BRCA1 or BRCA2 genes.Height, body mass index (BMI), and weight gain are associated with breast cancer risk in the general population. It is unclear whether these associations also exist for carriers of pathogenic variants in the BRCA1/2 variant carriers was used for retrospective and prospective analyses separately for premenopausal and postmenopausal women. Cox regression was used to estimate breast cancer risk associations with height, BMI, and weight change.An international pooled cohort of 8091 BRCA2 variant carriers . Higher young-adult BMI was associated with lower premenopausal breast cancer risk for both BRCA1  and BRCA2  variant carriers in the retrospective analysis, with consistent, though not statistically significant, findings from the prospective analysis. In the prospective analysis, higher BMI and adult weight gain were associated with higher postmenopausal breast cancer risk for BRCA1 carriers .In the retrospective analysis, taller height was associated with risk of premenopausal breast cancer for BRCA1 and BRCA2 variant carriers, with relative risk estimates that are generally consistent with those for women from the general population.Anthropometric measures are associated with breast cancer risk for The online version contains supplementary material available at 10.1186/s13058-023-01673-w. Taller height and higher postmenopausal body mass index (BMI) are well-established risk factors for breast cancer -5. WhileBRCA1 or BRCA2 breast cancer predisposition genes have high breast cancer risks [BRCA1 or BRCA2 [BRCA1 and 7912 in BRCA2 [BRCA1 or BRCA2 found weak evidence for an association of higher BMI at age 18 years with lower postmenopausal breast cancer risk, but no association of current BMI or weight change and breast cancer risk [Carriers of germline pathogenic variants in the er risks . Howeverer risks -21. Threer risks , 18, 20.er risks , 20, oneor BRCA2 . They alor BRCA2 . The retin BRCA2 , 5-8. ThBRCA1 or BRCA2, using data from the International BRCA1 and BRCA2 Cohort Consortium [The identification of non-genetic risk factors for breast cancer in high-risk populations is important for developing more accurate risk prediction models and designing risk-adapted prevention strategies. In the present work, we evaluated the associations of height, BMI, and change in weight with pre- and postmenopausal breast cancer risk for carriers of a pathogenic variant in nsortium -25.BRCA1 and BRCA2 pathogenic variant carriers: the International BRCA1/2 Carrier Cohort Study  [BRCA1 or BRCA2. Women with pathogenic variants in both genes were excluded.We used pooled data from three large prospective cohort studies of studies) , the Katstudies) , 26, andstudies) , 25 , weight at questionnaire completion, reproductive and medical history, surgical interventions, and menstrual history  for periods stopping) .BMI was calculated as weight (kg) divided by height (m) squared. Weight change was calculated as the difference (in kg) between baseline weight and young-adult weight.For women who indicated no periods in the past year, age at menopause was determined by adding one year to “age at last menstruation.” Women below the age of 60 years were considered premenopausal if they indicated that they had had a period in the past year, or if the “reason for periods stopping” was medication, oral contraceptive use, pregnancy, or breastfeeding. Women below the age of 60 years reporting risk-reducing salpingo-oophorectomy (RRSO) as the reason for menopause were considered premenopausal until RRSO. For women who reported a hysterectomy without bilateral oophorectomy, menopausal status was considered unknown. For women who were still menstruating when they started hormonal therapy and those who took hormonal contraceptives at older ages, age at menopause was classified as unknown.Occurrence of breast cancer was derived from follow-up questionnaires and, for some studies, through linkage to cancer registries. Information on vital status was obtained from municipal or death registries, medical records, or family members. For details, see Kuchenbaecker et al. . All stuBRCA1 and BRCA2 pathogenic variant carriers, and separately for pre- and postmenopausal women, resulting in eight sets of analyses.Associations with breast cancer risk were evaluated using Cox proportional hazards regression with age as the timescale, estimating hazard ratios (HR) and corresponding 95% confidence intervals (CI). Exposure variates analyzed were height, young-adult BMI, baseline BMI, and weight change between early adulthood and baseline. Each anthropometric variable was analyzed in a separate model. All analyses were stratified by year of birth  and study and were adjusted for age at menarche, number of full-term pregnancies, oral hormonal contraceptive use (ever/never), and hormone replacement therapy (ever/never), as reported in the baseline questionnaire. Robust variance estimation was used to account for familial clustering of study participants. Associations were examined separately for retrospective and prospective observation times, i.e., before and after baseline questionnaire, respectively, separately for BRCA1 and BRCA2 variant carriers [Associations of breast cancer risk with height and young-adult BMI were analyzed. For premenopausal women, the observation time started at birth and ended at diagnosis of the first primary breast cancer (invasive or in situ) as the event of interest, or was censored at diagnosis of any other type of cancer, risk-reducing mastectomy (RRM), completion of baseline questionnaire, or menopause, whichever came first. For postmenopausal women, observation started at menopause (if menopause occurred before baseline) and was censored at diagnosis of the first primary breast cancer (event), or at diagnosis of any other type of cancer, RRM, or baseline, whichever came first. Due to the non-random sampling of prevalent breast cancer cases, retrospective analyses were performed using the weighted retrospective cohort approach described by Antoniou et al. . Individcarriers .Associations of breast cancer risk with height, young-adult BMI, baseline BMI, and weight change between early adulthood and baseline were analyzed. For premenopausal women, observation time started at baseline questionnaire completion  and ended at diagnosis of the first primary breast cancer as the event of interest. Observation time was censored at diagnosis of any other type of cancer, RRM, last follow-up, or menopause, whichever came first. For postmenopausal women, observation started at baseline or menopause, whichever came last, and ended at diagnosis of the first primary breast cancer, or at diagnosis of any other type of cancer, RRM, or last follow-up, whichever came first.If a woman’s prospective observation period had included both pre- and postmenopausal periods, then follow-up periods were assigned to the pre- and postmenopausal analyses, as appropriate.P values are two-sided. P values < 0.05 were considered statistically significant. Statistical analyses were conducted using R 4.1.1 for Windows  and IBM SPSS Statistics for Windows Version 26 .All reported BRCA1: 4257; BRCA2: 2601). The mean age at the end of observation was 40.5 years (SD ± 10.6), see Table The retrospective analysis included 6858 pathogenic variant carriers . A consistent HR estimate was seen among postmenopausal women , see Table BRCA1 variant carriers, neither for pre- or menopausal women. Higher young-adult BMI was associated with lower risk of premenopausal breast cancer both in BRCA1  and BRCA2  variant carriers. Consistent inverse associations with premenopausal breast cancer risk were also seen when young-adult BMI was categorized. In postmenopausal women, high young-adult BMI was associated with reduced breast cancer risk in BRCA1 carriers compared to women with a normal BMI, although statistical significance was only reached in the category of low compared to normal BMI . A consistent, but not statistically significant result was observed for BRCA2 variant carriers. Young-adult BMI, considered as a continuous variable, was not significantly associated with postmenopausal breast cancer risk.Taller height was associated with higher premenopausal breast cancer risk in BRCA1: 2167; BRCA2: 1531 with information on height and baseline weight. In total, 397 incident breast cancer cases were diagnosed , and the postmenopausal cohort 1531 carriers , with a mean follow-up time of 5.3 ± 3.5 years. Information on young-adult weight was available for a subgroup of 3100 (84%) carriers.The prospective analysis was based on 3698 pathogenic variant carriers . There was no evidence for an association with postmenopausal breast cancer . However, there was no association between higher baseline BMI and risk for BRCA2 carriers .There was a suggestion for increased premenopausal breast cancer risk for taller BRCA1 variant carriers gained a mean of 6.5 ± 9.9 kg and postmenopausal BRCA1 variant carriers gained 11.3 ± 11.9 kg. Similarly premenopausal BRCA2 variant carriers gained a mean of 7.2 ± 10.5 kg and postmenopausal BRCA2 variant carriers gained 11.4 ± 12.1 kg. In BRCA1 variant carriers, weight gain was associated with increased risk of postmenopausal breast cancer ; however, no significant association was found for BRCA2 variant carriers . For premenopausal breast cancer, no associations with weight change were observed in carriers of pathogenic variants in either gene.Between early adulthood and baseline premenopausal These results were unchanged after adjustment for use of hormonal contraception and postmenopausal hormone therapy -positive breast cancer  [Height as a risk factor for pre- and postmenopausal breast cancer has been described in prospective cohort studies, and in meta-analyses for the general population , 2. We fr BRCA2) . Zhang eBRCA1 and BRCA2 variant carriers in the retrospective analysis, with consistent, although not statistically significant, risk estimates in the prospective analysis. This is in line with the associations seen in the general population, Mendelian randomization studies, and earlier retrospective studies by Manders et al. [BRCA1 and BRCA2 variant carriers, the data of which partially overlapped with the retrospective data of the present study. The reasons for the inverse association of high young-adult BMI with breast cancer risk are unclear, but might be mediated through early breast tissue differentiation [We found that higher young-adult BMI is associated with lower premenopausal breast cancer risk in both s et al.  and Qians et al.  for BRCAntiation , 9. In pntiation , 11, 30.Higher young-adult BMI is also associated with a lower risk of postmenopausal breast cancer in the general population , 5. We fBRCA1 pathogenic variant carriers, we found that higher baseline BMI and adult weight gain were associated with higher risk of postmenopausal breast cancer, but not with risk of premenopausal breast cancer. This is in line with the finding by Manders et al. for BRCA1/2 variant carriers and with the findings in the general population [BRCA2 variant carriers, we found no evidence of association, although a HR of similar magnitude compared to BRCA1 variant carriers cannot be excluded, because of the wide confidence intervals.In the prospective analysis of pulation , 31, 32.A recent study has suggested that weight may be more predictive of postmenopausal breast cancer risk than BMI . We analBRCA1 can be considered. A similar pattern (with an association for BRCA1- but not BRCA2-associated breast cancer) has been observed for oral contraceptive use [BRCA1 compared to BRCA2 or PALB2 [Two biological explanations for our findings of high baseline BMI and of weight change and higher breast cancer risk in the postmenopausal cohort of carriers of tive use . Both fitive use -38. One tive use -46. The or PALB2 .BRCA2 variant carriers associated with very early menopause and hormonal contraception use. In our study, however, the comparison of analysis with and without adjustment for use of hormonal contraception and postmenopausal hormone therapy did not support this hypothesis, since an association of high baseline BMI and weight gain with postmenopausal breast cancer risk was consistently seen in carriers of a pathogenic variant in BRCA1, but not in BRCA2.Early surgical menopause may lead to use of hormone therapy, usually a combination of estrogen and progestin. If BRCA1-deficient breast cells are particularly sensitive to hormonal treatment, this could lead to a significantly higher risk of breast cancer compared with BRCA1-associated postmenopausal breast cancer may be the lack of suppression of aromatase. BRCA1 is known to be an inhibitor of aromatase (CYP19) transcription and also interferes with transcriptional activation mediated by the estrogen receptor alpha (ERα) [BRCA1-associated breast cancer. Interestingly, after menopause the percentage of ER-positive BRCA1-associated breast cancer increases [Another mechanism of action promoting ha (ERα) . High BMncreases .BRCA1 and BRCA2 variant carriers are similar to those found in the general population, the absolute excess risks will be higher for BRCA1 and BRCA2 variant carriers because of the higher background breast cancer risk. Additionally, as shown by Hopper et al., the postmenopausal elevation of breast cancer risk by far outweighs the premenopausal protection associated with high BMI [Avoiding over- and underweight is important for both pathogenic variant carriers and non-carriers. Even if the relative risks for anthropometric measures and breast cancer in high BMI .BRCA1/2-pathogenic variant carriers  is currently recruiting [Variant carriers may be highly motivated to attempt to modify their breast cancer risk through a healthy lifestyle , 51. Heacruiting . It aimsBRCA2, but some adjustment may be needed for BRCA1. The association effect sizes for BMI are generally consistent with the general population estimates, at least for young-adult BMI [Anthropometric measures are included in cancer risk prediction models such as BOADICEA . In BOADdult BMI .The study has some limitations. Despite the large size of the cohort, the number of incident cases was still limited and the confidence limits were correspondingly wide, especially in subgroup analyses, such as postmenopausal high young-adult BMI. Thus, the results are still heavily dependent on the retrospective data, which are potentially subject to more bias. Much larger prospective cohorts with a broader age range and a longer follow-up are therefore needed.A general challenge is the definition of menopausal status. Ideally, this would be defined by taking a detailed menstrual history and, in many cases, a blood test—but this is not feasible in large epidemiological studies, which rely on self-reporting. This may have led to some misclassification of postmenopausal women as premenopausal women, diluting the difference between the two groups.A known limitation of retrospective studies is the potential for survival bias introduced by including prevalent cancer cases. There is evidence in the general population that higher BMI is associated with advanced tumor stage and a worse prognosis . If the BRCA1 and BRCA2 variant carriers. Height was a risk factor for premenopausal breast cancer in BRCA2 variant carriers, but not BRCA1 carriers. High young-adult BMI was associated with decreased risk of premenopausal breast cancer, but not for postmenopausal breast cancer. Higher BMI and weight gain in adult life were risk factors for postmenopausal breast cancer in BRCA1 variant carriers.This is the first prospective study to analyze the association of breast cancer risk with anthropometric measures by menopausal status, separately for BRCA1 and BRCA2 variant carriers are broadly similar to those reported in the general population when taking into account menopausal status. This research is not only important to inform carriers about age-specific cancer risks, it might also open up new risk reduction strategies by elucidating yet unknown signaling pathways.In conclusion, our findings indicate that the associations of height, BMI and weight gain with breast cancer risk in Additional file 1: Table S1. Overview of the studies contributing to the retrospective and prospective analyses.Additional file 2: Table S2. Retrospective and prospective analysis of height in quintiles and breast cancer risk, by menopausal status.Additional file 3: Table S3. Retrospective analysis of height, body mass index, weight change and breast cancer risk, by menopausal status.Additional file 4: Table S4. Prospective analysis of associations between height, body mass index, weight change and breast cancer risk, by menopausal status.Additional file 5: Table S5. Weight versus body mass index and breast cancer risk in BRCA1 and BRCA2 variant carriers, by menopausal status.


Given the increase in the incidence of breast cancer during the past decades, several studies have investigated the effects of variables on breast cancer, especially obesity. This systematic review and meta-analysis aims to evaluate any effects of obesity on breast cancer risk in women, before and after menopause, and in different continents.All forms of relevant literature examining any association between obesity and breast cancer, including cohort, case–control, and cross-sectional studies, were identified in the PubMed, Scopus, EMBASE, and Web of Science databases from January 1, 1990 until January 13, 2023. Body mass index (BMI) > 30 was used to indicate obesity. Every type of breast cancer was examined as outcome factors. The quality of the papers was evaluated using the Newcastle–Ottawa scale checklist. The Egger and Begg test was used to evaluate publication bias. To assess any extra impact of each research on the final measurement, a sensitivity analysis was carried out.2 = 65.4%), and for post-menopausal woman, OR = 1.26 CI: (1.19–1.34), (I2 = 90.5%).One hundred and two studies were included in this meta-analysis. Respectively, 48 and 67 studies reported associations between obesity and breast cancer in pre and post menopausal women. Combining all studies, the pooled OR of the association between obesity and breast cancer in pre-menopausal women was OR = 0.93 CI: (0.85–1.1), (IObesity has a protective role in breast cancer among pre-menopausal women, but this relationship is statistically significant only in European women. The chance of developing breast cancer increases in post-menopausal women who are obese. This relationship is significant among Asian, North American, African and European women.The online version contains supplementary material available at 10.1186/s12905-023-02543-5. The most frequent malignancy among women worldwide is breast cancer; 2.3 million new diagnoses of breast cancer in women, which represents 11.7% of all new cancer cases in the world, were made in 2020. Breast cancer, with 685,000 fatalities in a year, is the fifth cause of deaths among different cancers (1 in 6 cancer deaths) [Obesity and overweightness are common and serious risk factors for many chronic diseases and cancers. According to the World Health Organization's (WHO) definition of obesity, people with a body mass index (BMI) > 30 are considered obese. The relationship between obesity and the occurrence of some chronic diseases and cancer has been clarified [More than 50 research studies have looked into obesity and its role in the prognosis of breast cancer. A study revealed that the 5-year breast cancer survival rate for obese or overweight women was 55.6%, whereas it was 79.9% for women with normal weight. This study also demonstrated that obese women with breast cancer are more likely to have bigger tumors and invasive lymph nodes . Many reIt has been several years since systematic reviews and meta-analyses were done on the association between breast cancer and obesity. The meta-analysis study on the relationship between breast cancer and obesity needs to be updated as the numerous publications that have been published in recent years. According to our knowledge, no meta- analyse study has been conducted to investigate the relationship between breast cancer and obesity in different continents simultaneously. Since weight gain and breast cancer are both worldwide health concerns, this systematic review and meta-analysis aims to investigate the association between obesity and breast cancer risk in the pre- and post-menopause periods and also demonstrate any geographical variations by examining this association in different continents.The MOOSE and STROBE recommendations for reviews of observational studies were used in this systematic review , 17. TheGlobal databases including Scopus, Web of Sciences, Medline (PubMed), and EMBASE were searched to find all original published papers. No articles were found by searching through the Cochrane database. The papers listed in the retrieved studies were manually searched to increase search sensitivity. For January 1990 to January 2023, searches were carried out without linguistic constraints using "Obesity," "Body Weight," "Breast Neoplasms," "Breast Tumors," "Breast Carcinomas," and "Breast Cancer" as the the keywords. Only human observational studies were selected. Many of the articles from the original search results were eliminated after a review of the titles and abstracts. Two researchers separately identified the inclusion and exclusion criteria.A study was not included unless it satisfied the following requirements: original publication, cross-sectional/case–control/cohort research, human studies, the main independent variable being obesity (BMI > 30), and the outcome being breast cancer. Review papers, editorials, letters, case reports, conference abstracts, studies that were not peer-reviewed, and articles on animals or genetics, were all eliminated from the study. All discrepancies found during the stages of data collection, compilation, and analysis were investigated and resolved by the authors.Three researchers conducted separate evaluations of each included paper. A fourth author reviewed the work and helped them determine whether there were any differences of opinion. The two independent, matched reviewers who were responsible for gathering the data did so by using an Excel worksheet. Authors, publication year, study type, location, sample size, BMI, breast cancer type, and confonder variables of the association were listed in that order. After that, information from a systematic checklist was gathered. Figure The obsevestional studies quality were evaluated by the Newcastle–Ottawa Scale (NOS) from 0 to 9 stars . The art2 statistic were employed to determine statistical heterogeneity across papers in this research [This meta-analysis included all subtypes of breast cancer, regardless of clinical features or tumor stage. If several studies were published using the same data, the last study was selected and included in the meta-analysis . The indresearch .p < 0.05.A meta-regression and subgroup analysis were also carried out to identify the reason for research heterogeneity. Moreover, the funnel plot and Egger and Begg's tests were performed to assess publication bias . The triOne hundred and two studies were included in this meta-analysis. Forty eight studies reported an association between obesity and breast cancer in pre-menopausal women, and 67 studies showed a relationship between obesity and breast cancer in post-menopausal women. 34 studies  with a total sample size of 60,985 cases and 48,720 controls were used to evaluate the relation between obesity and breast cancer, without distinguishing between pre-menopausal and post-menopausal women.Fifteen studies were conducted in North America, 21 in Asia, 8 in Europe, 2 in Africa, 1 in South America for the pre-menopause period. Twenty three studies were conducted in North America, 27 in Asia, 10 in Europe, 2 in Africa, 3 in South America and 1 in Oceania for the post-menopause period. We aimed to pool the findings of the research in this analysis individually depending on the subgroup of studies that measured the relation between obesity and breast cancer before and after menstruation. Table In this meta-analysis, the quality of case–control, cohort, and cross-sectional studies was examined by using the Newcastle–Ottawa scale (NOS), the results of which were presented in the checklists completed based on the type of study. The quality assessment checklists of the case–control and cohort studies showed that most of these studies had a moderate to high-quality score Table s.P < 0.001 , did not show significant publication bias. When the trim and fill approach was used to further evaluate publication bias, no study was imputed. The result of the meta-regression analysis described that the study quality and a sample size of more than 1000 had no significant linear relationship with the OR of obesity and breast cancer risk, so these variables were not the reason for the heterogeneity  with a total sample size of 66,999 cases and 845,612 controls were included in the evaluation of the association between obesity and breast cancer in pre-menopausal women. Regardless of the type of study, the lowest and highest ORs were equal to 0.44  and 2.73 , respectively. After combining all studies, the pooled OR of the association between obesity (with case group BMI > 30) and breast cancer in pre-menopause was OR = 0.93 CI: (0.85–1.1), I2 = 65.4%, Sensitivity analysis showed that the pooled effect size on the relationship between obesity and breast cancer risk in pre-menopause women did not depend on a single study (CI range: 0.84- 1.01).P < 0.001. The trim-and-fill method used for more certainty  with a total sample size of 262,434 cases and 1,501,879 controls were used in the evaluation of the association between obesity and breast cancer risk in post-menopausal women. Regardless of the type of study, the lowest and highest ORs were equal to 0.56  and 3.26 , respectively. After combining all studies, the pooled OR of the relation between obesity and breast cancer risk in post-menopausal women was OR = 1.26 CI: (1.19–1.34), I2 = 90.5%, Sensitivity analysis showed that the pooled effect size on the relationship between obesity and breast cancer risk in post-menopausal women did not depend on a single study (CI range: 1.18–1.34).P < 0.001. Using the trim-and-fill procedure showed that 10 assumptive missing papers have been imputed, and after being included, the "adjusted" point estimate indicated a similar OR to the original analysis   with a total sample size of 34,962 cases and 2,076,826 controls were included in the evaluation of the relation between obesity and breast cancer risk, without distinguishing between pre-menopausal and post-menopausal women. After combining all studies, the pooled OR of the association between obesity and breast cancer was OR = 1.29 CI: (1.18–1.42), I2 = 84.9%, .001Fig. c; howeveSensitivity analysis indicated that the pooled effect size on the relationship between obesity and breast cancer risk did not depend on a single study (CI range: 1.17–1.42).P-value 0.001), although this difference was not statistically significant. Also, in the cross-sectional studies , obese women had a 6% lower risk of breast cancer than normal-weight women. There is a strong link between obesity and breast cancer in the pre-menopause period, according to cohort studies . Case–control studies that explored the correlation between obesity and breast cancer risk in post-menopausal women reported that being overweight significantly increases the probability of developing the disease . It means that obese women have a 27% more chance of breast cancer in post-menopause relative to normal-weight women. Moreover, cross-sectional studies and cohort studies both showed a stronger link between obesity and breast cancer risk in post-menopausal women , and OR = 1.29, 95% CI: 1.16–1.43, respectively.Figures 2: 80.3%; P-value < 0.001), cohort studies  and cross-sectional studies  report increased association between obesity and breast cancer risk.Combining the results of the studies that showed the relation between obesity and breast cancer risk regardless of menstrual status, the results of subgroups showed that case–control studies  and North American  obese woman in post-menopause were more likely to develop breast cancer than the European ones . The relation between obesity and breast cancer risk in post-menopause was not significant in European women. According to the different I2 tests in subgroup analysis based on geographic location, the difference in the geographical location of the studies is one of the reasons for the heterogeneity. Obesity was not a significant factor for breast cancer risk in pre-menopause in Asians , and North Americans . In European women, obesity was a significant protective factor for breast cancer risk in pre-menopause .Table The breast cancer burden is substantial in terms of incidence, mortality and taking treatment resources. For example, radiotherapy centers normally deliver a large number of breast cancer treatments every day  using a variety of techniques. , 24–26. The findings of this study divided the association between obesity and breast cancer risk into three categories: pre-menopause, post-menopause, and both together. This relation was also reported among the different continents in which the studies where conducted. The findings demonstrated that when combining those studies that did not separate the menopause period, obesity is shown to increase the risk of breast cancer. More specifically, obese women have a 1.29-fold higher chance of developing breast cancer than women of normal weight. The increased leptin in obese women has been associated with diagnosis of colon, breast, prostate and ovarian cancers in a previous study . HoweverObesity not only increases the chance of breast cancer, but it also has a significant effect on the disease development process. Obese women with breast cancer are more susceptible to having larger tumors. These women may become resistant to hormone treatment and have a greater incidence of metastases. Clinical studies have shown that obese breast cancer patients receiving chemotherapeutic or estrogen inhibitors have a lower chance of recurrence than those who have normal weight , 32.The dose–response meta-analysis conducted by Liu et al. reported that a 5 unit increase BMI leads to a 2% increase in the probability of breast cancer. Also, that study's findings revealed that women with greater BMIs before menopause had a lower chance of getting breast cancer . The resIt has been demonstrated that increased endogenous estrogen exposure in women raises the probability of developing breast cancer. Therefore, long-term exposure to estrogen for various reasons such as early-age menstruation or prolonged menopause may raise the probability of developing breast cancer . Due to According to the results of several studies, post-menopausal obesity increases the risk of breast cancer. This may be due to producing more estrogen hormone from adipose tissue in obese women in post-menopause .The results of several studies show that the serum level of sex hormones such as estrogen is higher in women with breast cancer compared to healthy women of the same age –38. Redu2 increase was significantly and negatively associated with the risk of breast cancer during the pre-menopause period among Africans  [After performing the subgroup analysis in each continent, it was found that obesity during pre-menopause is a significant protective factor among the population of European women. This protective relation was also found in the other continents, but without statistical significant. The findings of this study are in contrast with those of another meta-analysis that identified a significant positive relation between obesity and breast cancer risk in pre-menopausal Asian women . The dos1, 0.98) .Throughout this meta-analysis, heterogeneity was found in studies that show the relation between obesity and breast cancer risk in pre- and post-menopausal women. This heterogeneity was found in different study designs. The relation between breast cancer risk and obesity may have been confounded by a factor such as the status of taking hormonal drugs, the type of breast cancer, geographical location, sample size, physical activity, etc. To investigate the sources of heterogeneity observed among the studies, subgroup analyses, and meta-regression were performed for some of these confounding factors. The results of subgroup analyses showed that geographical location may be one of the reasons for heterogeneity. The meta-regression results showed that sample size and the quality of the studies do not have a significant effect on creating heterogeneity.One of the strengths of this meta-analysis compared to previous meta-analyses is combining different study designs separately and performing sensitivity analysis. Also, the results of the relationship between obesity and breast cancer risk have been reported separately before and after menopause.There were several limitations in our study. First, obesity was calculated using BMI by measuring height and weight at the time of diagnosis. The association between obesity and breast cancer did not take into account long-term variations in weight and body composition, and several other weight-determining factors (including waist circumference and waist-to-hip ratio). Second, BMI grouping in some articles was not based on WHO standards. Third, the type of breast cancer was not specified in many studies. Fourth, few studies have been done on obesity and breast cancer risk in Oceania, South America, and Africa. Therefore, generalizing the results of this meta-analysis in these continents should be done with caution. Finally, important confounders of breast cancer and obesity were ignored in some studies and this may affect the result of the current analysis.Obesity has a protective role in breast cancer among pre-menopausal women, but this relationship is statistically significant only in European women. The chance of developing breast cancer increases in post-menopausal women who are obese. This relationship is significant among Asian, North American, African and European women. Therefore, it is recommended that post-menopausal women prevent overweight and obesity by having sufficient physical activity and suitable nutrition.Additional file 1.


It may be important for women to have mammograms at different points in time to track changes in breast density, as fluctuations in breast density can affect breast cancer risk. This systematic review aimed to assess methods used to relate repeated mammographic images to breast cancer risk.The databases including Medline (Ovid) 1946-, Embase.com 1947-, CINAHL Plus 1937-, Scopus 1823-, Cochrane Library (including CENTRAL), and Clinicaltrials.gov were searched through October 2021. Eligibility criteria included published articles in English describing the relationship of change in mammographic features with risk of breast cancer. Risk of bias was assessed using the Quality in Prognostic Studies tool.Twenty articles were included. The Breast Imaging Reporting and Data System and Cumulus were most commonly used for classifying mammographic density and automated assessment was used on more recent digital mammograms. Time between mammograms varied from 1 year to a median of 4.1, and only nine of the studies used more than two mammograms. Several studies showed that adding change of density or mammographic features improved model performance. Variation in risk of bias of studies was highest in prognostic factor measurement and study confounding.This review provided an updated overview and revealed research gaps in assessment of the use of texture features, risk prediction, and AUC. We provide recommendations for future studies using repeated measure methods for mammogram images to improve risk classification and risk prediction for women to tailor screening and prevention strategies to level of risk.The online version contains supplementary material available at 10.1007/s10552-023-01739-2. Evolving technology from film mammograms to digital images has changed the sources of data and ease of access to study a range of summary measures from breast mammograms and risk of breast cancer . In partThe leading measure for risk categorization extracted from mammograms is breast density , 8. ThisGuidelines recommend screening mammography from age 45 (American Cancer Society ) or 50 , and identify gaps in evidence to prioritize future studies.We considered all studies of adult women (at least 18 years old) involving primary data. Abstract-only papers, review articles, and conference papers were excluded.We included studies measuring change in mammographic features between mammograms. A study had to use at least two different mammograms to be included.Our primary outcomes of interest were risk of breast cancer, including both invasive and in situ cancers, and differences in mammographic features over time. Presence of breast cancer was required to be dichotomized (yes/no), and analysis of other risks  were not included. Studies were required to assess the relationship of the change in mammographic features with risk of breast cancer.Only studies available in English were included.The published literature was searched using strategies designed by a medical librarian (AH) for the concepts of breast density, mammography, and related synonyms. These strategies were created using a combination of controlled vocabulary terms and keywords and were executed in Medline (Ovid) 1946-, Embase.com 1947-, CINAHL Plus 1937-, Scopus 1823-, Cochrane Library (including CENTRAL), and Clinicaltrials.gov. Results were limited to English using database-supplied filters. Letters, comments, notes, and editorials were also excluded from the results using publication type filters and limits.An example search is provided below (for Embase).('breast density'/exp OR ( (breast NEAR/3 densit*):ti,ab,kw OR (mammary NEAR/3 densit*):ti,ab,kw OR (mammographic NEAR/3 densit*):ti,ab,kw)) AND NOT  AND [english]/lim.The search was completed for the first time on September 9, 2020, and was run again on October 14, 2021 to retrieve citations that were published since the original search. The second search was date limited to 2020–October 14, 2021. Full search strategies are provided in Supplementary File 1.Two reviewers  worked independently to review the titles and abstracts of the records. Next, the two reviewers independently screened the full-text of the articles that they did not reject and indicated those measuring mammographic features over time, which were ultimately eligible for inclusion. Any disagreements of which articles to include were resolved by consensus.Reference lists of included studies were hand searched to find additional relevant studies.We created a data extraction sheet which two reviewers  used to independently extract data from the included studies. Disagreements were resolved by a third reviewer. If included studies were missing any desired information, any additional papers from the work cited, such as previous reports, methods papers, or protocols, were reviewed for this information.Any estimate of change in a mammographic feature over time or risk of breast cancer was eligible to be included. Predictive ability could be evaluated using an area under the curve, hazard ratio, odds ratio, or relative risk. Change could be reported as a percentage or an absolute value. No restrictions on follow-up time were placed. For studies that reported multiple risk estimates, we prioritized the primary models which were discussed in the results section of the paper. If all models were discussed equally, then we listed the models with the best ability to predict breast cancer. For studies that reported multiple types of change, we prioritized the primary types which were discussed in the results section of the paper. If all types were discussed equally in the results section of the paper, then we listed the most frequent types of change observed in women using data listed in the tables.The report: author, publication year;The study: location/institution, number of cases, number of controls;The research design and features: lapsed time from mammogram to diagnosis;The mammogram: machine type, mammogram view (s), breast (s) used for analysis, time between mammograms, number of mammograms;The model: how density was measured, type of model, baseline variable (s), texture feature (s), prediction horizon.We collected data on:The quality of the included studies was assessed using the Quality in Prognostic Studies (QUIPS) tool . Risk ofFor the prognostic factor measures domain, studies that used discrete categories of density were rated as high-risk of bias and those that used continuous measures assessed by machine were rated as low-risk of bias. For the study confounding domain, studies that adjusted for age, body mass index, menopausal status, and hormone therapy were considered to have a low-risk of bias.This review was not registered, and a protocol was not prepared.The search and study selection process is shown in Fig. Of the 5,329 unique citations, 5,124 were excluded based on review of title and abstract. Two hundred five full-text reports were retrieved and assessed for eligibility by two readers. Of these, One hundred eighty five were excluded for reasons such as not measuring change, not having risk of breast cancer as an outcome, being an abstract or a duplicate paper, or not being published in English.Ten potential reports were identified from hand searching of citations. All of these were reviewed by full-text, and nine were excluded for being duplicates or not having a measure of change in a mammographic feature.After fully screening search results, twenty studies meeting eligibility criteria were included in the review –42. ThesThe key descriptive features of the 20 eligible studies are summarized in Table Figure Data from studies of change in mammographic density or other features and subsequent risk incorporated into models that are evaluated using an area under the curve (AUC) are summarized in Table Kerlikowske et al. showed modest improvement in estimating 5- and 10-year risk with AUC increasing from 0.635 using only one measure of density to 0.640 using two measures . Brandt In Supplementary Table 3, we summarize the number of mammograms used and the prediction horizon, which is how far ahead the model predicts risk of breast cancer. Only 1 study   based onOther measures of association , odds ratio (OR)) are reported in studies that focus on the association between mammographic features and cancer risk. The statistical methods used to model change and assumptions including the breast imaged  and approach to comparing cases and controls for 15 other association studies are summarized in Supplementary Table 4 , 40–42. a < 5% increase or decrease, but these results were non-significant [Many of these studies also observed increased breast density over time was associated with an increase in the risk of breast cancer , 41, 42 Results from the assessment of risk of bias are shown in Supplementary Table 5. While many studies demonstrated similar risk of bias within specific domains, there is some variability, especially for prognostic factor measurement and study confounding. For prognostic factor measurement, studies that used categorical approaches such as BI-RADS or averaged the left and right breasts had a higher risk of bias than those using continuous measures assessed by machine approaches. For study confounding, studies that adjusted for age, body mass index, menopausal status, and hormone therapy were considered to have a lower risk of bias.Study reporting impacted our ability to rate risk of bias. Only one study reported information to judge study attrition risk of bias , leavingWe identified twenty studies addressing change in breast density or other mammographic features and risk of breast cancer. Of these, nine had only two images , 36, 42 Variation in risk of bias observed in these studies reflect the variation in methods particularly in prognostic factor measurement and consideration of confounding. Level of reporting impacted our ability to fully assess risk of bias in these studies.It is difficult to draw conclusions about the differences in results and overall conclusions across the different measurements of change summarized here. Since 2016 analyses draw extensively on digital mammograms with a number of approaches to summarizing breast density and change in density. For example, only one study reported mammographic density change in terms of breast dense area . In geneFocus of these studies is predominantly on mammographic breast density with limited study of change in texture features. Only two studies look at change in texture features , 39. A rThe twenty studies included in our review varied in the view of the breast used. A meta-analysis showed that the craniocaudal view may have a stronger association with breast cancer risk , but theWith only two images used, change in category is limited and the shorter time interval between images reduces power to differentiate trajectories of mammographic features over time. There is a steady decline in mammographic breast density through midlife to menopause and beyond , 49. ThiWe might ask, given the low rate of decline in mammographic density with age as described , 49, is Some studies indicate differences in mammographic density between the left and right breasts may be a risk factor for breast cancer, but more research is needed , 51, 52.It can be more difficult for radiologists to detect cancers in dense breasts, as the cancer can be masked by the dense tissue . BecauseThere is increasing interest in bringing breast cancer risk reduction approaches to women according to their level of risk , 58. In There are several limitations with the current review. Heterogeneity of the data did not allow for a meta-analysis. No joint models considering features through time and risk were also included in this review, as none were identified that met our inclusion criteria. This highlights a gap in methodology that future work could address. Additionally, systematic reviews are always subject to possible publication bias if all relevant studies have not been published. We used several strategies to reduce the risk of this including using a thorough search strategy designed by a medical librarian with expertise in searching for systematic reviews and searching clinicaltrials.gov for any ongoing studies.There exist several gaps in the methodology of studies assessing risk of breast cancer using change in mammographic features. Based on these, we provide recommendations for future studies to make use of accumulating image data. Despite current limitations in the literature, the more widespread use of digital mammography and availability of digital images repeated over time offers growing opportunities to improve risk classification and risk prediction for women.Supplementary file1 (PDF 116 KB)Supplementary file2 (PDF 353 KB)Below is the link to the electronic supplementary material.


AimThe development of lymphedema post-breast-cancer surgery has been identified as a significant burden worldwide, with nurses at the forefront of prevention and risk reduction practices. Prevention is of crucial importance to avoid lymphedema formation and its complications. This study aims to assess the knowledge gained through an educational session regarding risk reduction and prevention of breast cancer-related lymphedema (BCRL) among nursing professionals and compare the pre-test and post-test knowledge.Methods and materialThe research approach was quantitative in nature, and the design adopted was a pre-experimental, one-group pre-test post-test design. The study was conducted in a 400-bed multispecialty teaching hospital in Bangalore, Karnataka. After obtaining formal permission from the authorities, the participants were approached and informed about the purpose of the study. Eighty-four staff nurses working with breast cancer-related lymphedema (BCRL) patients participated in the study. The data for the study was collected using a validated questionnaire based on the National Lymphedema Network's (NLN) breast cancer-related lymphedema (BCRL) risk reduction and preventive guidelines. The questionnaire consisted of two sections. Section A consisted of the staff nurses' demographic data, and Section B consisted of questions on risk reduction and prevention of lymphedema. The pre-test was conducted, followed by a structured teaching session on risk reduction and prevention of lymphedema among 84 staff nurses working with BCRL patients. After the teaching session, the post-test was conducted.ResultsDescriptive and inferential statistics were used for analysis in this study. The t-test determined the statistical significance using the software SPSS . The result showed that the mean knowledge score was 4.286 with SD 0.97 in the pre-test, which increased to 4.452 with SD 1.511 with a significant p-value (<0.001). ConclusionAccording to the study's findings, nurses must get standardized lymphedema training in order to prevent lymphedema from developing in patients having breast cancer surgery. The study's outcome has implications on the focus areas for nurses in the context of the team's adoption and dissemination of breast cancer-related lymphedema preventive measures.Key messages of this study are - 1) BCRL is an irreversible, progressive complication with no cure if not diagnosed early. 2) Poor knowledge of lymphedema prevention among nurses leads to frustration for BCRL patients. 3) Risk reduction and prevention education enable the patient to reduce BCRL complications, minimize the severity of the condition, and improve the quality of life. 4) Pre-habilitation - patient education on early diagnosis and risk reduction/prevention of BCRL reduces the cost, time, and energy for the patient and health care delivery system. Women treated for breast cancer commonly experience breast cancer-related lymphedema (BCRL) as a complication. Since lymphedema (LE) has no known treatment, vigilance and prevention are crucial to reduce mortality and lessen the severity of its long-term effects. It can be avoided or diminished with the appropriate nursing measures. In order to prevent LE, nurses are essential in assisting patients in accepting accountability for their own LE . PatientBackgroundOne of the studies claims that most medical professionals cannot adequately inform patients who are having breast surgery. According to studies, most patients are not given even the most basic information concerning complications of lymphedema (LE). Healthcare professionals (HCPs) must have specialized training in lymphedema physiology, risk reduction, and preventive strategies. By educating patients on the causes, signs, and symptoms of lymphedema, providing ongoing, thorough assessments of lymphedema during each visit, and supporting research in this area, nurses being on the front lines may hold the answer to actively avoiding lymphedema in many patients .HCPs must have sufficient clinical knowledge to inform patients about breast cancer-related lymphedema (BCRL) appropriately. According to Thomas-MacLean et al., a lack of knowledge among HCPs is common and evident across various disciplines, including the surgeon, oncology department staff, and family physician . Many paPurpose of the studyHCPs understanding of lymphedema is crucial for educating patients or communities at risk. Finding the knowledge gaps in HCPs that may present an opportunity for appropriate interventions is crucial because lymphedema is not adequately addressed in medical research and education and may already have fallen by the wayside of healthcare delivery in various countries .This study aims to assess the efficacy of education in raising nurses' awareness of the risk factors and preventive aspects of lymphedema among patients who underwent surgery for breast cancer. This information may help nurses better fulfill their duty to educate patients effectively, provide high-quality care, and improve health outcomes for those who are at risk for lymphedema.Risk factors of breast cancer-related lymphedemaOne of the most worrisome side effects of cancer treatment is lymphedema, which develops when protein-rich lymph fluid builds up in the subcutaneous tissue and the lymphatic system's carrying capacity is reduced . LE can According to Torres et al., there are no nursing practice guidelines for educating about, assessing, managing, or monitoring lymphedema. For at least a year following surgery, educating patients about lymphedema "may help prevent and decrease subsequent lymphedema in patients undergoing breast cancer surgery, including dissection of axillary lymph nodes" . The greNurses must be aware of this challenging issue in order to inform breast cancer patients about the lifelong dangers of contracting this illness. Breast cancer survivors should also be taught how to maintain a self-care routine for managing symptoms and preventing exacerbation in order to reduce their risk of developing lymphedema. The self-care plan calls for regular skin care, the use of gloves during daily activities to prevent skin breaks, protection from harm on the affected side, prevention of muscular strain, and lymphatic drainage promotion. During hospital stays related to breast cancer treatment, nurses should look for opportunities to instruct patients on lowering their risk of developing lymphedema or managing it. The recovery of the patient may be affected by such a strategy. Additionally, the same needs to be emphasized in the outpatient setting during survival .Breast cancer-related lymphedema treatmentThe benchmark for managing arm LE is complete decongestive therapy (CDT) performed by a certified lymphedema therapist or trained lymphedema physiotherapist or under the supervision of a trained lymphedema nurse ,21. The Awareness and preventive action are crucial because it can be too late to avoid once symptoms appear. Women must be informed, educated, and instructed on preventative measures and cautionary behaviors to avoid lymphedema. They should start learning about lymphedema when choosing their breast cancer treatment.According to studies, the majority of cancer patients are unaware of LE. This could be because the nurses do not consider patient education part of their job description or lack the necessary expertise ,15,23,24Only a few studies look at nurses' knowledge, attitudes, and behaviors to avoid LE, even though a significant trend nowadays emphasizes the necessity of LE patient education. Preventing LE, a severe issue following cancer surgery should be a priority for nurses when educating patients. If nurses are not knowledgeable enough about lymphedema, they will not stress the importance of prevention or instruct patients on how to do so. The purpose of this study was to evaluate nurses' knowledge of LE.By describing and documenting the effects of an education program on healthcare providers' understanding of the risk and prevention of lymphedema for women who have undergone breast cancer treatment, this study considerably contributes to the field of nursing. The study's findings might be applied to enrich the healthcare workers' training programs that work with this patient population. Research questionWill nurses attending educational sessions on breast cancer-related lymphedema show a greater understanding of the causes, symptoms, risk reduction, and prevention of lymphedema?Study designThis study is a pre-experimental design that uses non-probability convenience sampling to examine the impact of an educational program on nurses' knowledge of reducing the risk and preventing breast cancer-related lymphedema among breast cancer patients.Study populationThe sample consisted of 84 female staff nurses in a teaching hospital eligible to care for patients undergoing post-mastectomy surgery for breast cancer treatment. The following factors were considered for sample selection for the study.1. Nursing staff who are working in the selected hospital2. Nursing staff who are available to attend the BCRL risk reduction and prevention session completely3. Nursing staff working in oncology and post-operative wards Data collection toolDemographic DataQuestions one to six included age, gender, years of experience, professional qualification, and experience in the oncology department.Knowledge QuestionnaireThis included questions on risk reduction/prevention of BCRL based on the National Lymphedema Network (NLN). NLN is a position paper that provides information on lymphedema, its treatment, and risk reduction practices as guidelines for healthcare professionals and patients. The tool had two sections:Sections A and BSection A included 10 items consisting of general information on lymphedema and Section B included 33 items regarding the knowledge that nurses should impart to breast cancer patients in order to lower their chances of developing lymphedema (26 items) as well as (seven items) on measures to improve the dissemination of reducing the risk of BCRL.Scoring and InterpretationEach correct answer was scored as one and the wrong answer as zero. The total score was 43.The score was interpreted as follows:>75 % Highly adequate knowledge50% - 75 % Moderately adequate knowledge< 50% Inadequate KnowledgeData collection The opinions of ten professionals, including faculty members, physicians, and nurses, were incorporated to ensure the questionnaire's content validity. These were further reviewed, and following the necessary preparations, ten nurses received pre-testing. The primary study did not include these nurses. The tool reliability was obtained by using a test-retest method, and the score was 0.86. The tool was reliable for conducting the study.The 'convenience sampling' technique was used. Nurses who were present on the day of the educational session and ready to attend the session were included in the study.After receiving approval from the Institution's Research Ethics Committee , a one-group pre-test post-test design was conducted. The participants received a verbal and written explanation of the study's objectives prior to the collection of data. The right to secrecy and anonymity, the opportunity to contact the researcher with any queries, and the right to withdraw from the study were all guaranteed by the written informed consent given to each participant. The participant's agreement to participate was indicated by the completed paperwork being returned.Eighty-four nurses in the study signed the consent form and received the questionnaire. This questionnaire included demographic data and information on lymphedema caused by breast cancer treatment and risk reduction practices/ prevention. After twenty minutes, the nurses submitted their completed forms. The participants then received a structured teaching session of 40 minutes on breast cancer-related lymphedema, including its definition, pathophysiology, risk factors, complications, risk reduction practices/ prevention, and management.Table After the education session, the nurses were given the same questionnaire on breast cancer-related lymphedema. Later, the completed forms were analyzed.Data analysisBoth descriptive and inferential statistics were used. Distribution, percentage, mean, median, and standard deviation were used in descriptive statistics. SPSS  was used to analyze the data. A paired t-test was used to analyze the data, and the p-value of <0.001 levels was highly significant.Major findings of the studyFifty-seven percent (57%) of the subjects had 'moderately adequate' knowledge and 29% had 'highly adequate' knowledge of BCRL risk reduction/prevention practices. Seventy-three percent (73%) of the subjects agreed that written information on BCRL risk reduction/prevention should be provided to the patients. Eighty-five percent (85%) of the subjects accepted that the initial days of breast cancer diagnosis are the best time to provide information on BCRL risk reduction/prevention. Eighty-nine percent (89%) agreed on the measures to improve the dissemination of reducing the risk of lymphedema to breast cancer patients.Table Table Table Table Nurses play a key role in health promotion and maintenance and are crucial in implementing learning to practice. Relevant care for BCRL patients will require education and training. Patients' chance of acquiring lymphedema can be decreased, and those who already have it can prevent it from getting worse by being informed about it.Fifty-eight percent of the subjects in this study revealed that the nurses' time to educate the breast cancer survivors on lymphedema prevention and risk reduction was less than an hour per day. In general, nurses state that despite their primary role to educate the patients on preventive aspects, they cannot do so due to an increased number of patients, lack of time, lack of continuing education to update the information, and lack of expectations on patient education. In addition, nurses' inefficient time management, turnover, burnout, lack of appropriate clinical setting, and inadequate nurse-patient ratio are some issues affecting patient education. Even though the effect of BCRL is vast, it has been undiagnosed and neglected for various reasons . YildiriIn the current study, 57% of nurses had good knowledge of risk reduction/prevention of BCRL, and 29% had excellent knowledge about BCRL risk reduction/prevention aspects, which is corroborated with the correct mention of aspects for BC patients to reduce risk of lymphedema development. One study highlights that when nurses know the definition, causes, signs and symptoms, physiology, and treatment, it enables early assessment of BCRL risk and recognition of symptoms . Patients unaware of BCRL and its symptoms cannot report it at the right time. Education and providing information to patients will help them to reduce the risk and prevent the progression of swelling. In this study, 85% of nursing staff agreed that the best time to provide information on lymphedema risk reduction/prevention is the day of breast cancer diagnosis. Ridner et al., in their study, emphasized that education on BCRL pre-treatment will enable the recollection of lymphedema information in breast cancer survivors and might have an impact on reducing the risk of developing lymphedema .In the present study, 96% of nursing staff agreed to measure the weight of the breast cancer survivors, and 73% agreed to calculate body mass index (BMI) as they were aware of the close relationship between BMI and lymphedema development. High BMI during breast cancer diagnosis is a well-established risk factor for developing BCRL . This fiTable As per breast cancer survivors and the nursing personnel, information on lymphedema risk reduction and prevention needs to be provided at various timeframes from breast cancer diagnosis during treatment through follow-up and beyond. Table Nurses are the key personnel in the healthcare team, who play a vital role in health promotion and maintenance and are crucial in implementing learning to practice. The healthcare delivery system in the present scenario needs to emphasize the preventive and rehabilitative aspects of patients with breast cancer and secondary lymphedema. Creating awareness among healthcare professionals, utilizing it for breast cancer patients, and involving family members will help control the severity of the condition.This study motivates students and oncology staff nurses to practice pre-habilitation by assessing baseline data like arm measurements preoperatively and preoperative education on BCRL to prevent and reduce the risk of breast cancer-related lymphedema development.The study has some limitations; one is the small sample size; hence the findings cannot be generalized. Secondly, the study was conducted among nursing personnel in a single hospital. The outcome variables may vary depending on the educational background and specialization of the participants, hospital policy, and study locality. The study can be replicated with a large sample size of different healthcare professionals to create and reinforce awareness of prevention and risk reduction practices among post-mastectomy patients. The study can be conducted as an experimental research design with interventions and follow-up of the patients to assess the adherence to self-care practices compared with the study and control group.The study results show increased knowledge of BCRL risk reduction practices in the post-educational session compared to pre-test data among the nurses. To lower the risk for lymphedema, nurses should educate breast cancer patients about their risk, offer instructions, and promote self-care practices.According to this study, a structured teaching/education program for nurses regarding the risk of LE incidence is urgently needed, primarily to provide information for patients who have undergone breast cancer surgery. Nurses will need to transition from past practices to the latest developments in rehabilitation with new cancer patients. Hence regular in-service education is required to update the present knowledge.


Breast cancer continues to be the leading form of cancer among women in the United States. Additionally, disparities across the breast cancer continuum continue to increase for women of historically marginalized populations. The mechanism driving these trends are unclear, however, accelerated biological age may provide key insights into better understanding these disease patterns. Accelerated age measured by DNA methylation using epigenetic clocks is to date the most robust method for estimating accelerated age. Here we synthesize the existing evidence on epigenetic clocks measurement of DNA methylation based accelerated age and breast cancer outcomes.Our database searches were conducted from January 2022 to April 2022 and yielded a total of 2,908 articles for consideration. We implemented methods derived from guidance of the PROSPERO Scoping Review Protocol to assess articles in the PubMed database on epigenetic clocks and breast cancer risk.Five articles were deemed appropriate for inclusion in this review. Ten epigenetic clocks were used across the five articles demonstrating statistically significant results for breast cancer risk. DNA methylation accelerated age varied by sample type. The studies did not consider social factors or epidemiological risk factors. The studies lacked representation of ancestrally diverse populations.DNA methylation based accelerated age as captured by epigenetic clocks has a statistically significant associative relationship with breast cancer risk, however, important social factors that contribute to patterns of methylation were not comprehensively considered in the available literature. More research is needed on DNA methylation based accelerated age across the lifespan including during menopausal transition and in diverse populations. This review demonstrates that DNA methylation accelerated age may provide key insights for tackling increasing rates of U.S. breast cancer incidence and overall disease disparities experienced by women from minoritized backgrounds. Despite advances in breast cancer screening technologies and extensive research on the disease, breast cancer persists as having the heaviest cancer burden in women in the United States (U.S.) with marked disease disparities occurring in minoritized populations. Since 2004, there has been a 0.4% rate increase of breast cancer incidence with estimates suggesting 1 in 8 women will be affected by this diagnosis in their lifetime . Early oAge remains one of the strongest predictors of breast cancer , 6 makinvia DNAm provides a key site of inquiry for disease prevention. This review focuses on elucidating the available evidence on DNAm in breast cancer risk as a potential marker for surveillance and intervention as DNAm has been found to be reversible and modifiable via lifestyle and psychological intervention  AND  AND (“risk factors” [mesh] or “risk” [mesh] OR “risk assessment” [mesh] OR “genetic predisposition to disease” [mesh] OR risk [tiab] OR risks [tiab] OR predictor* [tiab] OR association [tiab] OR correlat* [tiab] OR clock [tiab] OR clocks [tiab]). A total of seven searches of PubMed using search terms were completed by study team members from January 2022 to April 2022. The searches yielded a total of 2,908 articles. Seventy-five articles were identified as suitable for additional review and discussion for inclusion in this review.The eligibility for inclusion was: 1) the study must use an epigenetic clock to assess epigenetic accelerated age in their sample, 2) primary outcome is breast cancer risk, 3) U.S. based study sample 4) published in a peer-reviewed PubMed indexed journal, 5) must have been published by April 30, 2022. Three individuals  independently conducted reviews of all titles and abstracts yielded in the searches to assess the inclusion and exclusion criteria of each article. In the first round of reviews duplicate articles were identified and removed. During the independent reviews, the three individuals made decisions on the reviewed articles eligibility for inclusion. Articles that had conflicting decisions for inclusion or exclusion made during the independent reviews were discussed by the reviewers . Final decisions were made on the article with conflicting decisions based on consensus. In instances where consensus could not be reached, CIV made the final decision for inclusion. Through this process a total of five articles were identified as suitable for inclusion in the review.via discussions between DS, JD, and CIV to identify recurring themes and methods across the studies. The identified themes of the included studies are outlined in the results section.Following the team decision phase, articles identified as being appropriate for inclusion were then examined for data extraction. Data extraction was conducted using a uniform extraction tool that identified the research design, study sample, specimen type, analysis conducted, and study results. Data extraction and coding was conducted by DS, AV, and CIV. Next, we completed a data summary phase conducted by DS and CIV. As the studies included in the review were subjected to the peer review process of a PubMed indexed journal, this process was assumed to provide a robust critical appraisal of the scientific product within the studies in this review. Lastly, an additional level of scrutiny was applied to articles To assess the evidence on the utility of epigenetic clocks in predicting breast cancer risk, we used the PROSPERO Scoping Review Protocol for guidance on conducting a high-quality review. We first conducted a comprehensive search on the PubMed database to capture relevant articles. We then independently reviewed and applied the outlined inclusion and exclusion criteria to the articles yielded in the database search. We extracted the data for the studies deemed appropriate for inclusion for this review. Lastly, we synthesized the findings of the included papers to identify important evidence and themes. A total of five articles met the inclusion criteria Table 1 The data sources used by these studies included Komen Breast Tissue Bank , 28, theThe studies included in this review indicate that DNAm accelerated age as measured by epigenetic clocks had an associative relationship with the development of breast cancer. This indicates that DNAm accelerated age may serve as an important and understudied disease risk factor. A total of 10 different epigenetic clocks were used Table 1.r=0.96). Kresovich et al. (r=0.88), Horvath (r=0.87) and Levine (r=0.83) DNAm age and chronological age. Rozenblit et al.  all six epigenetic clocks DNAm correlated with chronological age  for normal breast tissue and r=0.30 (p <0.01) for malignant breast tissue  dt tissue . The stut tissue  found tht tissue  findingsKresovich et al.  identifiOur review identifies a gap in the literature on the assessment of social factors, such as adversity and epidemiological risk factors, as a driver of DNAm accelerated age measured by epigenetic clocks. This is a critical gap as there is substantial overlap in factors that result in DNAm age acceleration  and breaEpigenetic clocks have been developed to be applied to different biosamples such as tissue, blood, saliva, and cells such as buccal epithelial cells . CompariMenopausal transition and menopause are major milestones in women’s lives with health implications that extend beyond reproductive capacity . The impThe data gap of ancestrally diverse populations in human genetic research has been previously discussed . ValidatThis review paper comprehensively syntheses the available evidence on epigenetic clocks in breast cancer to understand the role of DNAm accelerated age in breast cancer risk with the goal of identifying translational tools to target disparities experienced by minoritized women. Epigenetic clocks are a promising tool for breast cancer risk surveillance and should be evaluated for integration into clinical practices for disease prevention intervention which could bring us closer to alleviating the overall breast cancer burden experienced by women. As DNAm is reversible and modifiable through psychological , 41, 42 CV, DS, JD contributed to conception and design of study. CV, DS, JD, AV contributed to the database searches and article reviews. CV wrote the first draft of the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.


Breast cancer is a heterogeneous disease, and the distribution of the different subtypes varies by race/ethnic category in the United States and by country. Established breast cancer-associated factors impact subtype-specific risk; however, these included limited or no representation of Latin American diversity. To address this gap in knowledge, we report a description of demographic, reproductive, and lifestyle breast cancer-associated factors by age at diagnosis and disease subtype for The Peruvian Genetics and Genomics of Breast Cancer (PEGEN-BC) study.The PEGEN-BC study is a hospital-based breast cancer cohort that includes 1943 patients diagnosed at the Instituto Nacional de Enfermedades Neoplásicas in Lima, Peru. Demographic and reproductive information, as well as lifestyle exposures, were collected with a questionnaire. Clinical data, including tumor Hormone Receptor (HR) status and Human Epidermal Growth Factor Receptor 2 (HER2) status, were abstracted from electronic medical records. Differences in proportions and mean values were tested using Chi-squared and one-way ANOVA tests, respectively. Multinomial logistic regression models were used for multivariate association analyses.vs. 76% overall, p=0.007; 152 cm vs. 153 cm overall, p=0.032, respectively). In multivariate models, IA ancestry was associated with HR-HER2+ subtype  and parous women showed increased risk for HR-HER2+  and HR-HER2- tumors  compared to nulliparous women. Multiple patient and tumor characteristics differed by age at diagnosis (<50 vs. >=50), including ancestry, region of residence, family history, height, BMI, breastfeeding, parity, and stage at diagnosis .The distribution of subtypes was 52% HR+HER2-, 19% HR+HER2+, 16% HR-HER2-, and 13% HR-HER2+. Indigenous American (IA) genetic ancestry was higher, and height was lower among individuals with the HR-HER2+ subtype (80% IA The characteristics of the PEGEN-BC study participants do not suggest heterogeneity by tumor subtype except for IA genetic ancestry proportion, which has been previously reported. Differences by age at diagnosis were apparent and concordant with what is known about pre- and post-menopausal-specific disease risk factors. Additional studies in Peru should be developed to further understand the main contributors to the specific age of onset and molecular disease subtypes in this population and develop population-appropriate predictive models for prevention. Globally, breast cancer is the most commonly diagnosed cancer and the leading cause of cancer death in women , 2. BreaThe use of gene expression profiles for molecular classification of breast cancer tumors  has identified three main intrinsic subtypes: Luminal (A and B), HER2-enriched, and Basal-like , 14. A cMultiple studies have suggested heterogeneity in the association between established breast cancer risk factors and tumor subtype. Family history of breast cancer in a first-degree relative is associated with increased breast cancer risk , 18, 19,The effects of some of the abovementioned factors are different among pre- and post-menopausal women. Controversial evidence shows that high BMI (obesity) is protective against breast cancer in premenopausal women, and conversely, it suggests that obesity increases the risk in postmenopausal women , 40, espPrevious studies have assessed the association of breast cancer risk with numerous structural, social, environmental, and genetic factors , 48–50; The Peruvian Genetics and Genomics of Breast Cancer Study (PEGEN-BC) is a hospital-based cohort including patients from the Instituto Nacional de Enfermedades Neoplásicas (INEN) in Lima, Peru. We have previously described the distribution of demographic, anthropometric, reproductive, lifestyle, and clinical factors for 1,312 breast cancer participants, with an emphasis on the distribution by breast tumor subtypes . MoreoveThe Peruvian Genetics and Genomics of Breast Cancer Study (PEGEN-BC) is a hospital-based cohort study. As of April 2022, we have recruited 1,943 participants from the INEN in Lima, Peru. Women were invited to participate if they had a diagnosis of invasive breast cancer in 2010 or later and were between 21 and 79 years of age when diagnosed. A blood sample was drawn by a certified phlebotomist at the INEN central laboratory. The present report includes analyses with a subset of 1,796 patients with available genetic ancestry estimates . This st2), normal (BMI ≥ 18.5 < 25 kg/m2), overweight (BMI ≥ 25 < 30 kg/m 2), and obese (BMI ≥ 30 kg/m2). Alcohol use was assessed as the self-reported frequency of glasses of alcohol consumed per day and categorized as < 1 glass/day, > 1 glass/day, and non-drinker (never). Smoking status was classified into “ever” (current and former) and “never.” If there was a history of familial breast cancer, the relative  was indicated to determine cases with breast cancer family history in a first-degree relative. Clinical variables, including ER, PR, HER2, lymph node status, tumor grade, and clinical stage, were extracted from electronic records.Each PEGEN-BC participant completed a standardized survey administered by a trained research coordinator at INEN. The survey includes questions regarding anthropometric (weight and height), demographic (place of birth and residence), lifestyle , and reproductive  variables, and family history of breast cancer. Weight and height were assessed by trained nurses/professionals at INEN at the time of diagnosis. Body mass index (BMI) was calculated as weight (kilograms) divided by height (meters) squared and categorized as underweight (BMI < 18.5 kg/m k = 4), including 122,605 independent variants. The PEGEN-BC study includes a large proportion of patients with > 98% Indigenous American ancestry, as previously reported  IHC result. These markers were used to classify tumors as HR+HER2−, HR+HER2+, HR−HER2+, and HR−HER2−. Two independent pathologists from the University of California San Francisco reviewed the IHC slides at INEN for a subset of 52 patients. The concordance rate was 100% for ER, 87% for PR, and 85% for HER2. Most of the discordant calls for HER2 were scored as “negative” or 1+ at INEN and 2+ by the independent pathologists. Immunohistochemical subtype classification was not available for 141 samples (7%).Tumoral tissues were obtained from core biopsy or freshly resected invasive breast cancers pre-treatment that were formalin-fixed and paraffin-embedded following standard protocols at INEN. Tumor subtypes were defined using immunohistochemistry (IHC) markers by a certified pathologist at INEN. HR positivity was defined at 1% or more cells showing ER and/or PR staining. HER2 positivity was defined as 3+ staining by IHC or by gene amplification detected by fluorescence 2 transformed. The correlation between genetic ancestry and continuous and categorical variables was performed using Pearson’s correlation coefficient test and Point-Biserial Correlation Coefficient, respectively. Multinomial logistic regression models were used to calculate odds ratios (ORs) and 95% confidence intervals (CI) for the association of multiple variables and subtype-specific breast cancer. East Asian and African ancestry proportions were not included in multivariable models due to the low contribution of these components and high correlation with the Indigenous American/European axis of ancestry variation. P-values (P) <= 0.05 were considered statistically significant. All analyses were conducted in R v.3.6.0 , and differences by tumor subtype were not statistically significant (p = 0.087). PEGEN-BC study patients included individuals born in the three main biogeographic regions of Peru (The most common breast cancer subtype among PEGEN-BC study participants was HR+HER2− (52.4%), followed by HR+HER2+ (18.7%), HR−HER2− (16.0%), and HR−HER2+ (12.9%) Table 1.Estimates of individual continental genetic ancestry were available for 1,796 patients. Average Indigenous American ancestry among patients was 76.5%, followed by 18.0% European, 4.2% African, and 1.4% East Asian Table 1.SD = 15)  Table 1.SD = 6.6), with lower average height among patients diagnosed with HR−HER2+ tumors compared with all other subtypes . There were no statistically significant differences in weight or BMI by tumor subtype, with a large overall proportion of patients being overweight (40.1%) (The average height of patients was 153.3 cm ( (40.1%) Table 1.Most PEGEN-BC patients (68.7%) reported low levels of alcohol consumption (< 1 glass/day), whereas 7.4% reported consuming more than one glass per day. Moreover, 27.9% of participants reported being a current or past smoker. There was no statistically significant association between alcohol consumption, smoking history, and tumor subtype Table 1.Demographic, anthropometric, and lifestyle variables that did not show statistically significant differences by tumor subtypes did not show significant differences by HR status either (SD = 1.7), the average age at first full-term pregnancy was 23.2 years (SD = 5.7), and the average number of full-term pregnancies was 2.42 (SD = 1.8). Most study participants reported having had at least one child (83.5%), and 80% of parous women had at least two children (p < 0.001) (The average age at menarche among PEGEN-BC patients was 12.9 years (children Table 2.Breastfeeding was a common practice among parous women (96.3%), and we did not observe the differences in the proportion of women who breastfed their children by tumor subtype category Table 2.p = 0.016). However, since many of these patients had induced menopause due to treatment, we did not consider this variable in subsequent multivariate analyses and stratified by age at diagnosis instead.More than 85% of women reported being menopausal at recruitment. Patients with HR+HER2− tumors were more likely to report being menopausal than patients with other tumor subtypes  (More than 90% of patients were diagnosed with Grades 2 and 3 tumors Table 3.N = 981) and at 50 years or older (N = 955). Compared with patients diagnosed at 50 years or older, younger patients had higher average Indigenous American ancestry ; they were more likely to reside in the Mountainous region , and they were 1.4 cm taller (p < 0.001) and had lower prevalence of obesity  , and a larger proportion of younger patients reported breastfeeding their children   and presented with more advanced disease   Table 4.Additional stratified analyses comparing demographic, anthropometric, reproductive, and clinical factors by tumor subtype in the two different age groups are included as Supplementary Materials , weight , height , age at first full-term pregnancy , family history of breast cancer in a first-degree relative , smoking history , HR+ status  and a positive correlation with age at menarche  and HER2+ status .We assessed the correlation between Indigenous American ancestry and patient and tumor characteristics to better understand the observed patterns in ancestry distribution and those factors by tumor subtype in the PEGEN-BC study. We observed an inverse correlation between Indigenous American ancestry and age at diagnosis (p = 0.02). Smoking history and height were no longer statistically significantly associated with subtype. Parous women were more likely to be diagnosed with HR−HER2+  and HR-HER2-  disease compared with the HR+HER2− subtype. Family history of breast cancer in a first-degree relative was not included as a covariate in the multivariate model because the number of patients that reported family history of breast cancer in a first-degree relative was relatively small and rendered unstable estimates when included. We tested models excluding patients with a family history of breast cancer, and results were similar to those using the full dataset . Patients that resided in the Mountainous region had reduced odds of being diagnosed at 50 years of age or older compared with those in the Coastal region . Breastfeeding was associated with lower odds of being diagnosed at 50 years of age or older . Compared with nulliparous women, giving birth to at least one child increased the odds of being diagnosed at an older age . Increasing BMI was no longer associated with age at diagnosis . This work constitutes an update of a previously reported study, including a larger number of recruited patients and extending analyses to describe the distribution of patient characteristics not only by tumor subtype but also by age at diagnosis .vs. 55.5% of cohort patients). The study has an overrepresentation of patients born in the Mountainous region (28.1% Peru vs. 36.4% of cohort patients) (vs. 7.5% of cohort patients)   and an uatients) . The proatients)  and inciatients) .A large proportion of patients were overweight/obese (67%), and the prevalence of exposure to alcohol and tobacco was higher than what has been previously reported for Peruvian women , 72. Thevs. 71.1%). This difference is likely to be explained by the higher positivity percentage cutoff value for HR+ status used in the previous report , increasing the proportion of HR+ tumors in our cohort. Other characteristics, such as age at diagnosis and stage, presented similar distribution to the PEGEN-BC study cohort.The distribution of tumor subtypes is similar to what has been previously described in other Latin American countries , with diWe found statistically significant differences by tumor subtype for Indigenous American genetic ancestry and height. In addition, we observed suggestive associations for age at diagnosis, family history of breast cancer in a first-degree relative and tobacco exposure. Differences were mostly driven by the HR−HER2+ subtype. Among patients with HR−HER2+ disease, we observed that the average height was lower compared with patients diagnosed with other tumor subtypes and was less likely to report smoking or a positive family history of breast cancer in a first-degree relative. Even though subtype-specific associations have been reported for these variables in other populations , 98–101,We did not find statistically significant differences for age at menarche by tumor subtype. Some studies have shown consistent associations between age at menarche and reduced risk of HR+HER2− breast cancer , 19, 20.vs. never) has been associated with a higher risk of HR−HER2− subtypes, especially among women of African origin  among U.S. Latinas and Mexican women , 103. Sovs. >= 50) instead to differentiate early onset versus late onset disease, as it has been widely used in epidemiological studies . Therefore, we did not perform stratification by menopausal status and used age at diagnosis . The patients/participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.LF= Conceptualization, Methodology, Investigation, Formal Analysis, Writing- Review and editing, Supervision, Project administration, and Funding acquisition. VZ: Methodology, Investigation, Formal Analysis, Writing- Original Draft, Software, Data curation, and Visualization. TV= Conceptualization, Resources, Project administration at INEN. SC-Z= Resources, Project administration at INEN. JN-V= Investigation, Data curation. CC, GV, MC, JA, HG, HF, RL-P, JC, SN, KR, JV, LM, MG-N= Conducted patient recruitment investigation process. All authors contributed to the article and approved the submitted version.