The aim of this study was to assess the acceptability and feasibility of offering risk-based breast cancer screening and its integration into regular clinical practice. A single-arm proof-of-concept trial was conducted with a sample of 387 women aged 40–50 years residing in the city of Lleida (Spain). The study intervention consisted of breast cancer risk estimation, risk communication and screening recommendations, and a follow-up. A polygenic risk score with 83 single nucleotide polymorphisms was used to update the Breast Cancer Surveillance Consortium risk model and estimate the 5-year absolute risk of breast cancer. The women expressed a positive attitude towards varying the frequency of breast screening according to individual risk and, especially, more frequently inviting women at higher-than-average risk. A lower intensity screening for women at lower risk was not as welcome, although half of the participants would accept it. Knowledge of the benefits and harms of breast screening was low, especially with regard to false positives and overdiagnosis. The women expressed a high understanding of individual risk and screening recommendations. The participants’ intention to participate in risk-based screening and satisfaction at 1-year were very high. Personalized breast cancer screening is characterized by risk-based recommendations for the ages of screening initiation and cessation, the screening frequency, the type of screening exam, consideration of preventive treatments for high-risk women, or even decisions regarding the non-screening of low-risk women. In modeling studies, personalized risk-based approaches to the early detection of breast cancer appear to be more efficient and have a better balance of benefits and harms than age-only strategies ,2,3,4,5.Although personalized screening will probably be the standard for early detection in the near future, the systematic reviews warn of the need for additional studies that assess risk estimation, acceptability, feasibility, and the legal and ethical aspects of personalized screening strategies ,4,5. To In 2019, the European Collaborative on Personalized Early Detection and Prevention of Breast Cancer (ENVISION)  organizePersonalized screening requires an accurate measure of individual risk. Age, reproductive history, breast density, family history of breast or ovarian cancer, previous benign breast disease, hormonal and lifestyle factors, and a combination of common genetic variants such as single-nucleotide polymorphisms (SNPs) and mutations in the BRCA or other susceptibility genes can be amalgamated to predict breast cancer risk ,13,14,15A widely used risk model, the Breast Cancer Surveillance Consortium (BCSC) model developed and validated by Tice et al. in 2008 , includeIn Spain, most population-based screening programs target women aged 50–69 and perform biennial mammograms. However, opportunistic screening in women younger than 50 years is widely used  and poseStudies assessing the acceptability of personalized screening by women who have participated in it are scarce. Although acceptability is generally good, the results are heterogeneous and vary according to a woman’s estimated risk of breast cancer. When less frequent screening is recommended, low-risk women are concerned about the possibility of a late diagnosis ,24. In cIn order to reduce the time lag between evidence generation and implementation, we designed the DECIDO project, which aims to assess the acceptability and feasibility of offering personalized breast cancer screening and its integration into the normal clinical practice. This proof-of-concept study, the protocol of which was published elsewhere , assesseFor practical reasons, this section reproduces in part the methods section of the published protocol . See theThe study was designed as a single-arm proof-of-concept trial. A pilot study was carried out with 20 women to test the suitability of the recruitment and data collection processes and the coordination of the involved healthcare professionals.From January 2019 to February 2021, 387 women aged 40 to 50 years were enrolled in the study. Potential participants were the 2038 women living in the “Primer de Maig” Basic Health Area in Lleida, Catalonia, on 31 December 2018, who would have turned between 40 to 50 years of age during the following 1.5 years. Accrual was suspended because of the COVID-19 pandemic in March 2020 when 252 women had been included and resumed in October 2020.All women who turned 50 during the study period would have received the first invitation to participate in the population-based Breast Cancer Early Detection Program. Instead, they were invited to participate in our study. Women that declined were invited by the early detection program.From women that turned 40 to 49 years during the study period, random samples of 20 to 50 women were selected from the potential participants on a monthly basis, and the women were invited to participate until the accrual goal was achieved.Exclusion criteria included having a previous diagnosis of breast cancer, undergoing a current breast study, or fulfilling clinical criteria for cancer-related genetic counseling. We also excluded women not understanding or speaking Catalan or Spanish or those with a physical or cognitive disability that prevented breast screening or the main outcome’s assessment.An invitation letter was mailed to the selected women, which was followed by a phone call 1–2 weeks afterwards where a healthcare professional of the study team provided a brief summary of the study and determined eligibility. Women that decided to participate were scheduled for a visit at the Primary Care center. Informed consent was obtained at the beginning of the first visit.The study intervention consisted of a baseline visit, the breast cancer risk estimation, a visit for risk communication and screening recommendations, the administration of a follow-up questionnaire, and a phone call to assess satisfaction after one year. Before the COVID-19 pandemic, all the visits were performed by physicians from the study team. As a result of the workload, during the pandemic, visits were made by a trained nurse, also a member of the study team, except for risk communication and recommendations to high-risk women. These visits continued to be performed by physicians.The baseline visit was held at the Primary Care center, where the healthcare professional provided information about the study objectives; facilitated an informative brochure about the benefits and adverse effects of breast cancer screening ; obtaineBreast density was classified according to the Breast Imaging Reporting and Data System (BI-RADS), 5th edition, scoring system : almost Collection, conservation, and delivery of saliva samples was completed following the saliva collection protocol provided by the University of Lleida’s Proteomics and Genomics Service. Details about the genotyping process can be found in the protocol . The PRSThe Breast Cancer Surveillance Consortium v2.0 (BCSC v2.0) risk model  that incOnce the breast cancer risk was obtained, a second visit was scheduled for risk communication and screening recommendations. The visit was performed by the same healthcare professional that performed the first visit. Women were informed of their 5-year absolute risk of breast cancer and the risk of a woman of the same age in the general population by means of two pictograms. Screening recommendations were given to them according to their risk, as described in the study protocol  and TablAt the end of the risk communication visit, a follow-up questionnaire that included the primary and secondary outcomes was given to women. They were asked to return it within 2–4 weeks.The primary outcome measures were attitude towards, intention to participate in, and satisfaction with personalized breast cancer screening by participating women.Attitude was measured with a three-item scale ,33, eachSecondary outcomes  have been detailed in full in the study protocol .The sample size was estimated considering that the primary outcomes could be expressed as proportions that facilitate the interpretation as positive or neutral-negative outcomes. In order to ensure that the 95% confidence interval estimate of a proportion was within 5% of the true proportion, a sample of size 385 was needed.Medians and quartiles or absolute and relative frequencies were used to describe quantitative and categorical variables, respectively. Likert scale responses corresponding to the primary outcomes were analyzed as ordered-categorical data with frequencies and proportions represented as stacked bar charts for the primary outcomes. The exact binomial test was used to obtain 95% confidence intervals for proportions. No imputation method was used when women omitted to supply answers to questions in the survey or the whole survey. The number of non-missing responses is always indicated.The R programming language  and the From December 2018 to January 2021, 861 women were selected, and invitation letters were sent to them; of these selected women, 249 could not be reached and 38 did not meet the inclusion criteria . Of the The absolute risk of breast cancer at 5 years could be estimated for 372 (96.1%) women. A median relative risk of breast cancer equal to 2.8 was obtained by comparing the risk characteristics of participants with the lowest risk categories of the BCSC v2.0 model. The median values of the estimated preliminary 5-year absolute risk of breast cancer and the PRS were 0.80% and 0.95, respectively. When the PRS was taken into account, the median of the updated 5-year absolute risk slightly decreased to 0.72% and the variability of the risk distribution increased, as the new quartiles and the plots of the distribution show .One out of four women were classified as high risk and were recommended for annual screening (risk at 5 years > 1.16% for women aged 40–44 or > 1.19% otherwise). Only 14% (one out of seven) were recommended for biennial screening, one out of four triennial screening, and one out of three were recommended to watch and wait to be invited to the screening program at 50 years. For ages lower than 50 (before being invited to the screening program), two out of three were recommended to watch and wait and one out of four for annual screening. Three women had very high risk (> 6% at 5 years) and were referred to the hospital breast unit for a more intense follow-up.> 12) towards personalized screening.The intention to participate in personalized breast screening, if invited, was rated as “definitely will” or “likely to” by 9 out of 10 women. Around 1 year after being included in the study, 97% of the women declared they were satisfied or very satisfied with personalized breast screening and nine (2.6%) were not sure. Only one stated that she was very unsatisfied.> 20). The attitude towards measuring breast cancer risk was also positive, with 3 out of 4 women considering that it would do more good than harm, in contrast to 1 out of 25 that expressed the opposite. More than three out of four women agreed that the information on individual breast cancer risk provided reassurance and more than one out of four agreed that receiving information about risks leads to anxiety or makes them worried. Compared to the current screening, two out of three would choose personalized screening and one out of four would choose the current screening.Attitudes towards undergoing breast screening  were positive overall. The median attitude score  was 22, and 9 out of 10 women met the threshold for a positive attitude (scores Only 5 (1.5%) of 328 women had an adequate overall knowledge according to the established threshold for the three subscales of benefit, false positives, and overdiagnosis. An adequate knowledge of the three mentioned subscales was possessed by 18.1%, 6.5%, and 8.3% of the participants, respectively. For the conceptual knowledge items individually, 9 out of 10 women had correct answers for the definition of a screening mammogram, the benefit of screening towards the reduction of breast cancer deaths, and the possibility of having a false positive result. A low number of correct answers was given to two items on the overdiagnosis subscale: “screening causes some women with low-risk cancers, which would never cause any health problems, to be treated unnecessarily” and “screening is more likely to detect low-risk cancers, which would never cause any health problems, than to prevent death from breast cancer.” Both items were answered correctly by one out of four women. One out of two women answered (incorrectly) that the sentence “screening will not find every breast cancer” was false.Scores for decisional conflict were low, with a median of 10 on a scale from 0  to 100 . About 4 out of 10 women had a score equal to 0, which indicates no decisional conflict. Confidence in decision-making was high, with a median score of 4.7 on a scale from 1 to 5. The anxiety scores had a median of 30 on a scale from 20 to 80, with higher scores indicating greater levels of anxiety. Out of five women, one was quite worried or very worried about breast cancer, and the other four were split between being not worried at all or a bit worried. When deciding whether to have screening, avoiding death by breast cancer was mentioned as very important for more than 8 out of 10 women. Being diagnosed and treated for a cancer that is not harmful and having a false positive result were rated as very important for half of the participants.“I have understood…” had the highest value (five = strongly agree) on a scale of one to five and the first quartile was four (agree) for both items. A total of 9 out of 10 women reported their intention (“definitely will” or “likely to”) to follow the recommendations.Most women considered that being informed about breast cancer risk empowered them or increased their autonomy. Most of them expressed that receiving and commenting on risk information from a healthcare professional made them feel safer or better about making decisions that affected their health. Consistently with these results, the overall experience of having participated in the proof-of-concept study was assessed as positive by 8 out of 10 women. The confidence in personalized screening also received high rates with a median of five on a scale of one to five. Moreover, the understanding of the individual risk and the screening recommendations was rated very high. The median scores of the two items starting with The median time spent on risk communication was about 5 min, with 25% of the encounters with a time greater than or equal to 7 min.This proof-of-concept study assessed the acceptability and feasibility of offering personalized breast cancer screening in the National Health System in Spain. The participating women expressed a positive attitude towards varying the frequency of breast screening according to individual risk and, especially, towards inviting women at higher risk more often than the average. A lower intensity screening for women at lower risk was not as welcomed, although half of the participants would accept it. The Intention to participate in risk-based screening and the satisfaction at one year were very high.Concerning the risk measurement, the women expressed a high understanding of individual risk and screening recommendations. While a significant proportion of women stated that risk information could cause anxiety or worry, most had a positive attitude toward measuring risk and felt that it would do more good than harm.Knowledge of the benefits and harms of breast screening was low, especially with regard to false positive results and overdiagnosis. Most women reported low decisional conflict, low or moderate levels of anxiety, and a high confidence in decision making. In deciding whether to have screening, the chance of avoiding death from breast cancer was considered very important more often than the chance of having a false positive result or being diagnosed and treated for a cancer that is not harmful. However, half of the women rated these adverse outcomes as very important.Recent studies have obtained results consistent with ours in relation to the acceptability of and intention to participate in personalized screening ,38. DunlAdditionally consistent with our findings, some studies have found that women are reluctant to reduce the frequency of screening or discontinue screening for low-risk groups, which healthcare professionals have mentioned as one of the barriers to the future implementation of the strategy ,40,41. SSimilar to other studies, our participants reported low levels of decisional conflict and anxiety about screening participation and a high confidence in decision making ,33,45,46Health professionals in Spain also stated the importance of general practitioners in the success of personalized breast screening . Women’sMost breast risk models estimate an absolute breast cancer risk over a specific timeframe, using personal, reproductive, and genetic risk factors. Clift el al.  point ouSeveral studies have shown that the addition of PRS to the classical breast cancer risk factors improves risk stratification. Vachon et al. , based oIn our study, as has been described, we observed that the 5-year risk distribution showed increased variability after considering the PRS. Before the PRS, no woman had a 5-year risk above the 3% threshold, whereas after the PRS 15 (4%) women were reclassified above it. In addition, in terms of screening recommendations , without considering the PRS, the recommendations would have been different for one in four women. Of those that would have been reclassified, 7 out of 10 would have been recommended for annual screening and the other 3 for less intense screening.Since most PRS are based on data from individuals of a white European origin, they can produce inaccurate results in women of other ethnicities if differences in the allele frequencies or in the odds ratios for the disease association exist. Evans et al.  found thA surprising result of our study is the high value that women placed in understanding the information they had received about their individual risks and their risk-based screening recommendations. Although the professionals that communicated risk in our study  did not receive specific training for breast cancer risk communication in personalized screening, they had experience in communicating other risks in the clinical care setting and they were part of the research team that designed the DECIDO project. The supporting material used—consisting of a report including their statuses for family history, benign lesions, breast density, PRS, and two pictograms with the 5-year absolute risk of breast cancer, one with their risk and the other with the risk of a woman of the same age from the general population—was probably very helpful in the clinical encounter.However, we found that conceptual and numerical knowledge of the benefits and harms of breast screening were low despite the fact that the study participants received an informative leaflet with detailed information on these benefits and harms. This result is consistent with a recent study on health literacy showing that one in every three to almost one in every two Europeans may not be able to understand essential health-related material . In addiPashayan et al.  indicateIn this regard, when Ahmed et al.  assessedThis is the first proof-of-concept study that provides an indication that personalized breast cancer screening might be feasible and acceptable in the target population under the Spanish National Health System. The novelties of this study are (1) breast cancer-risk estimation using known risk factors and a polygenic risk score, (2) tailored recommendations on breast cancer screening provided to women by a primary care doctor or a nurse in their health center, and (3) the inclusion of women aged 40–49 years, an age interval not covered by the public screening program.The study also has some limitations. First, the single-arm study design does not enable outcome comparisons between groups. However, this proof-of-concept study represents another step towards the implementation of personalized breast cancer screening in publicly funded health systems. Second, the results were based on a smaller sample compared to other published studies. Nonetheless, the study had a high acceptance and a low dropout rate, which ensures its validity and enables its generalization in the Spanish National Health System. Moreover, even though women that did not understand Catalan or Spanish were not included, the study sample was diverse with respect to age, educational level, and origin. Third, we did not explore the willingness to adopt preventive measures for women at high risk. Asking this type of question would have required providing additional information about the existing preventive interventions and about their pros and cons. Finally, the COVID-19 pandemic caused an interruption of around six months in the study’s accrual and development. It also caused a change in the risk communication process where a nurse of the study team took over for the primary care physicians who were at the healthcare frontline. The interruption in the study flow, for some women, may have caused non-response or recall problems when filling out the follow-up questionnaire or even study dropouts due to personal situations or a lack of interest. Finally, the low knowledge of the harms and benefits of screening for a non-negligible number of participants did not limit the understanding of the estimated risk and the screening recommendations.This study provides information relevant to the development of risk-based breast screening in a publicly funded health system. The PRS introduced variability to the estimated breast cancer risk and modified the screening recommendations for a quarter of the sample. Participants had a positive attitude towards personalized breast screening; expressed their intention to participate in a personalized breast screening program, if possible; and were very satisfied with having participated in the study. However, women were relatively unwilling to accept less frequent screenings following the results of a low-risk status. The understanding of individual risk and the screening recommendations was high and most women expressed the intention to follow them.Before implementing personalized screening, clear evidence of its benefits and harms must be established. In addition, for risk-based screening to be effective, valid risk models are needed, but equally important are the risk-based interventions that will be offered. In addition, more research is needed on its feasibility and acceptance by women through both quantitative studies with larger samples and diversity in the characteristics of women and qualitative studies that can deepen and broaden the scope of investigation, thereby enabling the realization of a better understanding of the factors that influence the acceptance of personalized screening by women.Likewise, it is necessary to design tools and strategies for the development of interventions focused on raising awareness about personalized screening, increasing literacy on risk measurement, and achieving collaborative decision making in clinical practice.


It is unknown whether this relationship exists in Black women, who have the highest incidence of TN breast cancer and the highest overall breast cancer mortality rate. We examined relationships between TDLU metrics and breast cancer molecular subtype among breast cancer cases in the Black Women’s Health Study (BWHS).Terminal duct lobular units (TDLUs) are the structures in the breast that give rise to most breast cancers. Previous work has shown that TDLU involution is inversely associated with TDLU metrics, such as TDLU count/100mm2, TDLU span (µm), and number of acini/TDLU) in digitized 247 hematoxylin and eosin-stained adjacent normal tissue sections from 223 BWHS breast cancer cases, including 65 triple negative (TN) cancers (estrogen receptor (ER) negative, progesterone receptor (PR) negative, human epidermal growth factor-2 (HER2) negative) and 158 luminal A cancers . We evaluated associations of least square mean TDLU metrics adjusted for age and body mass index (BMI) with patient and clinical characteristics. In logistic regression models, we evaluated associations between TDLU metrics and breast cancer subtype, adjusting for age, BMI, and tumor size.We assessed quantitative TDLU metrics  for tertile 3 versus tertile 1 of 2.18 , 2.77 , and 1.77  for TDLU count, TDLU span, and acini count/TDLU, respectively.Associations of TDLU metrics with breast cancer subtypes in the BWHS are consistent with previous studies of White and Asian women, demonstrating reduced TDLU involution in TN compared with luminal A breast cancers. Further investigation is needed to understand the factors that influence TDLU involution and the mechanisms that mediate TDLU involution and breast cancer subtype.The online version contains supplementary material available at 10.1186/s13058-022-01577-1. Triple negative (TN) breast cancer, an early-age onset and aggressive form, has the highest incidence in Black women among US women . StudiesRecent work has shown that histological measures of terminal duct lobular unit (TDLU) involution in adjacent normal breast tissues are associated with TN breast cancer risk relative to luminal A breast cancer in Chinese and European women –10. Char2, TDLU span/diameter (microns), and number of acini (substructures) per TDLU) have been shown to be inversely associated with TDLU involution and positively associated with breast cancer risk among women diagnosed with benign breast disease (BBD) [Higher levels of quantitative TDLU metrics (number of TDLUs per 100mmse (BBD) –15. Prevse (BBD) , 14.The aim of this study was to evaluate associations of quantitative measures of TDLU involution with breast cancer molecular subtype among women diagnosed with breast cancer in the Black Women’s Health Study (BWHS), and to examine associations of TDLU measures with reproductive risk factors. Understanding these relationships in Black women, who are at increased risk for TN breast cancer, may be important for better understanding the etiologic and pathologic heterogeneity of breast cancer.The Black Women’s Health Study (BWHS) is a prospective cohort that enrolled 59,000 self-identified Black women, ages 21–69 in 1995  and has Hematoxylin and eosin (H&E)-stained slides of adjacent normal tissues were shipped to the Molecular and Digital Pathology Laboratory at the National Cancer Institute, digitized at 40X magnification (Leica AT2) and prepared for viewing and annotation with HALO Link  .2. For TDLU span (microns) and number of acini per TDLU, up to 10 normal TDLUs were reviewed sequentially as follows: 1) TDLU span was measured with an electronic ruler (microns) and 2) acini counts/TDLU were assessed visually in categories , to provide stable representative measures of TDLU involution. For acini counts/TDLU and TDLU span measures, we used the median of the values obtained across the multiple TDLUs measured for each woman. These quantitative TDLU metrics have been found to be reliable and correlated with qualitative assessments of TDLU involution as previously described [Digitized H&E-stained whole slide images were reviewed by a single expert reviewer (RC) masked to other participant data to estimate percentage of fat and the presence of normal TDLUs. Tissue sections containing cancer were not evaluated. TDLUs were not evaluated if at least half the acini were dilated 2–3 times the normal diameter or if metaplastic changes involved at least half the acini. Sections with the presence of normal TDLUs were then analyzed for standardized measures of TDLU involution, including number of TDLUs per 100mmescribed .The analysis was restricted to women diagnosed with luminal A (n = 158) and TN (n = 65) breast cancers to remain consistent with previous analyses of TDLU involution measures and breast cancer subtypes  in other2) , and stratifying by breast cancer molecular subtype. Logistic regression was used to estimate associations  between TDLU involution measures and breast cancer subtypes . Tertile levels of standardized TDLU involution measures were created based on the distribution in the luminal A cases. Potential confounding factors were included as adjustment variables if the p value/trend was < 0.05 based on Chi-square tests for their associations with at least one TDLU involution measure and breast cancer subtype. To conserve degrees of freedom, we adjusted for age using a dichotomous variable and BMI and tumor size using an ordinal trend. Sensitivity analysis with additional adjustment for percent fat on the slide was also performed.Patient characteristics were compared using Chi-squared tests for categorical variables or student’s t-test for continuous variables. Adjusted least square means of each TDLU involution measure by participant characteristics were estimated using linear regression, adjusting for categorical age (≤ 55 or > 55 years) and body mass index  for some individuals. All statistical tests were two-sided, and a p value < 0.05 was considered statistically significant. R version 3.6.1 was used for all calculations.The R package “geepack”  was usedp = 0.04), BMI (p = 0.05), tumor size (p = 0.001), and tumor grade (p < 0.001). Compared with luminal A cases, the TN cases were more likely to be younger (≤ 55 years of age) at diagnosis and to have poorly differentiated and larger (> 2 cm) tumors ; TDLU span and acini count/TDLU metrics were lower for former and current smokers compared with never smokers ; TDLU count was significantly increased among parous women compared with nulliparous women (p = 0.01) and among parous women whose last birth was within the last 20 years as compared with parous women whose last birth was 20 + years ago (p < 0.01). All TDLU measures were lower among post-menopausal women as compared with pre-menopausal women , a pattern that was observed but not statistically significant in TN cases. For both luminal A and TN cases, TDLU measures decreased with increasing BMI.The TDLU involution measures were strongly and positively correlated with each other  versus smaller (≤ 2 cm: 15.1/100 mm2) tumors (p = 0.04). Among TN cases, all TDLU measures increased with increasing tumor grade, but the association was statistically significant only for TDLU count (p = 0.05). Among both case groups, all TDLU measures tended to be higher with positive lymph node invasion.Among luminal A cases, TDLU count was elevated for those with larger  compared with women diagnosed with luminal A breast cancer. We also observed associations between TDLU involution measures and several participant and clinical characteristics. Prior work has demonstrated relationships between TDLU involution, breast cancer risk factors, and breast cancer development in European and Asian populations , 10. OurOur findings of decreased TDLU involution in TN breast cancer cases as compared with luminal A cases are consistent with previous studies examining TDLU involution measures in European and Chinese breast cancer patients. In particular, among European women diagnosed with breast cancer, the core basal phenotype  was associated with a greater average number of acini per TDLU and larger average TDLU diameter compared with luminal A cancers . LikewisTDLU involution has previously been associated with many breast cancer risk factors. Among healthy women, decreased TDLU involution has been observed for non-smokers compared to former and current smokers, women with family history of breast cancer, with younger ages at menarche, and with denser breasts , 21. AmoAmong the Black breast cancer patients in this study, we also observed relationships between risk factors and involution metrics in their adjacent normal breast tissues. Consistent with prior studies , we obseOur study also revealed decreased TDLU involution in never smokers compared with former/current smokers in tissue from women with luminal A tumors, consistent with previous findings in healthy women . AdditioWe observed associations between measures of TDLU involution and clinical characteristics. Our results showed decreased TDLU involution in breast cancer cases with larger tumor size and lymph node invasion, two clinical characteristics associated with more aggressive breast cancer subtypes, including TN breast cancer . UnderstAlthough obtaining quantitative TDLU measurements from H&E-stained tissue is often time-consuming, laborious, and subjective, currently limiting its clinical and prognostic utility, recent work has focused on automated approaches to obtain these measurements using digital pathology tools , 27. TheLimitations of this study include the use of adjacent normal breast tissues from women diagnosed with breast cancer, preventing establishment of temporality of the observed associations. The relatively small sample size, especially for TN cancers, resulted in low power for some risk factor associations. Strengths of this study include the case-only study design for investigating etiologic heterogeneity between molecular breast cancer subtypes , 29, andOverall, this study confirms and extends previous findings of an association of reduced TDLU involution with higher risk for TN compared with luminal A breast cancer to Black breast cancer patients. Associations between TDLU metrics and breast cancer risk factors suggest that TDLU involution may play an etiologic role in breast cancer carcinogenesis. More research is needed to understand how breast cancer risk factors, including environmental and social factors, influence TDLU involution and the mechanisms that mediate TDLU involution and risk of breast cancer subtypes. Further studies should also examine TDLU involution in normal and adjacent normal tissues from Black women and other racial and ethnic groups. Gaining a better understanding of the complex and heterogeneous etiology of breast cancer in Black women is paramount to addressing and reducing the health disparities that greatly affect this population.Additional file 1: Supplemental Table 1. Association between TDLU measures and breast cancer subtype among adjacent normal breast tissue slides^, adjusted for percent fat. Supplemental Table 2. Correlations between TDLU involution measures.


Group 1 reported significantly higher breast cancer risk perception (p < 0.001) compared to group 2, and higher cancer worry than group 2 (p < 0.001). Some group 1 participants described how receiving their genetic information heightened their cancer risk perception and exacerbated their cancer worry while waiting for risk-reducing surgery. Group 1 participants reported a MICRA mean score of 27.4 , and an adaptation score of 2.9 (SD = 1.1). Conclusion: There were no adverse psychological outcomes amongst women who received clinically actionable germline information through a model of ‘genome-first’ care compared to those who did not. These findings support the return of clinically actionable research results to research participants.Background Research identifying and returning clinically actionable germline variants offer a new avenue of access to genetic information. The psychosocial and clinical outcomes for women who have received this ‘genome-first care’ delivering hereditary breast and ovarian cancer risk information outside of clinical genetics services are unknown. Methods: An exploratory sequential mixed-methods case-control study compared outcomes between women who did  and did not  receive clinically actionable genetic information from a research cohort in Victoria, Australia. Participants completed an online survey examining cancer risk perception and worry, and group 1 also completed distress and adaptation measures. Group 1 participants subsequently completed a semi structured interview. Results: Forty-five participants (group 1) and 96 (group 2) completed the online survey, and 31 group 1 participants were interviewed. There were no demographic differences between groups 1 and 2, although more of group 1 participants had children ( Access to genetic information has increased as direct-to-consumer models, research initiatives, and private companies offer germline testing to anyone irrespective of their underlying risk. These pathways promote a significant departure from the model of care offered by clinical genetics services (CGS), where access is driven by personal and family history of disease . CGS have traditionally been the largest provider of genetic information and offer genetic testing nested within the practice of genetic counselling, where pre-and post-test appointments facilitate preparation for, and delivery of, genetic information . The CGSindependent of any clinical parameters”  and thought it was pretty drastic and then the next option was the drug, the chemoprevention and so I looked into that as well and I weighed up the risks and decided not to do that. But I decided, yes, I would have my ovaries removed, because ovarian cancer is very hard to detect, whereas breast cancer is a slow growing and you can feel if there’s a lump, you can have a mammogram, and also, I was post-menopause. I didn’t really need my ovaries.BRCA2). Many were also menopausal or post-menopausal, which further justified their decision.With over half of the women with a Well, I was at that age [where] my ovaries were probably not working that well anyway because I was 55 … I’d started menopause so it was no big deal.BRCA2) and cognitive (p < 0.001) breast cancer risk perception compared to group 2 (Group 1 had significantly higher affective ( group 2 .BRCA1/2 genetic information from lifepool had significantly higher affective ovarian cancer risk perception compared to group 2 (p = 0.0001), whereas there was no observable difference between groups for cognitive ovarian cancer risk perception (p = 0.1). However, when women who had a BSO were excluded, the remainder of group 1 had a significantly higher cognitive ovarian cancer risk perception  compared to group 2 .Women who had received d = 0.64; p < 0.001) (p = 0.01).Despite recruitment being less than anticipated, a significant difference was identified in the CWS between the two groups, with group 1 having significantly higher cancer worry than group 2 (Cohen’s < 0.001) . FurtherFor many of the women from group 1, the link between their cancer risk perception and worry about developing cancer was evident. Many of these women could recall the numerical, absolute risk of breast or ovarian cancer associated with having a PV and ascribed different understandings of what it meant to them personally:The percentage of ovarian cancer [risk] is quite high if you are BRCA2 positive. It’s from 11% to 25%. So, it’s quite alarmingly high, one in four. “So, I don’t know whether I’m the one in four, you don’t know. It’s still something that worries you at the back of the mind”.BRCA2). The transition from knowing about cancer risks numerically to experiencing them subjectively was described by Sharon:After learning their genetic status, group 1 participants described becoming “It just made me reassess … and even though I get it, even though you know what the [cancer] risk is in numbers, when you actually experience someone going through cancer, it does actually highlight the risk and make your perception of that risk a bit more attuned, I would say. So I think that that was like, “OK I don’t want to go through that.” This is a real thing not just an academic thing”.BRCA2) .SD = 1.1), with 5 being the highest possible score.Group 1 completed the PAS to assess their adaptation to receiving the genetic information . The meaAll bar one participant in group 1 had informed their family members about the genetic information. Of the 41 group 1 respondents who were parents, 37 (90.2%) had told all their children the genetic information . Of the 41 who had siblings, 35 (85.4%) had told all their brothers and sisters . The next most informed groups were nieces and nephews with 26 of 39 (66.7%) respondents informing all or some.The results from this study provide early evidence of the psychological and clinical outcomes for women who attended a population mammographic screening program, enrolled in research, and subsequently received unexpected genetic information about hereditary breast and ovarian cancer risk. A strength of this study was the recruitment of a matched comparator group, enabling the comparison of psychosocial outcomes for women who received this information and women who did not . The womlifepool population who received ‘genome-first’ care to populations who receive traditional pre-test genetic counselling and result disclosure in a CGS [lifepool. In contrast, Chirico et al. (2021) studied women who had survived breast cancer, documenting their cancer worry 12 months after their primary treatment as substantially higher at 23.4 (SD 5.5) [lifepool incorporating telephone genetic counselling, followed by a referral to a CGS for genetic counselling and testing, works to mitigate any substantially detrimental experiences for participants [Cancer worry and risk perception are frequently examined psychosocial outcomes after delivery of genetic information, interventions in CGS, or participation in cancer risk management programs ,31. Thesin a CGS . Eijzengin a CGS . The mea(SD 5.5) . It is licipants . Furthericipants ,35.The previously unknown impact of receiving genetic information from a research study is gradually being elucidated from studies such as this and others that have returned clinically significant research results to participants. The participants in this study had a total MICRA score that was slightly higher  compared to research participants in the high-risk melanoma group  from Smit et al. (2018) . The quaParticipants in our study reported that waiting to confirm if they were at high-risk of cancer was a source of distress, which prompted feelings of uncertainty. Health system responsiveness has previously been identified as a barrier to research participants taking up genomic information identified through research . A modelBRCA1/2 PV finding a mean of 3.04 (SD 1.11) [How women adapt to this information is also under investigation. Adaptation, as defined by Biesecker et al. (2008), is “a dynamic and multi-dimensional process of coming to terms with the implications of a health threat and the outcomes of that process” ,39. UntiSD 1.11)  comparedSD 1.11) .Overall, results from our study provide preliminary evidence that receiving unexpected genetic information through research participation can be distressing although not obviously different from receiving similar information from CGS.lifepool and subsequently participated in this research could be viewed as proactive with regards to health information as they attended a population-based breast screening program, consented to research, and opted in to receive unexpected genomic information. We did not have access to women who do not attend a population-based screening program or those who are less inclined to participate in research. These individuals may have different outcomes. The views of men were also not captured. A limitation of this study is the women who attended Our findings demonstrate that the clinical and psychosocial outcomes of individuals who receive cancer risk information through ‘genome-first’ care are not dissimilar to those reported for patients who attend CGS. This alternative avenue of identifying individuals and their families in the population who have a significantly increased risk of cancer does not pose unmanageable risks due to the mechanism of notification involving telephone genetic counselling and follow up genetic counselling through a clinical service. A model of genetic counselling for ‘genome-first’ care is needed that incorporates expedited access to CGS to mitigate feelings of anxiety and uncertainty by confirming participants’ high-risk of cancer and enabling engagement with cancer risk management strategies.


A primary difference between black women (BW) and white women (WW) diagnosed with breast cancer is aggressiveness of the tumor. Black women have higher mortalities with similar incidence of breast cancer compared to other race/ethnicities, and they are diagnosed at a younger age with more advanced tumors with double the rate of lethal, triple negative breast cancers. One hypothesis is that chronic social and economic stressors result in ancestry-dependent molecular responses that create a tumor permissive tissue microenvironment in normal breast tissue. Altered regulation of N-glycosylation of proteins, a glucose metabolism-linked post-translational modification attached to an asparagine (N) residue, has been associated with two strong independent risk factors for breast cancer: increased breast density and body mass index (BMI). Interestingly, high body mass index (BMI) levels have been reported to associate with increases of cancer-associated N-glycan signatures. In this study, we used matrix assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) to investigate molecular pattern changes of N-glycosylation in ancestry defined normal breast tissue from BW and WW with significant 5-year risk of breast cancer by Gail score. N-glycosylation was tested against social stressors including marital status, single, education, economic status (income), personal reproductive history, the risk factors BMI and age. Normal breast tissue microarrays from the Susan G. Komen tissue bank  were used to evaluate glycosylation against socioeconomic stress and risk factors. One specific N-glycan (2158 m/z) appeared dependent on ancestry with high sensitivity and specificity . Application of a linear regression model with ancestry as group variable and socioeconomic covariates as predictors identified a specific N-glycan signature associated with different socioeconomic stresses. For WW, household income was strongly associated to certain N-glycans, while for BW, marital status (married and single) was strongly associated with the same N-glycan signature. Current work focuses on understanding if combined N-glycan biosignatures can further help understand normal breast tissue at risk. This study lays the foundation for understanding the complexities linking socioeconomic stresses and molecular factors to their role in ancestry dependent breast cancer risk. A primary difference between Black women (BW) and White women (WW) diagnosed with breast cancer is the aggressiveness of the tumor –5. Not oA study assessing prioritization of breast cancer risk factors determined that body mass index (BMI) and weight gain was listed as second only to Gail Model parameters  in importance –16. UnfoGlycoproteins are abundant on cell surfaces and serve as one of the initial points of contact in orchestrated interactions that mediate cell-cell, cell-matrix and cell-molecule cross-talk in normal and cancerous tissue , 27, 28.Aberrant alteration of N-glycosylation plays a significant role throughout breast cancer progression and influences clinical outcome , 38–47. While there is a clear and strong association between Black ancestry and poor breast cancer prognosis –3, the uHigh‐performance liquid chromatography–grade acetonitrile, ethanol, methanol, xylene, and water were obtained from Fisher Scientific . Citraconic anhydride for antigen retrieval was obtained from Thermo Scientific . Alpha‐cyano‐4‐hydroxycinnamic acid (CHCA) and Trifluoroacetic acid (TFA) were obtained from Sigma‐Aldrich . Recombinant PNGaseF PRIME™ was obtained from N‐Zyme Scientifics . Hematoxylin and Eosin (H&E) stains were obtained from Cancer Diagnostics .Archived normal breast tissue samples  were obtained from The Susan G. Komen for the Cure Tissue Bank at the IU Simon Cancer Center. A commercial breast cancer progression TMA was obtained from US Biomax, Inc. Use for the study was approved as exemption 4 status by the Medical University of South Carolina Institutional Review Board.After H&E staining, tissues were de-stained and processed for N-glycan analysis –59. For A Solarix dual source 7T FT-ICR mass spectrometer  containing a SmartBeam II laser operating at 2000 Hz was used for analysis of released N-glycan ions. Ions were detected with a laser spot size of 25 µm using 200 laser shots per pixel with a stepsize of 100 µm. N-glycans were measured in positive ion mode with a 1.2059 s transient over mass range 700-5000. Data was analyzed using FlexImaging 5.0 and SCiLS Lab 2019c  normalized to total ion current. Exported peak intensities were transformed using natural log prior to statistical testing. Glycans annotated by accurate mass were assigned by hexose content. Putative structures are described using databases from previous imaging studies on human tissues using GlycoWorkbench , 60–67. p-values <0.05 were reported as significant.GraphPad version 9.02 was utilized for receiver operating characteristics (ROC) curve analysis and Mann-Whitney U test analyses. A ROC curve is a plot of Sensitivity versus 1-Specificity which generates an area under the curve (AUC) used as an effective measure of accuracy . The ManThe patient cohort was comprised of Black women  and white women  with high risk of breast cancer. Stroma rich normal breast tissue microarrays (TMAs) from BW and WW with mapped ancestry were used for glycomics mass spectrometry analysis  2. A toN-glycans are constantly regulated based on environmental and molecular factors . In ordeAncestry has been shown to influence breast cancer risk , 72–77, When comparing N-glycan peak intensities between BW and WW, 2012 m/z was significantly upregulated in WW versus BW . Certain N-glycans were strongly associated with household income for WW, while the same N-glycans were strongly associated with marital status for BW (An important contributing factor of breast cancer risk that must be considered is a patient’s body mass index (BMI), as obesity affects specific genetic ancestry groups more than others , 19, 78.Based on our patient cohort, BW had an overall higher BMI average compared to WW  and WW (n=25) with similar BMI distributions were analyzed  and WW (n=10) with similar Gail Scores  were created as a subgroup  compared to post-menopausal . N-glycans 1866 m/z, 2012 m/z and 2158 m/z were then compared between BW and WW based on their menopausal status . It is aTo better understand the implications of N-glycans in the context of breast cancer risk, analysis was done on breast cancer progression TMAs that range from hyperplasia, benign and inflammation to metastatic lymph nodes  relative to white women , 83 and cer risk . Specificer risk , 80, 87.cer risk , 17, butcer risk , 5, 11.In the current study, we report that certain glycans show lower ancestry-dependent expression levels in normal breast within the obese groups when stratifying by BMI. We further detected a specific singly-fucosylated N-glycan structure (m/z = 2012) decreased in BW. We showed that in breast cancer progression, the same specific singly-fucosylated N-glycan structure (m/z = 2012) was decreased in malignant breast cores (stages I-III) compared to non-malignant breast samples . This suggests that glycosylation patterns from WW follow non-malignant breast tissue patterns, while BW follow glycosylation patterns more similar to tumor. Differences in baseline glycosylation in normal breast tissue may be contributing to specific differences in breast stromal biology disproportionally affecting BW. While previous studies have shown that increased fucosylation is associated with malignancy , 88–90, Fucosylation is a well-known glycosylation modification that has been well characterized in cancers , 92, 93.It is important to note that the current data does not determine whether it is the breast epithelium or the stroma driving the observed glycosylation patterns as the sampling strategy did not allow for cellular annotation. Our current studies on normal breast at risk focus on identifying the cellular source of these N-glycans to assess their functional roles in the normal breast tissue microenvironment. Because the samples are stroma rich TMAs, it is possible that specific stroma composition may play a role in breast cancer outcomes that is additionally altered by BMI status. For instance, obesity has been linked to an increased incidence of TNBC in premenopausal and postmenopausal African American women . FurtherFinally, our initial studies using linear regression data revealed distinct N-glycans associated with specific socioeconomic factors by ancestry. Previous literature supports the link between socioeconomic factors and their effects on health –107. OneIn summary, breast cancer is now the leading cause of cancer death among women and disproportionately affects BW at significantly higher rates than WW. Thus, there is great need to close this gap and lower the overall breast cancer related death rates. Improving breast cancer prognosis and death rates requires a research focus on cancer control and prevention. Our study focused on ancestry-dependent glycosylation patterns in normal breast tissues from women at risk for breast cancer. We demonstrated that unique N-glycosylation patterns in normal breast tissues can differentiate BW from WW with high risk of breast cancer. More specifically, we revealed that in tissue at risk for breast cancer, decreases in specific fucosylated glycans in BW relative to WW may contribute to differences in breast stroma biology that could account in part for differences in breast cancer subtypes. Future studies should aim to investigate cell-specific N-glycan molecular signatures in breast tissue and immune cells and their roles in creating a tumor-permissive tissue microenvironment.The original contributions presented in the study are included in the article/supplementary materials, further inquiries can be directed to the corresponding author/s.The studies involving human participants were reviewed and approved by exemption 4 status by the Medical University of South Carolina Institutional Review Board. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.Conceptualization, DR, DS, and PA; methodology, DR, DS, and PA; software, DR, DS, PA; validation, DR and PA; formal analysis, DR and PA; investigation, DR and PA; resources, HN, GS, RD, AM, and PA; data curation, DR, and PA; writing – original draft preparation, DR and PA; writing – review and editing, DR, PA, RD, YP, DS, and HN; visualization, DR and PA; supervision, PA; project administration, PA; funding acquisition PA. All authors have read and agreed to the published version of the manuscript.PA appreciates support by NIH/NCI R21 CA240148, R01 CA253460 and in part by pilot research funding from the Hollings Cancer Center Support Grant from NIH/NCI P30 CA138313 at the Medical University of South Carolina. DR is grateful for support from NIH/NIGMS R25GM072643. Additional support to RD provided by the South Carolina Centers of Economic Excellence SmartState program. The MUSC Imaging Mass Spectrometry Research Resource is supported in part by the NIH/NIDDK Digestive Disease Research Core Center P30DK123704 and is a division of the Mass Spectrometry Facility is supported by the University and P20GM103542 (NIH/NIGMS).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


This study aimed to investigate the important predictors related to predicting positive mammographic findings based on questionnaire-based demographic and obstetric/gynecological parameters using the proposed integrated machine learning (ML) scheme. The scheme combines the benefits of two well-known ML algorithms, namely, least absolute shrinkage and selection operator (Lasso) logistic regression and extreme gradient boosting (XGB), to provide adequate prediction for mammographic anomalies in high-risk individuals and the identification of significant risk factors. We collected questionnaire data on 18 breast-cancer-related risk factors from women who participated in a national mammographic screening program between January 2017 and December 2020 at a single tertiary referral hospital to correlate with their mammographic findings. The acquired data were retrospectively analyzed using the proposed integrated ML scheme. Based on the data from 21,107 valid questionnaires, the results showed that the Lasso logistic regression models with variable combinations generated by XGB could provide more effective prediction results. The top five significant predictors for positive mammography results were younger age, breast self-examination, older age at first childbirth, nulliparity, and history of mammography within 2 years, suggesting a need for timely mammographic screening for women with these risk factors. Breast cancer is the most prevalent cancer in women worldwide and is also the leading cause of cancer-related deaths in women . The resIn Taiwan, the government has promoted biennial mammograms for women aged 50–69 since 2004 and expanded the recommendation in 2009 to include women aged 45–69. The screening program was further extended in 2010 to include high-risk women aged 40–44  are modiDespite improvements in health delivery systems, barriers to adherence to mammography screening may also include personal factors such as age, lack of knowledge of the risk factors, lower economic status, and underlying chronic disease ,8,10. ThThe proposed integrated ML scheme combines the benefits of two well-known ML algorithms, namely, least absolute shrinkage and selection operator (Lasso) logistic regression and extreme gradient boosting (XGB), to generate complete and adequate model prediction and important risk factor identification results. XGB and Lasso methods are both widely and successfully used techniques in breast cancer/mammography researches ,18,19,20This study retrospectively reviewed the risk factor questionnaires completed by women who participated in a national mammographic screening program at a single tertiary referral hospital in northern Taiwan  between January 2017 and December 2020. The questionnaire and survey process were uniformly designed and set by the Ministry of Health and Welfare in Taiwan. We retrieved information from the medical records of the participants. This information includes age, age at menarche, body height, body mass index (BMI), education level, history of significant diseases, experience of breast self-examination and mammography within the preceding 2 years, history of breast surgery, age at first childbirth, parity, breastfeeding, reproductive lifespan, age at initiation and duration of hormone replacement therapy, age at initiation and duration of oral contraceptive use, and the number of relatives with confirmed breast cancer. Mammograms of the participants were also recorded.All women who underwent the national mammography screening program and completed a risk factor questionnaire during the study were eligible for the current study. Exclusion criteria were (1) participants with body weight below 35 kg or over 120 kg, (2) questionnaires with illogical data  or incomplete information, and (3) history of breast cancer. The study protocol and procedure were reviewed and approved by the Research Ethics Review Committee of Shin Kong Wu Ho-Su Memorial Hospital, which also waived the requirement for informed consent from the participants before the routine examination procedure (No. 20210703R). Out of a total of 21,384 questionnaires collected from the participants before their mammographic screening during the study period, those completed by 16 women with a body weight below 35 kg or over 120 kg, 133 questionnaires with illogical data, and 2 questionnaires with missing data were excluded. Finally, we used data from 21,107 questionnaires to analyze in the current study .To investigate the associations between participants’ characteristics and mammographic findings, 18 patient variables were assigned as the predictor variables. These are X1: age, X2: body height, X3: age at menarche, X4: body mass index (BMI), X5: education level, X6: history of major diseases, X7: breast self-examination, X8: mammography within the preceding 2 years, X9: history of breast surgery, X10: age at first childbirth, X11: parity, X12: breastfeeding, X13: reproductive lifespan, X14: age at starting hormone replacement therapy, X15: duration of hormone replacement therapy, X16: age at starting oral contraceptive therapy, X17: duration of oral contraceptive use, and X18: number of relatives with confirmed breast cancer. The mammographic findings (Y), categorized as either negative or positive based on the need for this study, were used as the target variables. The former were defined as mammograms without anomalies and those showing benign lesions  categories 1 and 2, respectively). The latter referred to “need additional imaging or prior examinations” (BIRADS 0), “probably benign” (BIRADS 3), “suspicious” (BIRADS 4), “highly suggestive of malignancy” (BIRADS 5), and “known biopsy-proven” (BI-RADS 6).For the current study, the education level (X5) was divided into five categories: primary school, lower secondary school, upper secondary school, university, and postgraduate. The history of major diseases (X6) was divided into three categories: without major diseases, with benign comorbidity, and cancer other than breast cancer. There were three categories of breast self-examination (X7): negative self-examination results; never performed self-examination; and detected mass, pain, or tenderness during self-examination. There were four categories of age at first childbirth (X10): below 21, between 21 and 34, greater than or equal to 35, and did not experience childbirth. Parity (X11) was divided into five categories from never to more than or equal to four times. Breastfeeding (X12) was divided into three categories: nulliparous, not breastfeeding, and breastfeeding. Reproductive lifespan (X13), the time from the onset of menarche to the date of menopause or the date of examination for those who were premenopausal, was divided into five categories: below or equal to 24, between 25 and 29, between 30 and 34, between 35 and 39, and equal to or over 40 years. There were six categories regarding the age of starting hormone replacement therapy (X14): less than 30, between 30 and 39, between 40 and 49, between 50 and 59, greater than or equal to 60, and those who did not receive hormone replacement therapy. For the duration of hormone replacement therapy (X15), there were three categories: those who did not receive hormone replacement therapy, those who underwent therapy for less than 5 years, and those being treated for more than or equal to 5 years. Focusing on the age at which oral contraceptives were started (X16), the three categories included less than or equal to 25, greater than 25, and never received oral contraceptives. The duration of oral contraceptive use (X17) comprised three categories: those who did not receive contraceptives, those being treated for less than or equal to 5 years, and those who underwent treatment for more than 5 years. The number of relatives with confirmed breast cancer (X18), which refers to the number of relatives who had breast cancer regardless of age, was classified into three categories: those who did not have a relative with breast cancer, those who had one relative, and those who had more than or equal to two relatives with confirmed breast cancer. A binary outcome (yes or no) was assigned to the parameters of mammography within the preceding two years (X8) and a history of breast surgery (X9).This study proposes an integrated ML scheme that utilizes the advantages of Lasso and XGB methods to construct predictive models and identify important predictor variables for predicting mammographic anomalies in high-risk individuals. XGB is implemented under the gradient-boosting framework, designed to be highly efficient, flexible, and portable. It belongs to a broader collection of tools under the umbrella of the distributed ML community and is a research project started by Chen . LogistiThe classes of the target variable  were skewed, and most data contained negative cases. Training the model with imbalanced data may cause the model to spend the most time learning the most negative cases and miss a large amount of information provided by the positive cases. This study utilized a bootstrap-based undersampling technique to address the imbalance issues. The main concept of the undersampling technique is to balance the data by decreasing the amount of the majority class (negative cases in this study) until the achievement of the desirable proportion between both classes . The equThere are two stages in the modeling of the proposed scheme. In modeling stage I, Lasso logistic regression was fitted with all variables  to calculate the confidence interval (CI) of the performance index area under the receiver operating characteristic (ROC) curve (AUC) for the method. Calculating the CI of the AUC can indicate the stability of the model’s performance. Simultaneously, XGB was also fitted with all variables in this stage to obtain the variable importance rankings, which were used to generate the variable combinations. It is important to remember that ML methods can highlight multivariate interaction effect information. Thus, the variable rankings obtained from the ML method in stage I may provide more information. Furthermore, using stepwise algorithms to generate stepwise-based ranked variable combinations (SRVCs) to model different predictive models makes it easier to evaluate the impact of the different SRVCs on the AUC values of the models. SRVCs consist of the top-ranking variable as the first combination and the top-two ranking variables as the second combination. To generate SRVCs based on XGB in stage I, the variable importance rankings obtained from XGB generate XGB-based SRVCs . In the stage II modeling of the proposed scheme, to obtain adequate prediction and beneficial risk factor identification results, Lasso logistic regression was used for XGB-SRVCs to generate different predictive models. The AUC of each combination of XGB-SRVCs was compared to the CI of the AUC of the Lasso logistic full model. Among all XGB-SRVCs, the most suitable variable combination was identified based on the lower bound of the CI of the AUC of the Lasso logistic full model, that is, among all variable combinations that exceed the lower CI of the AUC of the Lasso logistic full model, the combination that contains the fewest variables is the most suitable. Finally, a logistic model was developed with the selected suitable variable combination of XGB-SRVCs to reveal the effect direction of important predictor variables.The experiment was implemented in Python version 3.8.8   and JupyThe model results can be improved by using the balancing techniques before utilizing Lasso and XGB methods. The table shows that the sensitivity and specificity of the Lasso and XGB methods with undersampling were 60.97, 58.64, 63.00, and 52.87, respectively, whereas those with oversampling were 60.67, 58.89, 87.65 and 15.26, respectively. Meanwhile, using the same concept as the XGB-SRVCs, the Lasso-SRVCs are also generated according to the variable importance rankings of Lasso . Figure The Lasso model based on the five most important variables can generate the following logistic equation which can be used to predict the mammographic anomalies of a high-risk individual: Despite the popularity of mammography as a screening tool for breast cancer, no reports have focused on the risk factors associated with mammographic findings. In contrast to most previous studies that focused on the identification of the risks factors associated with established breast cancers, the current study investigated the risk factors significantly related to positive mammographic findings based on a simple questionnaire so that an increased level of attention can be paid to the high-risk population to improve the detection rate of breast cancer as well as allow early advanced diagnostic studies and treatments. In addition, two mixed machine learning approaches (XGB-SRVCs and Lasso-SRVCs) were compared to identify the best method that could more effectively predict positive mammographic findings. This is the first study that addresses this issue by incorporating demographic and clinical information into mammographic findings through an ML scheme. This study used information from questionnaires and ML analysis to assess the associations between 18 factors and mammographic screening results. Our findings showed that XGB feature rankings were more efficient than those of Lasso. Meanwhile, age, breast self-examination, age at first childbirth, parity, and mammography within 2 years were the top five significant variables predicting a positive result for mammographic screening for breast cancer. Therefore, our results may have significant implications for clinical practice.Our results showed that age was the most crucial predictor of mammographic findings, as reflected by the negative correlation between age and positive mammographic findings. Compared with the United States, a previous investigation reported that breast cancer in Taiwan is diagnosed at a younger age, with a higher and increasing incidence . HoweverAge at first childbirth (X10) was the third most important variable for predicting positive mammographic results in this study. Our findings demonstrated that early age at first childbirth was associated with a reduced risk of positive mammography findings. Previous studies have consistently shown a protective effect of first full-term birth at an early age against the development of breast cancer , contribThe fourth most important risk factor is parity (X11). Previous studies have shown that nulliparous women are at a higher risk of breast cancer than parous women, with the increased estimated relative risk of the former ranging from 1.2 to 1.7 compared with the latter . In contThe fifth risk factor in the present study was the participants receiving mammography within the preceding 2 years (X8). This finding may be partially attributed to a higher probability of pre-existing lesions or abnormal mammographic results requiring follow-up examinations in this population than in those without previous breast anomalies. In addition, individuals with higher screening adherence, such as those with a higher education level, have exhibited an increased incidence of breast cancer, but a decreased mortality ,49.Although various risk factors for breast cancer among Asian women have previously been reported, including early menarche, late menopause, family history of breast cancer, high body mass index, being overweight, and obesity , this stBy analyzing 18 factors possibly associated with the risk of positive mammography screening for breast cancer using the proposed integrated ML scheme, we identified younger age, breast self-examination, older age at first childbirth, nulliparity, and history of mammography within the preceding 2 years as the top five significant variables for predicting positive mammography results. Our findings suggest a benefit for women with the identified risk factors for timely mammographic screening.


Objective The study aimed to characterize the clinical, histological, and immunohistochemical profile of women with invasive breast cancer, according to the risk for Hereditary Predisposition Breast and Ovarian Cancer Syndrome in a Brazilian population.Methods This is a retrospective study performed from a hospital-based cohort of 522 women, diagnosed with breast cancer treated at an oncology referral center in the Southeast region of Brazil, between 2014 and 2016.Results Among the 430 women diagnosed with invasive breast cancer who composed the study population, 127 (29.5%) were classified as at increased risk for hereditary predisposition to breast and ovarian cancer syndrome. There was a lower level of education in patients at increased risk (34.6%) when compared with those at usual risk (46.0%). Regarding tumor characteristics, women at increased risk had higher percentages of the disease diagnosed at an advanced stage (32.3%), and with tumors > 2cm (63.0%), with increased prevalence for both characteristics, when compared with those at usual risk. Furthermore, we found higher percentages of HG3 (43.3%) and Ki-67 ≥ 25% (64.6%) in women at increased risk, with prevalence being about twice as high in this group. The presence of triple-negative tumors was observed as 25.2% in women at increased risk and 6.0% in women at usual risk, with the prevalence of absence of biomarkers being 2.5 times higher among women in the increased risk group.Conclusion From the clinical criteria routinely used in the diagnosis of breast cancer, the care practice of genetic counseling for patients at increased risk of hereditary breast cancer in contexts such as Brazil is still scarce. Breast cancer has a multifactorial etiology associated with hormonal, reproductive, genetics, lifestyle-related factors, and it is more frequent in post-climacteric women.Molecular biology has allowed the investigation of several genes associated with carcinogenesis, including the analysis of gene expression profiles of breast cancers, which makes it possible to correlate them with disease prognosis and with response to treatment.i-67 has an increased expression in breast tumors that may be associated with a higher risk of recurrence and worse prognosis.Some characteristics of the breast tumor are essential for the clinical follow-up of the patients. The cell proliferation marker KBRCA1andBRCA2genes.The hereditary condition is the cause identified in 10 to 25% of breast and ovarian cancers, involving mutations in genes of high and moderate penetrance, such as theFurthermore, the NCCN (2020)Therefore, frequent reviews of the recommendation guidelines to assess Hereditary Breast and Ovarian Cancer (HBOC) syndrome have been performed to advance the diagnosis and management of women with HBOC syndrome, which has enabled the incorporation of new and more comprehensive criteria.In Brazil, there are few studies on the genetic profile of patients and family members at risk for HBOC syndrome.This is a retrospective study, performed from a hospital-based cohort, consisting of 522 women diagnosed with breast cancer between 2014 and 2016, and treated at an oncology referral center in the Zona da Mata of Minas Gerais, in the southeastern region in Brazil.Sociodemographic, clinic, and pathological data were extracted from medical records, and additional information was obtained through interviews with patients, as well as from analysis of pathological anatomy and immunohistochemical test results.Through the criteria used to assess hereditary breast cancer risk, recommended by the NCCN (2020),n = 42) and those without information about at least one of the biomarkers of the tumor for estrogen, progesterone, and HER-2 (n = 50).The study excluded women with in situ breast cancer . Considering the relationship between the increased expression of Ki-67 and HG3, according to Gong et al.The characterization of the pathological profile of breast carcinoma was performed using the following variables: stage at diagnosis , histological type , tumor size , lymph node involvement, histological grade , Kindex < 2%, ≥ 25%.2), and the significance level considered was 5%. For these variables were estimated the prevalence ratios (PR) and the respective 95% confidence interval (95% CI). The analysis was performed using the STATA  software, version 16.0.From analyses stratified according to risk for hereditary breast cancer, the mean and respective 95% confidence interval (95% CI) for age at diagnosis, as well as absolute numbers and percentages for categorical variables were presented. The difference in the distribution of categorical variables according to the risk for hereditary breast cancer was assessed using the chi-square test , CAAE: 5342919.0.0000.5147.Among the 430 women diagnosed with invasive breast cancer who composed our study population, 127 29.5%) were classified as at increased risk for HBOC Syndrome, according to the criteria recommended by the NCCN (2020)..5% were The majority of women were white (72.3%), with more than eight years of education (55.8%), and users of the public health service (60.5%). There was a lower level of education in patients at increased risk (36.4%) when compared with those considered to be at usual risk (46.0%)  .i-67 < 25% (48.1%) (Most of the investigated patients did not mention a history of breast cancer in the family (69.5%). However, for women at increased risk, 39.4% had a positive history of cancer in up to third-degree relative. When we considered only first-degree relatives with breast cancer in the group of women at increased risk (20.5%), a 50% higher prevalence was found in the increased risk group than in the usual risk group . Regarding anatomopathological characteristics of the population of the study, it was observed that 74.4% had early-stage/intermediate type, 82.3% had invasive ductal histological type, tumor size > 2 cm (54.2%), non-involved lymph nodes (50.9%), histological grade 2 (37.7%), and K(48.1%) .i-67 index. Women at increased risk had higher percentages of diagnosed disease at an advanced stage (32.3%), with tumors > 2cm (63.0%), and an increased prevalence (∼1.4 times) for both characteristics, when compared with those at usual risk.There was a significant difference between the groups regarding staging, tumor size, histological grade, and Ki-67 ≥ 25% (64.6%) were found, with a prevalence about twice as high in this group . On the other hand, in women at usual risk, higher percentage of more differentiated tumors was identified, with HG2 (38.0%) and Ki-67 < 25% being intermediate or low (54.8%).Also in women at increased risk, higher percentages of HG3 (43.3%) and KThere was no significant difference in the distribution of histological types between groups. The lymph node involvement was 56.0% in women at increased risk, and 46.2% in women at usual risk, although it was also statistically insignificant .p < 0.01), with a prevalence about two times higher in the increased risk group. Higher percentages of HER-2 expression negativity were also observed in both groups , with no significant difference between groups (Regarding estrogen and/or progesterone hormone receptors (HR), an absence of HR expression was found in 30.0% of the women at increased risk, compared with 11.0% of women at usual risk ( groups .The biomarkers (HR and/or HER-2) used to classify breast cancer subtypes through the immunohistochemical technique had a percentage of 88.4 in the study population. However, its distribution was significantly different between the groups, with an absence of expression of biomarkers, that is, triple-negative tumors in 25.2% of women at increased risk, and 6.0% in women at usual risk, with a prevalence of absence of biomarkers 2.5 times higher among women in the increased risk group.The other variables related to tumor characteristics did not show a significant difference in distribution according to the groups considered .i-67 ≥ 25%, absents biomarkers, and absents HR for each group considered.i-67 ≥ 25% and absent biomarkers, a percentage of 83.3 versus 16.7% was observed in the increased and usual risk groups, respectively. Higher percentages were also observed in the increased risk group when Ki-67 ≥ 25% and absent HR (66.7%) were compared simultaneously to the usual risk group (33.3%).When considering KWomen in the increased risk for hereditary breast cancer group represented 29.5% of the study population and had a mean age of 42 years at diagnosis, which is far below the mean age of the group considered as usual risk (62 years), according to the results found in other studies.BRCA1andBRCA2genes, which reinforces the benefit that these women would have when performing an improved screening.Between 10 to 25% of breast and ovarian neoplasms are considered hereditary and will manifest earlier in women with some risk factors related to this heredity, that is, history cases of breast, ovarian, and male breast cancers due to the detection of some genetic alteration, especially in theIn our study, the frequency of women at increased risk for clinical criteria for HBOC syndrome was higher than reported in the literature, which generally addresses Caucasian populations from Europe and the United States. Moreover, it should be noted that divergence of some criteria and guidelines between referral institutions can make it difficult to reach a consensus on the identification of eligible patients for investigation of hereditary cancer.In Brazil, access to risk evaluation for hereditary cancers and genetic screenings is limited. Brazilian experts propose recommendations to expand early diagnosis, risk management, and treatment of hereditary breast cancer, as well as provide epidemiological information about the Brazilian population. The identification of women at increased risk for hereditary breast cancer allows patients and their physicians to assess the available options to mitigate the risk of developing breast cancer, including more frequent screening, chemoprophylaxis, and even prophylactic mastectomy.For hereditary breast cancer, family history is the most accepted risk factor among the scientific community, with a risk increase of 2 to 4 times in the presence of family members affected by breast cancer, especially if they have been diagnosed at an early age.Regarding sociodemographic characteristics, white skin color was the most prevalent among the women evaluated. However, there was a higher number of non-white women in the increased risk for hereditary breast cancer group. It is noteworthy that the worst prognostic features for breast cancer, such as younger age, late diagnosis, and triple-negative tumors, are more frequent in black women.Nevertheless, the study performed by Fejerman et al. (2009)p = 0.05) may highlight the relationship between educational level and socioeconomic status—which also interferes with greater access to information about the risk factors that permeate the development of cancer—and access to preventive measures, particularly important in women with hereditary predisposition to breast cancer.The higher education level predominant in the group of women at increased risk , as well as Ki-67 ≥ 25% (p < 0.01), compared with the usual risk group. The literature points to higher HG and Ki-67 values in women with hereditary predisposition.The histological grade (HG) of the invasive carcinomas is an important feature and must be evaluated to guide the therapeutic approach and predict the prognosis.BRCA1andBRCA2(CIMBA), HG3 tumors were identified in 77.0% and 50.0% of women with mutations in theBRCA1andBRCA2genes, respectively.In the study of Mavaddat et al. (2012),Newman (2015)p < 0.01), which reinforces the premise that women at risk for hereditary predisposition are more prone to estrogen receptor negativity.Regarding hormone receptors (HR), the higher frequency of cases with absence HR was observed in the increased risk for hereditary breast cancer group, compared with the usual risk group  also corroborates findings in the scientific literature. In the meta-analysis performed by Tun et al. (2014),BRCA1andBRCA2genes (51.1%). Moreover, according to data presented by Young et al. (2009),As observed in the study by Fernandes et al. 2019),,BRCA1ai-67 ≥ 25% in triple-negative tumors (83.3% vs. 16.7%), Ki-67 ≥ 25% and absence of hormone receptors (66.7% vs. 33.3%). The data presented suggests that a high Ki-67 proliferation index with the absence of expression of biomarkers could be clinical indicators of increased risk for HBOC.When evaluating the simultaneous occurrence of some characteristics in the categorized groups, we sought to verify that the information routinely collected at the time of diagnosis could favor the identification of women at increased risk for HBOC. Higher percentages were observed in the increased risk group, when compared with those of the usual risk group, regarding the presence of Ki-67 and HG in the prognostic of different subtypes of breast cancer. The results indicated that Ki-67 expression was significantly associated with HG in all breast cancer patients, and that patients with increased Ki-67 or HG3 had reduced recurrence-free survival and a worse prognosis.In a retrospective analysis performed by Liang et al. (2020),i-67 score increased the risk of breast cancer mortality by 2.7 times.It is important to highlight that these characteristics alone provide relevant information at the time of the diagnosis. This was demonstrated in the study performed by Pérez-López et al. (2016),Most of the Brazilian studies published so far regarding HBOC syndrome have been performed with specific populations, that is, with young women diagnosed with breast cancer and/or with an investigation of specific gene regions.The identification of patients and family members at risk for hereditary cancer is essential, as the cumulative vital risk is much higher in affected people. This identification makes it possible to know the risk that family members are exposed to, through screening measures that allow for an early diagnosis and the implementation of appropriate follow-up and treatment protocols, which can improve the outcome of the disease in patients and their families.A study conducted in the United States found that, in one year, only 8% of 603 women referred for genetic counseling, according to the NCCN criteria, attended the exam. This exemplifies how genetic counseling is still underused, even in developed countries.BRCAgenes, which would enable a better characterization of the increased risk for hereditary breast cancer, and the associations raised. It is worth mention the high cost of the test to assess pathogenic mutations in theBRCA1andBRCA2genes, which makes its use very restricted in countries with limited sources, such as Brazil.As a limitation of the study, we emphasize that genetic screening was not performed in the investigated population, particularly in relation to theIn this regard, information on tumor histopathology, routinely collected at the time of diagnoses, such as histological grade, the status of estrogen, progesterone, or HER-2, as well as identification of cell proliferation markers, can be incorporated into the criteria already recommended for investigation of the risk of hereditary breast and ovarian cancer, aiming to strengthen and expand the adoption of a practical strategy for genetic evaluation in patients with breast cancer. This becomes particularly important for countries in which specialized genetic services are scarce, financial resources for health are limited and concentrated in more developed regions, and where public and private health systems have major restrictions on coverage of such molecular analyzes, such as in Brazil and other Latin American countries.i-67 ≥ 25%, absence of hormone receptors, and HER-2, and family history of breast cancer in women classified in this study as at increased risk for HBOC syndrome. Based on the clinical criteria routinely used in the diagnosis of breast cancer, this study collaborated to guide the care practice of genetic counseling for patients at increased risk of hereditary breast cancer in contexts such as in Brazil. Therefore, it guides the indication of women to undergo genetic evaluation and who, consequently, could benefit from these more specific therapies. It also contributes to the risk management of their families, enabling the application of specific preventive measures.The results of this study allow the characterization of the clinical, histological, and immunohistochemical profile of women with breast cancer in a Brazilian hospital-based cohort, according to the risk of hereditary breast cancer. The findings show the possibility of considering, even if only in a complementary way, the frequency of some of these characteristics to help identify and manage women with clinical suspicion of hereditary breast cancer. In this regard, there is a higher frequency of tumors with HG3, K