We used cross-sectional data from 68 BRCA1/2 germline mutation carrying women participating in the randomized, prospective, controlled clinical study LIBRE-1. Assessments included cardiopulmonary exercise testing, medical and lifestyle history plus socioeconomic status. Additionally, the participants completed a psychological questionnaire regarding their attitude, subjective norms, perceived behavior control and intention towards PA. A multivariate logistic regression model was used to identify predictors for participants reaching their age- and sex-adjusted VO2peak reference values. 22 participants  33–46) were cancer-unaffected and 46 cancer-affected . The strongest predictor for reaching the reference VO2peak value was attitude towards PA . None of the other predictors showed a significant association. A positive attitude towards PA seems to be associated with VO2peak, which should be considered in developing therapeutic and preventive strategies.Physical activity (PA) helps prevention and aftercare of sporadic breast cancer (BC), cardiopulmonary fitness (CPF) being an age-independent predictor of tumor-specific mortality. Therefore, we wanted to identify predictors of CPF (represented by peak oxygen uptake: VOTrial registrations: NCT02087592; DRKS00005736. BRCA1/2 is substantially elevated compared to the general population. For BRCA1 mutation carriers, the risk estimate for breast cancer by age 80 is 72% and 44% for ovarian cancer. For BRCA2 mutation carriers, the lifetime risk estimate for breast cancer is 69% and for ovarian cancer 26%1.The risk for cancer in women with a germline pathogenic variant of BRCA1/2 mutation carriers are more likely to suffer from cardiovascular diseases2. Initial studies indicate, that VO2peak could be a predictor of overall mortality3 and breast cancer specific mortality4 in sporadic breast cancer patients. Cardiopulmonary fitness, measured by peak oxygen consumption (VO2peak), is an assessment of cardiovascular function. A recent investigation found an inverse association between VO2peak and several biomarkers linked to tumorigenesis5. A reduced VO2peak favors tumor-related side effects, e.g. cancer related fatigue or reduced quality of life6. A high level of physical activity leads to a higher VO2peak and thus better cardiopulmonary fitness. In a meta-analysis involving 571 cancer patients, a supervised exercise training was associated with significant improvements in VO2peak7.In addition to the high risk of developing cancer, there is also increasing evidence that 2peak in the large and fast-growing population of cancer survivors are of great clinical relevance. Hence, we wanted to identify factors, which influence physical activity behavior and consequently the VO2peak. Another two components are relevant in this undertaking, which are explained below.Therefore, strategies to prevent or restore a weak VOBRCA1/2 germline mutation carriers may be mitigated by physical activity, especially during adolescence and early adulthood9. In a retrospective, longitudinal case–control study of 886 BRCA1/2 mutation carriers, Lammert et al. (2018) showed that women moderately active between the ages of 12–17 years had a 38% lower risk of developing premenopausal breast cancer compared to less active women10. A further retrospective cohort study (725 BRCA1/2 mutation carriers) reported a 42% risk reduction for developing breast cancer among participants with increasing levels of sports activity prior to, but not after, age 3011.Studies indicate that the high risk of cancer in 14.The theory of planned behavior (TPB) includes the determinants attitude, subjective norm, perceived behavioral control and intention, and is validated for predicting physical activity behavior in breast cancer survivors. Studies have shown an association between attitude, the subjective norm, perceived behavioral control, and intention with regard to the current physical activity behavior in breast cancer survivors2peak in this high-risk group of BRCA1/2 mutation carriers.We wanted to examine the association of the aforementioned factors  in particular, adjusted for other available co-factors in this study with VO15.The LIBRE-1 study  is a multi-centric, prospective, randomized and controlled clinical trial. It is registered in the German Study Register for Clinical Trials (DRKS No.: DRKS00005736), as well as the study registry of the National Institutes of Health (NCT No.: NCT02087592) on 14/03/2014. The study was conducted according to the requirements of national laws and ICH E6 Good Clinical Practice (GCP) of June 1996. The recommendations of the Declaration of Helsinki in its current version were followed as well as the German Federal Data Protection Act (BDSG). The ethics review board of the Klinikum Rechts der Isar of the Technical University of Munich has approved the study protocol (Reference 5686/13). All participating centers and all participants provided written informed consent and the study design and methods are reported in detail elsewhereBRCA1/2 germline mutation were recruited from three centers of the German Consortium for Hereditary Breast and Ovarian Cancer . Inclusion criteria were: pathogenic germline variant in the BRCA1 or BRCA2 gene, age ≥ 18 years and written informed consent. Exclusion criteria were: presence of metastatic tumor disease, life expectancy < 3 years, Body Mass Index (BMI) < 15 kg/m2, clinically limiting cardiopulmonary disease and Karnovsky-Index  < 60%, blood pressure at rest > 160/100 mmHg. Further exclusion criteria were significant orthopedic or psychological problems that would not allow the participant to partake in a group intervention, or a current pregnancy15.In the LIBRE-1 study, 68 cancer-unaffected or previously breast and/or ovarian cancer-affected women with a 2peak) and assessed by cardiopulmonary exercise testing (CPET). The CPET was a ramp protocol  with the target of exhausting them with a respiratory exchange ratio (RER) > 1.05. During the CPET, the participants were asked about their received perception of exertion (RPE) based on the Borg scale every 2 min. The Borg scale ranges between 6  to 20 16. The VO2peak indicates the maximal number of milliliters of oxygen the body can utilize per minute when under workload. The VO2peak can be used as a criterion for evaluating a person's physical endurance. In the present analysis, the aim was to determine which participants could reach their VO2peak reference value. The VO2peak reference value was calculated with the SHIP study formula . This formula considers the gender, age, height and weight of the participant in calculating their VO2peak reference value17. In addition to the VO2peak, the determination of the oxygen uptake (VO2) at the first ventilatory threshold (VT1) as a criterion for the aerobic capacity was also assessed18.Cardiopulmonary fitness was determined by the peak oxygen uptake (VOInactive in youth and (2) participants who indicated that they were exactly as active or more active than their peers were classified as Active in youth.The physical activity in youth was determined with a clinical baseline interview using an international questionnaire, clinical baseline questionnaire. Participants’ activity ages 10 to 19 years were categorized into two groups: (1) Much less active and somewhat less active than their peers were classified as 19. The TPB is validated for predicting physical activity behavior in breast cancer survivors21. The TPB assumes that positive attitudes such as "exercise is fun" and subjective norms "my family thinks I should exercise more", as well as perceived behavior control "to exercise regularly is for me very feasible", influence intentions. Intentions such as "I intend to exercise regularly” are assumed to be mediators of the influence of subjective norms and attitudes on behavior. TPB's summary statement is that people intend to behave, if they rate it positively, believe that important other individuals feel that they should do it, and that they perceive it to be under their own control19. Participants completed a psychological questionnaire “Rating physical activity and nutrition” (Bewertung körperlicher Aktivität und Ernährung = BKAE) based on the TPB. The 9 sections of the exercise-related part of the BKAE questionnaire include 44 questions on a 7-step scale and were standardized for the analysis so that the 4 TPB determinant scores  would be comparable.The questionnaire for the assessment of the rating towards physical activity was developed based on the theory of the planned behavior of Icek Ajzen22. For the analysis we used an adaptation of the Winkler-Stolzenberg Index (WSI = ((education-1)/6) + employed − smoker) based on the following items with values between 0 and 1.323:owhether the participant was currently employedowhether the participant was a smokerothe participant’s educational level In the clinical baseline questionnaire the socioeconomic status was also determined2peak performance in the study sample, a multivariate logistic regression was carried out, where the dependent variable was the dichotomized VO2peak . The independent variables were the TPB determinants , cancer-affected status (binary), physical activity in youth (binary) and the socioeconomic status’ value (as explained in detail above). In order to illustrate the aims and methods of this analysis, we have added a graphical abstract . For all analyses, an alpha level of 0.05 was used to determine statistical significance (two-tailed).All statistical analyses were carried out using R version 3.4.2  of June 1996. The recommendations of the Declaration of Helsinki in its current version were followed. The LIBRE-1 study protocol has been reviewed and approved by the ethics committees of the three participating centers .24.Of the 68 participants, 46 (68%) were breast and/or ovarian cancer-affected of whom 44 had suffered from breast cancer and two from ovarian cancer, with one suffering from both. Of these 44 breast cancer-affected participants, 4 also indicated that they had had other cancers. Median time since the primary tumor diagnosis in this group was 3 years with a range of 0—23. The median age of the cancer-affected women at study entry was 44 years (IQR 35–50) compared to 40 years (IQR 33–46) in the other group. Further detailed comparisons and statistical testing between the two groups can be found in the publication by Kiechle et al. describing the first results from the LIBRE-1 study2peak of 26 ml/min/kg in both groups, while median VO2 at VT1 as its percentage was 61.9% in the cancer-affected group and 60.9% in the cancer-unaffected group (Table Results from the CPET showed a median VOCancer-unaffected participants had lower standardized median attitude and subjective norms scores in comparison to cancer-affected participants (attitude: 0.04 versus (vs) 0.30, subjective norms: − 0.37 vs 0.01), while their median intention and perceived behavior control scores were higher compared to cancer-affected group   3.0; 95% confidence interval (95% CI) 1.3–8.4; p = 0.021). The intention  scores showed a trend for higher chances of reaching the VO2peak reference values, whereas perceived behavior control  and subjective norms  scores showed the opposite tendency.As illustrated in Table 2peak reference values . Those who indicated they were active in their youth had lower odds of reaching their VO2peak reference values .Cancer-unaffected participants and those with a higher socioeconomic status had higher odds of reaching their VO2peak) in cancer-unaffected and cancer-affected BRCA1/2 mutation carriers.The purpose of this analysis was to identify predictors of cardiopulmonary fitness  was the only significant predictor found in our analysis  for reaching the participant’s VO2peak reference value, which may indicates that attitude towards physical activity should be considered when implementing physical activity programs, which consequently influences the cardiopulmonary fitness. A qualitative study by Smith et al. reported that participants' attitudes toward physical activity were negatively influenced by receiving little information from the oncologist and health professionals. A lack of social support and structured exercise programs were also identified as barriers to physical activity implementation26. Therefore, treatment strategies for BRCA1/2 mutation carriers should contain information dissemination and education about the beneficial effects of physical activity before and after tumor occurrence to improve the participants’ attitude towards physical activity. In addition, cancer patients should be educated that physical activity is feasible and safe during tumor therapy. For this, it can be advantageous to include, inform and educate people around the participant accordingly.In our analysis, the intention, subjective norms, and perceived behavioral control played a subordinate role for reaching the VO27. Therefore, we included physical activity in youth in our analysis, however no association was found. It should be noted that the activity in youth was only surveyed retrospectively in our analysis and did not include any information on the duration and intensity of the respective physical activity.It has been shown that age, sex, health status, self-efficacy and motivation are associated with higher levels of physical activity. Baumann et al. described that the personal attitude towards exercise and physical activity behavior in youth and adolescence and the intention to maintain a physical activity behavior are important components, which influence current physical activity2peak is determined by genetics, gender, body composition, physical activity behavior and age28. The VO2peak decreases by about 8–10% per decade from the 30th year of life29. In cancer patients, VO2peak has been found to be about 30% lower compared to healthy peers7. The reference values of VO2peak were age-adjusted so that the age-related decrease in cardiopulmonary fitness was implicitly included in our analysis. We found no significant association between cancer status and reaching the VO2peak reference value in our study.VOBRCA1/2 mutation carriers would reach their VO2peak reference value less often compared to the cancer-unaffected participants. Usually, there are great differences between cancer-unaffected and previously cancer-affected women depending on the respective tumor therapy30. Various tumor therapies in combination with a sedentary lifestyle additionally led to marked impairments in cardiopulmonary fitness and may not recover after treatment32. This circumstance has not yet been investigated in BRCA1/2 mutation carriers. However, some studies have shown that the knowledge of an increased cancer risk or a positive BRCA genetic test induces lifestyle changes35. Positive lifestyle changes, which promote a higher amount of physical activity can lead to a better cardiopulmonary fitness. This could be even more important especially after a cancer diagnosis and might explain our results.We had expected that previously cancer-affected 20. Whether this also applies to cancer-affected BRCA1/2 mutation carriers and has an influence on the VO2peak still needs to be investigated. If these findings are validated, the attitude should be taken into account in the treatment and preventive measures for BRCA1/2 mutation carriers with regard to cancer risk and prognosis.For sporadic breast cancer patients, the TPB might be a viable framework to promote physical activity successfully during cancer treatment. However, the salient beliefs of breast cancer patients concerning physical activity were different from those of the cancer-unaffected populationPhysical activity in youth and adolescence was recorded retrospectively and only in comparison with the peer group. This meant that no quantitative information was available on the extent, duration, intensity and type of physical activity. In future, this information should also be collected in order to ensure better comparability and significance with regard to physical activity in youth.As our results come from a feasibility study it should be noted that the informative value is limited by the small sample size and must be interpreted accordingly.2peak status in cancer-unaffected and cancer-affected BRCA1/2 mutation carriers. Physical activity during adolescence and the health and socioeconomic status did not influence VO2peak levels. These relationships need to be investigated in a larger sample size, for instance in the ongoing LIBRE-2 study. If these results are verified, future concepts and studies should consider the attitude towards being physically active in managing BRCA1/2 mutation carriers.In conclusion, a positive attitude towards physical activity seems to play a role in the current VO


Is family history of breast cancer (FHBC) associated with mammographic breast density in premenopausal women?In this cohort study of 14 415 premenopausal women, volumetric percent density was significantly higher in women with FHBC compared with women without FHBC, and the odds of having dense breasts was significantly higher in women with FHBC compared with women without FHBC.The findings highlight the heritable component of mammographic breast density and underscore the need to begin annual screening early in premenopausal women with a family history of breast cancer. This cohort study investigates the association of family history of breast cancer and mammographic breast density in premenopausal women using both quantitative and qualitative measurements. Family history of breast cancer (FHBC) and mammographic breast density are independent risk factors for breast cancer, but the association of FHBC and mammographic breast density in premenopausal women is not well understood.To investigate the association of FHBC and mammographic breast density in premenopausal women using both quantitative and qualitative measurements.This single-center cohort study examined 2 retrospective cohorts: a discovery set of 375 premenopausal women and a validation set of 14 040 premenopausal women. Data from women in the discovery set was collected between December 2015 and October 2016, whereas data from women in the validation set was collected between June 2010 and December 2015. Data analysis was performed between June 2018 and June 2020.Family history of breast cancer (FHBC).The primary outcomes were mammographic breast density measured quantitatively as volumetric percent density using Volpara (discovery set) and qualitatively using BI-RADS (Breast Imaging Reporting and Data System) breast density . Multivariable regressions were performed using a log-transformed normal distribution for the discovery set and a logistic distribution for the validation set.Of 14 415 premenopausal women included in the study, the discovery set and validation set had similar characteristics . In the discovery set, participants who had FHBC were more likely to have a higher mean volumetric percent density compared with participants with no FHBC (11.1% vs 9.0%). In the multivariable-adjusted model, volumetric percent density was 25% higher  in women with FHBC compared with women without FHBC; and 24% higher  in women who had 1 affected relative, but not significantly higher in women who had at least 2 affected relatives  compared with women with no relatives affected. In the validation set, women with a positive FHBC were more likely to have dense breasts (BI-RADS 3-4) compared with women with no FHBC . In the multivariable-adjusted model, the odds of having dense breasts (BI-RADS 3-4) were 30% higher  in women with FHBC compared with women without FHBC; and 29% higher  in women who had 1 affected relative, but not significantly higher in women who had at least 2 affected relatives  compared with women with no relatives affected.In this cohort study, having an FHBC was positively associated with mammographic breast density in premenopausal women. Our findings highlight the heritable component of mammographic breast density and underscore the need to begin annual screening early in premenopausal women with a family history of breast cancer. However, only a few studies have investigated the associations between these 2 strong risk factors for breast cancer in premenopausal with conflicting results.16 Two studies observed that a FHBC was positively associated with having dense breasts. They, however, did not stratify analyses by menopausal status or race, which is important because the only study in Asian women reported no association of FHBC with mammographic breast density.16 Furthermore, these studies evaluated mammographic breast density using Breast Imaging Reporting and Data System (BI-RADS).15 As many breast health centers begin to adopt volumetric measures of mammographic breast density in clinical practice, it is crucial to have data on the associations of FHBC with volumetric measures such as volumetric percent density. In addition, a greater understanding of the association of FHBC with mammographic breast density in premenopausal women could help identify high-risk women whose mammography screening strategies may need to be refined.Mammographic breast density and breast cancer share similar genetic pathways,The main objectives of our study were to determine the association between FHBC and mammographic breast density in premenopausal women and to clarify whether these associations are consistent or differ by the type of mammographic breast density measure used . To accomplish this, we (1) investigated the association of FHBC with mammographic breast density using Volpara (quantitative measures); (2) validated the findings within a larger study population using BI-RADS ; (3) further stratified analyses by race to determine whether race modifies the associations of FHBC on mammographic breast density.STROBE) reporting guideline.17The study population included 2 groups of women recruited at the Joanne Knight Breast Health Center (BHC) at Washington University School of Medicine and Siteman Cancer Center. The discovery set consisted of 383 premenopausal women recruited during routine screening mammograms in 2016. Mammographic breast density was measured quantitatively using Volpara. The validation set consisted of 14 040 premenopausal women recruited while undergoing screening and diagnostic mammograms between June 2010 and December 2015. Mammographic breast density was measured qualitatively using BI-RADS. We received study approval through the Washington University School of Medicine institutional review board, and all study participants provided informed consent. The study followed the Strengthening the Reporting of Observational Studies in Epidemiology  premenopausal at the time of mammogram; we identified women as premenopausal if they had a regular menstrual period within the preceding 12 months, no prior history of bilateral oophorectomy, and not used menopausal hormone therapy; (2) no serious medical condition that would prevent the participant from returning for her annual mammogram in 12 months, (3) not pregnant; (4) no history of cancer, including breast cancer; (5) and no history of breast augmentation or reduction. On the day of mammographic screening, participants completed a questionnaire with detailed information on demographics, reproductive and anthropometric measures, and breast cancer-related risk factors.Among the 383 premenopausal women in the discovery set, our current study is limited to 375 women with complete data. A detailed description of the study population has been provided previously,20 We also measured dense volume, and nondense volume using Volpara. Volpara volumetric percent density values range from 0.5% to 34.5% with a typical median of around 6%.21 In comparison with BI-RADS categories, Volpara volumetric percent density values less than 3.5% correspond to BI-RADS a: almost entirely fatty; volumetric percent density at least 3.5% and less than 7.5% correspond to BI-RADS b: scattered areas of fibroglandular density; volumetric percent density at least 7.5% and less than 15.5% correspond to BI-RADS c: heterogeneously dense; volumetric percent density at least 15.5% correspond to BI-RADS d: extremely dense.22 Our primary outcome in the discovery set was volumetric percent density, measured using Volpara .Women scheduled for mammogram at the BHC from 2010 to 2015 were mailed study flyers 2 weeks to 1 month before their visitation. Among a total of 56 423 women who underwent routine screening with mammograms, we excluded participants if they were postmenopausal (n = 31 893) at the time of mammogram. We identified women as premenopausal using the same criteria used for the discovery set. We additionally excluded women who were currently pregnant, had a history of breast cancer, and had a history of breast augmentation or reduction (n = 3551). Lastly, participants were excluded if they had missing information regarding mammographic breast density (n = 6266) or race (n = 473). Thus, 14 040 premenopausal women were eligible for analysis.24 For analytic purposes, we dichotomized women as either having dense (heterogeneously and extremely dense breast) or nondense .Our outcome of interest in the validation set was BI-RADS breast density. Women were categorized into BI-RADS a: almost entirely fatty; BI-RADS b: scattered areas of fibroglandular tissue; BI-RADS c: heterogeneously dense; BI-RADS d: extremely dense.Our primary exposure of interest was FHBC. We defined FHBC as participants with a first-degree relative  with a history of breast cancer. Therefore, FHBC was categorized into a dichotomous variable of yes and no. We further stratified this variable among women with FHBC in mothers or sisters alone. Lastly, we analyzed the total number of affected relatives with an FHBC: 0 = participants with zero first-degree relatives with a history of breast cancer; 1 = one mother or sister with breast cancer, 2 = mother and at least one sister with a history of breast cancer.Baseline demographic variables included self-reported race , age (continuous), and education . Education was obtained only in the discovery set. Health behaviors included ever use of oral contraceptives (yes or no) and current alcohol use (yes or no). Lastly, breast cancer-related risk factors included in this study were age at menarche, parity, age at first childbirth, and current body mass index (BMI). We calculated BMI as current weight in kilograms divided by current height in meters squared.2 test for categorical variables. We performed a series of analytic multivariable models to test the associations between FHBC with (1) quantitative measures of mammographic breast density  and (2) and qualitative measures of mammographic breast density (using BI-RADS categories). Quantitative measures were natural log-transformed to ensure the normality of the residuals in all regression models. Two multivariable linear regression models were used to evaluate the associations between FHBC and log-transformed volumetric percent density, dense volume, and nondense volume. Model 1 was adjusted for current age  and BMI (continuous). Model 2 was adjusted for current age , BMI (continuous), parity , race , age at menarche , and alcohol consumption (yes or no). β coefficients and 95% CIs from the regression models were evaluated and back-transformed for easier interpretation. In our second series of models, we performed logistic regression analyses with BI-RADS breast density as the dependent variable and FHBC as the primary explanatory variable. We adjusted these models similar to the aforementioned linear regression models for quantitative mammographic breast density measures. Results from logistic regression were presented as odds ratios (ORs) and associated 95% CIs. To determine if there were any race-specific differences in the effects of FHBC on mammographic breast density, we a priori decided to perform all linear and logistic regression models further stratified by race .Descriptive statistics are presented as mean and standard deviation (SD) for continuous variables, and number and relative frequencies (%) for categorical variables. We examined differences in participants’ characteristics by FHBC using ANOVA for continuous variables and χ25 thus we performed sensitivity analysis stratifying our validation cohort into 2 subcohorts based on when they had their mammograms: pre-2013  and post-2013 . All the analyses were performed using SAS software version 9.4 (SAS Institute) from June 2018 to June 2020. All tests were 2-tailed, and statistical significance was considered as P < .05.The American College of Radiology BI-RADS released the 5th edition in 2013,Of 14 415 premenopausal women included in the study, the discovery set and validation set had similar characteristics  .3 vs 77.8 cm3).Among the 375 eligible participants in the discovery set, 87 women (23.2%) had a FHBC . CurrentAmong the 14 040 eligible participants in the validation set, 2153 (15.3%) had a FHBC . SimilarP < .001) among women who had a FHBC than women with no FHBC. Women with a positive FHBC in mothers alone had a 31% higher volumetric percent density  compared with women with had no FHBC in mothers. Having a positive FHBC in sisters alone was not associated with higher volumetric percent density, likely due to the small number of women who had a positive FHBC in sisters alone (n = 26). Additionally, we analyzed the number of first-degree relatives with FHBC and volumetric percent density. Volumetric percent density was 24% higher  in women who had 1 affected relative, but not statistically significantly higher in women who had at least 2 affected relatives compared with women with no relatives affected .The associations between FHBC and volumetric percent density are presented in P < .001) in women with a positive FHBC compared with women with no FHBC in the multivariable-adjusted model. There were no associations between FHBC and nondense volume  among women with a positive FHBC compared with women with no FHBC in the multivariable-adjusted model. The odds of having dense breasts were 28% higher  among women with FHBC in mothers alone compared with women with no FHBC in mothers alone . The oddThere was no effect modification by race . Our study participants’ characteristics, however, are different from the study by Ziv et al.14. We focused on premenopausal women, this is important because hormone changes after menopause cause the breast tissue to become less dense.27 Moreover, we excluded women with any history of cancer, whereas their analysis included women with personal breast cancer history.14 Hence, our work provides new information about the associations between FHBC and mammographic breast density among premenopausal women.Our findings complement findings in a previous study, which also reported positive associations between FHBC and mammographic breast density. Ziv et alOur study has several strengths. First, our discovery cohort recruited participants among women attending annual routine screening mammography at the Joanne Knight BHC, which enhances generalizability. At the same time, we used the larger validation set with 14 040 participants to validate our findings in the discovery set, enhancing reproducibility. Second, our large sample size in the validation set allows us to thoroughly assess the associations among women with FHBC in mothers alone or sisters alone. In addition, our validation data set included women who had their mammograms pre- and postimplementation of the BI-RADS 5th edition, and as a result we were able to explore whether differential classifications of BI-RADS were associated with odds of having dense breasts. Lastly, to the best of our knowledge, this is the first study to investigate the associations of FHBC with volumetric measures of mammographic breast density.28 Second, the proportion of women with more than 1 first-degree relative with breast cancer was small , but we improved our power to find a statistically significant association between mammographic breast density and the FHBC in the large validation set. In addition, we did not have information on age at diagnosis for affected relatives. Studies suggested that the first-degree relative’s age at diagnosis varies the association between FHBC and the risk of breast cancer.30 Data from the Nurses’ Health Study indicates that women with a family member diagnosed with breast cancer before age 50 years of age had an increased risk of breast cancer compared with women with family members diagnosed at older ages.30 Our study population is mainly non-Hispanic White , and non-Hispanic Black or African American  with BMI in the overweight/obese categories, hence, our findings are likely to be generalizable to these groups. This is, however, representative of the population of the greater St. Louis region ,31 where most of our study participants come from. Lastly, within both the discovery and validation sets, the mean age was approximately 47 years; as a result, some of these women were closer to being perimenopausal.Our study also has some limitations. First, the prevalence of participants with a positive FHBC history in 2 study sets were higher  than the National Health Interview Survey for premenopausal women (aged 40 to 49 years: 8.4%). This is because women who had a positive FHBC are more likely to undergo annual screening.This cohort study found that having an FHBC was positively associated with mammographic breast density in premenopausal women, and the association was consistent and robust irrespective of whether qualitative or quantitative measures of mammographic breast density were used. Our findings indicate that women’s FHBC may play an important role in mammographic breast density, and underscore the need to begin annual screening mammogram at an early age in premenopausal women with an FHBC.


Patient-reported outcomes (PROs) can provide valuable information about drug benefit-risk tradeoffs from the patient perspective and are particularly important to patients with breast cancer due to its symptoms and adverse events from breast cancer treatments. The United States Food and Drug Administration (U.S. FDA) has acknowledged PROs as important approval endpoints used in clinical trials of cancer drugs. However, previous studies found that PROs are rarely mentioned in cancer drug labels, a widely used and trusted source of information about drugs. Our objectives were to compare PRO data reported in FDA labeling versus FDA medical review documents for breast cancer drugs approved in the U.S. between 2000 and 2019 to identify possible causes for PRO-data labeling exclusions.We included new molecular entities (NMEs) and biologic license applications (BLAs) initially approved for breast cancer treatment by the FDA between 1/1/2000 and 12/31/2019. Product labeling and FDA medical review documents were collected from the FDA-Approved Drugs database (Drugs@FDA). From these resources, details on PRO measures used in trials, design of trials using PRO measures, PRO-endpoint status, analytical methods, and FDA reviewer comments regarding PRO measurement were extracted.Of 633 FDA-approved drugs, 13 were indicated for breast cancer treatment; none of their prescribing information contained information about PROs. However, 11 of 13 (85%) included PRO measures and endpoint information in FDA medical review documents. PRO measures were used in 14 different clinical trials, and FDA reviewers’ comments regarding PRO measurement were related to lack of meaningfulness and clinical significance, lack of content validity, and inadequate analytical methods.Despite the importance of PROs to patients with breast cancer, PRO measures were only described in FDA medical review documents of breast cancer drugs, but not in drug product labeling. Therefore, it appears that PRO data are often collected in breast cancer trials, but have not been methodologically acceptable to FDA reviewers. Collaborative efforts between the FDA and industry are warranted to increase the number of breast cancer drug applications with appropriate use of PRO measures and endpoints. Prescribing information and other labeling are documents prepared by pharmaceutical companies and approved by the United States Food and Drug Administration (U.S. FDA). Prescribing information delivers key safety and efficacy information about prescription drugs and biological products –3. AmongThe FDA has put growing efforts into incorporating patient perspectives in drug development and evaluation. The FDA released the draft version of a PRO guidance for industry in 2006 and the final version in 2009 –9, whichIn breast cancer, patient perspectives and PROs are particularly important. The number of new cases of breast cancer in the U.S. reached approximately 270,000 in 2019, making breast cancer the most common cancer among women . Also, iFurthermore, according to the Voice of the Patient report on breast cancer, which summarizes information obtained through an FDA- or externally led meeting to understand patient perspectives for those living with breast cancer, adverse events from breast cancer treatments also significantly impact patients’ daily lives . AdverseHowever, previous studies report that PROs are rarely mentioned in labels of different cancer drugs including breast cancer drugs , 22. ForThese studies suggest that PROs may be collected in drug development, but not included in labeling. Since labeling needs to deliver key safety and efficacy information about drugs concisely, labeling often lack details compared to journal publications and trial documents such as study protocols and clinical study reports. However, such a gap may have significant clinical implications because the labeling  should deliver the information required to achieve what is best for patients. It is unclear how often information about PROs is excluded in labeling and reasons for exclusion, which may not be solely due to the need for conciseness. Therefore, this study’s objectives are to compare the PRO-endpoint data reported in FDA approved labeling with that reported in FDA review documents for breast cancer drugs approved in the U.S. between 2000 and 2019 and identify potential reasons for exclusion of PRO data in labeling.Compilation of the Center for Drug Evaluation and Research (CDER) NME Drug and New Biologic Approvals” from the FDA was used [This study included new molecular entities (NMEs) and biologic license applications (BLAs) initially approved for the treatment of any types of breast cancer by the FDA between January 1, 2000 and December 31, 2019. To identify these products, the “was used . The docwas used , 25.After identifying eligible products, documents were collected from Drugs@FDA, the FDA-Approved Drugs database, for each product: original labeling, the latest version of labeling , and FDA medical review documents . Since labeling can change over time, both original labeling and the latest version of labeling were examined to capture any difference due to revisions. The medical review documents contain the FDA’s evaluation of the trial documents  submitted by manufacturers for market approval. Information includes but is not limited to objectives, design, and research methods for pivotal trials and data supporting safety/efficacy of the study medications. Therefore, the documents can provide information about clinical trials beyond labeling and journal publications , 27 and From these documents, the following information about PRO measures and endpoints were searched and extracted: a) name of the PRO measure, b) design and characteristics of the clinical trial in which it was used, c) PRO-endpoint status , d) analytical methods for PRO data analysis, and e) comments from FDA reviewers on deficiencies related to the PRO measure or endpoint (if applicable). Analytical methods for PRO data analysis and FDA reviewers’ comments were extracted to understand how the PRO measure was utilized and identify potential causes for exclusion from the labeling. These analytical methods include but are not limited to comparison of time to deterioration/progression and comparison of score changes on PRO measures from baseline.After identifying PRO measures from labeling and medical review documents, each PRO measure was classified as symptom-related, function-related, or both. These categories were created based on concepts of interest commonly measured by different PRO measures , 28, 29.The FDA approved a total of 633 NMEs and BLAs between 2000 and 2019. Of the 633 drugs, 13 were initially approved for breast cancer treatment  were phase 3, and 6 (43%) were double-blind trials. Only one (7%) trial was a single-arm trial. Among trials with comparators, seven (54%) were active-controlled, and five (38%) were placebo-controlled. One trial (8%) compared different doses of the same treatment.N = 12, 86%) or an exploratory endpoint . Of the 14 trials, five (36%) analyzed their PRO data by comparing time to HRQoL deterioration or symptom progression, and six (43%) analyzed by comparing score changes from baseline. Three (21%) analyzed their PRO data using both methods. Four (29%) described strategies for handling the missing values in PRO measures. Two excluded the data from the analysis if there were missing values , and the other two used proration, unless 50% or more questions are unanswered .None of the clinical trials used PRO measures as the primary endpoint. PRO measures were used as either a secondary endpoint  insufficient psychometric properties of PRO instruments , b) inadequate analytical methods , and c) lack of clarity on the provided PRO data . Sometimes, such deficiencies led to disagreements between industry and the FDA regarding PRO endpoints. For example, PROs measuring global quality of life were among the secondary endpoints of a Kisqali’s pivotal trial , but FDA reviewers disagreed and considered the PROs as exploratory endpoints. These deficiencies align with potential reasons why the FDA may have rejected inclusion of PRO data for labeling claims suggested by previous studies that investigated review documents , 45. ForOur study’s findings suggest that breast cancer drugs approved as recently as 2019 still had these deficiencies in their PRO measure selection, data collection, and/or analyses. In particular, FDA reviewers commented on some PRO instruments’ lack of content validity . EvidenLess commitment to PRO endpoints from the industry has been suggested to contribute to suboptimal compliance with PRO guidance . For exaAdditionally, several studies state that inconsistencies within the FDA could contribute to such suboptimal compliance with the PRO guidances and lead to a low number of PRO labeling claims , 53. ForWith the passage of the 21st Century Cures Act in 2016, the FDA has begun to release required guidance documents related to patient engagement in drug development, including PROs , 14, 55.Additional research is needed to uncover the true, specific causes for there being no PRO-endpoint information included in breast cancer drug labeling over the last 20 years. There appears to be suboptimal compliance with the 2009 PRO guidance and additional recommendations. Nevertheless, it is unknown if that is because the guidance is not being followed by industry; if the guidance is unclear and, therefore, hard to follow; if the guidance is being interpreted differently by industry and/or across FDA divisions; or some combination of all of these explanations. If the FDA deemed the content validity or sensitivity of the PRO measures as lacking, providing additional justification and/or clarification to the industry may be a simple step to improve the compliance with the 2009 PRO guidance. Hence, a collaborative effort between the FDA and the industry is warranted to get to the heart of the issue(s). It would help to clarify the confusion around the use of PRO endpoints and promote PRO labeling claims. Efforts to improve the inclusion of PRO measure data in labels will be difficult to achieve without this information.It is important to note that this study has several limitations. First, this study did not examine breast cancer drugs approved through supplemental new drug application (sNDAs) such as Tecentriq or Lynparza; thus, it does not provide a complete picture of PRO labeling claims in all breast cancer drugs during the study period. While their inclusion may have provided additional insights, Drugs@FDA is often inconsistent in providing regulatory information related to drugs approved through sNDA.Second, this study only examined trials listed in medical review documents, which were mainly Phase 3 pivotal trials. Therefore, this study cannot make inferences about how PRO measures have been used in the entire breast cancer drug development process . Typically, Phase 1 and 2 trials do not include PROs or include them as part of PRO development and testing, as there is no intention to include the data in labeling.Third, this study did not examine statistical methods used for PRO endpoints. In the medical review documents, details on the statistical methods used for PRO endpoints were often limited to the descriptions of PRO measures used and the endpoints. Also, they were less comprehensive than the description of primary endpoints, as all the identified PROs were used as either secondary or exploratory endpoints. Examination of trial documents such as statistical analysis plans, clinical study reports, or study protocols may provide further insight into the statistical methods used for comparing PRO data.Notwithstanding the limitations, this study has several strengths. Compared to Hao et al., which previously examined labels and approval documents of 16 drugs commonly used for breast cancer treatment, this study examined all drugs initially approved for breast cancer treatment between 2000 and 2019. Therefore, this study provides a general overview of how PRO measures have been used and analyzed in breast cancer drug development specifically. This provides insight for future drug development endeavors in breast cancer. Not only was labeling investigated, but also the medical review documents. As a result, the review of these documents revealed some potential underlying causes that might have led to the exclusion of PRO information from the labeling.Despite the importance of PROs to patients with breast cancer, the labeling of breast cancer drugs lack information on PROs. PRO measures are often used in breast cancer drug development and described in medical review documents, but not included in labeling. This discrepancy appears to be because the PRO tools and/or analytical methods used for PRO measure data analysis have been considered inadequate by FDA reviewers. Research is needed investigating the specific causes for why PRO data have not been included in labeling and would likely be enhanced through collaborative efforts between the FDA and the industry. This is especially relevant as more PRO-related guidance documents  from the FDA are being released in the near future.


The aim of the study was to explore the lived experiences of people diagnosed with cancer from rural and remote areas of Western Australia, who utilise supported accommodation services whilst undergoing treatment in the capital city (Perth). Methods A qualitative phenomenological approach was used in this study. Ten participants were recruited using purposive sampling, who were aged between 35–65 years, were diagnosed with cancer within the previous three months and used accommodation services within the past 12 months. Semi-structured in-depth interviews were conducted with a duration of approximately 45–60 min via Zoom, FaceTime or phone call. Interview data was transcribed, thematically analysed and coded into relevant themes. Results: Three overarching themes were derived from the interviews–“It’s harder to have cancer when you have to relocate for treatment,” “The paradoxical experience of staying at the accommodation,” and “Feeling grateful for the support offered’. Conclusions: People diagnosed with cancer who have to relocate during treatment require emotional, logistical, and social supports. Cancer accommodation services are essential in enabling individuals to continue engaging in meaningful occupations and maintain their quality of life. Our study highlights the need for cancer accommodation services to consider the complex needs of individuals completing treatment for cancer in locations away from their usual homes. Cancer is a major cause of illness and death across all ages and the greatest contributor to the fatal burden of disease in Australia . In 2019Many people diagnosed with cancer who live in rural and remote locations incur additional expenses related to cancer treatment resulting in increased financial demands ,9. TheseIn WA there are very limited accommodation options for individuals with cancer who are required to relocate to Perth for treatment. These options are limited to a small group of not for profit organisations including Cancer Council Western Australia (CCWA) or short-term rental accommodation. Individuals with cancer who live more than 100 kms away from relevant services and are required to relocate to Perth for treatment are eligible to stay at one of the CCWA lodges. The lodges offer subsidised accommodation for both individual and family members. Individuals who are eligible for the Patient Assisted Travel Scheme (PATS) may receive further financial support to assist with accommodation costs and these are then offered free of charge in some instances. There is very limited research about the experiences of people with cancer from rural areas who are required to access treatment in Perth, WA. The aim of this study is to explore the lived experiences of people diagnosed with cancer from rural and remote areas of WA who utilise CCWA accommodation services whilst undergoing treatment in Perth. The findings from this research will assist to ensure unmet needs are addressed and services are developed to ensure these needs are met.Phenomenology is an interpretive form of qualitative research that aims to study the nature of an experience from the perspective of the individual experiencing the phenomenon, known as the “lived experience” ,13. PhenTen participants were recruited through purposive sampling. Purposive sampling increases the probability for observing the phenomenon of interest . ParticiOriginally, data collection was planned as in-person interviews at the accommodation service, however due to the restrictions of COVID-19, interviews transitioned to phone or video calls. Two researchers (E.N. and J.S.) completed the interviews which occurred between April and July 2020. A copy of the participant information statement, consent form, and interview questions were emailed to all participants prior to their interview. Due to the restrictions brought about by COVID-19, written consent was difficult to attain, therefore consent was obtained verbally at the beginning of each interview. Interviews were digitally recorded with the participant’s consent and stored according to the confidentiality agreement outlined in the participant information statement. Recruitment ceased when no new concepts were identified during data analysis and saturation of the data was considered to have been reached .The trustworthiness of this study was guided by the four criteria outlined by Lincoln and Guba 1985), which include credibility, dependability, confirmability and transferability ., An int85, whichThematic analysis described by Braun and Clarke (2006) was used to analyse the data . Two resAfter themes were explored and described, all researchers came to a consensus on the most relevant and appropriate labels to describe the themes identified in the data.Ethical approval was granted from the Curtin Human Research Ethics Committee (HREC) in December 2019. With changes in the method of data collection due to COVID-19, an amendment was submitted then approved on 18 February 2020 (HREC number: HRE 2020-0030). Information about the study  was provided to the participants for them to make an informed decision and provide consent prior to participating in the study. While interviews were not expected to create distress, prior to commencing the interviews, participants were provided with a range of strategies should they become distressed. These strategies included taking a break during the interview or rescheduling and providing information about the Cancer Council helpline and counselling services.Ten participants were interviewed  came in and checked on me once or twice and then call every couple of days just to make sure I was okay.”—P3Participants spoke highly of their experiences with various external services. The volunteer-run “Look Good Feel Better” service aims to improve consumer’s confidence with accessories, makeup, and outfits. The Solaris Centre, located in the main hospital, is a volunteer service that provides an array of complimentary therapies. The Patient Assistance Transport Scheme (PATS) is a government-funded program that provides eligible Australian residents residing in rural locations with financial assistance to access treatment away from home as well as social support and symptom management. Participant three appreciated the assistance with arranging flights and accommodation.“Can you just book the flights? Can you just book the lodge? Can you just take care of everything? And they did so, all of those technicalities of traveling 2000 kilometres were taken care of.”—P3Participants reported that the routine experienced while at the accommodation was very different. This created mixed feelings of being well supported but not being able to complete their usual activities and routines. Participants three and four noted boredom due to the change of location and responsibilities.“Oh, everything was turned upside down and I couldn’t work. I couldn’t do anything. … But then for the rest of the day, I had nothing to do and just have to kind of find ways to fill my time. Whereas at home I would be busy going to groups and doing all sorts of different things and working and taking care of the kids.”—P3“But I think it was probably easier to control there because I didn’t have to do a lot of meal preparation that was basically just taking the meal out of the freezer and then taking it down to the kitchen and zapping it in the microwave. So, it wasn’t the same as is at home.”—P4Participants had the opportunity to reflect on their cancer journey post-treatment and reported a change of perspective regarding their experiences. Three subthemes were explored: gratitude for services provided, the impact of having support from family and friends, and suggestions to improve service provision.Some participants highlighted the significant impact CCWA accommodation had on their cancer treatment in Perth. CCWA fostered a sense of “family” within its accommodation, which encouraged participants to give back, allowing others to have the same experience. Participants reported donating gardening supplies, hand-crafted items, and monetary donations. These donations enable CCWA to provide the same or even improved level of service to future guests, ensuring continuation of the service.“I got interested in the little vegie patch there. So I did some donations of some compost and some other stuff to go there because somebody else had sort of instigated getting the garden and had been running it.”—P5“I mean, you know, I know they might be struggling now but I gave them a donation anyways.”—P1Support from family, friends and others living in the participant’s local community played a significant role in mitigating some of the barriers discussed previously including assistance with pets, vehicles, homes and family members allowing them to focus on treatment. Some participants relied on others with similar experiences to assist them emotionally. Participants whose family or friends were with them during treatment stated this support was invaluable.“My sister looked after my dog...My mechanic looked after my vehicle, my four-wheel drive...My mum would ring me every day at the Lodge...I didn’t really have anything to worry about.”—P7“And like I said, my parents came out here as well to support and my in-laws came out to Broome to support us as well. So, during the month that I had to be gone, they were there as well to help for that time and afterwards to help with the kids and with my husband.”—P3The findings of this research demonstrate that temporarily relocating to the city from a rural or remote location for treatment impacts the individual with cancer due to a broad range of emotional, practical, social and financial factors. The availability of the accommodation services mitigated the severity of these factors, highlighting the pivotal role the service played. The supports offered by the accommodation service emphasised the need and value of the service.The literature reports many similar barriers for people with cancer and their families . These bSocial support was discussed as a major component of the experience among the participants. The availability of social support is pivotal in the wellbeing of individuals with cancer and is seen to be significant in providing much needed hope . ResultsThe results revealed a range of different experiences for guests staying at CCWA accommodation. Many participants highly valued the facilities that supported them to attend to basic care needs, desired activities and promoted social interactions. Despite being far from home, participants adapted to their environment and found a sense of normality by engaging in meaningful occupations that replicated their normal routine. People with chronic illness are resilient and can make adaptions to their lifestyle and social supports, which is crucial for developing self-empowerment and social capital ,29. PrioIn contrast, while the accommodation service permitted the continuation of meaningful occupations, temporarily relocating for treatment brings inevitable disruption to the usual routine that hindered the participants’ experience. Occupational roles are a set of culturally and socially agreed upon behaviours that comprise an individual’s primary life habits, routines, and rituals . For somThere is limited evidence on the experiences of people receiving services such as those offered by CCWA. Our study has revealed new insight into the nature of the accommodation service provision, the environment created and the impression it left on the participants. Feeling comfortable and safe while undergoing treatment is likely to assist people with cancer feel at ease and in control ,33. All COVID-19 has caused immense strain in healthcare services and is an ongoing unprecedented concern globally . The panThe emotional, practical and social supports provided by the accommodation service can assist to alleviate some of the concerns associated with temporarily relocating to the city for treatment. Thus, having access to suitable accommodation is essential to improve their quality of life during this critical time by helping guests engage in meaningful occupations and meet their daily needs in alternative living situations. Our study highlights the need for accommodation services to continue providing essential resources and offer additional social, occupational and emotional supports for people undergoing treatment for cancer.Limitations of this study include generalisability of findings. The study was conducted in a single setting. Despite CCWA having two accommodation facilities, most participants were from the lodge located within the main hospital. Participants were predominantly females and between the ages of 55 and 65. Questions pertaining to the participants’ racial and ethnic backgrounds were not asked and it is suggested that future studies could include this information. Potential exploration of these issues backgrounds could offer further comparison and contrast to the experiences of these individuals during their relocation for cancer treatment. These factors suggest that the range of experiences documented in our findings cannot be concluded as exhaustive. The study could be strengthened by exploring the experiences of guests from the other lodge, males, younger and older individuals, people from other rural and remote areas accessing a different metropolitan cancer accommodation, as well as people at different stages of cancer. Although our findings do not reflect the experiences of all people with cancer, previous research accentuated the additional burden people from rural and remote areas face in comparison to people from metropolitan areas ,6,10,11.Australia has an ageing population, and with the incidence of cancer increasing as people age, the demand for suitable care and supports, together with the associated economic costs, cancer is a growing concern for the Australian community . It is p


This study aims to evaluate the association and dose-response between triglyceride-glucose (TyG) index and breast cancer.This is a multicenter case-control study conducted in six public referral hospitals in Indonesia. Cases are individuals aged 19 years or above who were diagnosed with breast cancer within 1 year of diagnosis, based on histopathology and immunohistochemistry. Controls were recruited from corresponding hospitals. TyG index was determined by the formula: ln (fasting TG [mg/dl] × fasting glucose [mg/dl]).p < 0.001). When compared with TyG quartile of Q1, Q4 was associated with an OR of 2.42 , p < 0.001, Q3 was associated with an OR of 1.53 , p < 0.001, Q2 was associated with an OR of 1.39 , p = 0.002 for the risk of breast cancer. The dose-response relationship was nonlinear (p < 0.001). On univariate analysis, smoking , use of contraception , alcohol consumption , and TyG Index >8.87  were associated with risk of breast cancer. Independently associated with increased risk of breast cancer included smoking , use of contraception , and TyG Index >8.87 There were 212 participants in the breast cancer group and 212 participants in the control group. TyG index was higher in patients with breast cancer (median 8.65  vs. 8.30 , TyG index was associated with breast cancer in a nonlinear dose-response fashion. Breast cancer is the most common cancer worldwide , 2. TherRecent studies suggest that insulin resistance was associated with breast cancer and may affect its prognosis , 10. Eug2/(P1−P2)2.This was a multicenter case-control study conducted in six public referral hospitals in Indonesia, namely, Ciptomangunkusumo Hospital in Jakarta, Dharmais Cancer Center in Jakarta, Arifin Achmad General Hospital in Pekanbaru, Dr. Kariadi Hospital in Semarang, Wahidin Sudirohusodo Hospital in Makassar, and Prof. Dr. WZ. Johannes Hospital in Kupang. Recruitment of study participants was performed consecutively between April to August 2019. A total of 432 women consisting of 216 cases and 216 controls were recruited. The sample size was derived from proportion estimate of two population with the formula (Z1−α/2√2PQ + Z1−β√P1Q 1+P2Q2)The inclusion criteria for the case group are as follows (1): individuals aged 19 years or above who were diagnosed with breast cancer based on histopathology and immunohistochemistry between April to August 2019. The maximum year postdiagnosis was 1 year (2), patients with breast cancer that has not received therapy, (3) can read, understand, and provide consent, and (4) complete medical record and paraffin block. Those with incomplete questionnaire data were excluded. Controls were recruited from corresponding hospitals. Inclusion criteria for the control group were as follows: (1) women aged 19 years or above (matched 5 years), (2) in healthy conditions based on anamnesis and physical examination results, (3) no evidence of cancer or history of cancer, and (4) no evidence of chronic disease. Most individuals recruited as controls were hospital employees. The study was approved by Ethical Committee of Health Research in the Faculty of Medicine, Universitas Indonesia, Rumah Sakit Cipto Mangunkusumo, Jakarta, Indonesia (450/UN2.F1/ETIK/2018).Data were collected through medical records and a self-administered structured questionnaire. The questionnaire included information on age at menarche, smoking history, reproductive risk factors , family history of malignancy, alcohol consumption, and nutrition intake.TyG index was determined by the formula: ln (fasting TG [mg/dl] × fasting glucose [mg/dl]) .2), normal weight (18.5–24.9 kg/m2), and overweight and obese (>24.9 kg/m2).Weight and height were measured to the nearest 0.1 kg and 0.5 cm according to standardized procedures. The study participants wore light clothes and no shoes during the measurement. Body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters. BMI was classified according to WHO into underweight , while nonparametric data are presented as median, minimum, and maximum values (median (min-max)). Comparison of categorical variables was tested using Chi-square test. Continuous variables were compared using independent p < 0.05. Data were managed and analyzed using SPSS 25.0  and STATA® version 16 .The TyG was divided into four quartiles, and the odds ratios (ORs) for each quartile were calculated using the first quartile as the reference. Restricted cubic spline model was constructed using four knots at 7.9, 8.3, 8.7, and 9.4; nonlinearity of the dose-response curve was also assessed. The ORs for TyG index and breast cancer were calculated using logistic regression. A cutoff point for TyG index was set at the beginning of the fourth quartile for multivariate analysis. Multivariate logistic regression was used to test the association between breast cancer and each independent variable. The results are presented as ORs with 95% confidence intervals (CIs). Statistical significance was defined as There were 212 participants in the breast cancer group and 212 participants in the control group. The baseline characteristics of the participants in this study can be seen in p < 0.001). The patients were divided into four quartiles based on the TyG index, namely, Q1 (7.09–8.12), Q2 (8.13–8.47), Q3 (8.48–8.86), and Q4 (8.87–10.90); comprising of 101, 108, 108, and 107 patients, respectively. When compared with TyG quartile of Q1, Q4 was associated with an OR of 2.42 , p < 0.001, Q3 was associated with an OR of 1.53 , p < 0.001, Q2 was associated with an OR of 1.39 , p = 0.002 for the risk of breast cancer (p < 0.001) , use of contraception , alcohol consumption , and TyG Index >8.87  , use of contraception , and TyG Index >8.87    . In the The association between breastfeeding and breast cancer has been contradictive. The present study found a null association of breastfeeding with breast cancer. This finding is in line with several studies , 37. In A few studies have shown association between smoking and breast cancer , 41. ThiOne of the limitations was due to self-reported measurements used in the study, recall bias and social desirability bias might have occurred. Furthermore, selection bias might have occurred due to hospital-based study design. In addition, as different histological subtypes of breast cancer might have different risk factors, a larger longitudinal study is needed to assess factors associated with histological subtypes of breast cancer. Finally, levels of triglycerides and glucose are variable and are related to the time since the last meal.TyG index was associated with increased risk for breast cancer in a non-linear fashion. Further prospective studies are required to confirm this finding.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by Ethical Committee of Health Research in the Faculty of Medicine, Universitas Indonesia, Rumah Sakit Cipto Mangunkusumo, Jakarta, Indonesia (450/UN2.F1/ETIK/2018). The patients/participants provided their written informed consent to participate in this study.SP: conceptualization, design, data curation, investigation, and writing . NS: data curation, investigation, and writing . FW: data curation, investigation, and writing . NS: data curation, investigation, and writing . RR: data curation, investigation, and writing (review and editing). RH: data curation, investigation, and writing (review and editing). EP: data curation, investigation, and writing (review and editing). YP: data curation, investigation, and writing (review and editing). NP: Data curation, investigation, and writing (review and editing). WH: data curation, investigation, and writing (review and editing). DB: data curation, investigation, and writing (review and editing). MM: data curation, investigation, and writing (review and editing). DY: data curation, investigation, and writing (review and editing). JF: data curation, investigation, writing (review and editing). RW: data curation, investigation, and writing (review and editing). ET: data curation, investigation, and writing (review and editing). WF: data curation, investigation, and writing (review and editing). DY: data curation, investigation, and writing (review and editing). RP: conceptualization, investigation, formal analysis, and writing . 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.


For post-menopausal women with estrogen-receptor-positive breast cancer, treatment with aromatase inhibitors reduces disease recurrence and mortality, as compared to tamoxifen. Nevertheless, women treated with aromatase inhibitors more often develop hyperlipidemia, hypercholesterolemia and hypertension, which are recognized cardiovascular (CV) risk factors. Concerns about CV safety of aromatase inhibitors had been raised by several studies. Our results showed that adjuvant therapy with aromatase inhibitors of breast cancer women is associated with increased risk of heart failure and combined CV events, and such therapy probably amplifies the “intrinsic” CV risk of the patient. They underline the importance of interdisciplinary collaboration between oncologists and cardiologists in evaluating the risk/benefit ratio of the choice of hormone therapy.Background: Whether aromatase inhibitors (AIs) increase the risk of cardiovascular (CV) events, compared to tamoxifen, in women with breast cancer is still debated. We evaluated the association between AI and CV outcomes in a large population-based cohort of breast cancer women. Methods: By using healthcare utilization databases of Lombardy , we identified women ≥50 years, with new diagnosis of breast cancer between 2009 and 2015, who started adjuvant therapy with either AI or tamoxifen. We estimated the association between exposure to AI and CV outcomes  by a Cox proportional hazard model with inverse probability of treatment and censoring weighting. Results: The study cohort included 26,009 women starting treatment with AI and 7937 with tamoxifen. Over a median follow-up of 5.8 years, a positive association was found between AI and heart failure  and any CV event . The CV risk increased in women with previous CV risk factors, including hypertension, diabetes and dyslipidemia. Conclusions: Adjuvant therapy with AI in breast cancer women aged more than 50 years is associated with increased risk of heart failure and combined CV events. Five-year adjuvant treatment of women with breast cancer positive for estrogen receptors (ERs) with tamoxifen reduces breast cancer mortality of about one third every year, irrespectively from age, use of chemotherapy, progesterone receptor status, or other tumor characteristics . FurtherData were retrieved from the healthcare utilization databases of Lombardy, a region of Northern Italy accounting for about 16%  of its entire population. The Italian National Health Service (NHS) provides universal and free of charge healthcare services, including those for cancer care. In Lombardy, an automated system of databases collecting a variety of information allows management of healthcare services. Details on information included in the healthcare utilization databases of Lombardy and their use in the field of cancer have been reported elsewhere . SpecifiThe target population included all women who, during the years 2009 to 2015, were resident in Lombardy and beneficiaries of the NHS and had at least one hospital admission for breast cancer. The date of the first hospital admission for breast cancer occurred during this period was defined index date. We excluded women who (i) at the index date were younger than 50 years ; (ii) at the index date or in the following six months did not receive breast surgery (in order to identify a more homogenous cohort of breast cancer women); (iii) during the five-year period prior the index date had CV-related or cancer-related hospital admission or oncologic medicaments, including hormonotherapy (in order to include incident cancer cases without previous CV diseases and new hormonotherapy users); (iv) during the six months following the index date had signs of distant metastasis (in order to exclude women with advanced stage of the disease). Among the remaining women, those who started therapy with either aromatase inhibitors  or tamoxifen within one year from surgery were included in the final study cohort. We labelled the date of first prescription of hormonotherapy as “treatment start”.We used two approaches for defining exposure. First, with the intention-to-treat approach, cohort members accumulated person-years of exposure to either aromatase inhibitors or tamoxifen  from the date of treatment start until the earliest date among t outcome occurrence (see below), death, migration or 31 December, 2019 (end-point of follow-up). Second, for taking into account possible changes in therapeutic strategy during follow-up, with the as-treated approach, each woman was considered exposed to either aromatase inhibitors or tamoxifen until she switched from aromatase inhibitors to tamoxifen, or vice versa, being information censured at the earliest date among outcome occurrence, switching, death, migration or 31 December, 2019.We separately recorded hospital admissions for myocardial infarction, heart failure, ischemic stroke, or any CV event, the latter being defined CV composite outcome. We labelled the date of the first hospitalization for each of these causes as “outcome occurrence”.We considered baseline characteristics of cohort members including those measured at treatment start , comorbidities detected through in-hospital diagnoses experienced in the 3-year period prior starting therapy , and selected co-treatments dispensed in the year prior treatment start . Chemotherapy and radiotherapy dispensed between index date and treatment start were recorded.We also recorded time-varying characters, including hospital admissions, outpatient services  and cardiac medicaments dispensed from treatment start until the switch of therapy.Finally, according to previous treatment with statins, antihypertensive, and antidiabetic drugs, we stratified patients into three CV risk profile: low-risk , medium-risk , and high-risk .We compared patients starting treatment with aromatase inhibitors or tamoxifen in terms of standardized differences of baseline characters (we considered negligible those differences with absolute standardized differences < 0.10) , as wellTo minimize confounding by indication, we developed a propensity score (PS) matching design . We estiAs independence between switching and outcome is not ensured by the as-treated approach, that is, the reasons of switching may be related to the outcome onset so generating estimates biased by informative censoring, the exposure–outcome association was further estimated by means of a Cox proportional hazards model with inverse probability of treatment and censoring weights. The inverse probability of censoring weighting (IPCW) method consists of censoring observations at the time of switching therapy and assigning to each observation a weight inversely proportional to the probability of censoring, conditional to covariates measured until censor. Weights were generated by fitting a time-dependent Cox regression model to estimate the probability of censoring due to switching therapy. The model, fitted separately among patients initially treated with either aromatase inhibitors or tamoxifen, included the time-varying characters measured from treatment start until switching. The censoring weights were then stabilized by the probability of censoring conditional on the treatment received  .In addition, to minimize confounding by indication, the inverse probability of treatment weighting (IPTW) method was used. Weights were estimated using a logistic regression model to determine the probability of receiving aromatase inhibitors versus tamoxifen, conditional on variables measured at or before cohort entry. The treatment weights were stabilized by the probability of the treatment received .The product of the two stabilized weights (IPC and IPT) was used as final weights to estimate the parameters of the marginal Cox proportional hazard model for estimating the exposure–outcome association. Final weights were truncated at 1st and 99th percentile of their distribution, to reduce their variability . Since, p-values less than 0.05 were considered statistically significant.For all the tested hypotheses, two-tailed The process of the selection of the study cohort is reported in p = 0.029). There was no evidence that the type of hormonotherapy employed at starting treatment affected the risk of at least one CV event when observations were censored any time the switching occurred. Conversely, a significant 14% excess of CV hospital admissions was observed for both the intention-to-treat approach and the IPCW analysis  and 7.96 (7.21 to 8.71) events every 1000 person-year  were siganalysis .p = 0.470) (p = 0.954)  and 1.69 (1.34 to 2.03) events every 1000 person-year (= 0.470) . Cumulat= 0.954) . Finally= 0.954) .p = 0.106) (p = 0.198)  and 3.00 (2.54 to 3.46) events every 1000 person-year (= 0.106) . Cumulat= 0.198) . Finally= 0.198) .p = 0.097) (p = 0.166)  and 4.47 (3.91 to 5.03) events every 1000 person-year (= 0.097) . Cumulat= 0.166) . Finally= 0.166) .p < 0.001). The time trend analysis showed a different course of heart failure occurrence in the two treatment groups, suggesting an interaction between the hormone therapy and the patient’s CV risk profile (p = 0.085). However, continuing observation after the end of treatment, the aromatase inhibitors therapy was associated to an increased risk (HR = 1.88 (1.22–2.88), p = 0.003). Conversely, in high-risk patients, aromatase inhibitor therapy resulted in a significant increase in heart failure early during the treatment period (HR = 1.82 (1.29–2.58), p = 0.001). This significant difference was lost in the long period observation, after the completion of treatment, above all for an increase in heart failure events in the group initially treated with tamoxifen. Women at medium CV profile presented a trend with a consequent significant increase in hospitalizations for heart failure in the aromatase inhibitors group during the 5-year period of treatment (HR = 1.63 (1.21–2.20), p < 0.001) and thereafter (HR = 1.42 (1.12–1.81), p = 0.004).Matched cohort patients exhibited the following distribution of CV risk factors: 8136 (51.3%) patients had no CV risk factor (low risk), 5516 (34.8%) patients had only one CV risk factor (medium risk) and 2212 (13.9%) patients had two or more CV risk factors (high risk). As expected, during the follow-up, hospitalizations for heart failure occurred more frequently in the high-risk group (8.5%), compared to the medium-risk group (4.9%) and the low-risk group (1.1%)  increased risk of CV events in women treated with aromatase inhibitors, as well as with those of other “real life” registers reported in the recent literature . A recenIn our study, we adopted three different approaches for assessing the association between aromatase inhibitors and CV outcomes. With the intention-to-treat approach, women who started therapy with either aromatase inhibitors or tamoxifen were treated as they were continuously in that exposure group, regardless their exposure during follow-up. However, in our cohort, about 43% of women switched from tamoxifen to aromatase inhibitors, and about 6% from aromatase inhibitors to tamoxifen, so that exposure misclassification may lead to biased results . For thiOur study has several strengths. First, to our knowledge, this is the largest real-world study assessing the CV risk in almost 34,000 breast cancer women treated with adjuvant aromatase inhibitors or tamoxifen. Second, given the population-based nature of the study, the target population from which the study cohort was selected was representative of the real-world practice. Indeed, all women beneficiaries of the NHS with a diagnostic code of breast cancer during the recruitment period were selected. Third, the IPCW analysis allowed overcoming the bias due to both exposure misclassification and informative censoring.p = 0.764) and any CV outcome (p = 0.998) as compared to those who did not. Second, despite the high diagnostic accuracy of ICD9-CM codes for detecting CV outcomes, including myocardial infarction and heart failure [The present study has also some limitations. First, since patients were not randomly allocated to the treatment with either aromatase inhibitors or tamoxifen, the results may be affected by confounding. Although our analysis considered several measured potential confounders, unmeasured characteristics, such as body mass index, smoking status, menopausal status and physical activity, may affect our conclusions. Furthermore, based on the administrative data, we have no information on the phenotype of heart failure  nor on the incidence/prevalence of asymptomatic dysfunction of the left ventricle. We also do not know if the prescribed therapy adequately controlled hypertension, dyslipidemia, or diabetes. Moreover, our data did not include direct information on biomarkers status, including estrogen receptors, and use of anthracyclines. However, since all women included in our cohort were treated with hormonotherapy, it is likely that all of them were estrogen receptor positive. Moreover, in our cohort, women who received chemotherapy (9% in the PS-matched cohort) did not show higher risk of heart failure ( failure , outcomeIn conclusion, our study offers further evidence that adjuvant therapy with aromatase inhibitors in women with breast cancer aged more than 50 years is associated with increased risk of heart failure and combined CV events, and such therapy probably amplifies the “intrinsic” CV risk of the patient. This underlines the importance of interdisciplinary collaboration between oncologists and cardiologists in evaluating the risk/benefit ratio of the choice of hormone therapy. Considering the efficacy of aromatase-inhibitor hormone therapy against breast cancer, it is necessary to evaluate, by means of prospective studies, whether an appropriate control program for cardiovascular risk factors can improve the prognosis.


The incidence of breast cancer has been gradually increasing in Korea. Recently, the elevated level of serum gamma-glutamyltransferase (GGT) has emerged to be associated with the development and progression of some malignancies. This study aimed to determine the effect of serum GGT levels on the risk of developing breast cancer in Korean women.We used National Health Insurance Service Health Checkup data to examine the association between serum GGT levels and breast cancer development in Korean women. Women aged 40 years or older who participated in the Korean National Health Screening Examination between January 2009 and December 2009 and who did not develop any cancer within 1-year post examination were included in this analysis . Cox proportional hazard regression analysis was conducted to calculate hazard ratios (HRs) with 95% confidence intervals (CIs).in situ (CIS) . In post-menopausal women, the Q4 group also exhibited higher CIS risk . However, no significant difference in the risk of developing CIS was observed between the Q1 and Q4 groups in pre-menopausal women. Further analysis revealed that obese, post-menopausal women with a high GGT level (Q4) were associated with an increased risk of developing breast cancer  and CIS .Overall, an elevated serum GGT level was associated with the increased risk of developing breast cancer; compared to the Q1 group, the Q4 group showed a significantly increased breast cancer risk . Such a relationship was stronger in post-menopausal women than pre-menopausal women . Women with a high GGT level (Q4) were also at an increased risk of developing carcinoma Our study results demonstrate that increased serum GGT level is a risk factor for developing breast cancer. The post-menopausal women group with obesity and elevated serum GGT level showed the highest incidence of breast cancer. Thus, serum GGT concentration could be a novel and potential risk factor for breast cancer. Further validation in different ethnic groups would be warranted. In In this study, we analyzed the association between GGT and breast cancer risk by using a large cohort data from the Korean insurance registry by including 3,109,506 women (≥40 years old) who underwent health check-ups in 2009.This study was a nationwide population-based cohort study using a Health Check-up database from the National Health Insurance Service (NHIS) of Korea. The NHIS is a single universal insurance service covering approximately 97% of the entire Korean population. In Korea, breast cancer screening tests are provided free of charge to all women over 40 years of age every 2 years. This test result is registered in the health check-up database of the NHIS. From the NHIS cohort, we identified women aged 40 years and older who received health examinations and completed the cancer-screening questionnaire between January 2009 and December 2009 . Among them, we excluded women with the following conditions: (1) who reported that they had received a hysterectomy before; (2) who had been diagnosed with any cancer before health examination and had been registered with cancer registration code; or (3) those with insufficient data. If any cancer occurred within one year from the day of screening, it could have been caused by other cause than GGT. So we applied a 1-year lag period to minimize detection bias about the cancer diagnosis. Finally, 2,066,998 women were included in this analysis Figure 12 at the time of health examination, we defined obese women as BMI ≥25.0 kg/m2 . DevelopIncidences of breast cancer and CIS were calculated by dividing the number of events by 1000 person-years. Between the women who developed breast cancer (study group) and those who did not (control group), baseline demographic characteristics were compared using Student’s t test for continuous variables and chi-square test for categorical variables. Based on the quartiles of serum GGT levels, we stratified participants into each quartile group (Q1 to Q4) with an increasing GGT level.Investigating the relationship between breast cancer and serum GGT levels, we used Cox proportional hazard regression models for multivariate analysis; the hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated through cox proportional hazard regression using Q1 as a reference. The risk of breast cancer was evaluated in total women, pre- and post-menopausal groups, respectively. While none of the confounding factors were adjusted in Model 1, participants’ age was adjusted in Model 2. Model 3 adjusted for age, smoking status (3 levels), alcohol consumption (3 levels), regular physical activity and diabetes. Adding to this, Model 4 further adjusted for the number of parities, menopausal status, and age of menarche. For post-menopausal women, model 4 also included duration of hormonal replacement therapy as a confounder.http://www.R-project.org). Statistical and SAS version 9.4  and a p value <0.05 was considered statistically significant.All statistical analyses were performed using R statistical software , 25,182 individuals (1.22%) developed breast cancer and assigned to the study group while 2,041,816 individuals (98.78%) were assigned to the control group Figure 1Baseline characteristics of the two groups were displayed in Individual data were categorized into quartiles to investigate the association between GGT levels. The GGT ranges of each quartile (Q1-Q4) were displayed in Overall, women with higher GGT levels (Q4) had an increased risk of developing breast cancer, compared to those with Q1  regardless of the participants’ menopausal status Figure 2Similar results were also obtained in pre-menopausal subgroup and post-menopausal subgroup Figure 2Further investigation was done to ascertain whether serum GGT level is associated with the development of CIS and invasive breast cancer. Compared to the Q1 group, the Q4 group showed an increased risk of developing CIS  Figure 3Next, we performed subgroup analysis according to the menopausal status. In the post-menopausal women, the Q4 group exhibited a higher risk of CIS than the Q1 group  Figure 3Subsequently, the effects of serum GGT levels in post-menopausal women were analyzed by age  had a high risk of developing CIS at all ages except for women aged less than 55, also with the highest risk in women over 65 years  was higher than those of women with BMI less than 25 kg/m2   Figure 4Meanwhile, an analysis was also performed about the incidence of CIS Figure 5In this nationwide cohort study, we suggest serum GGT as a novel biomarker of breast cancer risk. Our results mainly showed that women exhibiting higher serum GGT levels had a high risk of developing breast cancer later according to the menopausal status, obesity status, age and conducted subgroup analyses. Additionally, subgroup analysis was conducted according to the menopausal status, age and obesity status. The subgroup analysis suggests that obese post-menopausal elderly women were more susceptible to breast cancer and CIS with elevated GGT levels.A previous study analyzing the data from a large cohort in Sweden showed a positive correlation between GGT levels and overall primary cancer risk. The cancer-site specific analysis showed that digestive organ, respiratory system/intra-thoracic organs, female genital organ/breast, urinary organs, and male genital organs cancer risk was significantly elevated in people with high serum level of GGT(>36U/L) . AnotherGGT is a main enzyme related to glutathione metabolism . GGT hasWe analyzed a large cohort covering almost the entire Korean women aged over 40 years old who were eligible for national breast cancer screening. The median follow-up period of the current study was 8.37 years, which is a relatively long period for monitoring the incidence of cancer. The cut-off value of quartile group4, serum GGT level of 26U/L, is suggested as a new cut-off value for Korean women for predicting the breast cancer risk. In addition, obesity was shown as a co-factor with the high serum GGT level in contributing the increasing breast cancer risk. However, the role of GGT in breast tumorigenesis remains largely uninvestigated. Therefore, future studies elucidating GGT on the breast cancer etiology are warranted.To summarize, our study elucidated the association between serum GGT and the risk of developing breast cancer by utilizing a big dataset from the Korean health insurance database. Elevated serum GGT is associated with increased breast cancer incidence particularly in post-menopausal women with obesity. We believe that our study could provide a new insight into the strategy of breast cancer prevention.nhiss.nhis.co.kr).The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: the Korea National Health Insurance Sharing Service homepage  of Seoul National University Hospital (IRB number: 2101-003-1184). Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.AS, WW, SK, YH, IP, JY, HJ, K-DH, and YS: design, collection of data, manuscript, editing, approval of final version, and accountability. All authors contributed to the article and approved the submitted version.This research was supported by BK21 Plus Program of the Department of Agricultural Biotechnology, Seoul National University , a grant of Health Technology R&D Project through the Korea Health Industry Development R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea [grant number: HI16C2037] and a grant from the National R&D Program for Cancer Control, Ministry of Health & Welfare, Republic of Korea [grant number: HA17C0037].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.