of care, and higher mortality rates than white women ,2,3. Thee points .With respect to health disparities generally, and breast cancer disparities specifically, residential racial segregation is one such leverage point. It has historically produced inequities in access to opportunities and resources . Place oWe begin with an overview of Black/white racial breast cancer disparities, followed by a brief outline of the state of the scientific literature on individual risk factors for, and protective factors against, breast cancer, with particular focus on those risk and protective factors that disproportionately impact historically marginalized groups. We then discuss various potential mechanisms by which racial discrimination may exert a causal influence on breast cancer disparities by conditioning the population distribution of these risk and protective factors, with the caveat that these mechanisms are not yet well understood. In order to re-conceptualize this web of interrelated influences in a more actionable framework, we echo other scholars and scientists in identifying systemic racism as the underlying cause that links all of the interrelated mechanisms of disparity together. We use concepts from systems theory to demonstrate that residential segregation is a key leverage point in the racial discrimination system. We then put forth a systems-oriented, community-engaged approach to breast cancer prevention and disparities research and outline opportunities for researchers, policymakers, and interventionists to harness the power of place by partnering directly with community stakeholders in coordinating breast cancer prevention efforts in under-resourced minority communities.While a detailed description of Black/white racial breast cancer disparities is beyond the scope of this paper, there is a large body of scientific data indicating that breast cancer and its consequences are differentially distributed by race. Because these differences adversely impact marginalized communities, and are related to injustice, they are called health disparities. In our usage, therefore, the term disparity should be taken to mean more than simply difference, but a difference which has its source in inequity or injustice. Racial breast cancer disparities can be understood as falling into three broad categories: disparities in incidence, disparities in care, and disparities in outcome. Historically, Black women have had lower rates of breast cancer than white women. However, recent literature indicates that breast cancer incidence is rising among Black women, and in 2012, overall breast cancer incidence for Black women reached levels equaling those of White women . In thatCompared with white women, Black women disproportionately experience longer waiting periods after abnormal screening, treatment delays, lower likelihood of receiving guideline-concordant cancer care , lower qreducing alcohol consumption, tobacco use, and chronic stress, as well as chemical, occupational, and ionizing radiation exposures, and promoting breastfeeding, healthy diet patterns, physical activity, and healthy vitamin D levels [Breast cancer disparities persist despite the development and implementation of numerous interventions seeking to eliminate them . There aD levels ,16,17. TAlcohol is a known risk factor for breast cancer, and there is a dose response relationship between the two, with higher consumption corresponding to greater breast cancer risk . Though The carcinogenic properties of tobacco smoke are well known. Though smoking is more strongly associated with cancers of the mouth, throat, and lungs, it is also a risk factor for breast cancer, particularly among women who started smoking at a young age or before carrying a pregnancy to term ,17. SmokEnvironmental pollutants and toxic exposures account for between 7% and 19% of the world’s cancer cases ,23. ExpoIonizing radiation is a risk factor for various cancers, including breast cancer, and a common mechanism of exposure is in medical imaging, such as CT scans and X-Rays . One areOccupational factors may relate with breast cancer incidence and outcomes through numerous possible mechanisms, including: “chemical exposure; stress, including around job security and fair wages, threats or acts of sexual and physical violence, and lack of power to advocate for oneself; challenges with time and accommodation for breastfeeding; light-at-night exposure; and many other issues”  (p. 204)Though the biological mechanisms linking breast cancer and diet are not well understood, the extant literature indicates that diet can function both as a risk factor and as a protective factor for breast cancer. Though some conflicting findings complicate the picture, the bulk of relevant studies show a positive association between consumption of red and processed meat and breast cancer ,31,32. AOn the other hand, the preponderance of scientific evidence suggests that healthy eating habits, such as the Mediterranean diet, have a protective effect against breast cancer, and improve overall health . Due to A recent meta-analysis including 13,907 breast cancer cases from 27 studies on the relationship between breastfeeding and breast cancer found that there was an inverse association between the two, with longer breastfeeding duration related with lower relative risk compared with shorter duration  . At the Vigorous physical activity is another likely protective factor against breast cancer ,16. ThesThere is some evidence to suggest that vitamin D deficiency may be related to breast cancer disparities. In one study, low levels of vitamin D were associated with an elevated risk of breast cancer of 23% in Black women . Black wWilliams et al. note that though both racial discrimination and racial breast cancer disparities are well documented, the mechanisms that link discrimination to disparities are not well understood . There aAt the individual level, the positive association between low SES and disease does not generally hold for breast cancer, but striking patterns emerge when examining incidence, severity of breast cancer subtype, race/ethnicity, and SES together ,44,45. DFurther, there is a growing body of literature demonstrating the neurobiological impacts of stress and trauma in early life, including methylation of the nuclear receptor 3C1, “the gene that codes for the glucocorticoid receptor on the hypothalamic-pituitary-adrenal axis” ,29. One Place of residence impacts breast cancer risk significantly. In a recent systematic review of 17 studies focusing on racial residential segregation and cancer disparities, 70% of studies showed a statistically significant association between segregation and health disparities. The authors state: “residing in segregated African-American areas was associated with higher odds of later-stage diagnosis of breast and lung cancers, higher mortality rates and lower survival rates from breast and lung cancers, and higher cumulative cancer risks associated with exposure to ambient air toxins”   ,50,51,52as a system. In the following section, we will introduce key concepts from systems theory, and discuss ways in which they can be used as tools to reconceptualize racial breast cancer disparities in light of the system of racial discrimination within which they arise.There is increasing scholarly and scientific consensus that racism itself is a fundamental cause of health disparities. Yearby argues that the social determinants of health framework articulated in Healthy People 2020 is insufficient precisely because it does not give a primary place to racism as an upstream factor contributing to all other social determinants . WilliamEstablished systems exhibit the property of emergence. In a network of interrelated subsystems, the system as a whole will begin to exert an influence over and above the sum of the additive effects of those component subsystems. As Reskin explains, within the race discrimination system, this means that, in addition to the effects of individual experiences of discrimination and explicitly traceable instances of institutional racial bias, the system of racial discrimination itself exerts influence in maintaining the equilibrium of racial disparity . In otheEstablished systems exhibit the property of robustness. This means that systems tend toward a state of equilibrium, and that that state of equilibrium will generally persist even in the face of significant disruptions within individual subsystems. The emergent effects of the system as a whole will ensure that the equilibrium is reasserted. In the case of racial disparities, this may explain the resistance of disparities to targeted interventions . For exaIn systems theory, complexity is a formal designation which refers to a system in which there are a large number of component subsystems, and a large degree of interrelatedness between those component subsystems . In the In the context of complex systems, a full representation of all subsystems and all their interrelationships would yield a model insufficiently parsimonious for practical use. We propose that researchers, policymakers, and interventionists should conduct a critical review of the complex relationships between upstream causes of breast cancer and racial breast cancer disparities to identify systemic leverage points. Drawing on Reskin, we define leverage points as systemic nodes (or subsystems) where multiple other subsystems intersect, modifications in which have the potential to exert significantly amplified effects across the entire system . As longAs Williams et al. state, “Residential segregation has been identified as a leverage point or fundamental causal mechanism by which institutional racism creates and sustains racial economic inequities”  (p. 117)Given that residential segregation has facilitated the production of disparate health outcomes, “place” is of central importance in shaping health trajectories of individuals and communities. The relationship between place, race, and breast cancer is already the subject of attention from health scientists and interventionists. State level authorities and researchers are actively working to understand and address racism, social and environmental exposures, and inequities in community infrastructure, based on the understanding that each of these represent critical upstream factors that condition the distribution of an array of other risk factors for breast cancer ,56. In fThere are three major areas of research that could help further the work of harnessing the power of place to reduce racial disparities in breast cancer. First, research is needed that traces the full causal pathway between the environment  and breast cancer outcomes. Second, further research is needed in the design and implementation of community-based (or place-based) intervention frameworks to address the upstream factors that contribute to racial breast cancer disparities in residentially segregated communities. Third, research should be conducted to explore the relationships between racial discrimination and other forms of discrimination as they pertain to breast cancer disparities.Though a significant and growing body of literature traces the associations between numerous social, environmental, and biological factors and breast cancer incidence, the causal mechanisms that underlie the observed associations are often not well understood. For instance, though studies near uniformly show a positive association between breast density and breast cancer risk, the biological mechanism through which this association is operationalized is unknown . It is pThere is a need to better understand how social factors, such as explicit and implicit discrimination, SES, occupational exposures, and access to nutrition, interact with factors in the built environment, such as chemical and other environmental exposures, light at night, and accessibility of green space, to exert influence on human physiology in ways that elevate breast cancer risk . In turnAccording to Williams et al., “we lack the empirical evidence to identify which mechanisms of segregation  should be tackled first, would have the largest impact, and is most likely to trigger ripple effects to other pathways”  (p. 117)One possible area of research would therefore engage community stakeholders in the development of community-specific concept maps of key systemic interrelationships to identify leverage points, whereas another would pilot interventions informed by these maps to coordinate community efforts toward addressing those leverage points. When promising intervention frameworks are available, larger implementation studies should be carried out to determine the most effective strategies to ensure program adoption, fidelity, sustainment, and effectiveness . OverallThough the focus of this discussion has been on racial discrimination as a determinant of breast cancer disparities, a third area of needed research would explore the intersectional relationships between racial discrimination and other forms of discrimination. For example, gender discrimination has been shown to be negatively associated with mammography screening, and it is plausible that this reduction in screening may disproportionately impact Black women . TherefoEliminating racial breast cancer disparities will require significant community investment and coordinated efforts across multiple systems to prevent breast cancer in communities of color. The upstream causes of disparities are tied to place, and these efforts will need to be guided by community stakeholders to address community-specific concerns. In this paper, we provide a conceptual framework for one approach to harness the power of place to reduce breast cancer disparities. The potential applications of systems theory, and related leverage points, to breast cancer prevention are numerous. Traditional approaches tend to ignore these interrelationships in favor of linear models that are perceived to be more parsimonious and actionable. However, they often obfuscate the reality that emergent, systemic effects maintain the equilibrium of disparity, even in the face of significant investment in interventions targeting subsystems. Given that the various subsystems that make up the causal foundations of racial breast cancer disparities are spread across a diverse array of interrelated domains of practice and expertise, we argue that efforts to reduce these disparities should: (1) engage stakeholders across multiple sectors (subsystems), especially community members; (2) be informed by appropriate concept maps of the complex systems at play in the specific community; and (3) represent a coordinated effort across these sectors to address key leverage points at which multiple subsystems intersect.If we are to offset the negative effects of systemic racism to reduce and ultimately eliminate racial inequities in health broadly, and breast cancer specifically, there must be a greater focus on creating “communities of opportunity” . This teFinally, it should be noted that marginalized communities are not monolithic, and there is significant heterogeneity both between and among the various communities who experience health disparities. Taking a place-based, community-engaged approach to breast cancer prevention is therefore advantageous, given that it will allow for the development of research questions and intervention strategies that address the specific strengths and challenges of each community. Though much of the focus in this essay has been on racial breast cancer disparities between Black and white women, the methods outlined here have significant applicability in the task of eliminating disparities in Latinx, indigenous, and other racial/ethnic populations.


Mammography-based breast cancer screening has been widely implemented in many developed countries. Evidence was needed on participation and diagnostic performance of population-based breast cancer screening using ultrasound in China.We used data from the Cancer Screening Program in Urban China in Beijing from 2014 to 2019 and was followed up until July 2020 by matching with the Beijing Cancer Registry database. Eligible women between the ages of 45 and 69 years were recruited from six districts and assessed their risk of breast cancer through an established risk scoring system. Women evaluated to be at high risk of breast cancer were invited to undergo both ultrasound and mammography. Participation rates were calculated, and their associated factors were explored. In addition, the performance of five different breast cancer screening modalities was evaluated in this study.A total of 49,161 eligible women were recruited in this study. Among them, 15,550 women were assessed as high risk for breast cancer, and 7,500 women underwent ultrasound and/or mammography as recommended, with a participation rate of 48.2%. The sensitivity of mammography alone, ultrasound alone, combined of ultrasound and mammography, ultrasound for primary screening followed by mammography for triage, and mammography for preliminary screening followed by ultrasound for triage were19.2%, 38.5%, 50.0%, 46.2%, and 19.2%, and the specificity were 96.1%, 98.6%, 94.7%, 97.6%, 95.7%, respectively. The sensitivity of combined ultrasound and mammography, ultrasound for primary screening followed by mammography for triage, was significantly higher than mammography alone (p=0.008 and p=0.039). Additionally, ultrasound alone ) and ultrasound for primary screening followed by mammography for triage ) were the most cost-effective methods for breast cancer screening than other modalities.Ultrasound alone and ultrasound for primary screening and mammography are superior to mammography for breast cancer screening in high-risk Chinese women. Breast cancer has surpassed lung cancer as the most commonly diagnosed cancer worldwide, with an estimated 2.3 million new cases occurred in 2020 . In ChinSufficient randomized controlled trials (RCTs) have confirmed that mammography-based breast cancer screening can effectively reduce breast cancer mortality in women aged 50-69 –9. It isUltrasound is a potential method to improve breast cancer detection, especially in women with dense breast tissue and younger women. Some Western countries recommended ultrasound as the supplementary of mammography because ultrasound is non-invasive, non-radioactive, and more appropriate for smaller and denser breasts. Although some studies conducted in Japan and China have used ultrasound as the primary tool for breast cancer screening , 13, theIn 2012, the government of Beijing launched a registered organized population-based cancer screening program  to screen common cancers, including breast cancer. For the present study, we reported the breast cancer screening results in Beijing between 2014 and 2019. The purpose of this study was to evaluate the participation rate and diagnostic yield of ultrasound and mammography for screening breast cancer, as well as to explore a cost-effective breast cancer screening strategy for high-risk Chinese women.We performed a population-based prospective breast cancer screening program among female residents in Beijing from 2014 to 2019. This study was conducted under the framework of the Cancer Screening Program in Urban China (CanSPUC). In brief, asymptomatic females living in the designated communities of the six participating districts were approached by trained staff through personal encounters or phone calls. Social media and community advertisements were used to raise public awareness of this cancer screening program. Eligible women were aged 45-69 years without a history of any cancer and registered in Beijing for at least three years were enrolled in this study. After signing the written informed consent, all eligible women were interviewed one-on-one by a trained community healthcare personnel to collect their socio-demographic characteristics and potential breast cancer risk factors. Next, an established risk scoring system was used to evaluate their risk of developing breast cancer. After that, women identified as high-risk of breast cancer were invited to undergo free ultrasound and mammography examinations at the tertiary-level hospital designated by the program. One year later, all subjects were followed up passively by matching the Beijing Cancer Registry (BCR) database to obtain their health outcome information (whether they were diagnosed with breast cancer or not). The Ethics Committee of National Cancer Center/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College approved the study and written informed consent was obtained from all participants prior to implementation. A flowchart of the study is shown in All participants were invited to health facilities and completed a paper-based questionnaire to collect individual breast cancer exposure information. Then, health professionals used an online tool to measure the personal risk of breast cancer which was followed the Harvard Risk Index , but theWomen at high risk for breast cancer were invited to receive a clinical breast examination performed by physicians in the tertiary-level hospital, followed by successive ultrasound and mammography conducted by experienced radiologists with at least five years of experience. Any abnormal findings during the examination were carefully checked and were required to be photo-documented. In addition, clinical information such as morphology, breast density, the structure of the gland, tumor characteristics , and the characterizations of lesions was recorded. All images of ultrasound and mammography were stored and transferred to the research center for subsequent verification at the end of the annual project.According to the Breast Imaging Reporting and Data System (BI-RADS) classification system, images of either type of imaging investigation were interpreted and classified into the following five categories : 1, negaThis study had three documents, including a risk assessment questionnaire, ultrasound examination form, and mammography examination form, all of which were filled out by trained healthcare workers or physicians. Then, data entry clerks at each community were employed to input the data from the paper documents to the online data management system. After that, researchers downloaded all the original data, performed logical verification of the data quality, and performed further analysis.in situ (ICD-10: D05.0-D05.9) were extracted and analyzed from the whole cancer database.All participants with breast cancer risk assessment results were passively followed up by matching their identification number with the BCR database to obtain their health outcomes at one-year intervals from October 1, 2014, to July 31, 2020. BRC has high standards of data accuracy population-based cancer registry covering 13 million (nearly 100%) permanent residents in Beijing . BesidesThe cost per breast cancer detected was calculated by dividing the total cost of a screening program by the number of breast cancer detected. The program cost included consultation, physician exam, ultrasound and/or mammography exam, biopsy, and histopathology. In this study, we used the estimated cost of China’s ‘Two Cancer  Screening’ campaign, which was 5 RMB (Chinese Yuan) for consultation and physical exam, 70 RMB for ultrasound, 200 RMB for mammography, and 300 RMB for biopsy . We used the exchange rate of 6.40:1 to convert RMB to the US dollar.Z test. The above-mentioned statistical analyses were conducted with the use of SAS software, version 9.4 , and the statistical significance level was set at 0.05 for two-sided tests.This study took the individual woman as the unit of analysis. The socio-demographic characteristics of the participants were described by mean and standard deviations (SD) of continuous variables or proportion and percentages of categorical variables. The chi-square test was used to compare the difference in participation rates between each group. Univariate logistic regression was employed to analyze the association of potential factors with examination participation rates. The parameters that were found to be significant (p <0.01) by univariate analysis were incorporated and examined using multivariate analysis. Odds ratios (ORs) with corresponding 95% confidence intervals (95% CIs) were calculated and reported according to the Wald chi-square statistics. Diagnostic yield was calculated for both screening and non-screening groups, including the histologic type and stages of breast cancer. One-year follow-up results of the cancer registry were regarded as the ‘gold standard’ of breast cancer screening. Sensitivity and specificity were calculated and compared with McNemar’s test. The area under the curve (AUC) of the receiver operating characteristics (ROC) and their 95% CIs of different screening modalities were assessed and compared using the From October 2014 to July 2019, 49,161 eligible women were recruited from the designated communities in BCSPCS and completed the risk assessment questionnaire. After excluding 33,611 who were assessed as low risk of breast cancer, the remaining 15,550 women were identified as being at high risk of developing breast cancer and were invited to attend both ultrasound and mammography examination. The characteristic of the high-risk population and women who completed ultrasound and/or mammography were presented in Among the 15,550 women at high risk of breast cancer, 7,500 received ultrasound and/or mammography, and the participation rate was 48.2% in our study. Overall, women aged 50-64 years had a higher participation rate than other age groups. Besides, univariate analyses showed that women who were married, had a BMI higher than 18.5, currently or had smoked, postmenopausal, had a history of breastfeeding, benign breast diseases, and a family history of breast cancer had relatively higher participation rates compared to the other groups (p<0.05). We also calculated multivariate logistic regression models to explore the potential factors associated with participation rates, as shown in in situ (DCIS). Among the screening group, 14 cases (11 with invasive breast cancer and 3 with DCIS) were detected, with a detection rate of 46.7% (14/30) and an early diagnostic rate of 77.8% (7/9). However, 16 breast cancers (10 with invasive breast cancer and 6 with DCIS) were undetected in our study, of which 88.9% (8/9) were early cases, and the missed diagnosis rate was 53.3% (16/30). For 8,050 women who were at high risk of breast cancer but did not receive any examination, 17 breast cancers (13 with invasive breast cancer and 4 with DCIS) were diagnosed, 71.4% (5/7) were early-stage cases. Furthermore, among the 33,611 women with a low risk of breast cancer, 58 breast cancer were found, of which early cases accounted for 30.4% (7/23). More characteristics of detected and undetected breast cancer are summarized in A total of 105 breast cancer were identified by matching the BCR database, with overall incidence rates of 213.6/100,000 . The incidence rate of breast cancers was 172.6/100,000  in the low-risk group and 302.3/100,000  in the high-risk group, respectively. Of the 7,500 women who underwent the screening, 30 breast cancers were diagnosed, including 21 with invasive breast cancer and 9 with ductal carcinoma We compared the performance of five different breast cancer screening modalities in this study, including mammography alone (model 1), ultrasound alone (model 2), combined of ultrasound and mammography (model 3), ultrasound for primary screening followed by mammography for triage (model 4), and mammography for primary screening followed by ultrasound for triage (model 5). As shown in Regarding the cost of the screening, we found that the most cost-effective method for finding each breast cancer was ultrasound alone ) and ultrasound for primary screening followed by mammography for triage ), followed by combined of ultrasound and mammography ). The worst was mammography alone ) and mammography for primary screening followed by ultrasound for triage ).We reported the results of 49,161 women participating in breast cancer screening in urban areas of China. To the best of our knowledge, this is the first large-scale population-based prospective cohort study of breast cancer screening in high-risk women in China. We achieved the participation rates and the detection rates of breast cancer screening in different populations and reported five screening modalities’ diagnostic yield and cost-effectiveness. These results suggest that various screening schemes targeting specific people are needed and provide evidence support for improving the effectiveness of screening in the future.Despite sufficient scientific evidence to support that screening reduces breast cancer mortality, the participation rate of high-risk women in our study has remained lower (48.2%) than organized breast cancer screening programs conducted in other countries and regions (50%-80%) –20. In aOf the 7,550 women who underwent ultrasound or mammography examination, 14 breast cancers were detected, with a detection rate of 1.87/1,000. Another study conducted in urban China showed that women who received ultrasound and mammography screening had a breast cancer detection rate of 0.56/1,000 after one year of follow-up, which was much lower than the current study . It may Our study demonstrates that ultrasound performed better or at least not worse than mammography in real-world settings, with higher sensitivity and specificity in high-risk Chinese women, as has been consistently shown in previous studies , 22. HowCost-effectiveness is one of the key elements for large-scale population screening. As far as we know, in the United States and other Western countries, ultrasound is expensive and usually not covered by insurance for breast cancer screening , 33. HowNotably, our study found that the overall breast cancer detection rate was only slightly higher in the screening group than in the non-screening group. Given the relatively low participation rate in screening, some breast cancer cases were missed during the program, which substantially reduced the effectiveness of screening. To improve the diagnostic yield of breast cancer screening in China, the following issues should be further addressed. First, optimize the risk assessment score based on current research findings and proven risk prediction scores, and incorporate genetic testing into risk assessment models in available regions. Second, design novel breast cancer screening strategies suitable for women in different areas and at different risks of breast cancer. Third, carry out multifactor interventions targeting multiple levels of care to optimize breast cancer screening compliance.The findings in this study need to be considered in light of its limitations. Firstly, data quality depends largely on the experience of the radiologists and healthcare staff who interviewed the participant. Thus, the results of Beijing cannot be generalized to other regions in China. Secondly, we used a self-reported questionnaire to assess the risk factor of breast cancer, so some residents may provide untrue information about breast cancer for the sake of getting free examinations. Thirdly, we used the cancer registry data as the endpoint of this study. However, the cancer registration data had about half-years later than the diagnostic time at the hospital that would miss some patients. Moreover, although Beijing had a complete registration system, there were still a small number of patients that may be omitted. Therefore, the sensitivity of this study may be overestimated, and the specificity may be underestimated. Fourthly, the current registration system does not require reporting of cancer stage, so there may be errors in the staging in this study. Last but not least, this study was a real-world screening program rather than well-designed scientific research; therefore, we did not collect the data on recall rates, the number of pathological examinations, and the number of benign cases. In addition, the small sample size of this study also resulted in limited applicability and worth of the findings.In conclusion, ultrasound alone or ultrasound for primary screening and mammography for triage offers a sensitive and cost-effective way for breast cancer screening in high-risk Chinese women. Long-term follow-up is needed to assess whether these approaches could reduce advanced breast cancer and breast cancer mortality in the future.The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding authors.The studies involving human participants were reviewed and approved by National Cancer Center/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College. The patients/participants provided their written informed consent to participate in this study.JJ, NW, and LY developed the protocol for the study. HL, QL, and YC executed and coordinated this study. XZ performed the statistical analyses and drafted the manuscript. SL participated in the data collection and revised the manuscript. All authors read and approved the final version of the manuscript.This study was funded by Beijing excellent talents training project (No. 2016000021469G189). The funder did not participate in any part of the study from study design to approval of the manuscript, except for supporting this project.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Like many other women in the developing world, the practice of breast cancer screening among Ghanaian women is unsatisfactory. As a result, many cases are diagnosed at advanced stages leading to poor outcomes including mortalities. An understanding of the awareness and predictors of breast examination is an important first step that may guide the design of interventions aimed at raising awareness across the general population. This study aimed to explore the awareness, risk factors, and self-reported screening practices of breast cancer among female undergraduate students at the University of Health and Allied Sciences.This cross-sectional study was conducted among 385 female undergraduate students using a pre-tested questionnaire. Data were analysed using Stata Version 13.1 and presented using descriptive and inferential statistics comprising frequency, percentage, chi-square, and binary logistic regression. Odds ratios and 95% confidence intervals were computed to quantify the association between regular Breast-Self Examination (BSE) and socio-demographic characteristics of respondents.Seventy-three per cent of the students were aware of breast cancer, with social media being the most important source of information (64.4%). The prevalence of breast cancer risk factors varied from 1% of having a personal history of breast cancer to 14.3% for positive family history of breast cancer. Current use of oral pills/injectable contraceptives was confirmed by 13.2% of participants; 20% were current alcohol users and10.1% were physically inactive. Regarding breast examination, 42.6% performed BSE; 10.1% had Clinical Breast Examination (CBE), while 2.3% had undergone mammography in the three years preceding the study. Women who did not believe to be susceptible to breast cancer  and those who did not know their risk status  were less likely to perform regular BSE compared to those who displayed pessimism. Further, women with no religious affiliation had 0.11 (95%CI: 0.02–0.55) odds of examining their breast regularly compared to Christians.This study demonstrated moderate awareness of the modalities of breast cancer screening and the risk factors of breast cancer among the students. However, there exists a gap between awareness and practice of breast cancer screening, which was influenced by optimism in breast cancer risk perception and religion. Awareness campaigns and education should be intensified in the University to bridge this gap. Breast cancer is the most prevalent cancer in women and generally the second most common cancer globally, with approximately 1.4 million cases diagnosed annually , 3. GeneIn Ghana, breast cancer is becoming a great public health challenge among women. With about 2,900 incident cases occurring annually, and one-eighth of them dying from it, the disease has become the most common cancer-related death among Ghanaian women , 6. PrevIt is anticipated that the incidence of breast cancer will increase as Ghana’s population ages and women adopt western lifestyles . StudiesLike most cancers, the primary risk factor for breast cancer in women is older age. Many other risk factors alter the exposure of breast tissues to reproductive hormones . Some ofEarly diagnosis of breast cancer can increase the chance of early case detection and favourable outcomes, resulting in improved survival rates and quality of life of women and is therefore important public health strategy at all settings . HoweverNotwithstanding that mammography is known to be the most effective screening tool for early detection of breast cancer , Breast-Women who practice regular breast screening have been known to have a lower risk of developing an advanced form of breast cancer than those who do not. Reports have shown low uptake of breast cancer screening among women in many sub-Saharan African countries and this results in late detection and increased mortality in affected women .Even though the incidence and mortality of breast cancer have been on the increase, there is a paucity of the empirical literature on student’s awareness, risk factors and screening practices in Ghana. This population is especially important because they have abundant access to health information as health students and they are potential sources of information for non-health students and the general population. College students have a significant influence on colleague students and also, findings regarding this target group have implications for their capacity in the role of promoting screening for breast cancer as potential health professionals. This study, therefore, explored breast cancer awareness, selected risk factors, and screening practices among female undergraduate students, to provide information for the control, prevention, and early treatment of the disease.We conducted a cross-sectional study among female undergraduate students at the University of Health and Allied Sciences (UHAS), Ghana in February 2019. Ghana has a projected population of 30,280,482 in 275 districts distributed among 16 administrative regions as of June 2019 and is divided into some 75 ethnic groups with the Akans forming the majority. UHAS is among the newest public Universities in Ghana which was established in 2011 and is located at Ho in the Volta Region. UHAS is so far the only public University solely dedicated to the training of varied health professionals such as medical doctors, nurses, midwives, pharmacists, public health professionals etc. in Ghana. The University has two main campuses; the main campus, which is located at Ho (where this study was carried out), and the Hohoe campus, which has the School of Public Health. There are currently six schools/colleges in the University, with a current student population of about 3,752. Among the programmes offered by the University are Medicine, Physician Assistantship, Nursing, Midwifery, Physiotherapy, Pharmacy, Dietetics, Speech and Language Therapy, and Public Health [2 pq/d2, where n = sample size, z = z-score at 95% confidence level, p = estimated proportion of an attribute that is present in the population, q = 1-p, d = margin of error. This study assumed a margin of error(d) of 0.05 at 95% confidence level and an estimated proportion of 60.9% women with regular breast screening practice [We obtained the required sample size for this study using Cochran’s single proportion formula; n = zpractice . AdjustiWe used two levels of stratified sampling method to select the study participants from to ensure representativeness. First, students were stratified according to faculty (school), defined as one of the 5 constituent schools in the University, namely, School of Allied Health Sciences; School of Basic and Biomedical Sciences; School of Medicine; School of Nursing and Midwifery; and School of Pharmacy. For each faculty, students were stratified according to their level (year) of study, where simple random sampling was used to select the required number of students separately from each faculty and academic year. This was done by obtaining names of all female students according to their faculty and level of study from the University’s administration. The names of eligible students were arranged and numbered alphabetically separately for each faculty and level in a Microsoft excel sheet, where random numbers were generated, and the corresponding students selected to take part of the study. The number of students selected from each academic year and faculty was proportional to the students’ population. Selected students were approached by the lead author who was also a student in the University in January 2019 and after explaining the study’s objectives and procedures to them, all (100%) agreed to participate in the study. Students who were under 18 years of age were excluded from this study.A structured pre-tested questionnaire was used to collect data from participants. The questionnaire contained closed-ended questions adapted from previously published studies that adapted validated questions and had the following sections: demographic information, breast screening practices, risk factors of breast cancer , and awareness of breast cancer.Consenting participants were handed printed copies of the questionnaire and were given 24 hours to fill their responses and return them anonymously to the researchers. The objectives of the study were explained to all participants before the questionnaires were given out. Filled questionnaires were checked daily by the researchers for consistency and omissions before collection. Where there were inconsistencies, participants were made to correct them in the presence of the researchers before they were taken.All analyses were carried out using STATA  statistical package Version 13. Descriptive statistics were used to describe the study population in relation to relevant variables. Bivariable and multivariable logistic regression models were used to identify significant predictors of regular BSE defined as having examined the breast at least once every month. First, the association of regular BSE with each variable of interest  was examined. Second, variables with p-value <0.20 in the first model were considered for inclusion to construct a model with risk factors independently associated with the outcome variable. The degree of association between dependent and independent variables was assessed using odds ratios (OR) with 95% confidence intervals (CI).The study approval by the University of Health and Allied Sciences’ Ethics Review Committee with reference UHAS-REC A.8  18–19. WAll 385 participants returned their completed questionnaire. The mean age of the study population was 22 ± 2.78. The majority (55.8%) were between 20 and 24 years old, while 1.3% were 30 years and above; 16.4% were currently married and 83.1% were single; 74.0% were Christians and 18.9% were Muslims. Regarding ethnicity, Akans were the majority (38.4%), followed by Ewes (30.9%), while 14.3% belonged to the Ga-Dangbe ethnic group. Respondents constituting 26.2% (n = 101) were in their first year of study, 21.8% were in the second year, 30.2% in the third year and 21.8% were fourth-year students. The comparative majority (52.5%) were studying Nursing and midwifery, 22.3% were Medical students, and 19.7% were Allied Health Sciences students .Regarding breast cancer awareness, 281 (73.0%) of the respondents reported having ever heard of breast cancer. The remaining items in Among students who were aware of breast cancer, 129 (45.9%) thought that they do not have the chance of getting breast cancer, while 46 (16.4%) did not know whether they were at risk or not .Among the 385 study participants, menarche occurred below age 12 in 48 (12.5%) of them, while 72 (18.7%) were more than 14 years at menarche. The prevalence of current oral pill/injectable contraceptive use was 13.2% (n = 51). The occurrence of breast cancer in the family was confirmed in 55 (14.3%) of the respondents; 14 (4%) had their first-degree relatives  affected with the disease, while 41 (11%) were second-degree relatives. Four (1%) of the students had a personal history of breast cancer. Regarding behavioural factors, 39 (10.1%) did not engage in physical activity and 77 (20%) currently use at least one standard of alcohol per day .Of the 385 participants, 212 (55.1%) ever applied at least one breast cancer screening method. Of these, 164 (42.6%) practised BSE, 39(10.2%) had undergone CBE, and 9 (2.3%) were screened for breast cancer via mammography. Of those who performed BSE, 136 (82.9%) did it at least once in every month; 6 (3.7%) examine their breast yearly, and 22 (13.4%) did it at random; 115 (70.1%) of them learned BSE skills from their school-teachers, 112 (68.3%) from the media, 37 (22.6%) were taught by their friends, and 26 (15.9%) learned it from their mothers. The most common (28.1%) reason for not practising BSE was “1 do not know how to perform it” followed by “I have no family history of breast cancer” (23.1%) and “I am not at risk of breast cancer” (17.2%), while 63 (28.5%) had no reason for not doing BSE .This study though has demonstrated considerable awareness about the existence of breast cancer, insufficient knowledge, and misconceptions regarding its risk factors and causes and disease presentation also existed among participants. Less than three-quarters of our study participants had heard about breast cancer. This is unexpectedly far lower than the 100% observed in medical students in Harar, Ethiopia , 98.7% aPredictors of breast cancer risk are varied, including individual lifestyle, reproductive status, and genetics. This study attempted to identify some of these risk factors among the students. First menstruation at an early age (early menarche) is known to be associated with increased levels of endogenous hormones (estrogen and progesterone) in a woman’s lifetime which increases the risk of breast cancer . In thisAmong the most extensively researched risk factors of breast cancer is the use of exogenous hormones in the form of oral contraceptives and hormone replacement therapy (HRT) . Lina etA positive family history of breast cancer in a first-degree relative is the most commonly known risk factor for the disease . Women wThe relationship between alcohol consumption and an increased risk of developing breast cancer has been the subject of many studies. Compared with non-alcohol drinkers, women who drink even in small amounts, have increased risk of breast cancer. The risk increases with an increased amount of alcohol consumed per day . In manyMany studies have reported an inverse relationship between regular physical activity and breast cancer risk. Several biologic mechanisms have supported the protective effect of physical activity on breast cancer which includes effect on immune, endogenous sex steroid hormone production, and antioxidant system –46. In tAccurate and early diagnosis of breast cancer depends mainly on the "opportunist approach". Given the challenges faced by resource-limited countries, improving breast cancer awareness and the application of screening methods remains a practical option for early detection and treatment of breast cancer. Similar to reports from previous studies done in different parts of the world including Ghana at different times, the performance of breast cancer examination is generally low –56. NotaWhile the effectiveness of BSE to detect breast malignant tumour remains debatable, its importance in breast self-awareness creation in resource-limited countries with non-existent population screening programmes cannot be overemphasis, thus deserves consideration. The level of BSE practice in this study is, however, higher than that reported among over 10,000 undergraduate students from 24 countries across Africa, Asia and America. (9.1%) , and thaExpectedly, this study demonstrates that risk perception, an important component of behavioural change paradigm, is a sufficient enough variable that is capable of affecting women’s breast cancer screening behaviour. Women who did not believe to be vulnerable to breast cancer and those who did not know their risk status were less likely to practice BSE regularly compared to those who were pessimistic about their risk of the disease. Our result confirms the assertion of the Health Belief model that women who with a higher risk for breast cancer, perceive breast cancer as a serious threat, have a lower perception barrier, and who hold a higher perception of the benefits are more likely to perform regular BSE . Erbil aIt is interesting to note that other risk variables such as physical activity, Alcohol consumption, and contraception use, and positive family history did not influence breast BSE in this present study. This is a worrying finding because women with risk factors are expected to perform regular breast examinations to detect the disease at its early stage to prevent complications and death. It can be suggested that university women do not practice BSE even though they have some risk factors of breast cancer.There are three limitations of our study worth mentioning. First, the findings cannot be generalised beyond the study population since they are young and well-educated women. University students are not representative of young adults in general, and the risk perception, risk factors, and breast cancer screening practice may differ from that of the general population. Secondary, all data were self-reported with no objective measures to assess the accuracy of these reports. Lastly, the instrument used was not tested for its validity, however, questions used were taken from validated tools from previous studies at other settings. Nevertheless, the results of this study provide some understanding regarding perceived risk and the practice of breast screening among future health professionals, which can be useful for directed health promotion and education.The research concludes that the awareness of breast cancer and its causes, risk factors, and disease manifestation was generally unsatisfactorily low. Additionally, even though some students possess some important risk factors of the disease, the practice of BSE coverage which was influenced by risk perception and religion was low. Improved methods of risk communication are recommended to ensure that women have appropriate risk information to make informed choices about risk management options and preventative interventions. Social media can also be a reliable tool for health education on breast cancer.S1 Data(XLS)Click here for additional data file.S1 Questionnaire(DOCX)Click here for additional data file.