P < .05) more likely to be of smaller tumor size, lower grade, progesterone receptor (PR)‐positive, human epidermal growth factor 2 (HER2)‐negative and have low Ki‐67 levels (proliferation‐marker). Moreover, ultralow risk tumors showed significantly lower expression scores of multi‐gene modules associated with the AKT/mTOR‐pathway, proliferation (AURKA), HER2/ERBB2‐signaling, IGF1‐pathway, PTEN‐loss and immune response (IMMUNE1 and IMMUNE2) and higher expression scores of the PIK3CA‐mutation‐associated module. Furthermore, 706 genes were significantly (FDR < 0.001) differentially expressed in ultralow risk tumors, including lower expression of genes involved in immune response, PI3K/Akt/mTOR‐pathway, histones, cell cycle, DNA repair, apoptosis and higher expression of genes coding for epithelial‐to‐mesenchymal transition and homeobox proteins, among others. In conclusion, ultralow risk tumors, associated with minimal long‐term risk of fatal disease, differ from other ER‐positive tumors, including luminal A molecular subtype tumors. Identification of these characteristics is important to improve our prediction of nonfatal vs fatal breast cancer.The metastatic potential of estrogen receptor (ER)‐positive breast cancers is heterogeneous and distant recurrences occur months to decades after primary diagnosis. We have previously shown that patients with tumors classified as ultralow risk by the 70‐gene signature have a minimal long‐term risk of fatal breast cancer. Here, we evaluate the previously unexplored underlying clinical and molecular characteristics of ultralow risk tumors in 538 ER‐positive patients from the Stockholm tamoxifen randomized trial (STO‐3). Out of the 98 ultralow risk tumors, 89% were luminal A molecular subtype, whereas 26% of luminal A tumors were of ultralow risk. Compared to other ER‐positive tumors, ultralow risk tumors were significantly ‐positive breast cancers is heterogeneous, and distant recurrences may occur months to decades after primary diagnosis. However, the long‐term risk of metastatic disease in breast cancer remains largely unexplored. Using a previously‐established 70‐gene signature to identify breast cancer patients with minimal long‐term risk of fatal disease, here the authors show that ultralow‐risk tumors differ from other ER‐positive breast cancer tumors, including luminal molecular subtype tumors. Differences were found in both clinical breast cancer markers and molecular features. These results are important for the characterization and prediction of non‐fatal vs fatal breast cancer. ERestrogen receptorFDRfalse‐discovery rateFFPEformalin‐fixed paraffin‐embeddedHER2human epidermal growth factor receptor 2IHCimmunohistochemistryPRprogesterone receptor1Estrogen receptor (ER)‐positive breast cancer patients have a steady long‐term risk of fatal disease, and distant metastatic recurrence can occur anywhere between a few months to several decades after primary diagnosis.The 70‐gene signature (MammaPrint) was originally designed to identify breast cancer patients with high or low risk of early relapse within 5 years after primary diagnosis to identify which patients require adjuvant therapy.Therefore, here we aimed to assess the clinical and molecular characteristics of ultralow risk tumors in ER‐positive lymph‐node negative postmenopausal breast cancer patients from the Stockholm tamoxifen randomized trial (STO‐3). Ultralow risk tumors were compared to other ER‐positive tumors, including PAM50 molecular subtype luminal A and B tumors, regarding the clinically used breast cancer markers, as well as the expression scores of 19 multigene modules representative of specific biological processes and pathways. Furthermore, differentially expressed genes on the single‐gene level in ultralow risk tumors vs other ER‐positive tumors were identified and categorized by their associated Hallmark gene set to better understand the molecular characteristics of ER‐positive tumors with very low long‐term risk of fatal disease.22.1The Stockholm breast cancer study group conducted randomized trials 1976 to 1990 in lymph‐node negative postmenopausal patients with tumors ≤30 mm in diameter.Molecular analysis was possible for 808 patients with available formalin‐fixed paraffin‐embedded (FFPE) tissue blocks from the primary breast cancer tumor.2.2Immunohistochemistry (IHC) analysis of ER, progesterone receptor (PR), human epidermal growth factor 2 (HER2) and proliferation marker Ki‐67 were performed 2014.2.3Tumor grade was retrospectively assessed by one pathologist according to the Nottingham Histologic Score system (Elston grade).2.4Agilent microarray profiling was performed in 2014.2.5The 70‐gene signature (MammaPrint) was used to classify primary tumors into “high risk”, “low risk” or “ultralow risk.” The molecular risk prediction tool was originally designed to identify patients with low or high risk of early relapse,2.6Tumors were assigned to one of five molecular subtypes: luminal A, luminal B, HER2‐enriched, basal or normal‐like, by the PAM50 classification,2.7The expression scores of 19 multigene modules, proxy‐signatures for activation of biological processes or pathways and associated with clinical outcome, were analyzed in the study.2.8On a single‐gene level, an exploratory analysis of genes differentially expressed in ultralow risk tumors compared to all other ER‐positive tumors of low or high risk was conducted. Prior to this, probes from the gene expression microarray data were filtered out if the median expression value was among the bottom 5%, if the variance was among the 25% lowest, if containing any missing values, or if the probe was not annotated to any gene. The differentially expressed genes were categorized by Hallmark gene sets (version 6.2)2.9t‐statistics output from the analysis of differentially expressed genes. A false‐discovery rate (FDR) of 5% was used to adjust for multiple testing.Using the 27 Hallmark gene sets, a gene set enrichment analysis (GSEA) was performed to identify which gene sets are significantly enriched of genes differentially expressed in ultralow risk tumors compared to other ER‐positive tumors of low or high risk. The GSEA calculates enrichment scores (ES) for each gene set to explore if genes belonging to the gene set tend to occur at the top (or bottom) of a specific preranked gene list.2.10P‐value less than .05 was considered statistically significant. The analysis to identify differentially expressed genes was conducted using R package OCplusGiven that all ultralow risk tumors were ER‐positive, only ER‐positive patients were included in our study  of the tumors as of ultralow risk Figure . On the 3.1P < .05) more likely to be of a smaller (pT ≤ 20 mm) tumor size, except in the comparison of luminal A tumors and of lower tumor grade, as compared to the other groups  different expression scores in ultralow risk tumors  in the ultralow risk tumors were compared to all other ER‐positive tumors (of low or high risk), and ER‐positive luminal A and B molecular subtype tumors (of low or high risk). Eight multigene modules showed significantly  differentially expressed in ultralow risk tumors as compared to all other ER‐positive tumors of low or high risk . Of thesTo further understand the biological function associated with ultralow risk definition, the 706 differentially expressed genes were categorized into different cancer‐related Hallmark gene sets . Figure Further gene set enrichment analysis (GSEA) showed significant (FDR < 0.05) enrichment of gene sets consistent with previous analyses . The gen4We have previously shown that the ultralow risk threshold of the 70‐gene signature identifies patients at minimal long‐term risk of death from breast cancer.The risk of distant recurrences in ER‐positive breast cancer remains steady decades after primary diagnosis.ERBB2‐signaling significantly differ between the ultralow risk tumors as compared to the other ER‐positive tumor groups. However, since this difference was not observed by the HER2 IHC assay  this finding should be confirmed in further studies. Furthermore, ultralow risk tumors exhibited higher expression scores of the ESR1‐module, indicating higher ER expression which is associated with better prognosis.Ultralow risk tumors differ significantly from other ER‐positive tumors in relation to the clinically used breast cancer markers. PR and Ki‐67 have prognostic value in breast cancer,Ultralow risk tumors differ significantly from other ER‐positive tumors on the molecular level by the expression of cancer‐associated biological processes and pathways. In brief, genes involved in the PI3K/Akt/mTOR pathway, which has a role in endocrine sensitivity and breast cancer survival,Lower expression of immune response genes is recognized in ultralow risk tumors, as observed by the multigene modules IMMUNE1 and IMMUNE2 and on the single‐gene level. While the immune response mostly has been investigated in the context of ER‐negative or HER2‐positive breast cancer were higher expression often has been associated with better survival and reduced metastatic risk,TPM1, WNT5A, TGFBR3, SLIT3 and PDLIM4.Another finding in our study indicate that ultralow risk tumors exhibit lower expression scores of the IGF1‐pathway‐associated module, which is involved in breast cancer development and progression.To summarize, our study suggests an ultralow risk phenotype characterized by clinically used breast cancer markers  and molecular characteristics. Importantly, the ultralow risk classification differs from the luminal A molecular subtyping. Furthermore, ultralow risk tumors show lower activation of the PI3K/Akt/mTOR‐pathway, immune response and IGF1‐pathway and lower expression levels of genes involved in proliferation, cell cycle, DNA repair and apoptosis and higher expression levels of EMT tumor suppressor genes. Also, an altered transcriptional state in ultralow risk tumors is suggested, including lower expression levels of genes coding for histones and higher expression levels of homeobox genes, which less is known about. These findings are supported by analysis of multigene expression modules and the identification of differentially expressed genes and their associated Hallmark gene sets.Our study was conducted using tumors from postmenopausal patients with generally low metastatic risks given their lymph‐node negative status and smaller (≤30 mm) tumors. There are limitations to our study. The STO‐3 trial was conducted mainly prior to the introduction of mammographic screening in Sweden; therefore, the majority of the breast tumors were clinically detected. Modern mammographic screening has increased the number of newly diagnosed low‐risk breast tumors, thus, a better clinical understanding of low‐risk tumors characteristics is needed. As with most long‐term follow‐up studies, clinical recommendations for disease management and treatment have changed since the trial. Molecular analysis was possible for approximately half of the tumors in STO‐3; however, we have confirmed that patient and tumor characteristics were well balanced to the original STO‐3 cohort.5Ultralow risk tumors, associated with minimal long‐term risk of fatal breast cancer, have distinct clinical, biological and molecular characteristics as compared to other ER‐positive tumors, including luminal A molecular subtype tumors that generally are considered as a low‐risk disease. A better understanding of the characteristics of breast cancer tumors of very low long‐term risk of metastatic disease is important to improve our prediction of fatal vs nonfatal disease.Dr van 't Veer is a cofounder, stockholder and part‐time employee of Agendia. All remaining authors declare no potential conflicts of interest.Conceptualization: Annelie Johansson, Nancy Yiu‐Lin Yu, Adina Iftimi, Laura van 't Veer, Christopher C. Benz, Laura J. Esserman, Christina Yau and Linda S. Lindström. Data curation: Bo Nordenskjöld, Tommy Fornander, Olle Stål, Laura J. Esserman and Linda S. Lindström. Formal analysis: Annelie Johansson, Nancy Yiu‐Lin Yu, Adina Iftimi, Christina Yau and Linda S. Lindström. Funding acquisition: Tommy Fornander, Olle Stål, Laura J. Esserman and Linda S. Lindström. Investigation: Annelie Johansson, Nancy Yiu‐Lin Yu, Adina Iftimi, Gizeh Perez‐Tenorio, Christina Yau and Linda S. Lindström. Methodology: Annelie Johansson, Nancy Yiu‐Lin Yu, Adina Iftimi, Christina Yau and Linda S. Lindström. Project administration: Annelie Johansson and Linda S. Lindström. Resources: Bo Nordenskjöld, Tommy Fornander, Olle Stål and Linda S. Lindström. Software: Annelie Johansson, Nancy Yiu‐Lin Yu, Adina Iftimi, Nicholas P. Tobin, Christina Yau and Linda S. Lindström. Supervision: Annelie Johansson and Linda S. Lindström. Visualization: Annelie Johansson, Nancy Yiu‐Lin Yu, Adina Iftimi, Gizeh Perez‐Tenorio, Christina Yau and Linda S. Lindström. Writing ‐ original draft: Annelie Johansson, Nancy Yiu‐Lin Yu and Linda S. Lindström. Writing ‐ review & editing: All authors.The STO‐3 trial was approved by the ethics committee at Karolinska Institutet and participants provided oral consent. The trial was conducted at the Regional Cancer Center Stockholm‐Gotland, Sweden, and began in 1976, which was well before trial registration started in Sweden; therefore, information on trial registration number is not available.Appendix S1: Supporting InformationClick here for additional data file.


In addition, we found a significant negative correlation between knowledge and barrier scores . It is recommended to develop target-oriented educational programs for the healthcare workers, which would empower them to educate the community regarding the risk factors and the importance of mammogram screening. Furthermore, a prospective study is warranted in other regions of the Kingdom of Saudi Arabia to understand the region-specific training needs for the healthcare workers.Breast cancer is the most commonly diagnosed cancer among women in the Kingdom of Saudi Arabia and other Middle East countries. This analytical cross-sectional study assessed knowledge, attitude towards breast cancer, and barriers to mammogram screening among 414 randomly selected female healthcare workers from multiple healthcare facilities in northern Saudi Arabia. Of the studied population, 48.6% had low knowledge, and 16.1% had a low attitude towards breast cancer risk factors and symptoms. The common barriers to mammogram screening were fear to discover cancer (57.2%) and apprehension regarding radiation exposure (57%). Logistic regression analysis found that lack of awareness regarding mammogram was significantly associated with age ( Breast cancer is one of the significant public health issues worldwide affecting women after puberty, as stated by the World Health Organization (WHO). In 2020, there were 2.3 million cases and 685,000 deaths worldwide due to breast cancer . SeveralVarious screening methods are available for detecting breast cancer at an earlier stage, including breast self-examination, clinical breast examination, and ultrasound; however, mammography remains the primary screening modality used worldwide. In the KSA, the mammography screening technique is used for early detection of breast cancer, and it uses low-frequency X-rays to detect the features of microcalcification or mass in the breast ,9. As peRecent epidemiological studies reported that women with inadequate knowledge regarding risk factors and susceptibility to breast cancer were less likely to accept breast cancer screening methods. Other factors associated with the low uptake of mammogram screening programs were low income, low education, and lack of information regarding available screening methods ,13.Healthcare workers (HCWs) play a critical role in imparting knowledge regarding available health services improving access and screening services provided by the concerned authorities. They also help in changing the behavior of an individual, families, and communities through different health-promotion activities ,15. HencHence, the present study assessed the knowledge and attitude towards breast cancer among the female HCWs and identified the correlation between knowledge and attitude. This study also aimed to identify the barriers to breast cancer screening programs among them.The current analytical cross-sectional survey was conducted in the Aljouf region from December 2021 to April 2022. This region is situated in the northern part of the KSA, with a total population of about 500,000. Healthcare in the Aljouf region is delivered by the ministry of health (MOH), private sectors, and other ministries through four levels: primary, secondary, specialty hospitals, and medical cities. There are 62 primary health centers, 13 general hospitals, and 2 specialty hospitals in this region under the MOH, KSA.We included all the female HCW categories working in the MOH sector for a minimum duration of one year, namely doctors, nurses, pharmacists, lab technicians, and other categories. We excluded the HCWs on vacation, in different sectors (other than MOH), and those unwilling to give informed consent to participate in the present survey.2 pq/e2), we estimated the minimum required female participants needed for this research. The following values were considered while calculating sample size, namely n = minimum size of the necessary sample, z = 1.96 at the confidence level of 95%, p = expected proportion , and q = 1 − p and e = margin of error at 5%. Considering all the above-specified values, the estimated minimum required sample size was 384. Finally, we adjusted the sample size to 480, with the expected 20% non-response rate.By using Cochran’s formula  was obtained.Risk to the participants: There was no risk for the participants, as it was questionnaire-based research.Respect for anonymity, privacy, and confidentiality: The collected details did not have any identification details of the study participants, and only the overall results of the participants were reported after the completion of the study. Hence, we maintained the anonymity of the respondents.After obtaining ethical clearance from the Aljouf regional research ethics committee, Qurayat health affairs, MOH , the data collectors began the survey. The following considerations were made to avoid ethical issues: The present study used a standardized self-administered questionnaire prepared by a team of experts from general surgery, radiology, and public health departments based on existing pieces of literature ,17,18. TAfter necessary administrative approvals from the concerned healthcare facilities, the data collectors initiated the survey. We used an electronic shareable document (Google form) with the IRB-approved questionnaire for data collection. After briefing about the research rationale and objectives and obtaining informed consent, the selected HCWs were requested to fill the google form on the personal electronic device of the data collectors. For data security, the research team decided to give authorization only to the principal investigator to access, download, and export the survey’s spreadsheet. In addition, the research team made three attempts in two weeks to communicate with the selected participants. The HCWs who were unwilling to participate and those who could not be communicated with despite three attempts were recorded as non-respondents.p < 0.001). Hence, we executed the Spearman’s correlation coefficient rank test was also used to find the strength and direction of correlation between knowledge, attitude, and barriers scores. Finally, we performed a multivariable analysis using the binomial logistic regression method to find the significantly associated socio-demographic factors with the knowledge, attitude, barriers, and awareness of the MOH, Saudi Arabia’s recommendation for mammogram screening for breast cancer. All the statistical analysis used in this research is two-tailed, and the p-value less than 0.05 was set as statistically significant.We used the statistical package for social sciences, version 21, to export data from spreadsheets, coding, recoding, and analysis . The categorical and other descriptive results are presented as numbers (frequencies) and proportions (%), while the continuous data are presented as mean and standard deviation (SD). Initially, we performed the Shapiro–Wilk normality assumption test for the knowledge, attitude, and barriers scores. We found that all three types of scores did not meet the normality assumption  and apprehension regarding radiation exposure (57%). Nearly half (48.6%) of the HCWs responded that embarrassment due to breast-related tests was their primary barrier to mammogram screening uptake .Of the 414 respondents, 93 (22.5%), 106 (25.6%), and 69 (16.7%) had high scores in the knowledge, attitude, and barriers categories, respectively. In comparison, 201 (79.1%), 79 (19.1%), and 254 (61.4%) had low scores in the knowledge, attitude, and barriers categories, respectively .p = 0.038), nationality , education , HCWs category , and family history of breast cancer . The binomial logistic regression revealed only the following two characteristics were significantly associated with knowledge subscales, namely education status (ref: diploma holders: Adjusted OR (AOR) = 2.47, 95% CI = 1.54–4.53, p = 0.001) and HCW category .p = 0.017) and family history of breast cancer . However, logistic regression analysis did not reveal any significant association between independent variables and attitude subcategories.Attitude subcategories and their association with sociodemographic characteristics are depicted in p = 0.015) and marital status .p = 0.030) and HCWs categories  were significantly associated with the awareness regarding MOH, Saudi Arabia’s recommendation for mammogram screening for breast cancer . In addition, we found a negative correlation between knowledge of the breast cancer risk factors and symptoms with the barriers towards uptake of mammogram screening  (The spearman’s rank correlation test revealed a significant positive correlation between knowledge and attitude scores (rho = 0.195, In spite of the availability of these programs, a low-level mammogram screening uptake was prevalent in all sectors of the population living in all provinces of the KSA. A study conducted in the KSA reported that among 1135 women aged 50 years and above, 92% never had mammogram screening .We conducted the current study among the 414 randomly selected different categories of HCWs. The present study found that a high proportion of the HCWs recognized family history and smoking as risk factors for developing breast cancer. In contrast, the lowest proportion of the participants reported early puberty, late menopause, and physical inactivity as risk factors. Similar to the current study findings, a study done by in Jordan found that female participants were highly aware of family history as a risk factor. However, only one-third recognized early puberty as a risk factor . A recenThe binomial logistic regression analysis of the current study found that knowledge scores were significantly associated with age group, nationality, level of education, and HCWs categories. Similar to the current study findings, a survey conducted among the female primary HCWs found a significant association between knowledge with the HCWs’ profession and education status . The preHealthcare services utilization, including mammogram screening utilization by the public, is influenced by numerous barriers ,26,27,28Health literacy is an individual’s competence and knowledge to understand and make a proper decision on the health-related needs of them and others. A high level of health literacy and knowledge is critical for making a proper health-related decision ,32. The The WHO Global Breast Cancer Initiatives is an essential collaboration formed in 2021 to empower women and reduce breast-cancer-related deaths by 2.5% and save 25 million lives by 2040. This aim can be achieved by raising awareness of breast cancer and the importance of early detection to the HCWs, as they play a central role in strengthening the existing healthcare system ,37.Based on the above-mentioned findings, it is recommended to develop evidence-based and target-oriented educational programs for the HCWs, which would empower them to educate the community regarding the risk factors of breast cancer and the importance of early detection. Additionally, concerned authorities may consider changing their strategies from a mass approach to a personalized risk assessment and screening method. Furthermore, a prospective study is warranted in other regions of the KSA to understand the region-specific training needs for the HCWs.The research team conducted the current survey using the validated tool with an adequate sample size using the standard methodology. At the same time, certain constraints need to be considered during the interpretation of this survey’s results. Firstly, this study design is cross-sectional and can find only the association, not the causation. Secondly, there is a possibility of bias due to self-reported studies present in this study. Thirdly, the present study assessed female HCWs’ knowledge, attitude, and barriers, not the general population. Hence, the current study’s findings may not be generalized to all sections of the KSA. Finally, we included only the HCWs working at the ministry of health, KSA. Nonetheless, the current research explored critical aspects of one of the significant global health issues to be addressed immediately.The present study depicted that the knowledge was significantly associated with age group, nationality, level of education, and HCWs categories. However, attitude was significantly associated only with the nationality of the HCW’s. Overall, the knowledge and attitude among the northern Saudi HCWs were found to be inadequate. There were several barriers reported by the HCWs to utilizing the free mammogram services provided by the MOH, KSA, and these barriers correlated negatively with the HCW’s knowledge of breast cancer. The need of the hour is to develop evidence-based and target-oriented educational programs for the HCWs, who in turn can play a pivotal role in educating the community regarding the risk factors of breast cancer and the importance of its early detection.


Women with breast cancer are at risk for the development of sarcopenia and occurrence of fractures. The initial and periodic screening of these conditions can prevent the risks of disability, poor quality of life, and death. The present study investigated the association between sarcopenia phenotypes and fracture risk, assessed by the Fracture Risk Assessment Tool (FRAX) in women with breast cancer.p < 0.05 was adopted for all tests using the SPPS 25.0 program.Cross-sectional study. It included women aged between 40 and 80 years, diagnosed with Luminal subtype breast cancer, with time of diagnosis ≤ 12 months, who had not started endocrine therapy, did not have metastasis, had not been treated for another malignancy, and had no recurrences. Sociodemographic, habits and lifestyle, clinical, anthropometric, and body composition variables were considered. Muscle strength, skeletal muscle mass, and physical performance were investigated using handgrip strength (HGS), appendicular skeletal muscle mass index (ASMI), and Timed Up and Go test (TUGT), respectively. Fracture risk was assessed using FRAX. Multiple linear regression models were conducted to verify the association between exposure variables and sarcopenia phenotypes. A significance level of p = 0.007) and FRAX major fractures (p = 0.007) in the adjusted models, while ASMI was associated with body mass (p < 0.001).Sixty-two women with a mean age of 58.1 ± 10.4 years were evaluated. Of these, 66.1% self-declared to be non-white, 41.9% and 71.0% did not consume alcohol or smoke, respectively, and 61.3% were insufficiently active. A total of 45.2% had clinical stage II carcinoma and 65.5% had the invasive breast carcinoma histological subtype. There was a predominance of adequacy of HGS (88.7%), ASMI (94.5%), and TUGT (96.8%), as well as low risk of hip fractures (85.5%) and major fractures (82.3%). HGS remained associated with FRAX hip fractures (Low muscle strength was the sarcopenia phenotype that remained associated with fracture risk in women with breast cancer, independently of sociodemographic factors, level of physical activity, and clinical factors. In addition to the assessment of probable sarcopenia, this measurement may point out the risk of fractures. Women with breast cancer often experience changes in body composition related to increased fat mass and decreased fat-free mass, particularly skeletal muscle mass . This coIn individuals with cancer, sarcopenia is classified as secondary and the result of the state of systemic inflammation caused by the tumor itself and the adverse effects of anticancer treatment. Both are associated with protein catabolism and, consequently, with the reduction of muscle mass and its functions , 4.Another component greatly affected in women with breast cancer is bone tissue, especially in those suffering from the subtype positive for hormone receptors  . The maiCancer Treatment-Induced Bone Loss (CTIBL) in women with breast cancer occurs at a faster rate than that related to age and the postmenopausal period and is related to different causes . ChemothThus, early care and safe and effective interventions are necessary to preserve bone mineral density (BMD) and prevent fractures in this population . Non-phaThe assessment of bone health in this population should include not only the analysis of BMD, but also the other risk factors that influence bone strength . In thisThe presence of sarcopenia and increased fracture risk are conditions reported in women with breast cancer that are associated with negative outcomes in this population –12. SarcBone and muscle tissues are linked from a biological and functional point of view . In thisAlthough women with breast cancer are at risk for sarcopenia and fractures, these conditions are little explored in this population. Early and periodic screening of both conditions can guide clinical and dietary management in order to avoid and/or reduce the chances of complications and aggravations during and after anticancer treatment. In this context, this study investigated the association between sarcopenia phenotypes and fracture risk, assessed by FRAX, in women with breast cancer.Observational cross-sectional study, with non-probability, convenience, and consecutive sampling, carried out in a mastology outpatient clinic of a public hospital located in Vitória, Espírito Santo, Brazil, from January 2021 to May 2022. Inclusion criteria were: to be treated at the referred outpatient clinic; to be aged between 40 and 80 years; to have a confirmed diagnosis of luminal subtype female breast cancer; to have a diagnosis time of up to 12 months; not presenting metastasis; not having started endocrine therapy; not having or having been treated for another malignant neoplasm, and not having recurrences. Women with unassisted mobility impairments, who had cognitive impairment and/or psychiatric illnesses predicted in medical records and who were under pharmacological treatment for osteopenia and osteoporosis and using calcium and vitamin D supplementation were not considered for the study.All medical consultations performed by the mastology team were screened and the patients considered eligible were contacted by telephone – at least three attempts – and invited to participate in the research, in order to limit possible sample selection biases.Data collection took place through face-to-face interviews using a structured protocol. All researchers involved were properly trained to apply the instruments and measure the parameters used.The outcome variables of this study were the sarcopenia phenotypes: muscle strength, muscle quantity and physical performance. The parameters, methods, and cut-off points suggested by the Revised European Consensus on Sarcopenia , proposeTo assess HGS, a manual dynamometer (Jamar®) with a scale from 0 to 90 kg/f and a resolution of 2 kg/f was used. The test was performed using the method recommended by the American Association of Hand Therapy (ASHT) . The par2(m)]. A cutoff point of ≤ 5.5 kg/m2 was considered to identify low skeletal muscle mass in women . For adult women, the BMI was classified considering the ranges proposed by the World Health Organization (WHO) [The anthropometric data measured were: height (m), body mass (kg), calf circumference (CC) (cm), and waist circumference (WC) (cm). The body mass index (BMI) was calculated as the ratio of body mass to height squared [weight(kg)/heighton (WHO) . Elderlyon (WHO) . CC was on (WHO) . Values on (WHO) . WC was on (WHO) . Women won (WHO) .2 were considered high, according to the median of the population itself.To assess the fat mass compartment, the values of percentage of total body fat mass (%BF) and abdominal visceral adipose tissue (VAT) obtained by DXA were considered. A %BF ≥ 32%  and a VAhttps://abrasso.org.br/calculadora/calculadora/ > .Fracture risk was identified by FRAX validated for Brazil. This tool is an algorithm calculated from age, BMI, and dichotomized risk factors, including previous fragility fracture, parental history of hip fracture, current smoking, long-term oral glucocorticoid use, rheumatoid arthritis, other causes of secondary osteoporosis, and excessive alcohol consumption. In addition, femoral neck BMD obtained by DXA was taken into account to increase the prediction of fracture risk . FRAX asSociodemographic data, habits and lifestyle data, menopausal status, current clinical history, and diagnostic classification of BMD were considered as covariates.The sociodemographic variables considered were: age in years; marital status (lives with or without a partner); schooling in years of study; self-reported race/color  ; and occRegarding habits and lifestyle, alcohol consumption, smoking, and physical activity level were considered. To estimate the level of physical activity, the short version of the International Physical Activity Questionnaire (IPAQ) for the Brazilian population was used . This vaMenopause status and time of menopause in years were considered. The variables time of diagnosis, clinical staging, histological subtype, and type of treatment characterize the current clinical history and were collected from the patient's medical records. The time of diagnosis was determined by the difference between the date of diagnosis in the medical record and the day of evaluation for this study. The type of treatment was classified as "No previous treatment", when the participant had not undergone treatment before the evaluation, "Neoadjuvant", for women who had only undergone neoadjuvant chemotherapy, "Surgical", for those who had only undergone surgery, and “Adjuvant”, for those who underwent adjuvant chemotherapy or radiotherapy. The histological subtype variable was categorized into “Invasive breast carcinoma”, “Invasive ductal carcinoma”, “Ductal carcinoma in situ”, and “Special subtypes”. The special subtypes found were: micropapillary ductal carcinoma, apocrine invasive breast carcinoma, micropapillary invasive breast carcinoma, pleomorphic invasive lobular carcinoma, invasive papillary carcinoma, encapsulated papillary carcinoma, cribriform ductal carcinoma in situ, and papillary ductal carcinoma in situ.BMD was assessed by DXA in the lumbar spine (L1-L4) and right proximal femur. BMD was classified according to the lowest T-score found into: normal BMD (T-score ≥ -1), osteopenia (T-score between -1 and -2.5), and osteoporosis  .r < 0.3), moderate (r = 0.3–0.7) or strong (r > 0.7) [p < 0.05.The sample was characterized through descriptive analysis expressed in means and standard deviations to describe continuous variables and percentages for categorical variables. The normality of quantitative variables was assessed using the Kolmogorov–Smirnov test. The presence of correlation between sarcopenia phenotypes and continuous variables was analyzed using Pearson's Correlation. Correlation coefficients can range from -1 to + 1 and were categorized as weak (r > 0.7) . MultivaDuring the study, 184 women with breast cancer, diagnosed 12 months prior to the evaluation, were seen at the outpatient clinic and contacted to participate in the research. Of those who answered the telephone contact, agreed to participate, and turned up for data collection, 45 did not meet the inclusion criteria, resulting in 66 patients evaluated in the present study. However, four did not complete data collection as they did not undergo the DXA exam, which resulted in a final sample of 62 volunteers   and the histological subtype invasive breast carcinoma (64.5%) was observed , with substantially increased WC (75.8%), high %BF (80.6%) and VAT (50.9%), and adequate CC (74.2%) , FRAX Hip fractures , and FRAX Major fractures   and a moderate one with CC . Muscle quantity (ASMI) had strong correlation with body mass  and BMI , in addition to a moderate one with CC , WC , %BF , and VAT . There were still moderate correlations between physical performance (TUGT) and age , FRAX Hip fractures , and FRAX Major fractures   showed moderate and inverse correlations with age  after adjustments for possible potentially confounding variables (data not shown in the table).Table This study found an association between muscle strength and fracture risk in women with breast cancer. Most of the women investigated showed preserved sarcopenia phenotypes and a low risk of fractures. In contrast, most of the group was characterized by excess body fat.The relationship between sarcopenia phenotypes and bone health is described in the literature. It does, however, remain unexplored in women with breast cancer. Most previous studies have determined fracture risk through fracture incidence in the population evaluated, and there are few studies using FRAX as an assessment tool , 20, 38.We observed that patients with higher fracture risk had lower HGS. Previous studies demonstrate that low HGS is an independent risk factor for fragility fractures and that fractured patients have relatively low HGS , 40.Amarowicz et al.  evaluateThis indicator is related not only to the risk and incidence of fractures, but also to the recovery of fractured individuals . PatientThe relationship between reduced HGS and increased fracture risk can be explained by the association between low muscle strength and decreased BMD . The mecThe association between risk of fractures and muscle strength observed in this study may contribute to the prevention of sarcopenia and fractures in women with breast cancer, especially of the Luminal subtypes, since muscle strength, when reduced, indicates the stage of probable sarcopenia, and HGS and FRAX assess preconditions for these ailments , 32. SarIn the present study, the muscle quantity, measured by the ASMI, was the only sarcopenia phenotype whose fracture risk was not associated in any of the analyses performed. There are controversies regarding the relationship between muscle mass and the risk of falls and fractures , 50, 51.Evidence suggests that DXA-derived ASM may not contribute to the prediction of falls and fractures, especially when considering femoral neck BMD, as seen in the present study , 51. ThiThe technical aspects of DXA also help to understand the positive association between body mass and ASMI found in the present study, despite the predominance of excess body fat in the population evaluated. Tissues quantified by DXA  are components of total body mass and their values are derived from it , 52.After insertion of adjustment variables, TUGT did not remain associated with the risk of fracture obtained by FRAX. According to the EWGSOP definition, TUGT is an indicator of the severity of sarcopenia, which means it should be compromised after reduced strength and muscle mass . Such reThe high prevalence of adequate sarcopenia phenotypes and the low risk of fractures in the sample evaluated can be explained by most patients not having started treatment, in addition to them all being free of endocrine therapy. In fact, it is known that breast cancer treatment is one of the main factors that lead to muscle tissue depletion and increased risk of fractures . NeverthThe impairment of sarcopenia phenotypes and the increased risk of fractures are also influenced by sociodemographic characteristics and habits and lifestyle , 55. AgeSimilarly, excessive alcohol consumption impairs protein synthesis, and exposure of muscle tissue to ethanol results in autophagy, while smoking can increase muscle fatigue, leading to protein metabolism disorders . On the Regarding the influence of lifestyle habits on fracture risk, there seems to be a decrease in bone formation in individuals with excessive alcohol consumption, in addition to a greater risk of falling when drunk . As for In our study, most women had never used alcohol or cigarettes, which may have contributed to the low prevalence of impaired sarcopenia phenotypes and low risk of fractures. However, most were insufficiently active. The IPAQ, the instrument used to measure this variable, takes into account the performance of activities in the last week, and after diagnosis, patients often reduce daily activities, in addition to often receiving a recommendation to rest during chemotherapy and radiotherapy, and after surgical treatment . These fAs for clinical features, Rathnayake et al.  observedClinical factors related to breast cancer also influence the risk of fractures, since the prescribed treatment depends on the histological type and molecular subtype of breast cancer  . PatientMuch like sociodemographic and lifestyle variables, time of menopause and clinical variables, such as time of diagnosis, clinical staging, and type of treatment, did not interfere in the association between muscle strength and fracture risk in the women evaluated.As for nutritional status variables, it has been reported that anthropometric measurements can be positively associated with sarcopenia phenotypes, since they are not able to compartmentalize the constituents of total body mass . On the Muscle mass also exerts a protective effect against increased fracture risk, through molecular signaling and regulation of hormone levels and bone anabolic factors . While tThis study observed a positive correlation between the variables of the fat mass compartment and ASMI, which can be explained by the limitation of DXA in measuring muscle mass, as discussed above, as well as in quantifying VAT separately. DXA assesses VAT by estimating the amount of subcutaneous fat in the android region, which is subtracted from the total fat mass of this region, thus limiting its interpretation . AnotherAs a contribution, this study demonstrated a relationship between HGS and FRAX, which optimizes the patient assessment process and supports early interventions and strategies, based on simple tools suitable for inclusion in assessment and clinical follow-up protocols. Compared to other tools that evaluate sarcopenia phenotypes, HGS is easy to use in clinical practice, in addition to being low-cost, portable, and not requiring specialized equipment and professionals. Because of these characteristics, its use as part of the routine is recommended in cancer patients .Thus, our results suggest that serial HGS measurements may help to identify women with breast cancer at high risk of fractures. Longitudinal studies are needed to determine whether incorporating muscle strength measures into fracture risk assessment tools would improve predictive accuracy.This study has some limitations. It has a small sample, not representative of the general population of women with breast cancer, as it was carried out with a group of women from a single outpatient clinic, from the secondary service of the public health system. It does, however, have a homogeneous and controlled sample, which contributes to the validity of the results presented here. In addition, the proposal to assess the relationship between sarcopenia phenotypes and fracture risk in women with breast cancer is an innovative one, not yet described in this population. Another limitation is the possibility of overestimating sarcopenia phenotypes, since there are no cutoff points for these parameters in the literature for cancer patients.Low muscle strength was the sarcopenia phenotype that remained associated with fracture risk in women with breast cancer, independently of sociodemographic factors, level of physical activity, and clinical factors. The inclusion of this parameter in the care and follow-up protocols of women with breast cancer may point to the risk of fractures, in addition to probable sarcopenia.


Breast cancer incidence is increasing rapidly in Latin America, with a higher proportion of cases among young women than in developed countries. Studies have linked inflammation to breast cancer development, but data is limited in premenopausal women, especially in Latin America.We investigated the associations between serum biomarkers of chronic inflammation (interleukin (IL)-6, IL-8, IL-10, tumor necrosis factor-α (TNF-α), interferon-γ (IFN-γ), leptin, adiponectin) and risk of premenopausal breast cancer among 453 cases and 453 matched, population-based controls from Chile, Colombia, Costa Rica, and Mexico. Odds ratios (OR) were estimated using conditional logistic regression models. Analyses were stratified by size and hormonal receptor status of the tumors.per standard deviation (SD) = 1.33 (1.11–1.60)) and TNF-α (ORper SD = 1.32 (1.11–1.58)) were positively associated with breast cancer risk in fully adjusted models. Evidence of heterogeneity by estrogen receptor (ER) status was observed for IL-8 (P-homogeneity = 0.05), with a positive association in ER-negative tumors only. IL-8 (P-homogeneity = 0.06) and TNF-α (P-homogeneity = 0.003) were positively associated with risk in the largest tumors, while for leptin (P-homogeneity = 0.003) a positive association was observed for the smallest tumors only.IL-6 (ORThe results of this study support the implication of chronic inflammation in breast cancer risk in young women in Latin America. Largest studies of prospective design are needed to confirm these findings in premenopausal women.The online version contains supplementary material available at 10.1186/s12885-022-09975-6. Breast cancer is the most frequently diagnosed cancer worldwide and the leading cause of cancer death among women . HoweverObesity is associated with a decreased risk of breast cancer in premenopausal women in different populations worldwide , includiSystemic inflammation is a known correlate of obesity, as macrophages become the largest cell population in obese adipose tissue, resulting in altered expression of pro- or anti-inflammatory cytokines in the circulation . In addiTight links exist between inflammation and the development of different cancers, including breast cancer . A meta-In this work, we examined associations between seven serum biomarkers of inflammation (interleukin 6 (IL-6), interleukin 8 (IL-8), interleukin 10 (IL-10), tumor necrosis factor α (TNF-α), interferon γ (IFN-γ) and adipokines (leptin and adiponectin) and breast cancer risk in premenopausal women from Latin America, using data from the multicentric PRECAMA population-based case–control study.PRECAMA is an ongoing multicentric population-based case–control study based in Chile, Colombia, Costa Rica, Mexico, and Brazil –19. InfoAll participants gave written informed consent before enrolment, and the study protocols were approved by the local institutional review and the International Agency for Research on Cancer (IARC).Cases were women diagnosed with first primary incident breast cancer in general or cancer-specific hospitals or private oncology institutes , recruitControls were selected from the general population residing in the same city district as the case for at least 3 years using a multilevel sampling frame . ControlParticipants from Brazil were not included in the present work as the recruitment started later.A total of 453 cases and 453 controls were included in the present analysis.Biological specimens were collected according to standardized protocols –21. Bloon = 6 for IL-6; n = 44 for IL-10; n = 7 for TNF-α; n = 40 for IFN-γ) while values above the upper limit of quantification were imputed to this upper limit (n = 6 for leptin).Laboratory measurements of IL-6, IL-8, IL-10, TNF-α, IFN-γ, leptin, and adiponectin were performed on serum samples at IARC (Biomarkers Group) using a highly sensitive and specific multiplexing electro-chemiluminescent assay . The laboratory technician who performed assays was blind to case–control status of the samples. Samples from cases and matched controls were analyzed in the same analytical batch. Three quality control samples were included in duplicate in each batch of analyses. Overall within-batch coefficients of variations ranged from 2.9% for IFN-γ to 9.7% for IL-6. Between-batch CVs ranged from 5.7% for adiponectin to 11.4% for IFN-γ. For each biomarker, values below the lower limit of quantification were imputed to this lower limit , and IL-8 on 628 subjects (314 case–control pairs).Population’s characteristics were described using frequency for categorical variables, and arithmetic mean and standard deviation for continuous variables, except for biomarker concentrations which were described using geometric means.In all following analyses, concentrations of biomarkers were log-transformed to approximate normal distribution and we used residuals of log-transformed variables regressed on analytical batch as exposures of interest. For covariates, missing values represented less than 5% of values and were imputed to the mode (parity) or to the median . Triple-negative (TN) tumors were defined as ER-negative, PR-negative, and HER2-negative. Among the TN tumors, basal-like tumors were defined as ER-negative, PR-negative, HER2-negative, and EGFR-positive (EGFR +) and/or CK5/6-positive (CK5/6 +).Spearman's partial correlation coefficients between concentrations of inflammation markers  and anthropometric factors and age were calculated among controls, adjusting for age (except for correlations with age).Odds ratios (ORs) for risk of breast cancer and their associated 95% confidence intervals (CI) were estimated using conditional logistic regression models. Concentrations of biomarkers and leptin/adiponectin ratio  were examined as continuous variables (OR estimated per standard deviation increment) and in quartiles, defined on the distributions of control participants. Tests for linear trends across quartiles were computed by assigning all individuals in a quartile the median value of the biomarker in this quartile and considering this variable as a continuous variable in the model. Potential non-linear associations were modelled using restricted cubic splines (3 knot), and BMI-adjusted models were compared by likelihood ratio test.We considered four models for each biomarker. First, we evaluated associations in a model including only matching variables. Second, we evaluated a model adjusted for BMI (continuous). Third, we examined a model adjusted for waist circumference (continuous) instead of BMI, as these variables are highly correlated but reflect different types of adiposity. Eventually, to rule out confounding originating from other variables than BMI and waist circumference, we examined a model adjusted for the following breast cancer risk factors: BMI (continuous), age at menarche , number of full-term pregnancies (0/1/2/ ≥ 3), age at first pregnancy , breastfeeding duration , use of hormones at blood collection (yes/no), personal history of benign breast disease (yes/no), family history of breast cancer in first-degree relatives (yes/no), smoking status (ever smoker/never smoker), alcohol consumption (g/day), moderate physical activity (hours/day), education level (up to primary school/secondary school/longer than secondary school), and adult height (continuous).2; < 30/ ≥ 30 kg/m2), using logistic regression analyses adjusted for matching factors. We assessed heterogeneity by including an interaction term between the variable used for stratification and the biomarker of interest.In cases for whom the information was available, analyses were stratified according to immunohistochemistry results for ER, PR, and HER2  and tumor size . All models in stratification were adjusted for BMI only, since sample size was too limited in subgroups to run the fully adjusted model. We additionally stratified analysis by BMI .We conducted a sensitivity analysis excluding women using exogenous hormones at inclusion  and in the 298 cases with available immunohistochemistry data, 72.1% of tumors were ER-positive, 68.8% were PR-positive, and 14.1% were triple-negative (Table 2 versus 29.2 kg/m2), waist circumference (91.0 cm versus 94.5 cm), and hip circumference (103.5 cm versus 106.5 cm).Compared with controls, cases were more likely to be nulliparous (18.1% versus 7.5%). Parous cases were on average older at their first full-term pregnancy (23.9 years versus 21.9 years) and breastfed less (41.8% did not breastfed or breastfed less than 8 months (first tertile) versus 26.0%) than parous controls. Cases had more frequently a history of benign breast disease (36.4% versus 12.1%) and a level of education above secondary school (37.1% versus 24.5%) than controls. Compared with controls, cases had a lower BMI (26.4 kg/mr = 0.36) and the leptin/adiponectin ratio (r = 0.42), negatively correlated with adiponectin (r = -0.23), and showed stronger correlations with anthropometric measures than with biomarkers . Leptin showed the strongest positive correlations with BMI, waist and hip circumferences  and leptin/adiponectin ratio , while adiponectin showed negative correlations with BMI, waist and hip circumferences . Correlations between waist-hip ratio and biomarkers were lower than with other anthropometric measures (0.12 ≤|r|≤ 0.22). Weak correlations were also seen between TNF-α and anthropometric measures (0.10 to 0.17).Age-adjusted Spearman correlation coefficients among control participants were moderate between circulating levels of different cytokines , TNF-α, and IFN-γ (0.13 ≤ r ≤ 0.41)  = 0.76 (0.66–0.87), ORQ4vsQ1 = 0.48 (0.33–0.70), P-trend < 0.001; leptin/adiponectin ratio: ORper SD increment = 0.75 (0.65–0.86), ORQ4vsQ1 = 0.53 (0.36–0.79), P-trend < 0.001). A positive but borderline statistically significant association was also observed for adiponectin (ORper SD increment = 1.14 (0.99–1.31); ORQ4vsQ1 = 1.45 (0.98–2.14), P-trend = 0.04).In the model including only matching factors Table , no signper SD increment = 1.32 (1.12–1.55); ORQ4vsQ1 = 1.55 (1.04–2.30), P-trend = 0.01).After adjustment for BMI, associations between leptin, adiponectin and leptin/adiponectin ratio and breast cancer risk were no longer significant, while a significant positive association was observed for IL-6 (ORper SD increment = 1.24 (1.07–1.44); ORQ4vsQ1 = 1.32 (0.90–1.95), P-trend = 0.06). In the same waist circumference-adjusted model, IL-8 was positively associated with risk (ORper SD increment = 1.15 (0.98–1.36); ORQ4vsQ1 = 1.59 (1.01–2.52), P-trend = 0.07). Leptin and leptin/adiponectin ratio were negatively associated with breast cancer risk when adjusting for waist circumference, although associations were attenuated as compared with the univariate model.When adjusting the univariate model for waist circumference, instead of BMI, the association of IL-6 and breast cancer risk was attenuated (ORper SD increment = 1.33 (1.11–1.60)), as was TNF-α (ORper SD increment = 1.32 (1.11–1.58); ORQ4vsQ1 = 2.03 (1.26–3.26), P-trend = 0.006). A significant positive association was observed for IL-8 in quartiles (ORQ4vsQ1 = 2.16 (1.14–4.07), P-trend = 0.06), but not for the continuous variable (ORper SD increment = 1.15 (0.93–1.44)). Borderline negative associations were observed for leptin (ORper SD increment = 0.82 (0.67–1.00)) and leptin/adiponectin ratio (ORper SD increment = 0.81 (0.66–1.00)). No associations were observed overall for IL-10 and IFN-γ.In the fully adjusted model (which included BMI but not waist circumference), IL-6 was positively associated with breast cancer risk  and TNF-alpha  .Although no departure from linearity was suggested from the linear trend test across quartiles, natural cubic spline models indicated evidence for non-linearity for IL-6 (per SD increment = 0.95 (0.72–1.24); ER-negative: ORper SD increment = 1.73 (0.98–3.06); P-homogeneityER+ vs ER- = 0.05). In contrast, a negative association was observed for IFN-γ in ER + tumors only (ORper SD increment = 0.82 (0.67–1.00), although the test for heterogeneity for receptor status was not significant (P-homogeneityER+ vs ER- = 0.14). No evidence of heterogeneity was observed for other biomarkers  or when comparing triple-negative to non-triple-negative tumors .When stratifying analyses by tumor immunohistochemistry Fig. , IL-8 waP-homogeneity = 0.90), although significant associations were observed only in tumors <  = 2 cm and 2–5 cm (< = 2 cm: ORper SD increment = 1.63 (1.09–2.44); 2-5 cm: ORper SD increment = 1.43 (1.01–2.02) but not for larger tumors (> 5 cm: ORper SD increment = 1.17 (0.85–1.61)).When exploring associations by tumor size, little evidence of heterogeneity was observed for IL-6 and breast cancer risk , P-homogeneity = 0.06; TNF-α: ORper SD increment = 1.58 (1.10–2.26), P-homogeneity = 0.003). Leptin and adiponectin were positively associated with risk in smaller tumors (leptin: ORper SD increment = 1.56 (1.07–2.28); adiponectin: ORper SD increment = 1.37 (0.99–1.89)), with P-homogeneity = 0.03 for both biomarkers), while negative associations were observed for larger tumors, only significant for leptin in tumors of 2 to 5 cm (ORper SD increment = 0.66 (0.45–0.97)).For IL-8 and TNF-α, a significant positive association was observed only for the largest tumors . However, when using a cut-off of 30 kg/m2, a significant interaction with IL-8 ; ≥ 30 kg/m2: ORper SD increment = 1.49 (1.05–2.15)), and a borderline significant interaction with TNF-α ; ≥ 30 kg/m2: ORper SD increment = 1.42 (1.05–1.95)) were observed. When restricting the analysis to women not using exogenous hormones, associations remained unchanged, except for a positive association between IL-8 and breast cancer risk overall in all multivariate models (BMI-adjusted: ORper SD increment = 1.22 (1.01–1.48); WC-adjusted: ORper SD increment = 1.22 (1.02–1.46); fully adjusted: ORper SD increment = 1.46 (1.13–1.90), not tabulated).When stratifying analyses on BMI using 25 kg/mThis analysis of seven inflammatory biomarkers and breast cancer risk in a case–control study in premenopausal women from Latin America showed that IL-6 and TNF-α were positively associated with breast cancer risk when accounting for adiposity and other breast cancer risk factors. While the association with IL-6 was consistent across different breast cancer subtypes and tumor sizes, the association with TNF-α was limited to larger tumors. A positive association was observed for IL-8 in ER-negative and in larger tumors, and in hormones non-users at blood donation, while a negative association was observed for IFN-γ in ER-positive tumors only. Leptin and leptin/adiponectin ratio showed negative associations with breast cancer risk in univariate models, that were attenuated when adiposity was accounted for. When associations were explored by tumor size, however, negative associations were observed in larger tumors (> 2 cm) and positive associations in smaller tumors.The positive association between IL-6 and breast cancer risk is in line with the only prospective study of biomarkers of chronic inflammation and risk of premenopausal breast cancer we identified . In thisIL-8 concentrations were previously reported to be higher in breast cancer cases than in healthy women , 28, witIL-10 is known to be an anti-inflammatory cytokine reported to have mostly anti-tumor properties, based on experimental and clinical data, but pro-tumor actions have sometimes been reported based on in vitro and animal studies . Higher P-trend = 0.02) [Our finding of a positive association between TNF-α and breast cancer is consistent with several case–control studies showing higher serum TNF-α concentrations in breast cancer patient than controls , 36–39.  = 0.02) . This pr = 0.02) .IFN-γ has anti-tumor properties, i.e., pro-apoptotic, anti-angiogenic, and promotor of anti-tumor immune response , that arIt is not clear why in our study we observed a significant association in ER-positive tumors only. However, since the heterogeneity between tumors with different estrogen receptors was not statistically significant, the observed difference in association could result from a lack of statistical power in the ER-negative subgroup.In the present work, leptin was inversely associated with breast cancer risk in both univariate and fully adjusted model, however this association lost significance when the univariate model was adjusted for BMI. Leptin is a pro-inflammatory adipokine  stronglyWe did not observe any association of adiponectin with breast cancer risk, consistent with findings from three prospective studies in premenopausal women , 45, 48 Strengths of PRECAMA, the largest ongoing multicentric population-based case–control study of premenopausal breast cancer in Latin America, include the use of standardized protocols for collection of a wide range of lifestyle and anthropometric factors. We were therefore able to account for adiposity, which is strongly associated with breast cancer risk in this population , and othA major limitation is the case–control design of this study, that does not enable to draw any conclusion regarding the temporality of the observed associations or their potential causality. However, cases were recruited, and biological samples collected, before the start of any treatment, and tumor size was carefully recorded, which allowed us to analyze the associations accounting for disease advancement. Another limitation is that sample size was sometimes limited for subgroup analysis and resulted in limited statistical power. In addition, a total of 7 biomarkers and one ratio were analyzed overall and in stratified analyses without adjustment for multiple tests, which increases the risk of chance findings and warrants caution in the interpretation of our findings. Lastly, the generalization of these results to other age groups or geographical regions requires careful consideration.In conclusion, this work showed that IL-6 and TNF-α are positively associated with breast cancer in premenopausal women in Latin America. While associations did not vary by hormone receptor status, except for IL-8, heterogeneity by tumor size was observed for several biomarkers . These findings add useful information for the characterization of the obesity and metabolic health and breast cancer in premenopausal women. However, given the complex interplay between biomarkers of inflammation and cancer development, largest studies of prospective design are needed to confirm these findings in premenopausal women.Where authors are identified as personnel of the International Agency for Research on Cancer/ World Health Organization, the authors alone are responsible for the views expressed in this article and they do not necessarily represent the decisions, policy or views of the International Agency for Research on Cancer/ World Health Organization.Additional file 1. Main characteristics of cases by hormone receptor status, and for triple-negative tumors (Supplementary Table 1). Associations between IL-6 and TNF-alpha and breast cancer risk allowing for non-linear effects  ; Abbreviations: BMI body mass index; ER Estrogen receptor; HER2 human epidermal growth factor receptor 2; IFN-γ interferon γ; IL-6 interleukin 6; IL-8 interleukin 8; IL-10 interleukin 10; OR odds ratio; PR progesterone receptor; SD standard deviation; TNF-α tumor necrosis factor α. (DOC 109 KB).


A number of modifiable risk factors have been designated as being causally related to cancer development. We aimed to estimate the percentage of incident cancer cases diagnosed in persons aged ≥25 years in Texas in 2015, overall and by race/ethnicity, that were attributable to these modifiable risk factors.We calculated population attributable fractions (PAFs) for cancers attributable to thirteen modifiable risk factors using prevalence data from the Texas Behavioral Risk Factor Surveillance System and the National Health and Nutrition Examination Survey, as well as relative risks estimates from prior studies and cancer incidence data from the Texas Cancer Registry.Overall, 32.3% of all incident cancers  in 2015 were attributable to modifiable risk factors. Men (35.1%) had a numerically higher overall PAF than women (29.5%). Tobacco smoking caused the highest proportion of cancers (18.4%), followed by overweight and obesity (6.6%) and excess alcohol consumption (2.9%). Non-Hispanic Blacks had a numerically higher overall PAF (36.8%) than non-Hispanic Whites (31.9%) and Hispanics (31.7%). Further, non-Hispanic Blacks had the highest combined PAFs for 85% of cancer sites analyzed, including lung/bronchus and mouth/pharynx/larynx.Modifiable risk factors cause about one third of cancers in Texas. Non-Hispanic Blacks are especially affected by an excessive preventable cancer burden. Through extensive epidemiological and experimental research, it is well established that cancer initiation and progression is driven by the interaction of host, environmental, and dietary or lifestyle factors . EnvironMonographs Programme  infection, human herpesvirus-8 [HHV-8] infection), and inadequate diet . Furthermore, we stratified our analysis by major racial/ethnic subgroups of the population to reveal any disparities in the cancer burden attributable to modifiable risk factors. We chose Texas as the setting for our study because the diversity of this minority-majority population allows for a unique opportunity to explore the role of race/ethnicity as an effect modifier in preventable cancer burden.We therefore aimed to estimate the population attributable fractions (PAFs) of cancer cases diagnosed in Texas in 2015 that were attributable to modifiable risk factors, overall as well as by race/ethnicity. We included in this analysis modifiable risk factors for which there is either “strong” evidence according to WCRF/AICR  [The Texas Cancer Registry provided counts of incident invasive cancers diagnosed in Texas in 2015, overall and by age group , sex, and race/ethnicity  [After identifying the modifiable risk factors for which there is either “strong” evidence according to WCRF/AICR or “sufficient” evidence according to IARC, relative risk (RR) estimates for each modifiable risk factor were taken directly from the WCRF/AICR’s Third Expert Report if available , or fromH. pylori infection, prevalence data were only available from survey years 1999–2000 [Depending on availability, we obtained weighted prevalence estimates of each modifiable risk factor from the Texas Behavioral Risk Factor Surveillance System (BRFSS) ,7 or the999–2000 ; however999–2000 , so we ux is the population proportion at exposure category x (category of modifiable risk factor) and ERRx is excess relative risk [x = (median consumption within exposure category x)–(reference level for exposure), and for protective exposures, Gx = (reference level for exposure)–(median consumption within exposure category x) [Standard formulae were used to calculate PAFs for each modifiable risk factor by cancer site, age, sex, and race/ethnicity: ive risk . For mos=(RRx−1) ; for alcg×Gx)−1) . For det that RR . For pron(1RR)y) . For detegory x) . HPV is egory x) . Likewisegory x) , we assuPAFs were multiplied by incident cancer counts to obtain the number of excess cancer cases attributable to each modifiable risk factor, stratified by sex, age group, and race/ethnicity. The assumed ten-year latency period was accommodated by pairing prevalence estimates and derived PAFs in each age group with the cancer incidence age group ten years older . Age-weighted percentages of incident cancers attributable to each modifiable risk factor were calculated by cancer site, sex, and race/ethnicity; for cancers that were specified by histological subtype or sublocation , the number of attributable cancers of that specific histological subtype or sublocation was used as the numerator, while the overall cancer site incidence was used as the denominator . For each modifiable risk factor, all excess cases across all cancer sites were summed to estimate the percentage of all incident cancer cases  diagnosed in Texans aged ≥25 years in 2015 that were attributable to each modifiable risk factor.We used previously described methods to calculate PAFs combining all risk factors ,19. For This study was conducted according to the guidelines laid down in the Declaration of Helsinki. All data were publically available. The research activities of this study were deemed as exempt by Baylor College of Medicine Ethics Committee as data were de-identified and aggregated. A waiver of consent was obtained because the study was a retrospective analysis and all data were aggregated and de-identified.In 2015 in Texas, 103,408 cases of cancer (excluding BCC and SCC of the skin) were diagnosed in adults aged ≥25 years, of which 51,472 cases were in men and 51,936 cases were in women. Most cases occurred in non-Hispanic Whites , followed by Hispanics  and non-Hispanic Blacks . An additional 3,532 cases were diagnosed in individuals collectively grouped as being of other races/ethnicities.Overall, 32.3% of all new cancers  diagnosed in Texas in 2015 were attributable to the thirteen modifiable risk factors analyzed in this study . The risH. pylori infection caused more cancers in Hispanics, and tobacco smoking caused more cancers in non-Hispanic Whites than other racial/ethnic subgroups. There was no difference in overall PAF for red meat consumption across racial/ethnic groups. In men, tobacco smoking had the highest overall PAF across the major racial/ethnic subgroups, followed by overweight and obesity; however, the third highest overall PAF in non-Hispanic Black men was for HCV infection, as opposed to excess alcohol consumption in non-Hispanic White and Hispanic men. In women, tobacco smoking had the highest overall PAF in non-Hispanic Whites and non-Hispanic Blacks, followed by overweight and obesity and insufficient physical activity; yet, in Hispanic women, the highest ranked PAFs were for overweight and obesity, tobacco smoking, and then HPV infection.When stratified by race/ethnicity, 36.8% of cancers in non-Hispanic Blacks were attributable to modifiable risk factors, compared to 31.9% in non-Hispanic Whites and 31.7% in Hispanics Figs –4. For cFor all risk factors combined, the cancer sites with the highest calculated PAFs  were lung and bronchus (84.7%); mouth, pharynx, and larynx (72.3%); and esophagus (66.8%) for all races/ethnicities combined . This trIn this analysis, we estimated that 32.3% of all cancers (excluding BCC and SCC of the skin) diagnosed in 2015 in Texans aged ≥25 years were attributable to modifiable risk factors, with a numerically greater proportion of attributable cancers in men (35.1%) than in women (29.5%). Tobacco smoking caused the highest proportion of cancers (18.4%) compared to the other risk factors analyzed, regardless of race/ethnicity. Non-Hispanic Blacks had a numerically higher overall proportion of cancers attributable to modifiable risk factors (36.8%) than non-Hispanic Whites (31.9%) and Hispanics (31.7%). When all risk factors were combined, the cancer site with the highest calculated PAF  was lung and bronchus, overall (84.7%) and for each racial/ethnic subgroup.Our results contribute to the expanding literature on cancer burden attributable to preventable behaviors and environmental factors. A recent study in the U.S. estimated that 42.0% of cancers (excluding nonmelanoma skin cancers) in 2014 in American adults ≥30 years were attributable to potentially modifiable risk factors . In the Although similar studies have been carried out in the U.S. and other parts of the world, none have expounded the differences in cancer burden across major racial/ethnic subgroups of the population. We found that non-Hispanic Blacks had relatively more cancers caused by modifiable risk factors (36.8%) than non-Hispanic Whites (31.9%) and Hispanics (31.7%). Further, non-Hispanic Blacks also had more of the numerically highest factor-specific PAFs (46% of the risk factors) and site-specific PAFs (85% of the cancer sites) than either Hispanics or non-Hispanic Whites, which explains the higher overall PAF for all risk factors combined and all cancers. These findings have major public health implications as they suggest that, overall, non-Hispanic Blacks are disproportionately burdened by preventable cancers compared to other racial/ethnic subgroups. Yet, closer inspection of PAFs specific to sex, cancer site, and/or risk factor may suggest otherwise, thus emphasizing the importance of such a thorough and detailed investigation. For example, in Hispanic women, overweight and obesity contributes the highest proportion of the cancer burden compared to other risk factors, which is different than for women of other racial/ethnic subgroups, or even men. By appreciating which modifiable risk factors are most pertinent to cancer prevention at certain cancer sites for a specific racial/ethnic subgroup, this information may be strategically employed by cancer prevention programs in order to more effectively customize and prioritize prevention efforts. Ultimately, a more targeted approach may help achieve cancer health equity.Our study has several limitations. Although our emphasis was on racial/ethnic effect modification, and we used race/ethnicity-specific prevalence data and incidence data, we were unable to use race/ethnicity-specific RR estimates, which may have influenced comparisons. Additionally, because we based our study in Texas, we attempted to use a state-level database for our prevalence estimates; however, when Texas-specific data were unavailable, we used NHANES data and assumed that these national data were representative of the Texas population. While it is possible that there are differences in the prevalence of infections and dietary risk factors from BRFSS and NHANES, this limitation does not impact the internal validity of our analysis, as estimates for each racial/ethnic subgroup came from the same data source. Other assumptions made throughout this analysis may also be considered limitations; for example, reference levels chosen may not actually represent the pathophysiological point of increased risk of cancer development, and latency periods may differ by cancer site and are not clearly established ,15,19–21In conclusion, we found that nearly one third of all cancers diagnosed in Texas in 2015 were attributable to modifiable risk factors, with a greater proportion of preventable cancers diagnosed in non-Hispanic Blacks than other racial/ethnic subgroups. Yet, given we were unable to include all potential preventable risk factors in the current analysis , our estimate of overall PAF is likely on the lower end of the preventable cancer burden in Texas. In general, greater prevention efforts focused on tobacco smoking, overweight/obesity, alcohol consumption, and physical activity would be invaluable to reducing cancer incidence and may also lessen long-standing racial/ethnic cancer disparities. While striving to achieve cancer health equity, cancer prevention programs should remain conscientious of racial/ethnic differences in cancers attributable to modifiable risk factors in order to more successfully prioritize and personalize primary cancer prevention.S1 Fig(PPTX)Click here for additional data file.S2 Fig(PPTX)Click here for additional data file.S3 Fig(PPTX)Click here for additional data file.S4 Figa. Combined PAFs (%) by cancer site for incident cancers attributable to all modifiable risk factors in Texas in 2015 for men of all races/ethnicities aged ≥25 years. b. Combined PAFs (%) by cancer site for incident cancers attributable to all modifiable risk factors in Texas in 2015 for women of all races/ethnicities aged ≥25 years.(PPTX)Click here for additional data file.S5 Figa. Combined PAFs (%) by cancer site for incident cancers attributable to all modifiable risk factors in Texas in 2015 for non-Hispanic White men aged ≥25 years. b. Combined PAFs (%) by cancer site for incident cancers attributable to all modifiable risk factors in Texas in 2015 for non-Hispanic White women aged ≥25 years.(PPTX)Click here for additional data file.S6 Figa. Combined PAFs (%) by cancer site for incident cancers attributable to all modifiable risk factors in Texas in 2015 for non-Hispanic Black men aged ≥25 years. b. Combined PAFs (%) by cancer site for incident cancers attributable to all modifiable risk factors in Texas in 2015 for non-Hispanic Black women aged ≥25 years.(PPTX)Click here for additional data file.S7 Figa. Combined PAFs (%) by cancer site for incident cancers attributable to all modifiable risk factors in Texas in 2015 for Hispanic men aged ≥25 years. b. Combined PAFs (%) by cancer site for incident cancers attributable to all modifiable risk factors in Texas in 2015 for Hispanic women aged ≥25 years.(PPTX)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.S5 Table(DOCX)Click here for additional data file.S6 Table(DOCX)Click here for additional data file.S7 Table(DOCX)Click here for additional data file.S8 Table(DOCX)Click here for additional data file.S9 Table(DOCX)Click here for additional data file.S10 Table(DOCX)Click here for additional data file.S11 Table(DOCX)Click here for additional data file.S12 Table(DOCX)Click here for additional data file.S1 File(DOCX)Click here for additional data file.


Primary Sjögren’s syndrome (pSS) and breast cancer are a highly prevalent autoimmune disease and malignancy, respectively, both occurring predominantly in females. Whether there is a link between these two diseases is uncertain. We conducted a systematic review and meta-analysis to investigate the risk, incidence, and mortality of breast cancer in patients with pSS.2.We systematically searched Embase, PubMed, and Web of Science on January 31, 2022 to identify the study that assessed risk, incidence, or mortality of breast cancer in pSS. The fixed or random-effects models were applied to pool the effect estimates based on heterogeneity measured by Cochran’s Q-test and Higgins’ IP=0.646) and mortality  of breast cancer; however, when stratified by geographic region, we found that patients with pSS in Asian countries  and Argentina  had an elevated risk of breast cancer, while pSS in Europe was associated with a reduced risk . The pooled result from 28,635 female pSS patients indicated that the incidence of breast cancer was 2.15 (95% CI: 1.33-3.50) per 1000 person/years.Ten studies involving 725,805 participants and 64,836 pSS patients were included in our analysis. The pooled result showed that, overall, pSS was not associated with the risk (SIR=0.92, 95%CI: 0.66-1.29, This study suggests that there may be geographical differences in the association between pSS and breast cancer risk; patients with pSS in European countries are associated with a lower risk of breast cancer, while Asia and Argentina are the opposite. Future research is needed to further characterize the effect of pSS on breast cancer risk and the pathophysiological mechanisms underlying this association to unravel the complex relationship between the two. Primary Sjögren’s syndrome (pSS) is one of the most common systemic autoimmune diseases characterised by dryness of exocrine glands such as the lacrimal and salivary glands . The pSSFemale breast cancer has overtaken lung cancer as the leading cause of cancer incidence worldwide by 2020 . Both pSThis systematic review and meta-analysis was reported based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines . The proTwo authors systematically searched Embase, PubMed, and Web of Science databases for relevant papers published up to January 31, 2022. To minimize the risk of omitting potentially eligible papers, we combined subject terms and free words for pSS and neoplasm to develop search strategies Table S1Studies that met the following criteria would be considered: (a) the study population was breast cancer or pSS patients; (b) the risk, incidence, and/or mortality of breast cancer in pSS patients were the result of interest; (c) the effect size and corresponding confidence intervals (CI) of the above endpoints were provided; (d) For comparisons of breast cancer incidence and mortality in pSS vs. non-pSS populations, the study should be comparative cohort or case-control design; for assessment of breast cancer incidence in pSS, single-arm studies or cohort studies that provided breast cancer incidence in pSS cohort were considered.Case reports/series and reports with fewer cases in studies with overlapping data would be excluded.Two authors independently extracted the following data of eligible studies: first author, publication year, region, age, gender, source of study population, study period, study design, identification of patients with pSS and breast cancer, follow-up, endpoints, effect estimates, and confounding factors considered.The quality of eligible studies was assessed by the Newcastle-Ottawa scale (NOS), with an NOS score >7 considered to be a high-quality study.Q-test and Higgins’ 2I. Random-effects models were used to pooled effect sizes to provide a more conservative risk estimate when 2I > 50% or P< 0.1, otherwise the fixed-effects model was used. The stability of the pooled results was assessed by excluding one study at a time and then re-combining the remaining studies. Funnel plots and Begg’s and Egger’s tests were performed to check for risk of publication bias and small study effects, respectively.All statistical analyses were performed by Stata/MP 16.0. We checked heterogeneity of published studies by Cochran’s The pre-developed search strategy initially identified 8911 records. A total of 10 studies were ultimately included in the meta-analysis based on the inclusion and exclusion criteria –16. The The ten eligible studies involved 725,805 participants, of whom 691,387 were women and 64836 had pSS. Nine studies explored the risk of breast cancer in patients with pSS, three assessed the incidence of breast cancer, and two compared the mortality of pSS patients with other patients among breast cancer. There were four studies each in Asia and Europe, and two studies from the USA and Argentina. Seven studies were population-based cohort or case-control studies with sample sizes ranging from 1516 to 409,929; three were hospital-based cohort studies ranging from 157 to 430. The mean follow-up time ranged from 3.1 to 11.1 years. The detailed characteristics of the included studies are presented in With the exception of one single-arm study assessing incidence (NOS score of 6) , all stu2 =I84.6%, P<0.001), so the random-effects model was used. The overall pooled result from the random-effects model indicated that breast cancer risk was comparable between pSS and non-pSS patients  . In the non-specific gender subgroup, breast cancer risk was elevated in pSS patients , which may be due to common risk factors, with female involvement predominating in both diseases. Of note, the correlation between pSS and breast cancer risk appeared to be influenced by geographic regions. When stratified analysis was performed according to study location, we found a significantly lower risk of breast cancer among pSS patients in European countries , while significantly increased risks in Asian countries  and Argentina ; no correlation between pSS and breast cancer risk was observed in the USA . For studies that adjusted only for age and sex, the pooled result was not significant , while the overall result from studies that considered confounders beyond these two  showed a lower risk of breast cancer in patients with pSS . Furthermore, hospital-based studies observe a higher risk of pSS than population-based studies . No significant differences were observed at different ages and follow-up , suggesting that it may be the source of heterogeneity  , with significant heterogeneity   per 1000 person/years. Patients with pSS did not have an increased mortality rate in female breast cancer.A meta-analysis published in 2014 showed no association between pSS and breast cancer risk  . Compare2I > 50%), but interestingly, the significant heterogeneity disappeared in the subgroups analysis according to geographic region, suggesting a relatively consistent trend within this stratification. Multivariate meta-regression analyses further determined geographical region may be the source of heterogeneity. All four studies from Europe showed a trend towards a lower risk of breast cancer in patients with pSS . In fact, there are many other confounders associated with breast cancer, such as weight, smoking, age at marriage, and family history, that have not been adjusted for in all published studies.A noteworthy finding was that studies adjusting for confounders more than age and gender overall showed a lower risk of breast cancer in pSS, with additional factors considered including study period, socioeconomic status, annual hospitalization rate, chronic disease, race, area, alcoholism, parity, and/or age at first childbirth; these studies were mainly from Europe , 15, 16.Pinteraction=0.246). Moreover, an important hypothesis is that there were effects of therapeutic agents for pSS including glucocorticoids, non-steroidal anti-inflammatory drug (NSAIDs), methotrexate, biologics, and disease modifying anti-rheumatic drugs on breast cancer risk. It has been shown that NSAIDs appear to have a protective effect on breast cancer, while immunosuppressive therapy may increase the risk of developing opportunistic infections and cancer  criteria. Although differences in medical practice between countries are difficult to quantify, an interesting finding is that studies based on a single reference hospital tended to report a higher relative risk of breast cancer compared to population-based studies ; studies from Turkey and Argentina with participants recruited from tertiary care centers both showed an effect size of more than 2 for the correlation between pSS and breast cancer risk, which suggests that the severity and activity of pSS may affect breast cancer risk . Howeverd cancer , 23. ThuOverall, due to the underrepresentation of populations outside Europe and the heterogeneity of study designs in different regions, the association between pSS and breast cancer risk may be coincidental, so the pooled results need to be interpreted with caution. However, given the alarmingly increasing incidence of breast cancer and the large population of patients with pSS, additional attention should be paid to such risk in regions where pSS has been found to be a possible risk factor for breast cancer. Future studies can further explore the correlation between the relevant clinical, histological, and laboratory features of pSS patients and breast cancer risk, which may help clinicians accurately identify those at high risk of developing breast cancer; periodic surveillance and rigorous screening of this population can facilitate early diagnosis and appropriate therapeutic management of the malignancy, thereby improving survival rates. In addition, the inverse correlation between pSS and breast cancer risk found in European studies suggests that there may be pathophysiological interactions between pSS and breast cancer, and further basic and translational research on the underlying mechanisms may provide new targets for breast cancer prevention and treatment.This study followed a pre-planned but unpublished protocol that can be accessible by contacting the corresponding author. The primary study objective was to examine the risk, incidence, and mortality of breast cancer in patients with pSS; the secondary objective was to characterize the association between pSS and breast cancer, so stratified analyses according to age, gender, region, study design, and follow-up were pre-planned. Analyses that were not performed after seeing the preliminary results were sensitivity analyses for incidence and mortality endpoints and funnel plots for publication bias; the exclusion of these analyses were due to the concern about lack of statistical power resulting from the relatively small number of eligible studies. Added analyses included stratified analyses based on confounding factors and multivariate meta-regression analyses; these analyses were performed to assess the effects of confounding factors on outcomes and to identify causes of heterogeneity. In addition, as discussed above, we also described as comprehensively as possible the effects of various confounding factors on published studies and carefully interpreted the findings to provide a balanced and critical perspective on the subject.The main limitation of this study is the lack of detail on the association between pSS and breast cancer. Because there are no studies specifically focusing on breast cancer among patients with pSS, almost all studies on this topic examined the risk of multiple malignancies in patients with pSS or the risk of breast cancer in multiple autoimmune diseases; of them, breast cancer or pSS is only a subanalysis. Therefore, the characteristics of breast cancer risk in patients with pSS are unclear; factors affecting the association between pSS and breast cancer risk, including the effects of treatment, severity/activity, and duration of pSS, remain to be elucidated. Many other confounding factors such as weight, smoking, family history, alcohol consumption, age at marriage, and gynecological history may bias our results. Representation of the population outside Europe is relatively insufficient. In addition, data on the prognosis and mortality of breast cancer patients with concurrent pSS are scarce. This study protocol is not pre-registered, but we have completed the pre-planned analyses as far as possible when sufficient data is available, so the results are unlikely to be biased due to methodology. Finally, although Begg’s and Egger’s tests indicated no small study effect, potential risk of publication bias may still exist.This study suggests that there may be geographical differences in the association between pSS and breast cancer risk; patients with pSS in European countries are associated with a lower risk of breast cancer, while Asia is the opposite. Future studies are needed to explore the characteristics of the association and underlying pathophysiologic mechanisms between pSS and breast cancer, particularly the impacts of disease severity, activity, and management of pSS, which may provide new insights into breast cancer prevention and treatment.The original contributions presented in the study are included in the article/Conception and design: ZS, ML. Acquisition of data: JW, JD, Statistical analysis: ZY, XL. Drafting of manuscript: JD, ML, ZS, RX. Critical revision of the manuscript: ZS. All authors contributed to the article and approved the submitted version.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.