Four analytical themes were generated. Women appraise their risk of breast cancer through comparison with their risk of other familial diseases. Clinically derived risk estimates were understood in relation to pre-conceived risk appraisals, with incongruences met with surprise. Family history is relied upon strongly, with women exploring similarities and differences in attributes between themselves and affected relatives to gauge the likelihood of diagnosis. Women at increased risk reported living under a cloud of inevitability or uncertainty regarding diagnosis, resulting in concerns about risk management. Women hold stable appraisals of their breast cancer risk which appear to be mainly formed through their experiences of breast cancer in the family. Healthcare professionals should explore women’s personal risk appraisals prior to providing clinically derived risk estimates in order to address misconceptions, reduce concerns about inevitability and increase perceived control over risk reduction.This review aimed to synthesise qualitative research on how women notified that they are at increased risk of breast cancer view their risk. Five electronic databases were systematically reviewed for qualitative research investigating how women who have received an increased breast cancer risk estimate appraise their risk status. Fourteen records reporting 12 studies were included and critically appraised. Data were thematically synthesised Since the inception of UK Family History Risk and Prevention Clinics (FHRPCs) in the late 1980s, women with a family history of breast cancer have been able to have their risk of developing the disease estimated. Risk is estimated through combining multiple risk factors, including family history of breast and other relevant cancers (ovary), hormonal and reproductive factors, as well as health related behaviours, i.e. smoking and alcohol consumption. In the UK the National Institute for Health and Care Excellence (NICE) clinical guidelines for familial breast cancer  is something I take for migraines because it allows me to function when I get my migraine headaches. I take one and it curbs the headache enough that I can continue to work or not be impaired…and the risks [migraine v. breast cancer] just aren’t the same.”  postmenopausal they explained that the risk wouldn’t be that high….But these are just statistics and I can’t really go by statistics, you know? All because it says I may not be, you know, at average risk or you’re a little higher than average risk; that doesn’t mean anything […] so I can’t really say I really trust the number that they gave me, you know?”  help you to feel you are in control of the situation rather than the situation is in control of your life so I think it is very important to do things, positive things, to make you feel you are doing all you can, you know, not to have it (breast cancer).”  than the knowing. If you know, then you can deal with it a lot better than not knowing… they can’t guarantee me [anything].” [thing].” Other women described living in a perpetual state of uncertainty. For these women not knowing when or if they would ever receive a diagnosis of breast cancer was anxiety inducing:dangerous as women may cause themselves undue distress worrying about something that may never happen It can be inferred from the present findings that for some women breast cancer risk is not seen in isolation of other disease risks, especially if multiple diseases run in the family. In the FHRPCs HCPs are focused on providing women with the most salient information about their risk, so that accurate risk appraisals can be made to encourage changes in risk-related behaviours, as well as to aid informed decision making about preventative action. However, in this same consultation women may be appraising their breast cancer risk against that of other diseases present in the family, drawing on their experiences to assess where their priorities for monitoring risk should lie. This may mean that for some breast cancer risk is not an immediate priority, potentially affecting their motivation to engage in preventative behaviours. For these women a multiple disease prevention programme (MDPP) whereby preventative behaviours  associated with reducing the risk of multiple diseases may be more appropriate than a prevention programme linked to breast cancer risk alone , 49. HowFamily history is a significant component of women’s breast cancer risk appraisals, although this is less important on a population basis. Specifically women look for comparisons between the self and affected relative, i.e. comparing breast size to gage the likelihood of diagnose. It would be beneficially for HCPs to explore misunderstandings such as this in clinically settings to facilitate more accurate risk appraisals. One method to improve understanding and dispel myths about the link between breast size and breast cancer risk might be to discuss the issue of breast density. Breast density notification in consultations where images from mammography are shown to illustrate the differing levels of fatty tissue to fibro-glandular tissue may improve women’s understanding, moving them away from inaccurate ideas about breast size. For example, providing medical images in the communication of disease risk has been found to motivate risk reducing behaviours . TherefoFindings from this review also highlight incongruences between ‘objective’ clinically derived risk estimates and women’s personal breast cancer appraisals. In some cases this misalignment leads to distrust in the clinical estimates provided. A distrust of this kind may cause women to feel dubious about risk reducing behaviours and prevention advice. Similarly, this review found that the majority of women who received an increased breast cancer risk estimate feel that diagnosis is inevitable, leading to thoughts that risk cannot be controlled or a diagnosis prevented. It is important therefore for the HCP to acknowledge how women appraise their risk and identify where the clinical risk estimate may differ from subjective understandings of risk. Identifying where incongruences lie may improve the accuracy of these risk appraisals, as well as instil trust in the estimate and prevention advice provided. One way of initiating such conversations could be to employ risk perception instruments such as the Tripartite model of risk perception , which cThis comprehensive review of the literature indicates that there is a discrepancy between how healthcare professionals communicate breast cancer risk estimates and how women appraise breast cancer risk. Future research should investigate how common these discrepancies are and whether these vary between healthcare professionals communicating risk results to women. Additionally, an investigation into the implications of healthcare professional-patient incongruences, for example regarding uptake of preventive options to reduce breast cancer risk would also be helpful.Since the publication of the included studies breast cancer risk prediction models have improved, with the inclusion of new strong independent risk factors, breast density and a polygenic risk score (PRS) –56. It iRisk prediction models which include a PRS and breast density are likely to be formally introduced into clinical settings in the near future. It is therefore expected that women under follow-up at FHRPCs will receive updated breast cancer risk estimates. Updated estimates could result in women experiencing a change to their risk and risk management, for example their entitlement to more frequent screening. It is currently unknown how women react to a change in their breast cancer risk. However from the present review it is evident that women question clinically derived risk estimates when they do not validate existing risk appraisals. Future research should explore how and if risk appraisals are adapted when women receive an updated breast cancer risk estimate, including whether there is any psychological impact. An exploration as to whether a change in breast cancer risk and entitlement to preventative management effects the perceived trustworthiness of risk estimates would also be beneficial.Clinically derived risk estimates are evaluated against personal appraisals of risk, with women shocked and dubious about results when results misalign with pre-existing risk appraisals. Those at increased risk appear to view the development of breast cancer as an inevitability or live in uncertainty, causing women to question whether breast cancer can be prevented or risk reduced. The findings of this review have practical value for HCPs by increasing their awareness of how women think about breast cancer risk, which may result in more effective and meaningful communication in clinical settings.Supplementary Material


There is a paucity of data on the spectrum and prevalence of pathogenic variants among women of African ancestry in the Northeast region of Brazil.We performed BROCA panel sequencing to identify inherited loss-of-function variants in breast cancer susceptibility genes among 292 Brazilian women referred to a single institution cancer risk assessment program.BRCA1, BRCA2, PALB2, and TP53. Pathogenic variants were also found in the ATM, BARD1, BRIP1, FAM175A, FANCM, NBN, and SLX4 genes in 6.4% of the affected women. Four recurrent pathogenic variants were detected in 11 patients of African ancestry. Only one unaffected woman had a pathogenic variant in the RAD51C gene. Different risk assessment models examined performed well in predicting risk of carrying germline loss-of-function variants in BRCA1 and/or BRCA2 in breast cancer cases.The study included a convenient cohort of 173 women with invasive breast cancer (cases) and 119 women who were cancer-free at the time of ascertainment. The majority of the women self-reported as African-descended (67% for cases and 90.8% for unaffected volunteers). Thirty-seven pathogenic variants were found in 36 (20.8%) patients. While the spectrum of pathogenic variants was heterogeneous, the majority (70.3%) of the pathogenic variants were detected in high-risk genes The high prevalence and heterogenous spectrum of pathogenic variants identified among self-reported African descendants in Northeast Brazil is consistent with studies in other African ancestry populations with a high burden of aggressive young onset breast cancer. It underscores the need to integrate comprehensive cancer risk assessment and genomic testing in the management of newly diagnosed Black women with breast cancer across the African Diaspora, enabling improved cancer control in admixed underserved and understudied populations.The online version contains supplementary material available at 10.1007/s10549-022-06560-0. Breast cancer is the most commonly diagnosed cancer among women worldwide . This noBRCA1, BRCA2, PALB2, and TP53 genes in consecutive women presenting with advanced breast cancer at tertiary hospitals in Nigeria, Cameroon, and Uganda [This rising global burden of breast cancer in low- to middle-income countries demands innovative interventions to accelerate progress in cancer control and prevention. Through genomic analysis of breast cancer predisposition genes, the burden of inherited susceptibility to breast cancer in diverse populations can be better estimated, allowing clinical management and treatment recommendations to be tailored to the needs of high-risk women and their families . With add Uganda , 8.Black women across the African Diaspora have the worst outcomes from breast cancer of all ethnic/racial groups. Given the reported high prevalence of aggressive breast cancer in young Brazilian women , we sougBetween 2008 and 2015, we recruited women with breast cancer referred by their primary care physicians to the Cancer Risk Assessment Program of the Serviço de Oncogenética of Laboratório de Imunologia e Biologia Molecular (ICS-UFBA). This public laboratory service is part of the Brazilian National Network of Hereditary Cancer. Women with breast cancer are usually referred to this service from private and public clinics and hospitals. Since this service is provided by a public entity, counseling was free of charge and more than 90% of patients were willing to participate in the research. To develop a reference control panel to improve interpretation of our findings, we recruited a cohort of cancer-free women who are not the relatives of the cases but were undergoing routine laboratory tests  in the same laboratory between 2014 and 2015.All participants signed informed consents, and data regarding their epidemiological and clinical profiles were collected along with questionnaires administered by a research coordinator. The research protocol #1.383.884 was approved by the Brazilian National Committee of Ethics in Research , the University of Chicago, and the University of Washington, where the sequencing was performed.ATM, ATR, BAP1, BARD1, BRCA1, BRCA2, BRIP1, CDH1, CHEK1, CHEK2, CTNNA1, FAM175A, FANCM, GEN1, MRE11A, NBN, PALB2, PPM1D, PTEN, RAD51B, RAD51C, RAD51D, RECQL, RINT1, SLX4, STK11, TP53, and XRCC2.The genomic DNA was extracted from peripheral blood using a commercial kit, the DNeasy® blood and tissue kit . The quality and quantity of the genomic DNA was assessed with 2% agarose gel electrophoresis analysis and the Quant-iT™ PicoGreen™ dsDNA Assay Kit . A total of 28 susceptibility genes were analyzed in the BROCA panel. Genes sequenced included established breast cancer genes of both high and moderate penetrance, and genes that have been suggested as candidate breast cancer genes, with varying levels of evidence: Paired-end reads were mapped to the human genome reference hg19. Subsequently, single-nucleotide variants and small insertions and deletions were called as previously described in detail , 11, andBRCA1 and BRCA2 mutational profiles and clinical and epidemiological data.Descriptive analysis was performed using Epi Info™ software  and SPSS® . Given the limited sample size of the study, we performed an exploratory analysis to estimate performance of different breast cancer risk assessment tools using online calculators: the Myriad Risk calculator , the PENOver 90% of the study participants were from the Northeast region of Brazil, particularly from the State of Bahia. About 67.0% of the breast cancer cases self-reported as African-descended (Black), with enriched family history of cancer, including breast cancer (~ 65%) Table . The meaBARD1:c.1921C>T and BRCA2:c.3860delA  carried 29 pathogenic variants in ATM, BARD1, BRCA1, BRCA2, BRIP1, FAM175A, FANCM, PALB2 and TP53 genes. The majority of pathogenic variants were found in BRCA1 and BRCA2 . Four recurrent loss-of-function variants were detected in 11 African-descended breast cancer cases, BRCA1:c.3331_3334delCAAG, BRCA1:c.211A>G, BRCA2:c.1389_1390delAG and PALB2:c.1671_1674delTATT , with BRCA1 and BRIP1 being the most commonly mutated genes  (Table Thirty-seven loss-of-function variants (30 distinct variants) were found in 36 breast cancer patients, one of whom carried both BRCA1 and BRCA2 carriers were HR- and HR+, respectively [BRCA1 and BRCA2 mutational spectrum of the study population compared with other Black women across the African Diaspora and White women in the literature [Congruous with previously published annotations, we did not observe any African-specific pathogenic variants, and the majority of tumors arising in ectively  . The data revealed that these risk models can discriminate high-risk from low-risk women , supporting the use of these models in this population.Using different risk models for pathogenic Little is known about the genetic susceptibility to breast cancer of African-descended Brazilian women, an understudied population. As there is a high degree of genetic admixture among Brazilian populations –25, we sBRCA1 and BRCA2 were the most frequently mutated genes in breast cancer patients, and their mutation frequencies in women from the Northeast region of Brazil are closer to that in Africans than the reported frequencies in African-Americans and women of European ancestry . Our observation that the BRCA1/2 pathogenic variants found in Blacks in Northern Brazil were not unique to the population agrees with the finding of a previous study by Friebel et al. [BRCA1/2 pathogenic variants in Africans are allelic heterogeneous with low frequencies [. study showed that variants identified in Africans were also reported in non-African populations [Using the validated BROCA panel, we identified 36 distinct pathogenic variants in 30 patients with breast cancer cases and only one pathogenic variant in cancer-free women. As observed in previous studies worldwide , 22, 26,y Cancer , as welly Cancer , 19–22. l et al. . BRCA1/2quencies , 8, 27; ulations . The posPALB2, as well as ATM and BRIP1, each found in 1.7% of the cases. Although the prevalence of pathogenic variants in these genes varies in breast cancer patients of African ancestry [TP53 is the third gene most frequently mutated among breast cancer patients. Among these patients, most carry TP53:c.1010G>A, which has a known founder effect in those regions of Brazil. However, this pathogenic variant was quite rare  among the breast cancer cases from the Northeast region of Brazil in our study  Supplementary Figure 2. BRCA1 and BRCA2 mutational spectrum in breast cancer cases from the Northeast region of Brazil and other populations worldwide. SRAA, self-reported African ancestry.Supplementary file2 (EPS 40 kb) Supplementary Figure 3. Performance of risk prediction models. We divided our study participants into three genomically stratified groups: high-risk cases (who carried pathogenic variants in breast cancer genes), low-risk cases (who did not carry any pathogenic variants), and cancer-free women. (a) The values of AUC of the risk prediction tools improved slightly for discriminating the high-risk cases from low-risk patients. (b) When the high-risk group was compared with low-risk group and cancer-free women, the power of the risk models to discriminate high-risk individuals from low-risk was increased.Supplementary file3 (EPS 70 kb) Supplementary file4 (DOCX 34 kb)Supplementary file5 (DOCX 31 kb)Below is the link to the electronic supplementary material.


Cancer is the second leading cause of death among women in the United States. Previous studies demonstrate a higher prevalence of cancer among female orthopaedic surgeons. This study aimed to provide an updated prevalence of breast and all-cause cancer among female orthopaedic surgeons using a larger and more current study population.We distributed surveys to female orthopaedic surgeons in national orthopaedic specialty societies. Six hundred seventy-two survey responses were collected. We calculated standardized prevalence ratios (SPRs) and 95% confidence intervals (CIs) based on gender-specific, race-specific, and age-specific cancer prevalence statistics in the US population. We compared the distribution of breast cancer risk factors with that of women in the 2018 and 2009 California Health Interview Survey.P < 0.001). The breast cancer prevalence was also higher among orthopaedic surgeons compared with the US female population .Fifty-one of the 672 surveyed surgeons reported a diagnosis of invasive cancer. Twenty reported breast cancer with a prevalence higher among female orthopaedic surgeons compared with the US female population (SPR: 2.89, 95% CI: 2.16 to 3.81, The increased prevalence of breast and all-cause cancer among a larger and more diverse cohort of female orthopaedic surgeons confirms previous studies and provides an update regarding a concerning public health issue within this specialty. Breast cancer is the second leading cause of cancer-related deaths among women.5 Among female orthopaedic, urology, and plastic surgeons, orthopaedic surgeons are the only subspecialty to demonstrate a higher prevalence of breast cancer than expected.6 These previous studies have shown an 85% higher prevalence in all-cause cancer and a 190% higher prevalence in breast cancer among female orthopaedic surgeons compared with the general female population.4-6Previous studies have shown a higher prevalence of breast cancer in female orthopaedic surgeons compared with the general US female population.Previous studies reporting a higher prevalence of breast cancer among orthopaedic surgeons were limited by sample breadth and size and were conducted more than 10 years ago. Thus, this study aimed to report an updated prevalence of all-cause cancer and breast cancer among female orthopaedic surgeons by using a more current, larger, and broader study population. We hypothesized that female orthopaedic surgeons would have a higher prevalence of breast and all-cause cancer than the general US female population.Between February 2019 and February 2020, we contacted 1290 female orthopaedic surgeons through e-mail or the websites of national orthopaedic specialty societies and asked them to complete a survey. Of these surgeons, 672 participated in the study (52% response rate). The surveys were sent to the following orthopaedic specialty societies: the Ruth Jackson Orthopaedic Society (RJOS), Pediatric Orthopaedic Society of North America, Musculoskeletal Tumor Society, Orthopaedic Trauma Association, American Association of Hip and Knee Surgeons Women in Arthroplasty Committee, American Orthopaedic Foot and Ankle Society, American Orthopaedic Society for Sports Medicine, and American Society for Surgery of the Hand.7 The survey was initially developed with a cancer epidemiologist in 2010. It was used in previous studies and subsequently revised and pilot-tested by multiple experts for this study.5 We provided a cover letter explaining the purpose of the survey, as well as a link to the survey. The survey was created in Research Electronic Data Capture, a secure web application used for building and managing surveys online. We used this encrypted survey through qualtrics. The survey participants were contacted through subspecialty societies and RJOS. To increase response rates, surveys were sent again to some society members, following each society's protocol. These societies included RJOS and Arthroplasty Committee, American Orthopaedic Foot and Ankle Society.The survey was based on previous studies and follows the principles for conducting surveys with orthopaedic surgeons described by Sprauge et al.Demographic survey questions collected information regarding age, race/ethnicity, body mass index, smoking history, menstrual and reproductive history, and use of hormones. Professional history questions focused on subspecialty, years in practice, use of fluoroscopy, polymethylmethacrylate (PMMA) use, lead protection, dosimeter use, and training or education on radiation exposure risk. Cancer diagnoses were self-reported based on the following questions: Have you ever been diagnosed with breast cancer? Have you ever been diagnosed with cancer other than basal or squamous cell carcinoma of the skin? What type of cancer were you diagnosed with? When were you first diagnosed with cancer? We also obtained a family history of cancer. This study was approved by the Stanford Institutional Review Board.8 Adult CHIS surveys include questions on demographics and women's health, such as age at first childbirth, number of births, and hormone replacement therapy. Samples from the 2018 and 2009 CHIS were limited to women aged 30 years or older to ensure similarity to the female orthopaedic surgeon data. We used a report on the US female population to obtain the total fertility rate for 2018.9 Both 2018 and 2009 CHIS samples were included because different questions that represented risk factors for breast cancer were asked each year.We obtained descriptive statistics regarding the clinical practice characteristics of female orthopaedic surgeons, including employment history, setting, subspecialty, and occupational radiation exposure, which was estimated by standard fluoroscopy use, minifluoroscopy use, and PMMA use. Breast cancer risk factors were compared between female orthopaedic surgeons and women in the 2018 and 2009 California Health Interview Survey (CHIS). The CHIS is a population-based survey conducted through telephone and is representative of the noninstitutionalized population in households.10 SEER prevalence statistics represent existing and new cancer cases for people who were alive on a certain date. We excluded four cases of cancer (two cases of lymphoma and two cases of thyroid cancer) that were diagnosed more than17 years ago and excluded two diagnoses of basal and squamous cell cancer because these are excluded from SEER. We examined both the total samples of female orthopaedic surgeons and only currently practicing surgeons. Based on their potential for occupational radiation exposure, we categorized the surgeons into two groups: high and low exposure. Surgeons who more frequently imaged thick, bony, or muscular areas  were considered to have a greater opportunity for radiation exposure and were categorized as high exposure. We compared cancer prevalence in the high-exposure group with that for all orthopaedic subspecialties with potentially lower radiation exposure. We compared cancer prevalence among surgeons by subspecialty, fluoroscopy use frequency, and protective shield use. To estimate the lifetime breast cancer risk for a representative woman in our study population, we used the National Cancer Institute Breast Cancer Assessment Tool .11Cancer prevalence analyses were limited to invasive internal cancers and melanomas diagnosed in female orthopaedic surgeons within 17 years of survey completion date. We selected the 17-year cutoff to align cancer rates among orthopaedic surgeons with the 17-year prevalence statistics (2000 to 2017) collected by SEER.P-values, we assumed a Poisson distribution for the observed number of cases and used an approximation to the exact Poisson test, as performed in previous studies.12We calculated standardized prevalence ratios (SPRs) by dividing the observed number of cancer cases among female orthopaedic surgeons by the expected number derived from age-specific, gender-specific, and race-specific cancer prevalences observed in the general US female population. To calculate confidence intervals (CIs) and 14We conducted sensitivity analyses to examine the effect of potential response bias in our results, assuming that women without a cancer diagnosis may be less likely to participate. We calculated SPRs and 95% CIs based on the following assumptions: (1) no nonrespondents had a history of cancer and (2) nonrespondents had the same cancer prevalence as the US female population. Analyses were conducted in R version 3.6.3 and Rstudio.http://links.lww.com/JG9/A218). More than half of the surgeons (55.8%) used standard fluoroscopy more than once a week. Minifluoroscopy use was less common, with 34.5% of respondents using it fewer than six times per year and 29.9% using it more than once a week.Of the 672 female orthopaedic surgeons who completed the survey, 87.5% reported working at least part-time and the mean duration of employment was 16 years . Compared with the general California female population, surgeons in our sample were more likely to be younger, have a normal body mass index (<25.0 kg/m2), be White, and have never smoked, which are deemed protective factors for breast cancer.15-17 Regarding hormone-related breast cancer risk factors, fewer surgeons had used hormone replacement therapy, and the surgeon respondents took hormones for a shorter duration than the California female population. Age at first childbirth was older for surgeons than the comparison group, which is considered an increased risk for breast cancer.15-17We compared breast cancer risk factors of female orthopaedic surgeons with those of population-based samples of women in California and the United States (Table P = 0.016), but the prevalence did not differ by individual subspecialty. Cancer prevalence did not differ by frequency of use of fluoroscopy, PMMA, or protective shielding (Table P = 0.015). Surgeons who used both standard and minifluoroscopy had a 5.6% breast cancer prevalence rate compared with surgeons who primarily used minifluoroscopy (6.4%), standard fluoroscopy (1.1%), or neither (2.4%). Post hoc tests indicated significant differences between surgeons who use both compared with those using only standard fluoroscopy (P = 0.018) and surgeons who use minifluoroscopy compared with those using standard fluoroscopy (P = 0.011).Fifty-one women reported a diagnosis of invasive cancer, and 20 reported a diagnosis of breast cancer (Table ng Table . Furtherhttp://links.lww.com/JG9/A220). The prevalence of breast cancer was fourfold higher among women in our sample compared with the age-adjusted and race-adjusted US population of women. When the sample is restricted to currently practicing orthopaedic surgeons, the prevalence was still markedly higher. Using the Gail model, we estimated the lifetime breast cancer risk of a hypothetical woman in our sample . The risk was 10.8% for women in our sample compared with 12.1% for matched women in the general US population (CIs are not provided for the Gail model breast cancer risk assessment tool).The prevalence of cancer was 189% higher among female orthopaedic surgeons compared with that of the age-adjusted and race-adjusted general US female population  when we assumed that there were no cancer cases among nonrespondents and 1.99 (95% CI: 1.54 to 2.52) when we assumed that the prevalence of cancer cases among nonrespondents matched that of the general US female population. In sensitivity analyses for breast cancer prevalence, the SPR was 2.07 (95% CI: 1.26 to 3.20) when no cases were assumed for nonrespondents and 2.55 (95% CI: 1.64 to 3.77) when population-expected rates were assumed for nonrespondents.19 Our study reports a 1.89-fold higher prevalence of all-cause cancer and a 3.97-fold higher prevalence of breast cancer in female orthopaedic surgeons compared with matched US women. Furthermore, our results are in contrast to the Gail model, which indicates a lower risk for breast cancer in our sample than the general population, indicating our results are even more surprising than expected. The finding of a higher cancer prevalence in a larger and more diverse cohort of female orthopaedic surgeons, which drew from a larger pool of female orthopaedic surgeons and recruited from more surgical societies than previous studies. The findings confirm previous studies and emphasize the importance of cancer as a public health issue within this specialty.4-6With an increasing percentage of women in orthopaedic surgery, it is imperative that we study and understand the occupational risks for this population to mitigate risks.202122232425262728 In a systematic review and meta-analysis, Lundqvist et al.24 demonstrated a higher incidence of breast cancer in patients with higher socioeconomic status . Although we did not collect data regarding socioeconomic status, surgeons are in the top 1% of US wage earners.3 Higher socioeconomic status has been correlated with both lower parity and nulliparity and greater age at first childbirth, and all factors associated with a greater risk of breast cancer and all observed in our population.30The many reasons proposed for this higher prevalence include higher socioeconomic status, delayed childbearing, lifestyle factors, and occupational exposures.31 Surgeons in training may be less likely to have access to appropriately fitting personal lead protection garments due to the costs and logistics of covering multiple hospitals. In particular, female trainees may be less likely to fit hospital-owned lead protection garments supplied by hospitals. Additional study has demonstrated that the addition of lead sleeves and/or axillary supplements decrease intraoperative lead exposure to the breast tissue most commonly affected by cancer.32Occupational exposure to ionizing radiation is common in orthopaedic surgery. Fluoroscopy times are generally higher for less experienced surgeons; thus, notable radiation exposure may occur during training and early practice.34 In this study, increased fluoroscopy use was not associated with an increased breast cancer prevalence. We also did not detect an increased breast cancer risk by radiation exposure group or specialty type; however, the sample size may have been too low to detect differences.In our study, the prevalence of cancer did not differ by individual subspecialty. Previous studies have demonstrated that those specializing in trauma are exposed to higher rates of radiation.28 used an anthropomorphic model to evaluate factors associated with higher breast radiation exposure and found that incorrectly fitting lead aprons and positioning relative to the c-arm affect the exposure rate for the upper outer quadrant of the breast. In addition, additional evaluation studying breast radiation with the use of appropriately fitting lead vests demonstrates that the upper outer quadrant of the breast, which is the most common site of breast cancer, is not well protected in many simulated intraoperative scenarios.32Researchers have not yet clarified the effect of decades-long exposure to low-dose radiation on the risk of breast cancer. Occupational radiation exposure is a modifiable risk factor that we can immediately change in practice. We therefore advocate for protective lead shielding of all radiation-sensitive tissue with appropriately fitted radiation-protective garments. Valone et al.15-17 Despite these protective factors, female orthopaedic surgeons still reported a higher prevalence of cancer compared with matched US women. Additional investigation is needed to further delineate these variables and their correlation with cancer risk.The female orthopaedic surgeons in our study had lifestyle factors protective against cancer. Compared with the general female population in California and the United States, more women in our study had a normal body mass index, were nonsmokers, and had lower exposure to hormone replacement therapy.34 which would not be captured in our analysis . In addition, there was no information on radiation exposure among the matched US cohort; therefore, we could not conduct comparisons between this group focused on radiation exposure. As another limitation, a roster of all female AAOS orthopaedic surgeon members was not available. We used specialty society rosters that may be incomplete. Compared with the 2018 AAOS Orthopaedic Practice in the US Census Report, which had a survey response rate of 22.5%, our study response rate was 52% and represents an estimated 39% of all female surgeons in the United States. Although the response rate was not as high as in our previous studies (52% vs 81.1%4 and 69.7%5), the results were similar across studies indicating that orthopaedic surgeons are still at higher risk of breast cancer. Also of note, although the use of fertility and assistive reproductive technologies are noted to be needed in more than 10% of the female orthopaedic surgeons,35 we did not inquire about fertility treatment nor did we evaluate the effect of fluoroscopy use on fertility treatment or the effect on various types of cancers. Finally, our study was limited to female orthopaedic surgeons, but male orthopaedic surgeons experience similar occupational hazards and may be at elevated risk for breast cancer.36 Studies including male surgeons are warranted.This study has limitations. For instance, healthier surgeons are likely to continue working, whereas a surgeon who has cancer may discontinue working and cease membership in a professional society. Thus, our recruiting mechanism may have introduced selection bias. Another limitation is recall bias inherent in the use of self-reported information. Although not ideal, it is unlikely that the study participants inaccurately reported cancer diagnoses, given the high education of women who participated in this study. A woman with a history of cancer may be more aware of her radiation exposure and may more accurately report her fluoroscopy use and be more vigilant with protective shielding. We did not observe a consistently different frequency of use of fluoroscopy types among orthopaedic surgeons, despite a markedly higher cancer prevalence; this finding suggests that if recall bias did exist, it was minimal. Relatedly, we used categorical criteria to evaluate fluoroscopic use  which limits analyses. Studies demonstrate differential use of fluoroscopy and radiation exposureOur findings strongly suggest that female orthopaedic surgeons are at a higher risk of breast cancer than the general US female population. A likely contributory factor may be occupational exposure to ionizing radiation. The potential adverse health effects among surgeons caused by a cumulative low dose of ionizing radiation from fluoroscopy use during surgery are unknown. In addition, the higher breast cancer prevalence may be partly due to delayed childbearing and lower parity. Although additional research is needed to determine the factors behind the increased cancer risk among orthopaedic surgeons, the community should educate current practitioners in the use of protective shielding. Such protective factors will help prevent all cancers, including breast cancer.


In relation to a clinically used lifestyle–family-based risk model, the AI risk model showed a significantly higher discriminatory performance .The aim of this study was to perform an external validation in a U.S. screening cohort of a mammography-derived AI risk model that was originally developed in a European study setting. The AI risk model was designed to predict short-term breast cancer risk toward identifying women who could benefit from supplemental screening and/or a shorter screening interval due to their high risk of breast cancer. The AI risk model showed a discriminatory performance of AUC 0.68, comparable to previously reported European validation results (AUC = 0.73). The discriminatory performance of the AI risk model was non-significantly different by race (AUC for White women = 0.67 and for Black women = 0.70), p < 0.01 and for Black women p < 0.01, but not for White women p = 0.38. The performance of the mammography-derived AI risk model was comparable to previously reported European validation results; non-significantly different when comparing White and Black women; and overall, significantly higher than that of the Gail model.Despite the demonstrated potential of artificial intelligence (AI) in breast cancer risk assessment for personalizing screening recommendations, further validation is required regarding AI model bias and generalizability. We performed external validation on a U.S. screening cohort of a mammography-derived AI breast cancer risk model originally developed for European screening cohorts. We retrospectively identified 176 breast cancers with exams 3 months to 2 years prior to cancer diagnosis and a random sample of 4963 controls from women with at least one-year negative follow-up. A risk score for each woman was calculated via the AI risk model. Age-adjusted areas under the ROC curves (AUCs) were estimated for the entire cohort and separately for White and Black women. The Gail 5-year risk model was also evaluated for comparison. The overall AUC was 0.68 (95% CIs 0.64–0.72) for all women, 0.67 (0.61–0.72) for White women, and 0.70 (0.65–0.76) for Black women. The AI risk model significantly outperformed the Gail risk model for all women  Breast cancer is the most commonly diagnosed cancer among women and is linked with considerable years of life lost (14.9 million DALYs), leading to increased cancer-related morbidity and mortality worldwide. Although mammographic screening reduces breast cancer mortality, a proportion of breast cancers are not detected at mammographic screening and are diagnosed later at a more advanced stage. Therefore, increasing attention is being given to new, personalized approaches to breast cancer screening in which both screening interval and modalities are tailored to an individual woman’s risk based on both clinical and imaging data [It is well known that women with the highest levels of mammographic breast density have 3–5 times the risk of developing breast cancer compared to women with lowest breast density ,3. In adIn the last 7 years, deep learning, the cornerstone of today’s artificial intelligence (AI) revolution in computational medical imaging, has pervaded mammographic screening as one of the most promising computerized imaging tools ,10,13,14® Risk 1.0, iCAD Inc., Nashua, NH, USA), originally developed and validated using data from Swedish screening cohorts [Acknowledging the critical need to adequately evaluate AI-based breast cancer risk models on heterogeneous screening populations, this study aimed to perform external validation of a commercially available FFDM-derived AI risk model (ProFound AI cohorts . To this cohorts  in a cohn = 182). We also identified a random sample of controls (n = 4997), defined as women who had mammographic screening studies resulting in negative or benign exams, with at least one-year of screening follow-up without a cancer diagnosis. In this institutional review board-approved, Health Insurance Portability and Protection Act (HIPAA)-compliant study under a waiver of consent, we retrospectively analyzed a case–control sample nested within the breast screening practice at the Hospital of the University of Pennsylvania . For theFor each cancer case and control, all views of the FFDM ‘For presentation’ imaging data were ascertained. Moreover, all available clinical risk factor data, such as age, race/ethnicity, body mass index (BMI), menopausal status, parity, BI-RADS density category (4th Edition), family history of breast cancer, number of previous breast biopsies, and history of atypical hyperplasia, as well as Gail 5-year risk scores were collected from medical records. For cancer cases, tumor characteristics, such as tumor size, nodal status, metastasis, stage, grade, ER status, and HER2 status, were also ascertained when available.ProFound AI Risk is a short-term risk prediction software that identifies women that have a high likelihood of being diagnosed with breast cancer within 2 years . The KARp < 0.05 was indicative of a statistically significant difference.Baseline characteristics of the study participants were summarized by standard descriptive summaries including means, standard deviations, and study group differences. Absolute 2-year AI risks were estimated and reported as means in four National Institute of Health and Care Excellence (NICE) guidelines risk categories . Risk stWe also performed an exploratory analysis focusing on potential variation in the discriminatory performance of the AI risk model over images obtained during the same mammographic exam of a women, however acquired at different acquisition time points. The rationale is that, typically, a mammographic exam consists of four FFDM images, with two views of each breast: a cranio-caudal (CC) and a mediolateral oblique (MLO) view of both the right and left breasts. However, multiple images in the same view or projection may be needed, mainly for two reasons: additional imaging may be necessary to adequately image large breasts; second, images may be repeated due to technical issues such as motion or image artifacts. Since the AI risk model uses one image per FFDM view , previoup = 0.002), family history of breast cancer (p < 0.001), number of prior biopsies (p < 0.001), and BI-RADS density categories (p < 0.001) between breast cancer cases and controls, but there were no statistically significant differences in BMI, race, menopausal status, parity, or atypical hyperplasia  and 4963 controls . There were statistically significant differences in age at screening   . Overall< 0.001) , compara subtype . Nonsign subtype .p < 0.001) (p < 0.01) for any breast cancer type and for invasive breast cancer   but not in White  women  . On the  < 0.01) . Moreove < 0.01) . The cor7) women .In this study dataset, 1772 of 5139 women (66 cases and 1706 controls) had more than four FFDM images per mammographic exam . The hisWe performed an external validation of an AI 2-year risk model for full-field digital mammography (FFDM) in a U.S. screening cohort with White and Black women, including 176 incident breast cancers and approximately five thousand controls. The risk stratification performance of the AI risk model was comparable to previously reported European validation results; non-significantly different when comparing White and Black women in the U.S. study; and overall, significantly higher compared to that of the established Gail risk model. The AI risk model also showed robust discriminatory performance over images of the same mammographic exam acquired on the same woman at different time points.The use of mammography-derived AI algorithms provides new possibilities for performing breast cancer risk assessment in an imaging clinic ,10. The Traditional risk models such as Gail and Tyrer-Cuzick predict 5-year, 10-year, or lifetime risk and are commonly reported to have low to moderate discriminatory performance . In compWhen comparing the AI risk model performance in our U.S. population to the previous Swedish population , we noteOur study was limited since the external validation of the AI risk model was performed with data from only one site in the U.S. Moreover, the comparison to clinically established risk models was restricted to the Gail risk model due to the lack of available risk factors required for using the Tyrer–Cuzick risk model. In our case–control study design, we estimated the 2-year risk using the AI risk model and the 5-year risk using the Gail model in a group of women who were followed for one year on average. Therefore, we could not assess the calibration of the two risk models. The study sample size was a limiting factor for observing potential significant differences in study subgroups including tumor characteristics and ethnicity. In addition, the women in our study were examined on screening machines that acquired both FFDM and digital breast tomosynthesis (DBT) images. The inclusion of DBT imaging may have detected more cancers at screening and, therefore, could have affected the reported discriminatory performance, which was based on FFDM images alone.Our preliminary external validation results suggest a promising performance of the AI risk model in a U.S. screening cohort of White and Black women and a clinically meaningful improvement over the established Gail risk model for identifying women at high risk of breast cancer. A mammography-derived risk assessment approach could provide an efficient way to identify women who may benefit from additional clinical follow-up or supplemental screening following a non-actionable screening exam. Future work will include further validation of the AI risk model, as well as its latest extension for DBT , at mult


Molecular subtyping of breast cancer is commonly doneforindividualzed cancer management because it may determines prognosis and treatment. Therefore, preoperativelyidentifying different molecular subtypes of breast cancery can be significant in clinical practice.Thisretrospective study aimed to investigate characteristic three-dimensional ultrasonographic imaging parameters of breast cancer that are associated with the molecular subtypes and establish nomograms to predict the molecular subtypes of breast cancers.A total of 309 patients diagnosed with breast cancer between January 2017and December 2019 were enrolled. Sonographic features were compared between the different molecular subtypes. A multinomial logistic regression model was developed, and nomograms were constructed based on this model.The performance of the nomograms was evaluated in terms of discrimination and calibration.Variables such as maximum diameter, irregular shape, non-parallel growth, heterogeneous internal echo, enhanced posterior echo, lymph node metastasis, retraction phenomenon, calcification, and elasticity score were entered into the multinomial model.Three nomograms were constructed to visualize the final model. The probabilities of the different molecular subtypes could be calculated based on these nomograms. Based on the receiver operating characteristic curves of the model, the macro-and micro-areaunder the curve (AUC) were0.744, and 0.787. The AUC was 0.759, 0.683, 0.747 and 0.785 for luminal A(LA), luminal B(LB), human epidermal growth factor receptor 2-positive(HER2), and triple-negative(TN), respectively.The nomograms for the LA, HER2, and TN subtypes provided good calibration.Sonographic features such as calcification and posterior acoustic features were significantly associated with the molecular subtype of breast cancer. The presence of the retraction phenomenon was the most important predictor for the LA subtype. Nomograms to predict the molecular subtype were established, and the calibration curves and receiver operating characteristic curves proved that the models had good performance. Breast cancer is a heterogeneous and complex disease. The main molecular subtypes of breast cancer are luminal A (LA), luminal B (LB), human epidermal growth factor receptor2-positive (HER2), and triple-negative (TN) , 2.This Hand-held ultrasonography (HHUS) has some limitations because of the lack of standardization . MeanwhiIn recent years, artificial intelligence for 3D-US has been applied in the differential diagnosis of benign and malignant breast masses, however there are only a studies on 3D–US in molecular typing .The study aimed to investigate the relevance of the 3D–US imaging characteristics of breast cancer associated with specific molecular subtypes in order to establish nomograms that distinguish the molecular subtypes of breast cancer. This study explored the possibility of predicting molecular typing models with large samples and provided insights into the future artificial intelligence prediction of molecular typing.The Institutional Review Board authorized this retrospective study, The requirement for informed consent was waived due to the retrospective nature of the study. Between January 2017and December 2019, 326 patients were consecutively enrolled from our hospital with random selection. All patients had invasive breast cancer, which was histologically diagnosed. Their molecular subtypes were estimated from the surgical specimens. Patients with lesions of undetermined immunohistochemical results (n=12) and patients with considerable deformity of the breast or chest (n=5) were excluded. After these exclusions, 309 patients were enrolled in this study.Patient information and lesion size and location were recorded. All imaging features were retrospectively reviewed according to the 5th edition of the American College of Radiology Breast Imaging Reporting and Data System lexicon . Two radCoronal features included the retraction phenomenon and the skipping sign. The retraction phenomenon was defined as the convergence tendency of the tissue surrounding a lesion with or without cord-like hyperechogenicity intervals on the coronal plane. The skipping sign was defined as anechoic lines around the lesion . ElasticMolecular subtypes were defined according to the 2015revised St. Gallen International Expert Consensus Recommendation .2test (parametric) or Fisher’s exact test (non-parametric). The factors of the entire dataset were compared between groups, and the p values were calculated. Second, factors with p<0.05 were included in the establishment of a four-category prediction model, and a multi-classification regression model was established using multinomial logistic regression for the entire dataset. Third, nomograms were constructed based on the results of the multivariate logistic regression model  was used for all analyses. Statistical significance was set at p<0.05. Nomograms were developed in four steps.First,single factors were compared between the different molecular types using the χon model . The totThe average age of the study population was 54.25 ± 11.18 years, ranging from 25 to 85 years. There were 288 cases of invasive ductal carcinoma and 21 cases of special types of invasive breast cancer. The general characteristics of the study population, including height, weight, type II diabetes status, and hypertension, are shown in There was no significant difference in age and maximum diameter among the four subtypes. However, the maximum diameter stratifications  showed statistical significance. On-mass lesions cannot be expressed in terms of mass description, therefore ‘NA(no answer)’is entered in the table. The detailed distributions of the histologic types are shown in p< 0.05 in the single-factor analysis were entered into the model. These included maximum diameter, irregular shape, non-parallel growth, heterogeneous internal echo, enhanced posterior echo, lymph node metastasis, retraction phenomenon, calcification, and elasticity score.Variables with Three nomograms were created to predict the probabilities of the LB, HER2-positive, and TN subtypes. Each independent variable value corresponded to a point value on the top row, and the individual scores were added to yield the total score. The probability was then calculated based on the total score . The resUS is the most widely used auxiliary examination technique for the preoperative evaluation of breast cancer. However, certain errors may occur during the preoperative puncture, which can have adverse effects. Therefore, identifying the molecular classification of breast cancer is vital to guide the selection of an individualized clinical plan. Moreover, it is difficult to utilize the traditional classification for these treatment plans. Therefore, establishing a model that incorporates multiple factors to identify the molecular subtype can be used to predict the risk of mortality and facilitate the implementation of individualized treatment , 19. SinLA and LB cancers account for approximately 70% of breast cancer cases . SimilarABVS is a 3D–US imaging system that overcomes the main shortcomings of HHUS, such as lack of standardization, non-repeatability, small field of view, and excessive time investment. Additionally, for women with dense breast tissue, ABVS can recognize calcification and the retraction phenomenon more due to its the unique coronal reconstruction. Furthermore, ABVS is more accurate than HHUS in assessing the extent of the disease, average lesion size , and larvia step wise analysis, Nomograms were subsequently developed based on the fitted multivariate logistic regression model.Tumor size, calcification, post-acoustic enhancement, and the retraction phenomenon were used to construct the nomogram model for distinguishing the molecular subtype of breast cancer. The scores of the influencing factors could show the individualized prediction results. The discriminative power of the nomogram was quantified using the AUC, exhibiting the accuracy of the test. Previous studies have shown that models with AUCs of 0.5–0.7 have low predictive value, models with AUCs of 0.7–0.85 have better predictive value, and models with AUCs of 0.85–0.95 have the best predictive value (A nomogram is a graphical calculation model that uses known predictive factors to calculate the numerical probability of a clinical event. Such prediction models are valuable. A multivariate logistic regression model we constructed ve value . The modRecent studies have developed models to predict the molecular classification of breast cancer through radiomics or machine learning approaches using image segmentation , 28. TheThe study has several limitations. First, this was a retrospective study performed at a single institution. A multicenter prospective study with a large sample size needs to be performed to validate this study’s results. Second, the sample sizes of the four molecular subtypes were unbalanced. As a result, the ROC curves of subtypes with fewer samples are unsatisfactory. Further studies should consider having balanced sample sizes.In conclusion, sonographic features such as calcification and posterior acoustic features were significantly associated with the breast cancer molecular subtypes. In addition, the presence of the retraction phenomenon was the most important predictor for the LA subtype. Nomogramsfor the prediction of the molecular subtypes were established based on the results of the multifactor analysis, The calibration and ROC curves showed that the model had good performance. Further multicenter studies will be useful for updating and validating these nomograms to improve the predictions of molecular subtypes.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by Hangzhou First people’s Hospital ethics committee. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.LB contributions to design of the work. YT and LY analysis of data for the work, XX and LL, drafting the work. LZ revising it critically for important intellectual content. All authors agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.The study was supported by The Construction Fund of Medical Key Disciplines of Hangzhou.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.


Despite the benefits of genetic counseling and testing, uptake of cancer genetic services is generally low and Black/African American (Black) women are substantially less likely to receive genetic services than non-Hispanic White women. Our team developed a culturally sensitive, narrative decision aid video to promote uptake of genetic counseling among Black women at risk for a hereditary breast cancer syndrome that can be incorporated in conjunction with population-based cancer risk assessment in a clinical setting. We report here a pilot study to demonstrate changes in intention to access genetic counseling and intervention satisfaction.Black women who were personally unaffected by breast cancer and were recommended for genetic counseling based on family history screening in a mammography center were recruited at the time of the mammogram. A prospective, pre-post survey study design, guided by theoretical constructs, was used to evaluate baseline and immediate post-intervention psychosocial factors, including intention to participate in genetic counseling and intervention satisfaction.n = 30). Pre-intervention, 50% of participants indicated that they were extremely likely to make a genetic counseling appointment, compared with 70% post-intervention (p = 0.05). After watching the intervention, 50% of participants indicated that the video changed their mind regarding genetic counseling.Pilot recruitment goals were met (This study demonstrated cultural satisfaction with a decision aid intervention designed to motivate Black women with hereditary breast cancer risk to attend a genetic counseling appointment. Our study showed that intention may be a specific and key construct to target in interventions designed to support decision-making about genetic services. Study results informed the design of a subsequent large scale, randomized implementation study.Clinicaltrials.govNCT04082117.Trial registration: Registered September 9, 2019.Retrospectively registered.The online version contains supplementary material available at 10.1186/s12913-022-08193-x. BRCA1-associated cancers, such as younger age of onset, high tumor grade, and negative hormone receptor status, which all contribute to disparate breast cancer mortality rates [Carriers of germline mutations in cancer susceptibility genes have up to an 85% lifetime risk of developing breast cancer compared with 12% for the general population . Cancer ty rates , 7–10. Tty rates , 12.Despite the benefits of genetic counseling and testing, uptake of cancer genetic services is generally low. This is particularly problematic among Black women, who are approximately 50% less likely to receive genetic services than NHW women due to multi-level barriers, including bias in provider referrals, lack of perceived benefit, barriers to access and lack of awareness of genetic services, and cost , 13–26. Decision aids promote positive health behavior change, improve health outcomes and mitigate health literacy barriers. Relatively little work has been conducted to understand the decision-making process among racial/ethnic minority women recommended for genetic counseling for breast cancer risk, or to develop culturally-tailored decision aids to promote uptake of genetic services , 29–33. A prospective, pre-post survey study design was used to evaluate baseline and immediate post-intervention intentions, knowledge, and beliefs regarding genetic counseling, as well as to assess satisfaction with the video intervention. The study was registered at Clinicaltrials.gov (NCT04082117) and was approved by the Institutional Review Board at the University of Illinois at Chicago (#2016–1219). All study participants provided written informed consent.n = 30 is commonly recommended for pilot studies [The study was conducted in a mammography center at a safety net academic medical center in Chicago, IL, between August 2019 and October 2019. Eligibility criteria included: 1) Black women between the ages of 25 to 69 years old presenting for a screening or diagnostic mammogram; 2) no personal history of breast cancer; 3) never attended an appointment with a genetic counselor; 4) underwent breast cancer risk assessment at the time of the mammogram; and 4) were recommended for genetic counseling based on family history of breast and/or ovarian cancer. Formal power calculations are difficult to perform for pilot studies. A sample size of  studies . We follThe participating mammography center conducted family history screening for hereditary cancer risk as a routine component of the evaluation for all women undergoing screening or diagnostic breast imaging beginning in 2018. Risk assessment was conducted at the time women checked-in for the mammogram using a software application (CancerIQ®) on tablet computers and patient-reported information on family cancer history. Women who met national guideline criteria for genetic counseling referral  due to hRadiology technicians gave a study recruitment flyer to all women who were recommended for genetic counseling and briefly described the study to eligible women using a recruitment script. Women who expressed interest in participating in the study were directed to a privacy-protected area in the mammography center where research personnel completed eligibility screening and informed consent. Research personnel then administered a pre-viewing survey, played the six-minute narrative decision aid on a laptop computer for the participant to view, and then administered a post-viewing survey. Women completing all study activities received a stipend for research participation.The pre-viewing survey and post-viewing survey were administered by research personnel using an electronic data capture and management system (REDCap) with an encrypted laptop computer. The initial study protocol included review of the electronic health record 6 months after completion of study recruitment to determine rates of attendance at a genetic counseling session. However, due to clinic restrictions that were initiated in 2020 due to the COVID-19 pandemic, all elective outpatient appointments were cancelled, so the 6-month medical record review was not completed.A culturally sensitive, narrative decision aid was developed by the study team to promote uptake of genetic counseling among Black women at risk for a hereditary breast cancer syndrome . DevelopOriginal and adapted pre- and post- survey questions, guided by the IMBP theoretical constructs, assessed participants’ intentions, knowledge, perceived normative beliefs, barriers, self-efficacy beliefs, attitudes, and environmental constraints. Intentions regarding genetic counseling attendance were measured with six items. Responses for four of these items were measured on a 5-point likert scale ranging from 1 (extremely likely) to 5 (extremely unlikely); one item was open-ended; and one item was single response. Knowledge about genetic counseling was measured by six true/false adapted items . Perceivp-values were computed using McNemar’s test of marginal homogeneity (symmetric table cell proportions). For data from pre- and post-intervention survey items with a 3 × 3 response  p-values were computed using the generalization of the McNemar’s test, commonly referred to as generalized McNemar’s test or Stuart-Maxwell test for homogeneity of the marginal distributions [p-value less than 0.05 was considered statistically significant.Demographic characteristics of participants were summarized with descriptive statistics. Survey responses were summarized as frequencies and percentages. Responses of “no” and “not sure” were combined into the same response group. Pre- and post-intervention responses were compared using McNemar’s test for paired data. For data from pre- and post-intervention survey items with a dichotomous response (extremely vs. somewhat likely) ibutions . Analysehttps://youtu.be/_bR81v_nCaMURL link to the intervention: Thirty Black women enrolled in this study and completed all study activities. The median age among participants was 53 years (interquartile range 48–60); ages ranged from 30 to 69.p = 0.05)  Table . After w5) Table . Additiop = 0.02) following the intervention. Eleven women (37%) indicated that they anticipated experiencing barriers or would have difficulties attending a genetic counseling session before the intervention. There was a decrease in this proportion following the intervention . Only 7 women responded to the item asking if they believed they could overcome any difficulty they may have in attending a genetic counseling session. At baseline, 3 women responded yes, and 5 women responded yes following the intervention.At baseline, 77% of participants believed their family would be interested in learning more about genetic counseling because of cancer in their family Table . This inp = 0.02) following the intervention. The proportion of women indicating that they were confident that they knew who to call to make an appointment to attend a genetic counseling session increased from nine (30%) to twenty women  following the intervention.Before the intervention only 17% of participants were confident that they could pay for genetic counseling services Table . This inn = 19) indicated they did not know how much their medical expenses will cost when seeing a doctor. Despite this, 83% (n = 25) indicated they could easily get needed medical care when needed, and over 90% felt comfortable asking their doctor questions and making and getting to and from medical appointments.When asked about health care in general, 50% of women indicated they often worry about the cost of medical care and 63% (n = 27) of participants thought the video would motivate their loved ones to engage with their doctors about genetic counseling. Four participants indicated they would make changes to the video. Women who did specify suggested changes recommended giving more details about the personal benefit a woman gains from genetic counseling in addition to limitations of genetic counseling.The majority of participants enjoyed watching the video and felt they could relate to the actors Table . All butThe intervention was designed to motivate attendance at a genetic counseling session. As expected, knowledge about genetic counseling did not change significantly after viewing the intervention Table .Table 4PThis study demonstrated changes in intention to attend genetic counseling and satisfaction with a decision aid intervention designed to motivate Black women with hereditary breast cancer risk to attend a genetic counseling appointment. The intervention has now been thoroughly evaluated for cultural appropriateness using qualitative research with focus groups in earlier work , and nowBRCA1 and BRCA2 genetic testing in women with breast cancer found that all studies examined (n = 9) described gains in knowledge about hereditary breast cancer, but lacked a theoretical justification for why or how interventions impacted outcomes [Evidence-based decision aid interventions increase patient knowledge, supplement clinical consultations, improve congruence with patient values, reduce decisional conflicts, and help patients make informed decisions , 47, 48.outcomes . Use of outcomes . Guided outcomes , 33, 48 p-values for every pre/post comparison. The intervention was designed for urban Black women with a family history of breast cancer. It is unclear whether this intervention would have the same effect with women from other racial/ethnic groups or in other geographic settings, or with different family cancer histories. Additionally, we were unable to complete planned analysis of genetic counseling uptake at 6 months post-intervention since clinic restrictions resulting from the COVID-19 pandemic prevented women from scheduling a non-urgent appointment. However, it is likely that a multilevel approach that also addresses barriers to scheduling and attending the consultation will be necessary in order to maximize uptake of cancer genetic services among underserved, high-risk Black women. We are testing this hypothesis in a randomized trial (NCT 04378751) that will couple additional evidence-based strategies (patient navigation and transportation assistance) with the decision aid in order to increase utilization of genetic counseling in this patient population. We will also assess implementation feasibility with clinical providers. An additional limitation of this study is that we did not test the effect of the decision aid on diffusion of knowledge about genetic risk and counseling among the social networks of Black women recommended for genetic counseling. This is an important aspect of a population health approach to cancer genetics and risk assessment, since the benefits of population screening for genetic risk can be amplified by identifying and testing at-risk family members of patients found to carry a pathogenic variant (cascade testing). We are addressing this issue in the ongoing randomized trial.This pilot study has limitations. It was intended to inform the design of a subsequent large scale implementation study, and therefore the sample size was relatively small by design. The sample size resulted in sparse data or zero cells for some survey responses, which precluded us from presenting We developed a culturally tailored narrative decision aid that meets the need for cost-effective interventions to facilitate informed decisions on genetic counseling and testing and communication about heritable cancer risks among medically underserved, Black women. Satisfaction with the intervention among the target audience was very high. The intervention increased self-efficacy and intentions to attend genetic counseling among high risk Black women, and it may facilitate cascade testing among at-risk family members. This intervention warrants further investigation as a component of population-based strategies to identify racial/ethnic minority women with hereditary breast cancer risk in an effort to curtail health disparities that may be perpetuated with advances in precision medicine , 36, 49.Additional file 1. Pilot Study Pre and Post Survey.


This cohort study examines the risk of anaplastic large cell lymphoma (ALCL) following postmastectomy implant reconstruction among US women with breast cancer and ductal carcinoma in situ (DCIS). We previously reported that the incidence of ALCL is increasing rapidly in the US.4 Here, we report on the risk of breast ALCL in a population of women who have undergone implant reconstruction.Approximately 291 000 and 51 000 cases of breast cancer and ductal carcinoma in situ, respectively, are diagnosed in the US annually, the majority of whom undergo local curative surgery, including mastectomy with implant-based reconstruction. National and regulatory guidelines recommend that patients eligible for reconstruction be counseled on the association of breast implants with subsequent anaplastic large cell lymphoma (ALCL) as part of routine informed consent.ICD-O-3 code 9714) through December 2019 until death, loss to follow-up, or end of study, with a latency exclusion period of 2 months from diagnosis. In a sensitivity analysis, we included cases of T-cell lymphoma, not otherwise specified .4 Multiple primary-standardized incidence ratios (SIRs) were used to compare the number of observed vs expected cases diagnosed in the study population based on US incidence rates derived from the US general female population in SEER 17, adjusted for age, race, and year of diagnosis. The prevalence of breast implants in US women is approximately 3.6% to 4.9%.5 Statistical analyses were conducted using SEER*Stat Version 8.3.9  and RStudio version 1.4.1106  software. This study was exempt from review by the Columbia University institutional review board. This report follows the STROBE reporting guideline for observational studies. Two-sided P < .05 was considered statistically significant.We identified women who underwent cancer-directed mastectomy with implant reconstruction for any tumor within the breast, diagnosed from 2000 to 2018, using the Surveillance, Epidemiology, and End Results (SEER) 17 database, excluding women with less than 12 months of follow-up. Participants were assessed for pathologically confirmed primary breast ALCL . The sample included 7% Asian or Pacific Islander women, 8% Black women, and 84% White women. The median (IQR) follow-up time was 81 (46-125) months, including 15 765 women with follow-up times of at least 10 years. Five cases of breast ALCL were diagnosed over 421 223 person-years. The observed vs expected incidence rates were 11.9 vs 0.3 per million persons per year  . There w4To our knowledge, we report the first population-based estimate of the risk of ALCL after implant-based reconstruction. Although the relative risk is significantly increased, the absolute risk remains extremely low. Furthermore, our risk estimates are within the range of reported literature for cosmetic or reconstructive implants. Breast implant–associated ALCL was not readily diagnosed in practice before 2008. The risk of ALCL will likely increase with longer follow-up, as the incidence rate is rapidly increasing in the US.Limitations of this study include retrospective analysis of registry data that depends on accurate reporting. We performed a sensitivity analysis, including cases of T-NOS, to account for underreporting. The latency time to develop secondary ALCL after implantation may be very long, and while our follow-up period was commensurate with other cohort studies, it likely underestimates the true incidence. Furthermore, we may underascertain cases due to migration from SEER registries. We did not account for implant removal or exchanges. Additionally, the confidence intervals of our risk estimates were wide.6 and may be avoided based on regulatory guidelines and clinical discretion.Patients with breast cancer who are eligible for mastectomy should be counseled on the risks of breast ALCL after implant reconstruction. However, based on these results, we do not believe that women should be dissuaded from pursuing implant-based reconstruction due solely to the risk of ALCL. Specific brands of macrotextured implants with high-surface-area have been associated with higher rates of ALCL


As genetic testing becomes increasingly incorporated into clinical practice to aid in both the diagnosis and risk assessment of genetic diseases, patients benefit from genetic counseling to support their understanding of test results either before and/or after genetic testing. Therefore, access to genetic testing and counseling is imperative for patient care. It is well established that health insurance coverage is a major determinant of access to health care in the United States as individuals without insurance are less likely to have a regular source of health care than their insured counterparts. Different health insurance plans and benefits also influence patients’ access to health care. Data on the association of health insurance and the uptake of genetic testing and/or counseling for cancer risk are limited. Using data from the National Health Interview Survey, we examined the uptake of genetic testing and/or counseling for breast/ovarian cancer risk by health insurance type. We found that only a small proportion of women undergo genetic testing and/or counseling for breast/ovarian cancer risk (2.3%), even among subgroups of women at risk due to family or personal history (6.5%). Women with health insurance were more likely to undergo genetic testing and/or counseling for breast/ovarian cancer risk, particularly those with military and private insurance plans, than those without health insurance after adjusting for various demographic, socioeconomic, and health risk covariates. Further investigations are needed to examine potential disparities in access and health inequities.  BRCA1/2 pathogenic mutation are at a much greater risk of developing breast and ovarian cancer than those in the general population  were significantly more likely to have had genetic testing and/or counseling when compared to those with no health insurance. The statistically insignificant results for some of the health insurance types in the multivariable regression models were most likely due to the lower rates of uptake after adjusting for covariates. While it is encouraging that some women with health insurance, particularly those at-risk of breast/ovarian cancer and who would benefit from its access, have greater access to genetic testing/counseling for breast/ovarian cancer risk than those uninsured, our findings suggest that access likely differed across insurance types. It is well known that there are complexities in the United States health insurance coverage plans, as well as variations in access to health services ,38,39,40There have been other studies that used the NHIS to study the uptake of genetic services for breast and/or ovarian cancer ,30. AlleThere are several strengths to our study. It is one of the first to systematically analyze the various types of health insurance and their association with the uptake of genetic services for breast/ovarian cancer risk. Furthermore, by utilizing the NHIS, we were able to generate a larger cohort that was representative of the national population and limited confounders. However, there are still several limitations to the present analysis. As a cross-sectional analysis, we cannot make statements about the temporal relationships between the insurance types and uptake of genetic testing and/or counseling for breast/ovarian cancer risk. Since our study was observational in nature, we also cannot make any causal claims, and there is still the possibility of confounding variables that were not accounted for. We attempted to minimize bias by performing a subgroup analysis limited to women who were at-risk for breast/ovarian cancer (a more homogenous group) and for whom health insurance policies are likely to be more similar. While the NHIS does collect some information about patient cost-sharing, we were unable to examine its interactive effects with health insurance due to the sample size. We are also unable to examine the separate associations of the health insurance type with the specific genetic services due to insufficient statistical power, and we created a composite outcome variable that combined genetic testing and/or counseling for breast and/or ovarian cancer risk. Furthermore, our variables were limited by the design of NHIS. For example, we were not able to identify women who have family members with inherited cancer syndromes , which is why we included a family history of breast/ovarian cancer. Finally, the self-reported survey data may be susceptible to recall bias .The findings from this inferential analysis suggest variations in the access to genetic services for breast/ovarian cancer risk across different health insurance types. The current lack of standardization in health insurance coverage policies for genetic services may present a significant barrier for women who could otherwise benefit from such services. Further investigations are needed to examine the potential disparities in access and health inequities. Increasing efforts to align health insurance coverage policies with clinical guidelines, and to minimize variations in insurance coverage policies across insurers for genetic testing and/or counseling, are needed. These efforts will allow for the equitable integration of genetic services in the clinical setting.