Breast tissue biopsies, fasting blood draw and body composition were collected at baseline and 6 months, with between-group changes examined using analysis of covariance method. Baseline and post-intervention biopsies were conducted in 49 and 42 women, respectively, with pre- and post-epithelial tissue available from 25 tissue samples. Average 6-month weight loss was 6.7% for the weight loss group and 2.0% increase for the usual care group (p < 0.0001). At baseline, body fat and serum insulin levels were inversely associated with breast tissue insulin receptor levels and CD68 (p < 0.05). At 6 months, favorable changes were observed in serum leptin and adiponectin levels and tissue CD163 among women randomized to weight loss vs. adverse change in women randomized to usual care (p < 0.05). Breast tissue biopsies are feasible to collect in a clinical research setting among breast cancer survivors, with weight loss favorably impacting metabolic and inflammatory markers associated with breast cancer.Few trials have examined the effect of lifestyle behavioral interventions on tissue markers in patients with cancer. The purpose of this study was to examine the feasibility and impact of a 6-month weight loss intervention on breast tissue and serum biomarkers in women with breast cancer. Fifty-one women who completed breast cancer treatment and had a BMI ≥ 25.0 kg/m The American Cancer Society recommends cancer survivors achieve and maintain healthy body weight, avoid physical inactivity, participate in 150 min of aerobic exercise plus two weekly sessions of strength training, and adhere to a dietary pattern high in vegetables, fruits, and whole grains3. Unfortunately, over 65% of breast cancer survivors are overweight or obese, with fewer than 30% engaging in recommended levels of physical activity5.Obesity is a risk factor for 13 different cancers7. A growing number of studies have examined serum biomarkers such as adiponectin, insulin, C-reactive protein, IL-6, TNF-α, and particularly leptin as said biomarkers are associated with these mechanisms in exercise and/or weight loss trials in cancer survivors or those at risk of developing cancer12.Possible mechanisms through which obesity affects breast cancer risk and mortality include inflammatory, immune, metabolic, and hormonal pathways10 and in women at increased breast cancer risk due to high body mass index , inflammatory macrophage biomarkers of the M1 and M2 phenotype , and biomarkers related to insulin  strongly associated with recurrent breast cancer13.However, examining changes in tissue markers provides a more direct investigation of the impact of lifestyle interventions on tumor biology and allows for the assessment of underlying mechanistic pathways that cannot be examined from blood-based biomarkers alone. Preliminary evidence suggests that weight loss and/or exercise interventions may impact tumor biology in both breast cancer patients14. Given these findings and given the paucity of research examining lifestyle interventions on tissue markers, we sought to determine the feasibility of collecting breast tissue via a baseline- and 6-month biopsy among women treated for breast cancer, and to examine the effect of the LEAN intervention on changes in body composition and breast tissue and serum biomarkers, and explore associations between 6-month changes in body composition and serum and breast tissue biomarkers.Our previous Lifestyle, Exercise, and Nutrition (LEAN) trial demonstrated that a 6-month weight loss intervention was effective in producing an average 6% weight loss and 30% decrease in serum C-reactive protein levels among 100 breast cancer survivors who completed chemotherapy and/or radiation therapyBetween 1 February 2014 and 1 January 2016, 150 women were approached to participate in the LEAN biopsy study, with 110 women screened for participation in the trial. Fifty-one women of those screened (46%) agreed to have two breast biopsies and complete all other baseline and 6-month measures; 26 were randomized to the intervention group, and 25 were randomized to the wait-list/usual care group. Baseline and post-intervention biopsies were conducted in 49 and 42 women, respectively, with pre- and post-epithelial tissue available from 25 women . The mean (SD) age of participants was 56.8 (8.9) years, and their mean BMI (SD) at enrollment was 32.8 (6.0) kg/m2. They have diagnosed a mean of 3.3 years prior, and 54% presented with Stage I breast cancer.Baseline characteristics were similar for women randomized to intervention and usual care Table , except Of the participants randomized to intervention, 12 of 13 women attended 100% of the 11 weight loss counseling sessions; one woman missed one session. A total of 142 weight loss counseling sessions occurred across the 13 women, with 89 (62.7%) sessions occurring in-person and 53 (37.3%) sessions occurring via telephone.p < 0.0001) (Table p = 0.008).At 6 months, there was a 6.7% weight loss in the intervention group versus a 2.0% weight gain in the usual care group (1) Table . Percentp = 0.03) (Table p = 0.03). No other biomarkers changed differently by arms (p > 0.05).Post-intervention, leptin significantly decreased by 27.0% in the intervention group compared to an increase by 7.0% in the usual care group p = 0.0 (Table 3p = 0.51) (Table p = 0.54). CD163 significantly decreased 15.9% in the weight loss group compared to a 34.3% increase in the usual care group (p = 0.04). There was no significant effect of the intervention on CD68 (p = 0.87).At 6 months, Ki67 increased 17.9% in the weight loss group and 25.8% in the usual care group (1) Table . Insulinr = −0.47, p = 0.03) and serum insulin levels  .At baseline, there were statistically significant inverse correlations between breast tissue levels of insulin receptor with both percent body fat , and change in Ki67 breast tissue expression was borderline significantly inversely associated with a change in serum levels of insulin . Change in CD68 breast tissue expression was inversely associated with a change in serum levels of CRP . Change in CD163 breast tissue expression was statistically significantly correlated with change in bone mineral density .At month 6 Table , change A 6-month weight loss intervention in breast cancer survivors who completed chemotherapy and/or radiation therapy led to changes in body weight and fat, serum levels of leptin and adiponectin, and breast tissue levels of CD163.15. Due to the biopsying of normal tissue, the use of ultrasound guidance was not required thus further ensuring cost savings and preventing scheduling challenges required for ultrasound room reservations.Adherence to the intervention was high with 12 of 13 women attending 100% of the 11 weight loss counseling sessions. Furthermore, we demonstrated the feasibility of performing research biopsies of the breast in breast cancer survivors. Fifty-one (46%) of the women approached to participate in the study agreed to undergo two biopsies; of these 100% of participants assigned to the intervention and 92% of participants assigned to the usual care, the group underwent both biopsies. We used a core needle biopsy procedure with a 14-gauge needle without ultrasound guidance which differs from the fine needle aspirate approach used in breast cancer prevention studiesn = 49). Additional exercise prescription consisted of home-based aerobic exercise to achieve a total of 220 min of exercise per week in a mean of 29.3 days prior to breast surgery. The study demonstrated that the intervention, which increased exercise of the patients by 200 min per week from baseline, did not change Ki67 expression but significantly reduced leptin (−12%) and upregulated cytokine–cytokine receptor interactions, NF-kB and chemokine signaling, and natural killer cell-mediated cell cytotoxicity16.To our knowledge, our study is the first to examine the effect of a weight loss intervention on breast tissue changes in women with breast cancer. The Pre-Operative Health and Body (PreHAB) study tested an aerobic and resistance training intervention consisting of supervised aerobic exercise, followed by strength training, on women diagnosed with breast cancer  demonstrated the feasibility of the collection of breast tissue and (b) laid the foundation for larger randomized controlled trials to assess lifestyle interventions on alterations in both breast tumor and healthy tissue. Other studies have examined the impact of the same in prostate tumor tissue in men with prostate cancer17. In addition, we found an inverse association between CRP and CD68/CD163. Given that CD68 and CD163 are macrophage markers of the M1 and M2 phenotype, and CRP is produced by macrophages, it is plausible that our intervention impacted the ratio of M1/M2. We had previously found that aerobic and resistance exercise intervention positively alters M1/M2 macrophage phenotype within subcutaneous abdominal adipose tissue of breast cancer survivors18.Various associations of body composition and serum and tissue biomarkers indicate the necessity of future explorations in this area. In our study, we observed body fat was inversely related to IR gene expression in the breast tissue despite a nonsignificant increase in IR gene expression in the intervention group. This suggests that with a larger sample statistical significance may have been attained. Goodwin et al. (2007) had previously reported higher expression of IR in breast tumor tissue to be independently and significantly associated with more favorable clinical outcomes including low tumor grade, lymph node negativity, progesterone positivity, and improved breast cancer and overall survival19, for example, reported favorable changes in tissue levels of Ki-67 (among 15 women with measurable Ki-67), adiponectin:leptin, cyclin B1, phosphorylated retinoblastoma, and ribosomal S6 proteins in breast tissue of postmenopausal overweight or obese women who had lost weight over a 6-month period19. It is plausible that post-treatment weight loss interventions that alter breast tissue biology elicit a similar protective response to breast cancer recurrence.It is important to recognize our examination of healthy breast tissue rather than breast tumor tissue, as women who participated in this trial had completed therapy and were free of active disease. It is known that benign breast tissue is susceptible to biomarker changes due to modifications in body weight. Fabian et al.20; 11.9% in our exercise trial in women with breast cancer21). The 50%  of breast tissue yielding epithelial tissue is lower than we hypothesized yet understandable given biopsies were performed without ultrasound guidance. Using ultrasound may have increased the number of samples with epithelial tissue22 yet would also increase the cost of the study and also add scheduling challenges. Other study limitations are that imbalance in obesity at baseline across groups, lack of adjustment for multiple comparisons, our final sample size was underpowered for the efficacy outcomes, and in theory, biopsy specimens obtained from a single site may not be indicative of whole breast tissue alterations.Limitations of our study must be acknowledged. Overall, 46% of women screened for the study consented to the two biopsies, implying feasibility. Our 46% enrollment rate (51/110) is higher than we hypothesized and higher than other randomized trials of lifestyle behaviors in healthy women and women with breast cancer  was a randomized trial comparing a weight loss intervention to usual care. All measures were collected at baseline and 6 months. All procedures, including written informed consent, were approved by the Yale School of Medicine Human Investigation Committee.2, who had completed chemotherapy and/or radiation therapy. Women had to be physically able to exercise, give informed consent, be accessible by telephone, and be able to communicate in English.We recruited a new cohort of women treated for breast cancer into the LEAN biopsy study. Women were recruited between 1 February 2014 and 1 January 2016 from Smilow Cancer Hospital medical oncology clinics at Yale, self-referral via study brochures in the Breast Center at Smilow Cancer Hospital, and the Yale Cancer Center Survivorship Clinic. Eligible participants were women diagnosed with breast cancer, with a BMI ≥ 25.0 kg/mTM. Both frozen tissue and tissues placed in RNAlaterTM solution were stored at a lab of Yale Tissue Pathology Services (YPTS) until further analysis. Formalin-fixed, paraffin-embedded biopsy specimens collected in this study were analyzed for KI67, Insulin receptor, CD68, and CD163.Core needle biopsies using a 14-gauge needle were taken from the unaffected breast following standard guidelines and protocols. Three cores were taken: one core was snap frozen, one core placed in 10% neutral buffered formalin, and one core placed in RNAlaterFresh cuts of LEAN study whole tissue slides were deparaffinized and rehydrated before undergoing antigen retrieval using citrate buffer (pH = 6) for 20 min at 97 °C . Slides were incubated with a solution of 0.3% hydrogen peroxide in methanol to inactivate endogenous peroxidase for 30 min, followed: 30 min of incubation with 0.3% bovine serum albumin with 0.05% Tween-20 blocking solution, incubation with a cocktail of Ki67  at 0.46 μg/ml and a wide-spectrum rabbit anti-cow cytokeratin antibody , followed by a 1-h incubation at room temperature with Alexa 546-conjugated goat anti-rabbit secondary antibody . Cyanine 5 (Cy5) directly conjugated to tyramide  at a 1:50 dilution was used as the fluorescent chromogen for Ki67 detection. Insulin receptor staining followed the same protocol with the primary antibody  at 2 μg/ml.Fresh cuts of LEAN study whole tissue slides were deparaffinized and rehydrated before undergoing antigen retrieval using an EDTA buffer (pH = 8) for 20 min at 97 °C . Next, we incubated the slides with a solution of 0.3% hydrogen peroxide in methanol to inactivate endogenous peroxidase for 30 min, followed by another 30 min of incubation with 0.3% bovine serum albumin with 0.05% Tween-20 blocking solution. Fluorescent staining for pancytokeratin, CD68, and CD163, biomarkers of inflammation, was performed by using a sequential multiplexed protocol with different isotype-specific primary antibodies. Antibodies against these targets were used to detect epithelial tumor cells , all macrophages  and M2-class macrophages .23 and then normalized to the exposure time and bit depth at which the images were captured.We used the AQUA method of QIF (Navigate Biopharma), to quantify the fluorescence signal of Ki67, IR, CD68, CD163 that were measured within whole tissue compartments. QIF scores were calculated by dividing the target pixel intensity by the area of the compartment of interestHeight was measured using a stadiometer. Weight was measured while participants were wearing light indoor clothing, without shoes. Dual-energy X-ray absorptiometry scans were performed to assess body fat, lean body mass, and bone mineral density using a Hologic 4500 scanner.A fasting (≥12 h) blood draw was performed and serum samples were stored at −80 °C until assayed. Serum concentrations of insulin, leptin, and adiponectin were measured using radioimmunoassay kits; IL-6 and TNF-α were measured using high-sensitivity enzyme-linked immunoabsorbent assay kits; and C-reactive protein (CRP) was measured using an automated chemistry analyzer.25. Past month dietary intake was assessed at baseline and 6 months by a 120-item food frequency questionnaire developed for the Women’s Health Initiative Study26.At baseline and 6 months, participants completed the Modifiable Physical Activity Questionnaire (MPAQ) administered by an interviewer. The past 6 months of physical activity was assessed including frequency, duration, and type using a validated physical activity questionnaire27 with updates using the 2010 US Dietary Guidelines28 and adapted to breast cancer survivors using the American Institute for Cancer Research/World Cancer Research Fund and American Cancer Society nutrition and physical activity guidelines3. The intervention included a combination of reduced caloric intake, increased physical activity, and behavioral therapy. Participants received individualized counseling sessions once per week (month 1), then every two weeks (months 2 and 3), and once per month . Each of the 11 sessions was 30 min in duration, and represented a core curriculum with specific information about nutrition, exercise, and behavior strategies from the 11-chapter LEAN book developed for the LEAN Study14. Given our previous study comparing in-person and telephone weight loss counseling to usual care found no difference in weight loss via in-person or telephone12, participants were able to choose if a session occurred in-person or via telephone. Participants recorded all food and beverage intake, minutes of physical activity and pedometer steps in the LEAN Journal on a daily basis. Participants were provided with a scale (HoMedics) to weigh themselves once per week, and recorded their weight in the LEAN journal.The weight loss intervention was adapted from the Diabetes Prevention ProgramParticipants were instructed to reduce energy intake to the range of 1200 to 2000 kcal/day based upon baseline weight and to incur in an energy deficit of 500 kcal/day. The dietary fat goal was <25% of total energy intake. The home-based physical activity program included a goal of 150 min per week of moderate-intensity activity, such as brisk walking. Women were given a pedometer and coached to increase their number of steps to 10,000 per day. Reducing sedentary behaviors was encouraged through activities of daily living.The usual care group was provided with the American Institute for Cancer Research nutrition and physical activity brochures and referred to the Yale Cancer Center Survivorship Clinic which offers a two-session weight management program. At the completion of the study, usual care participants were offered the entire LEAN program including the 11 counseling sessions, LEAN book, and LEAN journal.t test or Chi-square test as appropriate. Baseline body composition variables and biomarkers were compared using t test, while 6-month changes of body composition variables and biomarkers were compared between groups using the analysis of covariance (ANCOVA) method with covariate adjustment for baseline value and baseline BMI. Spearman correlation analysis was used to explore the relationship between tissue and serum biomarkers and body composition outcomes at baseline as well as 6-month change from baseline. SAS 9.4  was used for all statistical analyses. Statistical significance was set as p < 0.05, two-sided. Since all the analyses were exploratory, raw p values were reported without adjusting for multiple comparisons29.Demographics and other baseline characteristics were summarized as means and standard deviations for continuous variables or frequencies and percentage for categorical variables. The baseline characteristics were compared using Further information on research design is available in the Reporting Summary


Greater early life adiposity has been reported to reduce postmenopausal breast cancer risk but it is unclear whether this association varies by tumour characteristics. We aimed to assess associations of early life body size with postmenopausal breast cancer and its subtypes, allowing for body size at other ages.A total of 342,079 postmenopausal UK women who reported their body size at age 10, clothes size at age 20, and body mass index (BMI) at baseline (around age 60) were followed by record linkage to national databases for cancers and deaths. Cox regression yielded adjusted relative risks (RRs) of breast cancer, overall and by tumour subtype, in relation to body size at different ages.2=1.20, 95%CI 1.18-1.22) whereas greater adiposity in childhood and, to a lesser extent, early adulthood, was associated with a reduced risk . Additional adjustment for midlife BMI strengthened associations with BMI at both age 10  and at age 20 . The association with midlife adiposity was confined to hormone sensitive subtypes but early life adiposity had a similar impact on the risk of all subtypes.During an average follow-up of 14 years, 15,506 breast cancers were diagnosed. After adjustment for 15 potential confounders, greater BMI at age 60 was associated with an increased risk of postmenopausal breast cancer (RR per 5 kg/mEarly life and midlife adiposity have opposite effects on postmenopausal breast cancer risk and the biological mechanisms underlying these associations are likely to differ.The online version contains supplementary material available at 10.1186/s12885-022-09233-9. Adiposity has qualitatively different associations with pre- and postmenopausal breast cancer . GreaterWe examined associations of prospective, validated information on body size in childhood and early adulthood, and midlife adiposity, with the risk of postmenopausal breast cancer and its main subtypes, as defined by histology, grade, and ER, progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status, in a large study of UK women.www.millionwomenstudy.org) and cohort profile ). Women who did not report body size at age 10, clothes size at age 20, and/or recent height and weight were excluded, as were women diagnosed before baseline with Women contributed person-years from date of completion of the baseline survey, if they reported being postmenopausal by then, or from age 55 otherwise, since most women reach menopause by this age . Person-2). Time since baseline was the underlying time variable. Unless otherwise specified, analyses were stratified by year of birth , year at baseline , and region of residence . Relative risks were adjusted for social deprivation  were used to estimate adjusted relative risks of postmenopausal breast cancer by categories of the three main exposure variables: body size at age 10 ; clothes size at age 20 ; and BMI at baseline , based on the variance of the log risk for each group . HoweverAssociations between risk and adiposity at different ages were summarised using log-linear trends in risk with BMI at age 10, age 20 and at baseline (i.e. around age 60). For BMI at age 60, trends were calculated by assigning a mean BMI to each category of self-reported baseline BMI, derived from measurements in a subsample of participants around 6 years later . For earSummary trends in postmenopausal breast cancer risk with BMI at age 10 and BMI at age 60 were examined by histology, grade, ER status, joint ER and PR status, and by molecular subtype . Summary trends were also compared across subgroups of women defined by time since menopause, reproductive factors, family history of breast cancer and various lifestyle characteristics. Heterogeneity across subgroups was assessed by likelihood ratio tests for addition of an interaction term between each subgroup variable and a body size variable.Of 837,985 women who took part in the baseline survey, 53,241 were excluded because they had a prior history of cancer. Of the remaining 784,744 women, 11,956 were excluded because they had missing information on body size at age 10 or 20, and a further 14,967 were excluded because they had missing information on recent height and/or weight. Among the remaining 757,821 women, 415,742 had ever used menopausal hormone therapy and so were excluded from the main analyses, although they were included in certain sensitivity analyses. Characteristics of the 342,079 women who were included in the main analyses are shown in eTable There was a modest correlation between body size at age 10 and BMI at around age 60  and a moderate correlation between clothes size at age 20 and BMI at around age 60 . The Spearman correlation between body size at 10 and clothes size at 20 was 0.37 (p<0.0001).2 increase in BMI at age 10, age 20, and at age 60 were 0.70 (0.66-0.74), 0.92 (0.89-0.96) and 1.20 (1.18-1.22), respectively.During an average follow-up of 14 years, there were 15,506 incident breast cancers. After adjustment for 15 potential confounders, but not for body size at other ages, greater BMI at around age 60 was associated with increased risk of postmenopausal breast cancer, but greater body size at age 10 and, to a lesser extent, clothes size at age 20, were associated with decreased risk  and 0.78 (0.75-0.81), respectively  was also attenuated, from 0.63 (0.60-0.68) to 0.69 (0.65-0.74), after adjustment for clothes size at age 20 (results not shown). Subsequent analyses, aimed at contrasting the relationships between risk and early versus midlife BMI, focussed on the strongest opposite associations of body size at age 10 and BMI at age 60.The trend in breast cancer risk with BMI at age 20 (adjusted for BMI at age 60) was attenuated from 0.78 (0.75-0.81) to 0.85 (0.82-0.89) per 5kg/m2 but not for HER2-enriched or basal-like cancers (p<0.0001 for heterogeneity by molecular subtype). There was no evidence of any variation in the association of BMI at age 60 with risk by histology or grade  , 0.79 (0.67-0.93), respectively; results not shown), albeit less marked than those for body size at age 10. Categorical relative risks according to body size at age 10, and BMI at age 60, are shown according to ER status in Fig. The association of BMI at age 10 with breast cancer risk, adjusted for BMI at age 60, was very similar for ER+  and ER- cancers  per 5kg/mWhen trends in risk with BMI at age 10 and at age 60 were examined according to 11 personal characteristics (eFigure In this prospective study of 342,079 postmenopausal women, including 15,506 breast cancers, women with greater early life body size had a lower risk of both ER+ and ER- cancer subtypes. Although body size in childhood and young adulthood were both associated with a decreased risk of breast cancer, childhood adiposity appeared to be a bigger determinant of any long-term reduction in risk.Several prospective studies have reported a lower risk of postmenopausal breast cancer among women with greater body size during childhood –5. The lOur finding of a significantly lower risk of postmenopausal breast cancer among women with greater body size at age 20 is supported by some , 4, 14 bMidlife adiposity has been shown to primarily affect ER+ breast cancer , althougThe established associations between adult adiposity and pre- and postmenopausal breast cancer are qualitatively different, but both could be mediated by sex hormones. In postmenopausal women, increased adiposity leads to increased oestrogen synthesis and reduced circulating sex-hormone binding globulin, leading to higher levels of bioavailable oestradiol, which is positively associated with breast cancer risk . In premIn contrast, the explanation for the association between early life body size and breast cancer risk is unclear. Greater early life body size is associated with greater adiposity throughout the adult premenopausal years, which, in turn, is associated with reduced risk of premenopausal breast cancer, which may not be reversed until some years after menopause. However, this is unlikely to explain the strong inverse association observed between body size at age 10 and postmenopausal risk given that the average age at diagnosis in these data was 67, and that the association remained after adjustment for clothes size at age 20. Our findings provide convincing new evidence that childhood adiposity has similar associations with ER- and ER+ subtypes, which suggests that it may influence risk through different mechanisms from those that underlie the association with adult adiposity, for example through its effect on growth hormone profiles  or breasTwo large Mendelian randomisation studies have shown that genetically determined adiposity is associated with a substantial reduction in the long-term risk of postmenopausal breast cancer, and that this risk reduction is similar for both ER+ and ER- breast cancer , 25. GivThe main strengths of this study are the availability of large-scale prospective data on early life body size, and complete, long-term follow-up for breast cancer incidence. Although tumour characteristic information was not complete in these data, the large sample size allowed for reliable assessment of risks by several key tumour characteristics, including ER status and molecular subtype. Restriction of primary analyses to never MHT users eliminated the potential for MHT use to distort the findings, although sensitivity analysis in MHT users showed similar effects of early life body size. While self-reported early life body size in these data corresponds well with BMI measures taken at relevant ages  some misWomen with greater adiposity in early life, and particularly in childhood, have a lower risk of postmenopausal breast cancer. This apparent protection is evident for both ER+ and ER- breast cancer subtypes suggesting that early life adiposity may affect risk through pathways that are not directly related to sex hormones.Additional file 1.Additional file 2.Additional file 3.Additional file 4.


To evaluate the association between body composition and subsequent risk of the major gynecologic malignancies.This is a prospective analysis of participants from the UK Biobank. We measured baseline body composition and confirmed cancer diagnosis through linkage to cancer and death registries. We evaluated hazard ratios (HRs) and confidence interval (CIs) with COX models adjusting for potential confounders.We document 1430 cases of the top three gynecologic malignancies  from 245,084 female participants . For premenopausal women, whole body fat‐free mass (WBFFM) was associated with an increased risk of uterine corpus cancer . For postmenopausal women, compared with the first quartile, the fourth quartile of WBFFM and whole body fat mass(WBFM) was associated with 2.16 (95% CI 1.49–3.13) times and 1.89 (95% CI 1.31–2.72) times of increased uterine corpus cancer risk, respectively. Regarding the distribution of body fat mass (FM)/fat‐free mass (FFM), FFM distributed in the trunk was associate with increased uterine corpus cancer risk in premenopausal  and postmenopausal women . Meanwhile, FM/FFM distributed in the limbs present an U‐shaped associations with uterine corpus cancer risk. We did not observe any association between aforementioned body composition indices with ovarian or cervical cancer.FM is associated with an increased risk of uterine corpus cancer in postmenopausal women. Meanwhile, FFM is found to be a risk factor for uterine corpus cancer in both premenopausal and postmenopausal women. No association of body composition with ovarian or cervical cancer was observed. The aim of this study is to reveal the relationship between body composition and the risk of gynecological malignancies. In addition to finding that body fat mass(FM) is a risk factor for postmenopausal uterine corpus cancer, we also find that fat‐free mass(FFM) is a stronger risk factor for uterine corpus cancer in both premenopausal and postmenopausal women. No association of body composition with ovarian or cervical cancer was observed. Uterine corpus cancer, the vast majority of which is endometrial cancer, has been suggested to be in relation to hormone imbalance.For most previous studies evaluating obesity and risk of gynecological malignancies, traditional anthropometric measurements such as body mass index (BMI), waist circumference (WC), and waist‐to‐hip ratio (WHR) were used as exposure factors. Although these indicators provide simple, cheap, and crude measures of body size, they could neither directly discriminate between fat mass (FM) and fat‐free mass (FFM), nor precisely evaluate the distribution of fat. It has been shown that lower body, upper body, subcutaneous, and visceral fat depots have unique characteristics with regards to fatty acid metabolism. Meanwhile, selective dysregulation of these depots probably plays an important role with the metabolic complications of obesity.UK Biobank is a large prospective study that collected data about body composition and cancer incidence from 0.5 million UK adults.22.1This is a population‐based prospective cohort study based on the UK Biobank dataset. At recruitment in 2006–2010, the participants underwent a range of physical measurements and detailed assessments of health‐related factors. UK Biobank also collected blood, urine, and saliva samples for biochemical analysis. Follow‐up is conducted through linkages to routinely available national datasets. Details of the rationale, design and survey methods for UK Biobank can be found elsewhere.2.2UK Biobank evaluated FM (kg) and FFM (kg) with electrical bio‐impedance  at baseline interview. The whole body as well as site‐specified  FM/FFM were evaluated. Detailed descriptions of the procedures used to measure body composition can be found on the study website.2.3UK Biobank obtains data on cancer diagnosis through the Health & Social Care Information Centre for participants in England and Wales, and the NHS Central Register for participants in Scotland. These registrations recorded the diagnosis of cancer and cancer deaths using ICD‐10 codes. The primary outcome for this study was cervical cancer (C53), uterine corpus cancer (C54‐55), and ovarian cancer (C56).2.4We calculated person‐years from the recruitment date to the date of the first diagnosis of cancer, death, or the last date of follow‐up (30 October 2015), whichever came first. We evaluated the risk of the top three gynecologic malignancies by quartiles and as continuous per kilogram (kg) increase in FM/FFM. To compare the ability to predict major gynecologic malignancies  across various body composition and anthropometry measures, we evaluated the HRs per standard deviation (SD) increase with Cox regression. To investigate potential nonlinear associations, we fitted restricted cubic splines in Cox regression models. We checked the proportional hazards assumption using Schoenfeld's tests. For covariates with selection of “do not know” and “prefer not to answer,” or with missing covariate data, we included an “unknown/missing” value indicator.We used Cox regression models, taking age as the underlying timescale, to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association of anthropometric measurements with subsequent gynecologic malignancies risks. We additionally adjusted for ethnic, index of multiple deprivation, smoking status, alcohol consumption, physical activity, fruit and vegetable intake, diabetes, family history of gynecologic malignancies, surgical history , menarche age, oral contraceptives history, reproductive history, and height in the multivariate Cox regression. For the analysis of body composition, we included both FM and FFM in the model to examine their independent effects.We evaluated potential stratification of age, smoking status, obesity, and family history of cancer on the associations between WBFM/whole body fat‐free mass (WBFFM) and risk of major gynecologic malignancies. The effect of stratification was tested by introducing interaction terms in the regression model. To check the robustness of the primary analysis, a series of sensitivity analyses were performed. First, we excluded cancer diagnosed during the first 2 years of follow‐up to minimize reverse causality. Second, we use the complete‐case analysis to verify the influence of missing data. The statistical analyses were conducted using the SAS  and R software .3This study included a total of 245,009 female participants, of which 75,284 were premenopausal and 169,725 were postmenopausal. The distribution of the study population characteristics by quartiles of FM/FFM is presented in Table We documented 1427 cases of the top three gynecologic malignancies  over 1613477 person‐years of follow‐up. Tables We further investigate the risk of the major gynecologic malignancies with continuous per unit increase in anthropometric measurements and FM/FFM. In multivariable analysis, BMI, WC, and WHR were positively associated with the risk of uterine corpus cancer in both premenopausal  and postmenopausal women  Table . There iAs for the associations between continuous body composition measurements and gynecological malignancies, WBFM/WBFFM presented statistically associations with increased risk of uterine corpus cancer but were not associated with the other two gynecological malignancies Table . For preAssessment of the nonlinear association of body composition with gynecological malignancies showed that uterine corpus cancer risk was associated with higher WBFFM and TFFM in premenopausal women, and higher WBFM, WBFFM, TFFM, and trunk fat mass (TFM) in postmenopausal women. FM/FFM distributed in the limbs present U‐shaped associations with substantially increased risk of uterine corpus cancer in postmenopausal women Figures .4This large prospective analysis of 245,009 female participants shows that traditional anthropometric indicators such as BMI, WC, and WHR, might be associated with an increased risk of uterine corpus cancer. This trend tends to be stronger in postmenopausal women. The above results are generally consistent with previous prospective studies.Obesity, especially abdominal adiposity, has been considered as a risk factor for certain hormone‐dependent tumors in women, such as breast cancer and endometrial cancer. As an indicator of overall adiposity, BMI is unable to represent the whole picture of obesity. Whether WC, WHR and other measures reflecting abdominal adiposity are more advantageous than BMI in reflecting the risk of malignant tumors is still inconclusive.Current epidemiological studies evaluating the associations between body composition and gynecological malignancies risk remain inadequate. A cohort study involving 18,700 women found that WBFM was associated with increased risk of ovarian cancer .The exact mechanisms of FFM on uterine corpus cancer risk remain unclear. A potential explanation is that FFM is associated with nutritional factors, such as red meat consumption, which is linked with increased risk of uterine corpus cancer.4.1To the best of our knowledge, the present study is the first cohort study evaluating body composition and the major gynecologic malignancies risk. This analysis was based on a well established nationwide cohort of over 0.45 million participants, with detailed measurement of body composition and a wide range of known and putative gynecologic malignancies risk factors, allowing us to adequately control potential confounding factors. For the first time, we evaluated the effect of FFM on uterine corpus cancer risk. In addition, we applied a range of approaches to evaluate body composition effects, including the assessment of nonlinearity and effect modification. Lastly, a wide range of robust sensitivity analyses further strengthened our confidence in the results.[2]. Fourth, body composition measured by bioelectrical impedance analysis in this study may be influenced by other factors such as ethnicity, phase of menstrual cycle, and underlying medical conditions. However, high correlation between bio‐impedance and the DXA‐derived measures indicated that bio‐impedance is reliable. Last, as most participants in the UK Biobank were of European ancestry, the generalizability of the study findings to other ethnicities remains unclear.This study has limitations. First, as an observational study, we cannot eliminate the residual confounding effect and confirm the causal relationship. Second, with limited cases of other types of uterine corpus cancer  according to the ICD‐10 code in UK Biobank and absence of histological classification data, we could not separately evaluate associations of body composition measurements with subtype of uterine corpus cancer. Further studies investigating these associations are still required in the future. Third, we only documented 68 cases of cervical cancer in UK Biobank database, thus we were unable to evaluate the associations of body composition and cervical cancer risks separately by pre/postmenopausal status. However, previous studies have demonstrated that HPV infection is the most important risk factor for cervical cancer, and the change of sex hormone before and after menopause might have no effect on the incidence of cervical cancer5Overall, this large‐scale prospective study suggests that FFM is associated with an increased risk of uterine corpus cancer in both premenopausal and postmenopausal women. We did not observe associations between body composition measures and ovarian/cervical cancer. In clinical and public health practice, our findings provided evidence for individualized weight management for the prevention of gynecologic malignancies. Interventions for controlling excessive lean mass may have benefits in reducing uterine corpus cancer. Further research is warranted to confirm the causality and to investigate the underline mechanism of the effects of FFM on uterine corpus cancer.The authors declared that they have no conflicts of interest to this work.UK Biobank was approved by the North West Multicentre Research Ethics Committee (MREC), the Patient Information Advisory Group (PIAG) in England and Wales, and the Community Health Index Advisory Group in Scotland (CHIAG).Supplementary MaterialClick here for additional data file.


A few studies have examined the relationship between carbohydrate quality index (CQI) and risk of breast cancer (BC) among women in Middle Eastern countries. We studied the associations between carbohydrate quality index and the risk of BC in overall and by menopausal status.In this case-control study, dietary intake of 461 women with pathologically confirmed BC within the past year were examined. The same information were collected for 495 apparently healthy controls using a 168-item validated FFQ. Carbohydrate quality was determined by considering four criteria including: ratio of solid carbohydrates to total carbohydrates, dietary fiber intake, GI and the ratio of whole grains to total grains.P = 0.01). We found that women with the greatest CQI had lower odds for BC, compared with those with the lowest CQI . This association was remained after stratifying analysis by menopausal status in premenopausal .Mean GI and GL of participants were totally 57.5 ± 7.2 and 245.7 ± 64.7, respectively. A trend toward significant association was seen between GI and odds of BC in the whole population; such that after stratifying analysis by menopausal status, premenopausal women in the highest quartile of GI were 1.85 times higher likely to have BC than those in the lowest quartile (95% CI: 1.12, 3.07, We found that GI was directly and CQI inversely associated with odds of BC. In order to determine the effects of dietary carbohydrate quality prospective cohort studies are needed. Globally more than 2 million women diagnosed with breast cancer and about 630,000 deaths occurred in 2018, out which half of deaths belongs to low-middle income countries like Iran [Several risk factors including genetic, lifestyle and dietary intake are related to breast cancer risk . Many stTwo case-control studies have illustrated an association between breast cancer risk and dietary glycemic index , 14, whePrevious studies have limitation as the intake of simple components were evaluated with risk of breast cancer, which cannot entirely represent the whole quality of carbohydrate consumption. Therefore using a broader criterion that combine several of these simple components into a compound index which could better represent the whole quality of carbohydrate intake. Some studies defined Carbohydrate Quality Index (CQI) which can take into account dietary fiber intake, GI, whole grains to total grains ratio and solid carbohydrate to total carbohydrates. Only one cohort study on Spanish university graduates women examined the relation between CQI and breast cancer risk .Considering that only one study has been conducted about the association between carbohydrate quality and breast cancer risk and knowing that high consumption of refined carbohydrates  are common in the Middle East, , this stWe conducted a hospital-based case-control study among Iranian women aged 19–80 years old between 2014 and 2016. The details about this study was described elsewhere [A 168-item validated food-frequency questionnaire was administered to all patients by trained interviewers. Participants were asked to designate their intake frequency for each food item consumed on a daily, weekly, or monthly basis. Patients reported their consumption over the previous year. Participants who could not respond to their frequency of consumption based on the values mentioned in the questionnaire, had reported their own portion sizes which were converted to the portion size of the questionnaire. The daily portion size of reported consumed foods was calculated and then converted to grams. Total energy intake was calculated by summing up the energy from all foods and nutrient content of foods that were analyzed using the USDA food composition database modified for Iranian foods. In a previous study, the validity and reliability of this FFQ was confirmed by comparing the data from 12 dietary recalls and two similar FFQs that completed 1 year apart.a × available carbohydratea)/total available carbohydrate, where GIa is each food’s GI and available carbohydrate was calculated as total carbohydratea minus fibera. GL values was calculated by multiplying the available carbohydrate content of each food by its GI value and then multiplied the resultant value with the amount of consumption (divided by 100) and then summed the values from all food items. Contribution of four criteria including: ratio of solid carbohydrates to total carbohydrates, dietary fiber intake (g/day), GI and the ratio of whole grains to total grains  was used to construct CQI. Initially, subjects in each of these four criteria, were divided into quintiles and received a value (ranging from 1 to 5) according to each quintile. But, the scoring of GI was reversed, such that those in the highest quintile were given the score of 1 and those in the lowest quintile were given the score of 5. Finally, the scores were then summed up to compute CQI score (ranging from 4 to 20) [Total dietary GI was calculated by using the following formula: Σ (GI4 to 20) . CarbohyP values < 0.05 were considered statistically significant. The analysis was performed by Stata version 14 .We categorized all participants based on quartiles of Carbohydrate intake, GI, GL and CQI. We used Student t-test and chi-square test to compare the mean of continuous variables and categorical variables of cases and controls, respectively. We applied one-way ANOVA and chi-square test to compare variables across quartiles, where appropriate. We calculated age-, residential place, and energy-adjusted food and nutrient intakes by quartiles of the all criteria using ANCOVA. The association between the dietary Carbohydrate intake, GI, GL and CQI and odds of breast cancer was checked by using crude and multi-variable logistic regression models. The analyses were first adjusted for age and energy (continuous), residential place. Additional adjustments were done for educational level , parity , oral contraceptive use (yes vs. no), marital status , family history of breast cancer (yes vs. no) body mass index (continuous) and physical activity (continuous) in the second model. All confounders were selected based on recent research. The trend of odds ratios across quartiles of all criteria was examined by considering the median value of criteria in each category as a continuous variable. Compared to controls, cases were slightly older, had lower BMI, were older at first birth, and were more likely to have family history of breast cancer Table . These pThe mean GI of all participants was 57.5 ± 7.2) and no significant differences were seen between cases and controls. The mean (± SD) of CQI was 11.5 (± 3.4) in all participants the comparison of CQI indicated no different between cases and controls. Subjects in the top quartile of GI had lower intakes of total carbohydrate, solid carbohydrate, fiber, protein, fruits, vegetables, high fat dairy, low fat dairy, legumes, vitamin C, D, B6, B9, and B12 than those in the lowest quartile . Women in the highest quartile of CQI had significantly lower risk of breast cancer than those in the lowest quartile . When stratified by menopausal status, we found that premenopausal women in the top category of GI had higher odds of breast cancer, compared with those in the bottom category . In addition, premenopausal women in the top category of CQI had lower odds of breast cancer compared with those in the bottom category . We found no significant association between all carbohydrate quality criteria  and odds of breast cancer in postmenopausal women, either before or after controlling for confounders.Multivariable-adjusted odds ratios and 95% CIs for breast cancer, separately for whole population, pre- and post-menopausal women, across quartile categories of carbohydrate, glycemic index, glycemic load and carbohydrate quality index are provided in Table 3In this study we observed a significant association of high GI with odds of breast cancer in the whole population. Regarding CQI the results were reversed that those women with higher CQI (quartile 4 of the score) had a significantly lower odds of breast cancer compared with those who had the lower CQI (quartile 1). Also, we found the same results for GI and CQI in the premenopausal women. To our knowledge, this case-control study is among the first investigations that reports the association between Total carbohydrates, GI, GL and CQI with odds of breast cancer with large sample size in a Middle Eastern country.This study examined several dietary carbohydrates that may have varied effect on blood glucose responses. The association of this criteria with risk of breast cancer have been frequently assessed by several studies with inconsistent results. Previously a study showed that 60% of total energy intake was supplied by carbohydrates among Iranian  especialWe found a significant association between dietary GI and risk of breast cancer among whole participants and premenopausal women. In line with our results Alboghobeish et al. found an association between high GI and risk of breast cancer . HoweverIn this study we observed all participants and premenopausal with best CQI had a significantly lower risk of breast cancer. The total quality and quantity of carbohydrate and their dietary source are related to cancers. Recent discussion indicate that fiber and whole grain should be considered for carbohydrate quality as well as GI . In addiThe strengths of the current study include considering several potential confounders, the use of validated questionnaires for dietary assessment, recruiting participants from a referral hospital, in which subjects are from the whole country. Stratified analysis by menopausal status is strength of this study. However, several limitations need to be considered. First, due to the case-control design of the study with its inherent recall and selection bias, one cannot infer causality. Second, misclassification of participants in terms of dietary intakes cannot be excluded due to the use of FFQ in the current study. Third, we did not have information of the hormone receptor status of the tumor for the participants.In conclusion, we found a significant association between carbohydrate quality and breast cancer. So considering the carbohydrate type intake might be important for cancer control in society. Additional studies are required to prospectively examine the association of carbohydrate quality and risk of breast cancer considering the specific subgroups of estrogen receptor.


Objectives: This study aimed to estimate the long-term trends of breast cancer incidence in Shanghai, Hong Kong, and Los Angeles (LA).Methods: Data were obtained from Cancer Incidence in Five Continents (CI5plus) database. The average annual percent change (AAPC) was conducted by joinpoint regression analysis, and the age, period and cohort effects were estimated by age-period-cohort (APC) analysis.Results: The age-standardized incidence rates (ASIRs) in LA were higher than Shanghai and Hong Kong. During 1988–2012, the ASIRs significantly decreased in white women in LA  while increased in Shanghai (2.5%: 2.1%–2.9%) and Hong Kong (2.2%: 2.0%–2.5%). The APC analysis revealed significantly increased effects of age and period, and decreased effect of birth cohort.Conclusion: Although age and cohort effects were relatively strong, the period effect may be the key factor affecting trends of incidence, which may be caused by increasing exposures to carcinogens and risk factors. Therefore, more effective measures should be carried out promptly to protect high-risk populations such as elder women, to avoid exposures to risk factors of breast cancer. Cancer has been recognized the major threat to health globally, which caused a total of 4.11 million deaths in 2017 . With thThere were extensive studies focused on the etiology of breast cancer in recent years, and many factors were proven to be related to its development –8. EstabCI5plus) database, which provide annual incidence cases and rates for 28 major cancer types in 124 selected populations from 108 cancer registries, and the incidence accuracy was relied on the local registries [CI5plus database, breast cancer was identified based on the Tenth Revision of the International Classification of Diseases (ICD-10) (code as C50).Data were extracted from Cancer Incidence in Five Continents  –27. Therp value <0.05 were considered statistically significant.In our study, the Joinpoint regression analysis was implemented using Joinpoint software from the Surveillance Research Program of the US national Cancer Institute. The APC model was performed using the Stata 12.0 software . Results with a 2-sided and The APC and AAPC of breast cancer cases and ASIR by four populations from 1988 to 2012 were presented in CI5plus database, the current study analyzed breast cancer incidence rates across temporal dimensions in Shanghai and Hong Kong compared with white and black populations in LA by Joinpoint regression and age-period-cohort analysis with IE algorithm, which uncovered the underlying causes of long-term trends of breast cancer to estimate when and how each of the three time-dependent parameters affecting these trends [Based on long-term data from e trends . Our disOur results revealed that the age-standardized incidence rates presented contrary tendencies between Shanghai, Hong Kong and two populations in LA during the study period. The highest level of incidence risks were observed in white and black populations in LA, while the lowest risk occurred in Shanghai. The disparities between cities in China and USA in our study were consistent with the findings of a mortality trends discovered by Wang et al, which conducted historical trends in breast cancer mortality at country-level in China and United States . More siAge is an importantly nonmodifiable risk factor for breast cancer, and it was found the breast cancer incidence risk increased with the advancing age in four of the selected populations . ContinuThe period effects indicated the immediate effects of the factors on disease incidence and mortality . In the The cohort effects showed declining trends of breast cancer incidence risk for most generations in four selected populations except some cohorts in Shanghai and Hong Kong which level off or slightly increase, which indicated that earlier birth cohort had a higher risk of breast cancer than later cohorts, and similar result was observed in a study conducted by Mubarik S . The posNevertheless, our study had some limitations. Firstly, due to the unavailability of the data, we didn’t analyze the influences of all risk factors on breast cancer, such as dietary changes, physical inactivity and socioeconomic status, and these data would have led to better interpretation of the results. Secondly, we excluded the age groups over 84 years due to the fixed pattern of the IE method. Thirdly, our study included Shanghai, Hong Kong in China and LA, although these three cities were representative cities in China and United States, they can’t fully represent the real conditions of all other cities in their home countries. Therefore, more future studies should be conducted on the breast cancer incidence risk in all cities in China and the United States, to guide the rational allocation of health resources and targeted prevention and intervention strategies. Despite the limitations, our study is beneficial for providing some references to domestic and foreign breast cancer prevention.In conclusion, the age-standardized incidence of breast cancer in LA for both white and black women were all higher than those in Shanghai and Hong Kong, while upward trends were observed for two latter populations. By APC analysis, the incidence risk of breast cancer increased with advancing age in four selected populations, which was even more pronounced for postmenopausal women in LA. The incidence risk of breast cancer increased with time periods for these four populations. The cohort effects decreased for all selected populations except Shanghai and Hong Kong had slight increase during 1943–1962. Although age and cohort effects were relatively strong, the period effect may be the key factor affecting trends of breast cancer incidence, which may be caused by increasing exposures to carcinogens and high-risk factors. Therefore, more effective measures should be carried out promptly to reduce the burden of breast cancer, especially among high-risk populations such as elder women who are exposure to risk factors of breast cancer.


Breast lesions with uncertain malignant behavior, also known as high-risk or B3 lesions, are composed of a variety of pathologies with differing risks of associated malignancy. While open excision was previously preferred to manage all high-risk lesions, tailored management has been increasingly favored to reduce overtreatment and spare patients from unnecessary anxiety or high healthcare costs associated with surgical excision. The purpose of this work is to provide the reader with an accurate overview focused on the main high-risk lesions of the breast: atypical intraductal epithelial proliferation , lobular neoplasia , flat epithelial atypia, radial scar and papillary lesions, and phyllodes tumor. Beyond merely presenting the radiological aspects of these lesions and the recent literature, information about their potential upgrade rates is discussed in order to provide a useful guide for appropriate clinical management while avoiding the risks of unnecessary surgical intervention (overtreatment). B3 lesions are various pathologies with differing risks of associated malignancy.Tailored management of B3 lesions has been increasingly favored to reduce overtreatment.Most patients with high-risk lesions may be sparred surgical excision.Breast lesions with uncertain malignant behavior, also known as high-risk or B3 lesions, are composed of a variety of pathologies with differing risks of associated malignancy. In the past several decades, the diagnosis of B3 lesions has significantly increased with the widespread implementation of screening programs and the advent of new imaging modalities . B3 lesiOverall, high-risk lesions have a low risk of malignancy. Nevertheless, up to 35% of lesions of uncertain malignant potential (B3) are subsequently upgraded at surgical specimen to DCIS or low-grade carcinoma . While oThe purpose of this work is to provide the reader with an accurate overview focused on the main high-risk lesions of the breast: atypical intraductal epithelial proliferation (AIEDP), lobular neoplasia , flat epithelial atypia, radial scar and papillary lesions, and phyllodes tumor. Beyond presenting the radiological aspects of these lesions and the recent literature, information about their potential upgrade rates will be discussed in order to provide useful guidance for appropriate clinical management while avoiding the risks of unnecessary surgical intervention (overtreatment). In Table Atypical ductal hyperplasia (ADH) is one of the most common B3 lesions of the breast and the one with the highest risk of malignant transformation. It is therefore considered a non-obligate precursor of invasive cancer as well as an independent risk factor for breast cancer , 16. ADHADH is diagnosed in 12–17% of percutaneous biopsies . ADH is Upgrade rates to DCIS or invasive carcinoma from core needle biopsy to excision in the literature range from 0 to 62% for ADH . The repDifferentiating ADH from low-grade DCIS is challenging on histopathology and is often a diagnosis of exclusion, with cytological atypia and architectural changes similar to low-grade DCIS but with an involvement of no more than two membrane-bound spaces with an extent lower than 2 mm . From thSeveral studies have been performed to determine specific biomarkers for ADH, but currently no biomarker has been clinically validated. The limited data on the molecular biology of ADH demonstrates its close similarity to low-grade DCIS: Cells are positive for ER but negative for high molecular weight cytokeratins , and then = 330) or atypical lobular hyperplasia (n = 327) who later develop breast cancer, 69% of the women developed moderate or high-grade invasive ductal breast cancers; moreover, while the risk of developing breast cancer is elevated in both breasts, the risk is doubled in the ipsilateral breast compared with the contralateral breast [ADH is associated with a higher risk of invasive breast cancer, four to five times higher compared with the normal population . In theil breast .Imaging findings are not specific, and ADH can be found in the peripheries of a papillary lesion and even inside a fibroadenoma. At mammography, ADH can be seen as microcalcifications, mainly amorphous with grouped, linear, or regional distribution. It can also arise as a mass with or without microcalcifications. Only seldom is ADH detected at ultrasound. According to Mesurolle et al. , the sonADH has the highest risk of underestimation among all types of high-risk lesions. The diagnosis of ADH at CNB or VAB is challenging, since ADH can be an isolated finding or a small component of DCIS . Kohr etInitially, the first International Consensus Conference on lesions of uncertain malignant potential (B3 lesions)  recommenIf clinical surveillance is elected, in women diagnosed with ADH before age 40, there is a lack of consensus between guidelines on how to follow these patients. The majority consider these patients more than average risk for developing breast cancer and close imaging follow-up, even with MRI, should be considered , 37.Lobular neoplasia (LN) is considered both a risk indicator and a non-obligate precursor for breast cancer. LN is found in 0.5–4% of otherwise benign breast biopsies, and it can be seen at any age but is most frequent in premenopausal women , 38. TheThe term lobular neoplasia is used to represent atypical epithelial lesions characterized by the proliferation of poorly linked monomorphic cells due to the lack of E-cadherin expression, with possible pagetoid diffusion into galactophorous ducts. According to World Health Organization (WHO) classification, atypical lobular hyperplasia (ALH) and lobular carcinoma in situ (LCIS) represent the majority of LN and their differentiation is based on the extension of lobular units that are involved by the lesion: While LCIS compromises more than a half of TDLU acini, ALH is usually less extensive. Moreover, WHO classification encourages the use of the terminology “intraepithelial lobular neoplasia” (LIN), with a three-type classification . According to this classification, ALH is referred to as LIN1 and LCIS is referred to as LIN2, and LIN3 includes non-typical variants of LN which differ from the classic variant, either lacking the distension of the lobular unit (florid form) or lacking cellular atypia (pleomorphic form) , 40.The prognostic significance towards malignancy for ALH and LCIS is not supported by evidence to date. Therefore, on both CNB and VAB samples, they are classified as B3 lesions, whereas pleomorphic or florid LN are classified as B5a  lesions . LN may Immunophenotyping and cytogenetic studies demonstrate similarities between LN and lobular invasive carcinoma as well as low-grade DCIS, namely high expression of estrogen receptor (ER) and progesterone receptor (PR), low Ki-67, and well-differentiated cytokeratin profile (CK5- and CK18+), and these findings lead some to consider LN as a precursor of invasive breast cancer . HoweverThe lack of expression of E-cadherin can be helpful in differentiating LCIS from DCIS or for classifying a lesion as indeterminate. Although rare, LCIS can express E-cadherin, and so in all cases where a histologic sample cannot be surely classified as LCIS or DCIS, the definition “carcinoma in situ with mixed ductal and lobular features” should be used .Molecular analysis has demonstrated that LN is a clonal neoplastic proliferation and a precursor to invasive cancer. The relative risk of developing breast cancer is 4–12 times higher for women diagnosed with LCIS compared with women without LN, and 4 to 5 times higher for women with ALH compared with women without LN. The upgrade rate after surgical excision ranges widely from 0 to 40% in the literature, which may be due to differences in inclusion and exclusion criteria used in different studies  , 38. TheLN has no typical radiological or clinical manifestations; it is usually discovered fortuitously in breast tissue biopsied for other reasons , often aOn mammography, LN usually goes unnoticed, but when detected, it can be seen as microcalcifications, with amorphous morphology and grouped distribution , 38, 55.Management of classic LN diagnosed on CNB remains controversial even though recent studies recommend conservative management based on the low upgrade rate reported , 58, 59.Similar considerations for imaging follow-up of ADH have been made for LN. In women diagnosed with LN, close imaging follow-up with beast MRI should be considered, especially if other risk factors are present , 37.Flat atypical epithelia (FEA), also known as columnar cell changes with atypia or cellular hyperplasia with atypia, is a non-malignant, atypical lesion of the breast. The WHO defines FEA as a neoplastic intraductal alteration of the breast characterized by replacement of native epithelial cells by a single layer or three to five layers of mildly atypical cells without architectural atypia . AlthougFrom the histological point of view, FEA appears as a neoplastic alteration in which normal luminal cells are replaced by one layer or three to five layers of columnar cells and the TDLU shows a low grade of atypia . CellulaGenerally, two forms of columnar metaplasia are distinguished: columnar cell changes, in which acini are lined by one or two layers of modified epithelial cells; and columnar cell hyperplasia, in which acini are lined by more than two layers of epithelial cells –67.Immuno-phenotype studies show a correlation between FEA, DCIS, and invasive breast cancer . In factFEA is of great scientific interest as the morphological spectrum of intraductal proliferations from FEA to ADH and low-grade DCIS seems to represent a continuum. FEA seems to be associated with a very slight increased breast cancer risk (1–2 times), which is substantially lower than the risk due to ADH. While the breast cancer risk is only slightly elevated, it is important to note that this is a lesion that, by definition, contains a degree of epithelial atypia.Forester et al. in their meta-analysis demonstrated that the upgrade rate to malignancy for FEA lesions is 11% . MalignaAs these lesions produce intraluminal secretions, they commonly present mammographically as fine amorphous or branching microcalcifications with associated marked duct dilatation , 74  remains controversial. Current guidelines increasingly favor surveillance if the lesion is small and radiological findings are completely removed by CNB or VAB .According to AGO  guidelines, when FEA is found at CNB or VAB, surgery can be avoided in the following situations: small lesion (< 2 TDLU involved at VAB) and/or partial or complete resolution at imaging . On the Radial scar (RS) is a breast lesion that may mimic invasive carcinoma because of its stellate configuration. RS is a focus smaller than 10 mm while complex sclerosing lesion (CSL) refers to a lesion which is larger than 10 mm and which has more complex features , 18, 78.RS and CSL are characterized by a central fibroelastic core, which is surrounded by elastic fibers and which contain one to several ducts showing obliterated mastopathy Fig. a. In addRS and CSL are proliferative lesions which are frequently associated with other high-risk lesions and proliferative lesions such as atypia, and which may themselves contribute to the high frequency of associated cancers and to the upgrade rate to malignancy at excision. The prognosis of RS/CSL depends on the presence of associated atypia . PreviouThe mammographic appearance of a RS/CSL typically consists of a radiolucent star-shaped lesion, which can be confused with a form of presentation of invasive carcinoma. Over the years, authors have reported certain findings that may be helpful in detecting RS/CSL at mammography, including the presence of radiolucent linear structures paralleling the radiopaque spicules and the “black stars” appearance over the “white stars” appearance of breast cancer . Other tNowadays, the use of recently developed digital breast tomosynthesis techniques has gained momentum, due to their more accurate visualization, characterization, and identification of architectural distortion –91. ArchWith the increasing use of ultrasound in both screening and diagnostic settings, an increasing number of mammographically occult RS/CSLs have been detected at ultrasound and diagnosed at subsequent ultrasound-guided CNB, ranging from approximately 15.7 to 39% among radial scars without atypia diagnosed at percutaneous biopsy . HoweverThe MRI appearance of RS/CSL is similarly variable. In Ha et al.’s study involving 13 radial scars that were imaged with MRI, six lesions were not detected, six appeared as a mass , and one appeared as non-mass enhancement with regional, homogeneous enhancement, and a Type 3 enhancement kinetic curve  , both belonging to the B3 category on BI-RADS  can be categorized as B2 lesion, if the lesion is completely surrounded by a duct structure)Papilloma with DCIS or papilloma completely involved by more extended DCIS (encapsulated papillary carcinoma)Solid papillary carcinoma belonging to B4 or B5a category Papillary lesions are composed of papillary fronds which are attached to the inner mammary ductal wall through a fibrovascular core and which extend into the lumen of the duct Fig. b. DuctalUsually, papillary lesions can be divided according to their localization into two main groups: central , i.e., arising from the ducts of the sub-areolar region sparing TDLU; and peripheral , i.e., originating from TDLU following the involvement of galactophorous ducts .The risk of an invasive cancer onset is two times that of the normal population for the central form and three times for the peripheral form, with a higher risk of invasive cancer onset of up to 7.5% in the case of papilloma with atypia . The diaIt is important to note that the upgrade rates for papillary lesions vary widely in the literature and may be as low as 3.1% for solitary papillomas . SeveralPapillomas can be asymptomatic and detected at routine breast screening. However, when symptomatic, they can be present as a palpable mass near the nipple or with bloody nipple discharge, in up to 20–50% of cases, due to pedicle torsion , 91. MamBreast ultrasound is of great value in the diagnosis of papillomas, whether conventional ultrasound, Doppler ultrasound, or elastography . UltrasoMRI is useful for determining the extent of disease in cases when a diagnosis of papilloma has already been established. MRI allows a comprehensive assessment including the identification of connections with the ductal system and a more accurate estimation of disease extent in cases of malignant papillary lesions. The MRI protocol should include acquisitions before and after intravenous contrast administration, due to the significant enhancement of small papillary lesions. MR ductography images can also be obtained to map the entire breast ductal system, whereby the ductal system would be characterized by strong enhancement in which papillomas can be detected as defects  Table 33.2) and an agreement with imaging findings is found; for papillomatosis, surgery is recommended [Certain clinical and imaging factors including patient age, lesion multiplicity, and peripheral location are associated with increased breast cancer risk. Overall, management depends on a number of factors, including age at diagnosis, lesion type, and presence of atypia. As previously mentioned, it is well established that a papillary lesion with atypia diagnosed at CNB can show malignant evolvement or simultaneous malignancy , 101. Thommended , 115. CuBland-looking spindle cell lesions encompass a heterogenous group of tumor-like and tumor entities, ranging from benign reactive to low-grade malignant neoplasms with metastatic potential . The morPhyllodes tumor of the breast is a rare tumor that accounts for fewer than 1% of all breast tumors and 2–3% of fibroepithelial neoplasms , 118. AlPhyllodes tumors are rare breast fibroepithelial lesions and are similar to fibroadenomas and hamartomas, and they can range from benign to borderline or clearly malignant forms from the histological point of view Fig. c. In somTherefore, WHO recommends the diagnosis of fibroepithelial tumors (BI-RADS 3 category) for unclear cases. Briefly, both benign and borderline phyllodes tumors are considered B3 lesions of the breast, histological classification, whereas malignant Phyllodes tumors are included into the B5b category . B3 lesiThe majority of phyllodes tumors have a benign behavior, with a risk of recurrence of approximately 10–20% for benign lesions, and up to 30% for borderline or malignant lesions. Metastatic capacity depends on histology, with 15–20% for malignant phyllodes tumors , 121. SeThe typical appearance of a phyllodes tumor is a unilateral mass that is frequently symptomatic  and mobile (not fixed to deep tissues); as a large palpable tumor, it stretches the skin with distension of superficial vein, with a size that ranges from 2 to 5 cm , 124. ImAt mammography, phyllodes tumors appear as a big ovoid high-opacity mass with irregular edges and usually lobulated ; coarse Ultrasound findings of phyllodes are variable. Several reviews report that these lesions can have either circumscribed as well as non-circumscribed borders , 126; thThere is lack of data regarding the assessment of phyllodes using MRI. Several authors focused on identifying signal features that may predict benignity or malignancy. Farria et al. reported that rapid enhancement after gadolinium injection is associated with benign phyllodes tumor ; in addiAvailable data suggest that the most common management for phyllodes tumor is surgical excision , 132. ThDiagnosis of high-risk lesions occurs frequently and incidentally at percutaneous biopsy, following suspicious imaging findings such as distortion, a group of microcalcifications, or even a mass. Traditionally, high-risk lesions are managed with surgical excision because of their low but latent potential of upgrade to malignancy. The most recent guidelines recommend a more conservative approach, sparing open surgery when this can be avoided. This trend has been adopted for the continued concerns raised regarding potential harms associated with unnecessary biopsies and surgeries when suspicious imaging findings are found. Further, radiological follow-up by means of mammography and breast MRI should be considered in patients diagnosed with high-risk lesions as they are not only non-obligate precursors of malignancy but also risk indicators for the homolateral and contralateral breast. It is essential that management of high-risk lesions takes on a multidisciplinary approach with close communication between all members of the breast team  to assess the individual risk of patients with such a diagnosis and their suitability for either surgical excision or imaging surveillance.


While breast cancer accounts for the highest mortality among women across the globe, little is known about its perceived risks among them. We examined the perceived risk of breast cancer among undergraduate female university students in Ghana.  This was a cross-sectional survey of 358 undergraduate female students at the University of Health and Allied Sciences, Ghana. Descriptive and inferential statistics comprising frequencies, percentages, chi-square, and binary logistic regression analyses were used in analysing the data collected. All analyses were done using STATA Version 13.1. p=0.02), school (p=0.01), knowledge of someone with breast cancer (p < 0.001), family history of breast cancer (p < 0.001), current use of oral pills/injectable contraception (p=0.03), history of breast cancer screening (p < 0.001), and intention to perform breast self-examination (p < 0.001) were the risk factors of breast cancer risk perception. Students without a family history of breast cancer were 90% less likely to perceive breast cancer risk  compared with those having a family history of breast cancer. Students who had never screened for breast cancer were also 62% less likely to perceive that they were at risk of breast cancer  compared with those who had ever screened for breast cancer.  Seventy-three percent were aware of breast cancer and 45.2% out of this did not perceive themselves to be at risk of breast cancer. Academic year ( This study showed that female university students tend to estimate their breast cancer risk based on their experience of breast cancer. Students who have ever screened for breast cancer and those with the intention to perform breast self-examination in the future are more likely to perceive themselves as being at risk and thus take action to avoid getting breast cancer. Globally, breast cancer has become the leading cancer among women with about 2.1 million cases each year and 627,000 deaths in 2018 .Research has shown that breast cancer screening remains a useful tool for reducing breast cancer mortality among women , 5. HoweRisk perception is recognized as a strong driving force for women to engage in preventive and screening behaviours, yet previous studies suggest that most women incorrectly perceive their breast cancer risk , 12. WomSince risk perception may be an important motivator for women to adopt preventive behaviours including breast screening, it is important to understand the predictors of perceived risk of breast cancer, which can be considered when planning interventions to alter health behaviours. The perception of risk, health beliefs, and attitudes towards breast cancer can affect the choice and use of early screening methods , 17, 18.We conducted a cross-sectional survey among female undergraduate students at the University of Health and Allied Sciences (UHAS) of Ghana in April 2019. UHAS is the only public university dedicated to the training of healthcare professionals in Ghana. There are six academic schools and one institute in the university. The current study was conducted among students from the school of Nursing and Midwifery, the School of Pharmacy, the School of Medicine, the School of Allied Health Sciences, and the School of Basic and Biomedical Sciences. The university's current student population is about 3,750. UHAS offers eighteen undergraduate programmes including Medicine, Physician Assistantship, Nursing, Midwifery, Physiotherapy, Pharmacy, Dietetics, Speech and Language Therapy, Disease Control, etc. [n = z2(pq)/d2 where n is the needed sample size; z, the degree of accuracy at 95% confidence level; p = the estimated proportion of an attribute that is present in the population; q = 1 − p; and d = margin of error. We assumed a margin of error (d) of 0.05 at 95% confidence level and an estimated proportion of 50%, since to the best of literature search made, there was no study done in the study area. Stratified sampling was used to select the study participants from the various academic years of study and different schools to ensure representativeness. The number of students selected from each academic year and school was proportional to the students' population.A sample size of 385 female students was estimated using a single proportion formula: A structured pretested questionnaire was used to collect data from participants. The questionnaire contained closed-ended questions. “Perceived risk of breast cancer” was the main outcome variable. Participants were asked to respond “yes,” “no,” or “do not know” to the following question: “Do you think that you have a chance of developing breast cancer?” Sociodemographic variables comprising age, marital status, religion, ethnicity, the academic year of study, and school were examined as explanatory variables. Breast cancer risk factors including age, family history of breast cancer, age at menarche, and age at first live birth also constituted explanatory variables in the study. The others were alcohol consumption, hormonal contraception use, and physical activity. Screening-related factors consisted of a history of breast cancer screening and the intention to perform BSE in future. The questionnaires were self-administered after explaining the study's objectives to them. The filled questionnaires were checked by the researchers together with the participants for consistency and omission before collection. Where there were inconsistencies, participants were made to correct them in the presence of the researchers before they were taken. Participants were given 24 hours to return filled questionnaires to have enough time to fill them.p value <0.05 in the bivariate analysis were included in a multivariate binary regression analysis. The degree of association between dependent and independent variables was assessed using adjusted odds ratios (AOR) with 95% confidence intervals (CIs). All analyses were done using STATA statistical package Version 13.1 from Stata Corp.Descriptive statistics were used to describe the study population in relation to relevant variables. Chi-square analysis was used to test for statistical significance between sociodemographic and risk factors of breast cancer and perceived risk, which was the main outcome variable. Variables significant at n = 23.6%), and I have no family history of breast cancer (30.7%) were the main reasons for perceiving as not being at risk of breast cancer (t cancer .p=0.67) but significantly increased with an increasing year of study (p=0.02). Additionally, the proportion of students who perceived themselves to be at risk of breast cancer was higher (71.4%) among students in the school of Basic and Biomedical Sciences, followed by the School of Medicine (55.2%) and School of Nursing and Midwifery (36.9%), but lowest among Pharmacy (16.7%) and Allied Health Sciences students (23.6%) (p=0.01). Academic year (p=0.02), school (p=0.01), knowledge of someone with breast cancer (p < 0.001), family history of breast cancer (p < 0.001), current use of oral pills/injectables (p=0.03), history of breast cancer screening (p<0.001), and intention to perform breast self-examination (p < 0.001) were the risk factors of breast cancer risk perception (rception .p < 0.001) compared with those having a family history of breast cancer. Women who had never screened for breast cancer were also 62% less likely to perceive that they were at risk of breast cancer  compared with those who had ever screened for breast cancer. Students without any intention to perform breast self-examination in the future were as well 83% less likely to perceive breast cancer risk  than those with an intention.For an individual to adopt any healthy behaviour, he/she should be able to feel vulnerable to a particular threat and must perceive the threat as serious, thus taking actions to salvage him/herself from that condition , 21. ThiPredictably, the study demonstrates a significant level of optimism in breast cancer risk perception among Ghanaian female Undergraduates. Most of our study participants did not think they are vulnerable to breast cancer, and the most important reason underlying their optimism was “I take good care of myself.” The high rate of optimism towards breast cancer among this population could be due to the fact that they are relatively young as almost all of them (98.7%) were less than 30 years and might be aware of the fact that female breast cancer is most frequently diagnosed among women in advance age and as with most malignancies, the risk increases with age . NotwithOn the contrary, Constance et al. found a surprisingly inverse relationship between risk perception and willingness to screen for cervical cancer in women in Northern Ghana and postulated that fear of the unknown could deter women who think they are likely to be positive from accessing screening services . Among TWhen we examined the relationship between breast cancer risk factors and perceived risk of breast cancer, family history of breast cancer, which can be perceived as a risk by directly experiencing the events, was the only risk factor associated with a higher perceived risk of breast cancer. Many studies in different locations and among different populations have shown that experience of breast cancer at a close range is associated with a higher odds of perceived risk of breast cancer , 25, 30.To establish whether the perceived risk of breast cancer predicts preventive behaviour, we examined the association between perceived risk and the intention to perform breast examination in future. Expectedly, the results showed that women who did not have an intention to perform breast cancer examination in future were 83% less likely to perceive themselves as being at risk of breast cancer, compared to those with the intention to perform breast examination in future. This confirms Park et al.'s  study whThis study has two limitations. First, the findings cannot be generalized beyond the study population because they are young and well-educated women. University students are not representative of young adults in general, and the risk perception may differ from that of the general population. Second, all data were self-reported with no objective measures to assess the accuracy of these reports. However, the results of this study provide some understanding regarding the perceived risk and related factors of breast cancer among future health professionals, which can be useful for strategized communication and education.This study shows a significant level of optimism in breast cancer risk perception among female undergraduate students in Ghana with an average risk of breast cancer. Only a family history of breast cancer that could be directly perceived through experience was found to be associated with a perceived risk of breast cancer. Furthermore, women who had previous breast cancer screening experience and those with the intention to perform a self-breast examination in the future positively perceived themselves as being at risk of breast cancer. We recommend periodic risk perception assessment among women of different birth cohorts in order to develop strategies that influence preventive behaviour among women.


Oral and oropharyngeal squamous cell carcinoma (SCC) is the 10th most common cancer in the United States , with an estimated 54,010 new cases expected in 2021, and is primarily associated with smoked tobacco, heavy alcohol consumption, areca nut use and persistent high-risk human papillomavirus (HPV). Family history of cancer (FHC) and family history of head and neck cancer (FHHNC) have been reported to play an important role in the development of OSCC. We aimed to investigate the role of FHC, FHHNC and personal history of cancer in first/second degree-relatives as co-risk factors for oral cancer.This was a retrospective study of patients diagnosed with OSCC at the Division of Oral Medicine and Dentistry at Brigham and Women’s Hospital and at the Division of Head and Neck Oncology at Dana Farber Cancer Institute. Conditional logistic regressions were performed to examine whether OSCC was associated with FHC and FHHNC of FDRs and SDRs, personal history of cancer and secondary risk factors.Overall, we did not find an association between FHC, FHHNC and OSCC risk, whereas patients with a cancer history in one of their siblings were 1.6-times more likely to present with an OSCC. When secondary risk factors were considered, patients with a history of oral leukoplakia and dysplasia had a 16-times higher risk of having an OSCC.Our study confirmed that a previous history of oral leukoplakia or dysplasia was an independent risk factor for OSCC. A positive family history of cancer in one or more siblings may be an additional risk factor for OSCC. Oral and oropharyngeal squamous cell carcinoma (SCC) is the 10th most common cancer in the United States , with an estimated 54,010 new cases expected in 2021, a 5-year relative survival rate of 65% and incidence rates more than twice as high in men than in women , 8. OtheFamily history of cancer (FHC) has been reported to play an important role in the development of different cancer types in first-degree-relatives , with recent studies pointing toward a family history of head and neck cancer (FHHNC), as well as the loss of function TP53 mutations and CDKN2A inactivation, expression of certain proto-oncogenes and frequent copy number alterations –13. The This was a retrospective case-control study of patients aged greater than or equal to 18 years who were diagnosed with OSCC at the Division of Oral Medicine and Dentistry at Brigham and Women’s Hospital (BWH) and at the Division of Head and Neck Oncology at Dana Farber Cancer Institute (DFCI) from January 2000 through March 2016. Eligible cases included patients with a diagnosis of SCC of the tongue, gingiva, floor of mouth, palate, and oral mucosa . Oropharyngeal SCCs  were excluded from this analysis given that the majority (79.2%) are HPV-associated and thus a separate etiological entity.Controls were selected from patients aged ≥18 years seen in the Division of Oral Medicine and Dentistry at BWH between January 2000 and March 2016 for one of the following benign oral conditions: trigeminal neuralgia (ICD10-G50.0), atypical facial pain (ICD10-G50.1), temporomandibular disorder (ICD10-M26.60), burning mouth syndrome (ICD10-K14.6), aphthous stomatitis (ICD10-K12.0), oral fibroma (ICD10-D10.39), geographic tongue (ICD10-K14.1), orofacial granulomatosis (ICD10-K13.4), varix (ICD10-I86.8), and mandibular/maxillary torus (ICD10-M27.8). Exclusion criteria of controls included a current diagnosis of head and neck cancer (ICD10-C00-C14) or a potentially malignant condition such as oral leukoplakia (ICD10-K13.21), oral dysplasia (ICD10-K13.29) and oral submucosal fibrosis (ICD10-K13.5). The study protocol was approved by the Institutional Review Board of the Brigham and Women’s Hospital/Dana Farber Cancer Center.Data was collected verbally from prior patient encounters and included patient demographics, medical history, FHC , and social history. Cases and controls were exact matched by sex, alcohol, and tobacco. Conditional logistic regressions were performed to examine whether OSCC was associated with FHC and FHHNC of FDRs and SDRs, personal history of cancer, history of leukoplakia/dysplasia, as well as history of head and neck radiation therapy. All statistical analyses were carried out using R statistical software .n = 496), 79.1% of controls (n = 284)), males in cases (58.6%) and females in controls (76.9%) with a median age of 63 years (range: 18–98) in the cases and 61 years in the controls (range: 24–96). Amongst the cases, the most common anatomic site for the OSCC was the floor of the mouth , followed by the gingiva , and palate . More than 70% of the cases were ever-tobacco users , and current alcohol drinkers , whereas about two-thirds of the controls were never tobacco users  and half were current alcohol users  ) and 359 controls ) remained in the dataset. The majority of the patients were Caucasians (92.7% of cases (8–98) andp < 0.01). No significant association was found between overall family history of cancer (FDRs and SDRs) and OSCC risk , between overall family history of HNC (FDRs and SDRs) and OSCC risk , and with history of cancer in children , SDRs  and grandparents .After exact matching for sex, alcohol, and tobacco use, 255 cases and 255 controls remained in the dataset; a conditional logistic regression was used to examine whether FHC, or FHHNC in first degree relatives  and second degree relatives  were associated with OSCC. Overall, 253 patients  reported a FHC and 26 patients  reported a FHHNC  had a 16-fold increased risk of having OSCC . Personal history of solid cancer, hematologic malignancies and previous head and neck radiation therapy were not significantly associated with a higher risk of developing OSCC  and secondary risk factors , were significantly associated with risk of OSCC. Overall, patients with a personal history of oral leukoplakia and dysplasia (p = 0.01). When secondary factors were analyzed, personal history of oral leukoplakia and dysplasia was found to be associated (15.6-times) with the development of OSCC .This retrospective case-control study investigated the role of FHC, FHHNC, personal history of cancer and secondary factors in the development of OSCC. Overall, we did not find an association between FHC, FHHNC and OSCC risk, whereas a history of cancer in one or more siblings was associated with a greater OSCC risk  of 105 patients with HNC had 31 cases of cancer of the respiratory and upper digestive tract, with 41.9% (n = 13) of them located in the head and neck area. Interestingly, when the frequency among all FDRs was evaluated, siblings had the highest rate of frequency (OR: 14.61 95% CI 3.1–69.1) whereas there was no evidence of association between history of cancer in parents and increased HNC risk. Similarly, in our study, a history of cancer in one or more siblings was associated with a greater OSCC risk .Previous studies have reported on the role of alternative risk factors for OSCC aside from the well-documented tobacco and alcohol. o et al.  in theiri et al.  conductei et al. . A histoer et al  evaluateOur study has several limitations including its retrospective nature and self-report of FHC/FHHNC. In addition, some providers did not systematically record FHC, which overall may have altered part of our results compared to the afore-mentioned studies (OR: 1.59 vs OR: 14.61 ). FinallIn summary, our study suggests that a family history of cancer in one or more siblings may be an independent risk factor for OSCC, along with a history of previous oral leukoplakia or dysplasia. No evidence of an association was found between a family history of any cancer and increased risk of OSCC in this patient cohort from the New England region of the USA. The identification of additional risk factors for OSCC may help clinicians better identify which patient subgroups are at risk and should be screened regularly for such malignancies.


BRCA1 was identified and cloned [BRCA 1 and BRCA 2 are well-known susceptibility genes for breast cancer, which are also associated with ovarian and pancreatic cancers. Recent advancement in the mechanism of hereditary breast cancer has changed the clinical approach to patients and families who are considered “high risk” for breast cancer. Genetic testing is becoming a feasible option to accurately estimate their own risk and to optimize screening/surveillance strategy.Research on breast cancer risk revealed that 5–10% of breast cancer patients are genetically predisposed to cancers [d cloned , 3. BRCADue to the accumulating evidence and continuous efforts by professional societies, several medical examinations, and treatments related to HBOC have become covered by insurance in Japan . These iNowadays, clinicians and professionals who are involved in the management of breast cancer need to have sufficient knowledge of hereditary breast and ovarian cancer (HBOC) and other high-risk conditions of breast cancer to support patients’ choice. The benefit and harm of breast cancer screening/surveillance vary depending on individual risk of breast cancer. Conducting genetic testing and knowing the results affect patients’ life and families’ life and therefore fully-informed decisions should be made.As a journal dedicated to breast cancer, we have dealt with the issues related to the high risk of breast cancer –10. ThisScreening strategy by imaging is a crucial component of HBOC management. The paper by Tozaki and Nakamura describes the current status of breast cancer screening in high-risk women in Japan . Based oMore practical side of MRI-guided vacuum-assisted biopsy (VAB) is covered in this featured paper . There aWorldwide, various professional societies in many countries issue guidelines for breast cancer screening for normal and elevated risk of breast cancer. Onishi et al. encompass the guidelines and compare these guidelines . There aI hope that these special feature papers are useful for reviewing up-to-date knowledge of HBOC for readers who are interested in this topic and are helpful in supporting those with high -risk of breast cancer.