U.S. professional organizations have provided conflicting recommendations on annual vs. biennial mammography screening. Potential harms of more frequent screening include increased anxiety and costs of false positive results, including unnecessary breast biopsies and overdiagnosis.To characterize current practices and beliefs surrounding mammography screening frequency and perspectives on using risk-based screening to inform screening intervals.Semi-structured interviews informed by the Consolidated Framework for Implementation Research (CFIR).Patients, primary care providers (PCPs), third-party stakeholders .Qualitative data, with a codebook developed based upon prespecified implementation science constructs.We interviewed 25 patients, 11 PCPs, and eight key stakeholders, including three radiologists, two radiology administrators, and three patient advocates. Most patients reported having annual mammograms, however, half believed having mammograms every two years was acceptable. Some women were worried early breast cancer would be missed if undergoing biennial screening. PCPs were equally split between recommending annual and biennial mammograms. Although PCPs were interested in using breast cancer risk models to inform screening decisions, concerns raised include time burden and lack of familiarity with breast cancer risk assessment tools. All breast radiologists believed patients should receive annual mammograms, while patient advocates and radiology administrators were split between annual vs. biennial. Radiologists were worried about missing breast cancer diagnoses when mammograms are not performed yearly. Patient advocates and radiology administrators were more open to biennial mammograms and utilizing risk-based screening.Uncertainty remains across stakeholder groups regarding appropriate mammogram screening intervals. Radiologists recommend annual mammography, whereas patients and PCPs were evenly split between annual vs. biennial screening, although both favored annual screening among higher-risk women. Breast cancer risk assessment tools may help facilitate decisions about screening intervals, but face barriers to widespread implementation in the primary care setting. These results will inform future implementation strategies to adopt risk-stratified breast cancer screening.The online version contains supplementary material available at 10.1186/s12885-022-09900-x. Invitation to mammography screening has been associated with a 20% relative risk reduction in breast cancer mortality –3. For dAlthough annual screening has enabled detection of cancers at earlier stages and improved breast cancer-specific mortality, over-screening presents unique harms including anxiety from abnormal mammograms, unnecessary biopsies for benign lesions, and increased use of surgical procedures with no clear mortality benefit , 9. As aOur study objective is to understand current practices and beliefs surrounding mammogram screening practices among three stakeholder groups: patients, primary care providers (PCPs), and key stakeholders including breast radiologists, radiology administrators, and patient advocates. Additionally, we aim to characterize individual-level and structural barriers and facilitators to the adoption of risk-based mammography screening.We conducted semi-structured interviews among women undergoing screening mammograms, PCPs, and other key stakeholders  to explore their beliefs and behaviors surrounding mammogram screening frequency. This study was approved by the Columbia University Institutional Review Board.We recruited patients, providers, and stakeholders who previously participated in related studies through email and phone. We interviewed a purposeful sample of patients who undergo screening mammography at our institution, aiming to capture perspectives of women from various socioeconomic and racial/ethnic backgrounds and different screening frequency. We interviewed a purposeful sample of providers who were primary care providers, aiming to capture perspectives from internists, family practitioners, and gynecologists. We interviewed a purposeful sample of key stakeholders who were not primary care providers who still had experience working with patients undergoing mammograms and interviewed breast radiologists, mammography center directors, or community/patient advocates.Semi-structured interview guides for all three groups were based on prior literature and constructs adapted from the Consolidated Framework for Implementation Science (CFIR) . One intA total of 25 patients, 11 providers, and eight key stakeholders participated in the semi-structured interviews  reported having a mammogram every year. Of the women who reported yearly mammograms, most appeared to be motivated by their PCP recommendation and annual reminders.I tend to schedule my annual checkup like February/March timeframe … when my primary care physician puts that down there, I schedule an appointment and see whatever is available. [Patient #22].Overall, most women  believed that having a mammogram every two years is acceptable if that was the recommendation from their healthcare provider. Another woman stated that the guidelines are confusing and wondered how to weigh differing recommendations. Several women believed that very high-risk women like those with a I think if you are in a high-risk category you should be surer to do your annual or what is recommended for your age or risk level. [Patient #9].I would personally not feel comfortable with that. […] Because I have been told and it’s been demonstrated to me that I am high risk. I am going through menopause and I just think that’s a long time to wait. I mean I have a kid, I don’t want to die in my 50s.Eleven women (44%) felt that two years is too long to wait to have a mammogram and they would feel more confident in having a mammogram every year, particularly if they are high-risk.n = 14), reminder letters (n = 13), family history of breast cancer (n = 9), desire for early detection (n = 5), and age (n = 2). When asked “who orders your mammogram,” the majority reported their PCP or gynecologist. Annual reminder letters from radiology were another top factor that influenced a woman’s decision to have a mammogram. The majority (n = 17) received a letter as a reminder to have their annual mammogram, six received a phone call, and three reported receiving a reminder through the patient portal.It’s from the breast screening patient navigator at Columbia. I don’t know that this is my latest letter, but I know that I kept this letter as sort of sitting out just to remind me. Basically, it says if you have not had a mammogram in 1–2 years, we encourage you to call. [Patient #4].Participants named a variety of factors that influenced their decision to have a mammogram, including doctor’s recommendation  viewed mammography as having harms such as radiation (n = 12), pain and discomfort (n = 4), and false positive results (n = 3).Early detection to see if there are any abnormalities; to see if anything else is wrong or right. The earlier the better, so there is a chance for early intervention if something is seen or found. [Patient #19].All participants believed that mammograms save lives and viewed the benefit of mammography as catching cancer in earlier stages and having the opportunity to intervene early. Some women  believed that women over 40 years old should receive yearly mammograms while the remaining five (45%) thought women should receive biennial mammography. All PCPs felt that their decisions were influenced by external guidelines, with five (45%) using USPSTF, three (27%) using ACOG, and one (9%) using ACR. Two only stated using “guidelines” without specifying further.I feel like those letters really drive my practice a lot because when the patient gets a letter from the hospital saying it’s time for your mammogram, I can’t possibly say, well I think it will be okay to wait another six months, you had one a year ago …but since they got it and they are requesting it, I’m sort of driven by that. [Provider #6].In most cases patients are anxious for the annual and I can’t think of any patient who has requested less frequent mammograms. [Provider #2].Three PCPs felt that yearly reminders from breast radiology influence them to obtain yearly mammograms because patients request them. Eight (73%) providers said they incorporate patient preferences and concerns when deciding on frequency.I honestly do not have a good mental algorithm for in whom that is most appropriate. The people who I usually aggressively promote more frequent intervals are those who have had abnormal mammograms in the past. [Provider #3].Seven providers (64%) stated they screen patients more frequently when patients have a family history of breast cancer, and four (36%) screen patients more frequently when they have a history of abnormal mammogram.n = 9, 82%) were confident about discussing mammograms with their patients; however, two (18%) providers felt they have knowledge gaps. When communicating breast cancer risks, five (45%) PCPs mainly discussed family history as a risk factor, three (27%) stated that they discuss all risk factors pertinent to patients’ histories, and three (27%) were hesitant about bringing up risk factors because it would incite unnecessary anxiety. Many PCPs stated that they do not discuss breast density with their patients, unless patients directly ask them, since they don’t know how density influences optimal management.I can talk to my patients about breast density all day, but the answer is, oh okay, so what should I do and I’m like, I don’t know. [Provider #3].Most PCPs  providers recommend mammograms to patients without any discussion about benefits and harms, while three (27%) only explain that benefits outweigh harms. Only one (9%) provider uses shared decision-making surrounding mammogram recommendations.n = 7, 64%), reduced likelihood of missing serious cancers , reduced breast cancer mortality , and reduced patient anxiety .The goal with screening is to pick up on early cancers in order to prevent morbidity and mortality associated with breast cancer. I think it is often high on their healthcare maintenance to-do list and something that they want to do. [Provider #1].All providers were strong proponents of mammogram screenings, with two (18%) stating there are no harms associated. All providers discussed some benefits of mammography screening, including early detection , increased patient anxiety , and physical discomfort . No provider felt that there was enough radiation emitted during exams to cause harm.The potential harms are over screening and over identification of breast lesions and changes that are going to lead to unnecessary worry and unnecessary procedures. [Provider #8].However, providers brought up harms, including unnecessary follow-up procedures . Three (27%) PCPs stated it would have to be automatically calculated and accessible in the electronic health record (EHR) to be useful.I’m just thinking through a busy clinic visit where we have 15 minutes, sometimes less, and spending a significant chunk of that on calculating a risk for breast cancer. We end up doing it for statins, we end up doing it for aspirin, I guess if it already popped up and it was there and I didn’t have to do anything to plug numbers into a calculator, it would be a helpful part of a decision making. [Provider #1].Nine (82%) providers were interested in a calculated breast cancer risk for their patients. However, many felt there were too many barriers to utilizing risk scores in practice, such as time constraints during clinic visits  believed that women over 40 years old should receive yearly mammograms while the remaining two stakeholders  thought biennial mammography was acceptable for the general population. In particular, stakeholders endorsing yearly mammograms are influenced by prior experiences of seeing rapid progression of disease and seeing the negative impacts of delayed diagnosis. One stakeholder stated that social marketing campaigns also promote more frequent mammograms.I think age, either on the low side or on the high side. I mean like continuing mammography in women that are 80 years old that never had a history of breast cancer, and then it comes down to what are you going to do for them at 80 years old. .Although all three radiologists believe in annual screening, two radiologists state that they will defer the decision on frequency to the primary clinician and the patient’s decision. One administrator stated that her organization strongly promotes yearly mammograms, and that they send yearly screening reminders to patients. All three radiologists felt that patients of all ages should be screened at the same rate. However, two patient advocates and one administrator felt that younger and older patients should be screened less frequently.If they have any kind of genetic predisposition, a family member, if they have been tested in the past. Anything that will make them high risk, I think, yes, they should definitely also get yearly mammos. .Two patient advocates, one administrator, and one radiologist stated that patients with a family history of breast cancer should be screened earlier and using supplemental methods.I think a lot of our patients when they come, I think it’s sort of part of their routine. They understand that it’s an annual thing and so we don’t have a time carved out where we routinely speak with them, but certainly if they had questions. .Three radiologists and one patient advocate stated they were confident in discussing mammograms with patients because it is their job to do so. Three stakeholders  tell patients that benefits of mammograms outweigh harms. One administrator does not explain any harms and only describes benefits to patients.When we do our community education, we also explain mammographic breast density and why it is considered putting woman at higher risk for breast cancer. .There is also now a statement about breast density so patients who have either heterogeneously dense or extremely dense breast tissue are required to be told as much and those patients are told that breast density can increase risk for breast cancer and that they should discuss with their provider the utility of adding some sort of supplemental screening test, although that’s where the language sort of stops. .All three radiologists and both administrators state that patients are informed about breast density through a letter. One radiologist, one administrator, and one patient advocate stated that higher density is described to increase breast cancer risk, while two radiologists state that ultrasounds are recommended for patients with higher breast density. All three radiologists and one patient advocate mentioned that perceived benefits of mammograms include early detection and reducing mortality. Five stakeholders  stated that false positives and unnecessary procedures are the harms of mammograms. One patient advocate and one administrator felt that exposure to radiation was a harm and one patient advocate felt that mammograms heightened anxiety.Some of the other, softer side of things of negative consequences are false positive findings, [and] additional biopsies. .There is a level of anxiety that occurs when you are called back to do additional film. Often times when you are called back, you’re not really told what it is they are seeing, what it is they are trying to rule out. You’re just told to come back and get the additional film. And so, I do think that there is an area where it causes a great deal of anxiety, there is a possibility that you might have to have several biopsies because of what is seen. . Five stakeholders  said that breast cancer risk assessment tools could be well-received. However, all radiologists and one administrator were concerned about how accurately it can risk-stratify patients. One radiologist also stated that this type of tool would not be used if its recommendations go against radiologists’ screening philosophy.I would really appreciate it. I think it will be beneficial. Absolutely anything to help the community understand. .I think that’s a great idea, but I don’t think there is enough research data to accurately predict somebody’s risk. Certainly, there is a lot of thought about what is contributory, but if you think of a large population to see how that could be applied, I think there is a potential to miss a lot, especially if this or any risk model suggests that you are maybe at lower risk...We probably wouldn’t use it. .Our study showed diverse stakeholders, including patients, primary care providers (PCPs), radiologists, administrators, and patient advocates, hold divergent views about optimal mammogram screening frequency resulting in general uncertainty. For example, radiologists recommended annual mammograms, consistent with their society guidelines, whereas patients and PCPs were split between annual versus biennial screening, although both favored annual screening among women at higher risk. Breast cancer risk assessment tools may help facilitate decisions about screening intervals, but face barriers to widespread implementation in the primary care setting, including time burden, clinicians’ unfamiliarity with using risk calculators to guide cancer screening, and distrust of risk calculators’ accuracy.One of the major factors influencing women’s decisions to pursue mammography was annual reminders to schedule a mammogram mailed by the radiology department. These reminders are universally applied to women following their initial mammogram, without attention to individual patient risk factors or preferences. Prior studies have shown that reminders are a highly effective means of influencing repeat use of mammography, and possibly more effective than education/motivation or counseling . As a re, radiology, patient advocates, some PCPs) overemphasize the benefits of mammograms to patients, while minimizing potential harms of screening. For example, very few providers informed patients about the possibility of false-positive results, which have a cumulative probability of 61.3% among annual screeners compared to 41.6% for biennial screeners over a 10-year period [Half of the patients interviewed favored annual screening because they were concerned the risks of biennial screening outweighed the benefits. Our interviews with PCPs and stakeholders show that patients are receiving incomplete information: we found that multiple stakeholders (e.g.r period , 20. Howr period –23, inclr period  and exper period .Despite the overemphasis on the benefits of annual screenings, many women express intent to follow their PCP’s recommendation about screening intervals. However, providers are faced with conflicting guidelines from ACOG and the USPSTF, as well as divergent patient preferences, when making recommendations to patients. Furthermore, our interviews revealed knowledge gaps among providers and patient advocates. For example, most providers used family history of breast cancer to determine whether patients are at high risk and most do not mention breast density. However, breast density is an established breast cancer risk factor . FurtherStrengths of our study include a wide set of stakeholders, ranging from racially diverse patients to physicians from multiple specialties to patient advocates, which captured more perspectives regarding mammogram frequency. Limitations of our study include that this was a single institution study conducted at an urban academic medical center so results may not be generalizable to community-based practice settings. Although we interviewed a diverse set of stakeholders, we had relatively few radiologists and patient advocates so responses may not be representatives of these subgroups. Although there were relatively few breast radiologists and patient advocates, because this is a single-institution study, we were able to interview a sizeable proportion of total breast radiologists and total patient advocates working within the department at our institution. Future studies should seek to further investigate the practices and beliefs of third-party stakeholders in this area beyond our single institution.In conclusion, risk stratification tools for cancer screening are in early stages of development and require further research to maximize their clinical utility. As they become more widely adopted, other aspects of implementation and dissemination, particularly acceptability among providers and radiologists, need further investigation.Additional file 1: Supplemental Table 1. Interview guides for providers and key stakeholders. Supplemental Table 2. Interview guides for patients.


Several studies have explored the predictive performance of machine learning–based breast cancer risk prediction models and have shown controversial conclusions. Thus, the performance of the current machine learning–based breast cancer risk prediction models and their benefits and weakness need to be evaluated for the future development of feasible and efficient risk prediction models.The aim of this review was to assess the performance and the clinical feasibility of the currently available machine learning–based breast cancer risk prediction models.We searched for papers published until June 9, 2021, on machine learning–based breast cancer risk prediction models in PubMed, Embase, and Web of Science. Studies describing the development or validation models for predicting future breast cancer risk were included. The Prediction Model Risk of Bias Assessment Tool (PROBAST) was used to assess the risk of bias and the clinical applicability of the included studies. The pooled area under the curve (AUC) was calculated using the DerSimonian and Laird random-effects model.Q=576.07, I2=98.44%; P<.001). The results of head-to-head comparison of the performance difference between the 2 types of models trained by the same data set showed that machine learning models had a slightly higher advantage than traditional risk factor–based models in predicting future breast cancer risk. The pooled AUC of the neural network–based risk prediction model was higher than that of the nonneural network–based optimal risk prediction model . Subgroup analysis showed that the incorporation of imaging features in risk models resulted in a higher pooled AUC than the nonincorporation of imaging features in risk models . The PROBAST analysis indicated that many machine learning models had high risk of bias and poorly reported calibration analysis.A total of 8 studies with 10 data sets were included. Neural network was the most common machine learning method for the development of breast cancer risk prediction models. The pooled AUC of the machine learning–based optimal risk prediction model reported in each study was 0.73 , with a high level of heterogeneity between studies (Our review shows that the current machine learning–based breast cancer risk prediction models have some technical pitfalls and that their clinical feasibility and reliability are unsatisfactory. Of all the cancers worldwide among women, breast cancer shows the highest incidence and mortality . Early aTraditional risk factor–based models such as Gail, BRCAPRO, Breast Cancer Surveillance Consortium, Claus, and Tyrer-Cuzick models have been well-validated and used commonly in clinical practice, but these models developed by logistic regression or Cox regression or those presented as risk scoring systems have low discrimination accuracy with the area under the receiver operating characteristic curve (AUC) between 0.53 and 0.64 -12 and tThis systematic review and meta-analysis was performed according to the PRISMA  statement , the ChePapers on machine learning–based breast cancer risk prediction models were searched in PubMed, Embase, and Web of Science by using the terms “machine learning OR deep learning” AND “mammary OR breast cancer OR carcinoma OR tumor OR neoplasm” AND “risk assessment OR risk prediction” published until June 9, 2021, and limited to papers published in English. The complete search strategy is detailed in Studies describing development or validation models for predicting future breast cancer risk were included in our study. The inclusion criteria were as follows: (1) breast cancer risk prediction model developed using a machine learning algorithm, (2) mean follow-up period for cohort studies should be longer than 1 year, and (3) future breast cancer risk is the assessment result. The exclusion criteria were as follows: (1) review or conference or editorial or only published abstracts, (2) the original full text not available or incomplete information, and (3) studies with no AUC or C-statistic and its 95% CI. When papers included the same population, studies with larger sample size or longer follow-up periods were finally included.Two researchers independently collected data on the first author, publication year, geographic region, study design, study population, sample size, study period, age of participants, time point for breast cancer risk prediction, name of the risk prediction model, number of participants and cancer cases in test data set, input risk factors, development and verification methods, and AUC with its 95% CI. The Prediction Model Risk of Bias Assessment Tool (PROBAST) was used to assess the risk of bias (ROB) and the clinical applicability of the included studies ,26. Any Q test and I2 value were employed to evaluate the heterogeneity among the studies. High values in both tests  showed high levels of inconsistency and heterogeneity. We also calculated an approximate 95% prediction interval (PI) to depict the extent of between-study heterogeneity [The discrimination value was assessed by AUC, which measures the machining learning risk prediction model ability to distinguish the women who will and will not develop breast cancer. An AUC of 0.5 was considered as no discrimination, whereas 1.0 indicated perfect discrimination. We calculated the pooled AUC of the risk models by using DerSimonian and Laird’s random-effects model . A head-ogeneity . Sensitiogeneity ,30. All A total of 937 papers were identified, and 8 studies with 10 data sets met our inclusion criteria and they were finally included in the meta-analysis  7,19-2121,31-34.PROBAST was used to assess the quality of the included studies in terms of both ROB and clinical applicability. All 8 studies demonstrated a low applicability risk; only 1 of the papers had low ROB , indicatQ=576.07, I2=98.44%; P<.001) (Pheterogeneity<.001) , with a high level of heterogeneity between studies ( P<.001) . We also P<.001) . The res P<.001) A was higty<.001) B-3E.Q=131.42; I2=95.43%; P<.001)  (Pheterogeneity=.001), respectively (Pheterogeneity=.12) (Pheterogeneity=.10)  A, which  P<.001) B. When sectively . Subgrouity=.12) . Our resity=.10) .P=.46)  . AccordiP=.46) .In this meta-analysis, 8 studies showed that the pooled AUC of machine learning–based breast cancer risk prediction models was 0.73 (95% CI 0.66-0.80). The results of head-to-head comparison of the performance difference in 2 types of models trained by the same data set showed that machine learning models had a slightly higher advantage than the traditional risk factor–based models in predicting future breast cancer risk. Machine learning approaches have the potential to achieve better accuracy and incorporate different types of information, including traditional risk factors, imaging features, genetic data, and clinical factors. However, of note, the predictive ability of the machine learning models showed substantial heterogeneity among the studies included in this review.Machine learning represents a data-driven method; it has the ability to learn from past examples and detect hard-to-discern patterns from large and noisy data sets and model nonlinear and more complex relationships by employing a variety of statistical, probabilistic, and optimization techniques . This caIn our stratified analysis, neural network–based breast cancer risk prediction models incorporating imaging features showed superior performance. This result suggests that the incorporation of imaging inputs in machine learning models can deliver more accurate breast cancer risk prediction. Previous breast cancer risk assessments have already recognized the importance of imaging features in mammography ,12, but The findings in this study showed that neural network–based models that predicted short-term (≤5 year) breast cancer risk had slightly better discriminatory accuracy than models predicting long-term risk, although confidence intervals overlapped. Improvement of public health literacy and the popularization of healthy lifestyles motivated more opportunities for women in their lifetime to participate in breast cancer prevention and screening and modify their identified modifiable risk factors associated with breast cancer. Unlike many currently known risk factors that do not change and maintain constant risk values, short-term risk factors may change over time. The cumulative effect of these changes may reduce the incidence of breast cancer. Therefore, it is unreasonable to predict the long-term risk of breast cancer by using these risk factors, which may lead to high probability of false-positive recall.Our study showed several issues regarding machine learning model reliability. The PROBAST analysis indicated that machine learning models have technical pitfalls. First, most machine learning models did not report sufficient statistical analysis information, and only few studies ,31 proviThis review had several limitations. First, most of the included studies ,31-34 diIn summary, machine learning–based breast cancer risk prediction models had a slightly higher advantage in predicting future breast cancer risk than traditional risk factor–based models in head-to-head comparisons of the performance under the same experimental settings. However, machine learning–based breast cancer risk prediction models had some technical pitfalls, and their clinical feasibility and reliability were unsatisfactory. Future research may be worthwhile to obtain individual participant data to investigate in more detail how the machine learning models perform across different populations and subgroups. We also suggest that they could be considered to be implemented by pooling with breast cancer screening programs and to help developing optimal screening strategies, especially screening intervals.


Male breast cancer is rare and frequently diagnosed at later stages of disease with low survival rates. There is a lack of knowledge of how breast cancer impacts men's occupations. Methodology. Twenty-four men with breast cancer participated in semistructured phone interviews. Data was open-coded and analyzed for themes. Findings. The six major themes are as follows: (1) death as a reality, (2) unique personal insights, (3) social environment, (4) interactions with the healthcare system, (5) decreased engagement in occupations, and (6) finding meaning in new occupations.  This study is aimed at understanding the lived experiences of men with breast cancer and their changes in occupation.  The healthcare team can improve the patient experience by discussing and responding to the client's experience throughout the diagnosis, intervention, and survival continuum. The scope of occupational therapy is well suited to address the needs of men with breast cancer to maintain optimal levels of functioning. Men diagnosed with breast cancer (MBC) face many challenges from diagnosis through the treatment process. This rare disease in men has an approximately 1.2 per 100,000 incidences and 2710 new diagnoses expected in the United States , 4. MaleA small bank of literature indicates there are a host of emotional and psychosocial challenges faced by men diagnosed with breast cancer , 9. ManyOccupational therapists have delved into understanding the female experience of breast cancer and its impact on everyday occupations, occupational engagement, and interaction with the environment –19. ThesThis study utilized a qualitative, phenomenological approach to foster the understanding of our male participants' experiences with breast cancer. The use of semistructured interviews allowed researchers to gather personal narratives about the breast cancer experience concerning participation in everyday life while providing participants the opportunity to share personal experiences and perspectives with minimal guidance from the interviewer.Recruitment was initiated through the primary author's personal contacts with male breast cancer survivors. We utilized snowball and convenience sampling with assistance from Male Breast Cancer support groups and online organizations. A recruitment flyer was sent to the support organizations and disseminated to members through email blasts. Twenty-nine men responded to the recruitment flyer; twenty-four men completed interviews. The inclusion criteria of this study required that all participants be (1) male; (2) an individual with a personal experience of a breast cancer diagnosis ; (3) older than 18 years of age; and (4) willing to consent to participate in qualitative interviewing for research-based data collection and use. Participants who could not speak English or communicate verbally were excluded from the study due to the interactional nature of the interviewing process.This research study was approved by the Institutional Review Board in January of 2018 as IRBNet ID #1167096-1 at Elizabethtown College, Elizabethtown, PA, USA. All participants completed a verbal informed consent before commencing the interview.Semistructured telephone interviews were conducted between January and March 2018. A semistructured phone interview format  was deveResearch team members, all females, were randomly assigned participants for interviews. Participants in the USA called into a Google Voice number created for this study. International calls used Skype voice. Each interview was recorded, downloaded into a password-protected file, and transcribed using VoiceBase. A research team member checked the transcripts word-for-word with the audio recording and added notes to reflect participants' expressions of emotion. Researchers followed up with participants on multiple occasions to clarify interview responses. Data saturation occurs in collection through a deductive process and inductively during analysis . Data coEach transcript was read, open-coded by hand, and themed independently by two members of the primary research team. The primary research team jointly confirmed the themes and conclusions. A second research team of occupational therapy graduate students, 2 female and 1 male, uploaded the cleaned transcripts to Dedoose and performed an additional two rounds of open coding and theming. These results were compared to the first round of coding results and finalized. Inductive thematic saturation  was achiThe method of researcher triangulation is a validation strategy to view the research data from multiple different points . MultiplTwenty-four men completed interviews describing their experience with breast cancer. Five individuals did not follow up with attempted email and telephone communication regarding scheduling and participation. We identified six major themes: (1) death as a reality, (2) unique personal insights, (3) social environment, (4) interactions with the healthcare system, (5) decrease in engagement in occupations, and (6) finding meaning in new occupations.I appreciate life a lot more. Before my cancer, I didn't take life seriously. I took life for granted. I didn't appreciate people in my life and the things I see. So, after cancer, [it] was a good kick in the butt. Just how much you appreciate it, and also made me realize to go after my dreams, chase it, and achieve it. Go after it and every day is a gift. (P-4)Receiving a potentially life-threatening diagnosis forced ideas of mortality to be consciously considered for many men. This realization of death led to a sense of proactivity that increased their efforts to reach their dreams. Understanding death as a reality positively changed individuals considering their life journey as a gift. I think [the diagnosis of cancer] really emphasized that for me the fact that I had vulnerabilities of this nature. That I needed to stay focused a little more on my health in terms of eating properly and losing some weight and getting some more exercise, and that sort of thing. (P-1)For other men, the reality of receiving a life-threatening diagnosis increased their consciousness of their health, resulting in routine and habit changes. Throughout the experience of being diagnosed with a life-changing disease, all participants experienced an abundance of feelings that forced them to face the challenges ahead. However, these feelings also led to changes in values and beliefs that ultimately shaped them as individuals today.There's a comfort in having your loved ones nearby. That goes beyond having a conversation with them, or having them get coffee for you, or help you clean out the drain [from mastectomy], or whatever. It's the presence that is comforting. (P-1)Participants shared personal insights and perceptions and drew on inner strength and external support as their ability to perform roles and occupations was challenged. Support systems provided encouragement and reassurance of the self. I found that when I was sharing, it is where the courage and strength came from. When it was uncovered, that I always had in me. I never knew and how important it was for this to come out and to be shared so that people know. (P-19)I think that being a male and having had breast cancer has given me strength in a way and it's given me purpose because I saw the benefit of speaking out. (P-23)Additionally, many men suggested the importance of being open and sharing with support groups. Some men found that by being honest and willing to share their experiences, they could attain the emotional and physical support that they needed. I feel very guilty about my ability to do things, you know, with my wife that I used to be able to do more easily (P-15).As treatment progressed, some men reported changes in occupational participation due to side effects, including fatigue, weakness, pain, mood changes, and loss of libido. Feelings of guilt for not being able to complete previous occupations required to maintain a household, perform job responsibilities, or keep the same relationships with family and friends were reported by participants. I had like prepared this whole Facebook Post, and I feel so stupid saying it now, but I called it chest cancer instead of breast cancer because I was embarrassed. And then my wife convinced me, she's like ‘No, you know, tell it how it is'. So, I had this whole big post ready for Facebook and everything, and I just like held my finger over that post button for five minutes just scared to do it, and my wife grabbed my hand and we did it together… I definitely think it's because society views it as a woman's disease. And I thought people would consider me less of a man because I had breast cancer. (P-21)Body image was significantly impacted and became a source of stress and fear of what others perceived about their scars, compounding the perception that breast cancer is a women's disease. The surgery and my scar were going to tell a story. It is my battle wound. The scar is just going to be there, and it's a conversation piece (P-16).In contrast, other men specifically discussed that the mastectomy scars did not affect their ability to engage in social occupations shirtless. One participant described his scar in a positive sense,Personal factors, such as beliefs, values, self-concept, and motivation, were apparent in how participants coped with their initial breast cancer diagnosis and their survivorship journey after that. There were mixed negative and positive self-concepts after receiving a women-dominant breast cancer diagnosis or acquiring a mastectomy scar.When I would tell people, that's when it would bother me because they wouldn't believe you. I'd say, “I've got cancer.” “What kind of cancer?” “Breast Cancer.” “Oh, you full of shit, man!”… and I was like, “No, I'm not, you know, I wished I was”… but that is the part that bothers me the most because it happened even at the cancer center where I would get treatment. (P-17)I told all my friends I had chest cancer, and nobody really questioned what chest cancer is. So, I kind of got away with it there for a couple of years, just calling it chest cancer. And then when I finally came out of the closet, so to speak, and said I had breast cancer, um, people kind of looked at me differently. (P-7)Due to the small population of men with breast cancer experience, many of the participants shared how society has shaped breast cancer into a women's disease. Because of that, they have experienced a sense of stigma behind their unique condition. Many men felt that the public  were unaware and lacked the knowledge to understand breast cancer affecting both men and women. So, I found the men's group. And even though I was the only one with breast cancer, I found it more comfortable and helpful. But I think that fact they had a specific men's group, it was very important in my journey and in my recovery… I really found that women would react to me in a different way (P-23)Social system support came from the family, community, and religious organizations. While help from family and friends was emphasized as necessary throughout these journeys, men expressed the need for more information from the health care team. Due to the rarity of breast cancer in men, many participants lacked communication and support from people in similar situations to their own. All the participants expressed positive feelings towards involvement in the male breast cancer community. Due to shared diagnoses, these men emphasized the importance of connecting with others in similar situations for a network of emotional and information support.I think the doctor told me one time that I'm at 90 percent success rate where I'm at in treatment, and I said, ‘Well, that's pretty good, and he goes ‘You know, I'll just tell you this is data for women' and I said ‘What about data for me' and he said ‘Well, we don't know. We don't know where you are at.' And I was like, ‘well, that is a bunch of bull,' but that's the way it is because all the concentration is on women. (P-17)The level of awareness and knowledge surrounding male breast cancer can affect men's quality of care from the medical community, ultimately affecting their occupational performance. All the participants acknowledged hindrances and benefits of their interactions with the healthcare system and professionals throughout their journey with breast cancer. My oncologist you know he is a wealth of information you ask him a question and his answer is ten minutes long you know can be a short answer of just yes, but he goes on and on and you know everything. You know on the way they kept me at ease and helped me understand everything and made it feel much better. (P-2)She was now tell me your journey with this with cancer and I was like, oh my god you want to hear what I'm going through. (P-14)Positive interactions with healthcare providers put the men at ease and built a collaborative relationship. I had some issues with my insurance company with getting more tests done. I guess insurance company's computers weren't geared towards men as well, for these kinds of tests, so I got a letter that my sex change was approved, and it kind of destroyed me mentally. (P-14)The person who had the most impact on my recovery was a onocology nurse navigator, who called me… I had some fairly lengthy conversations about how, you know, patients of her's have reacted to the medications, and to the surgical procedure itself. And provided a level of both knowledge and comfort for me that…and I think a lot of people look at it like no one's ever going through this but me…. So, the recognition that…yes you're…I am unique and my experiences are unique, but there are hundreds of people out there, thousands of people out there, who are going through their own unique path with the same thing. (P-17)Along with the lack of information for men struggling with breast cancer, participants revealed how the physical environment, printed educational resources, and insurance coverage within the healthcare system are targeted solely toward women. They reported a preponderance of pink, pink ribbons, pink robes, and florally decorated ice packs. The female-oriented healthcare environment negatively impacted the participants. This was not the case for all participants, with some expressing satisfaction with the quality of information and support provided. And the radiologist looked at me, and I can tell that she was kind of nervous. And she starts adjusting the machine, up and down and back and forth. And I could tell she's really nervous, and I can tell she just isn't quite sure what to do with a man. And I actually turned her on I said, ‘you've never done a mammography on a man have you?,' she said ‘No.' I said, ‘OK, why don't you think of me as a flat chested woman.' And do whatever you do for a woman like that. Then it's like a light bulb went on over her head. (P-1)Additional challenges with the healthcare environment centered around the lack of awareness of many healthcare providers, which led to misdiagnosis and delayed diagnosis. Overall, the health care environment presented multiple barriers to the men in this study. Several men were fortunate to develop strong connections with their healthcare providers resulting in the sense of trust.I used to be able to go to the gym on a Saturday morning and work out and then come home and do yardwork for a few hours, and now I am not capable of that. If I go to the gym Saturday morning, I only have an hour or two left of work in me when I come home. (P-15)I got behind on housework. Slept a lot. Went from the bed to the couch a lot. I'm not out doing a lot of the things that I used to before (P-2).I lost interest in my hobbies. I like to fish. I like to play golf. I no longer golf, and I haven't been fishing from the day this started (P-9).The rigorous treatment protocols for cancer take a toll on the person and the desire to engage in occupations. Side effects of various treatments such as surgery, chemotherapy, radiation, and medication resulted in alterations to daily routines, roles, and participation in occupations. When I started having problems with my memory, I kind of lost my confidence in being able to remember because you kind of have followed along like I've asked the customer to do this, and now I'm asking the customer to do that. I didn't want to go back to work, and I didn't go back to work. I never did go back to work. (P-13)I was off for a couple weeks for my surgery and then when I was going through chemotherapy, I would take off the day of the chemotherapy initially and then towards the end of my chemotherapy um started to catch up with me. So, I was working four days a week when I began my chemotherapy and by the end, I was working three days. (P-15)Due to side effects, the inability to work affected many of the men in the study and resulted in disruption and changes to work schedules. Extended periods away from work were frequently required of men who underwent surgery. The aspect of losing my libido was you know that's had an effect on my wife it's denying her an aspect of our marriage, and that's been hard (P-15)Participants reported the impact on their socially ascribed roles of husband and father. Well, I know at work, I've had to get guys to help me do stuff that I never had to have the help to do (P-17)I'm the breadwinner, you know, I mean my wife works as well, but I'm the main breadwinner, so I need to be out there doing it (P-21).Asking for help was a challenge to masculinity. Overall, the men in our study experienced a decrease in engagement and participation due to the effects of breast cancer and its treatment. Fatigue, memory problems, joint pain, and mobility challenges contributed to altering or completely giving up on activities such as cooking and meal preparation, exercise routines, pet care, auto maintenance, driving, and paid employment. Ultimately, these changes in daily routines, meaningful activities, leisure, work, and roles pushed some of the men to develop new occupations in life.The goal was if I can help one male through that, it was done. I achieved my goal. But one person, you know, I mean once you get that satisfaction from that, you just have to keep going. (P-16)So, part of my support now is trying to educate people and support especially men who have never met another male breast cancer survivor (P-15).I thought you know what I've left my teaching as an elementary teacher and I'm thinking and realizing my new path is going to be teaching about this. [P-14]Most participants found meaning in new occupations related to advocacy. This new role centered around building awareness and support for men past, present, and future with breast cancer through public speaking, joining male breast cancer organizations, participating in research, volunteering, and educating others. Some participants expressed the move into advocacy as a natural progression from their profession. Men described themselves in terms of becoming activists. Multiple participants started nonprofit foundations focused on meeting individual and societal needs related to male breast cancer. Some expressed finding new occupations through pursuing their dreams. It is not uncommon when being diagnosed with a serious illness such as cancer that a person's life perspective changes. Some men took their diagnosis of breast cancer as an opportunity to engage in occupations that they have always wanted to undertake.Each man who participated in our study shared their journey of becoming an advocate for male breast cancer to ensure that men in similar situations had the necessary information and support.The men in this study revealed the various impacts breast cancer had on their occupations throughout everyday life. They shared what it was like living with a widely female diagnosed disease, the personal implications, and the resulting changes in their occupations. Similarities in cultural norms across the world consisted of different gender norms, including the idea of hegemonic masculinity . This coChanges in activities of daily living (ADL), instrumental activities of daily living (IADL), social participation, and work were connected to the diagnosis of cancer and side effects including fatigue, pain, physical limitations, support systems, and social perceptions. Declines in functional status, ADLs, and IADLs for all types of cancer survivors, male and female, are well documented –28. ADLsEvery participant related a story of their involvement in and the importance of advocacy without a direct question or prompt. This highlights the importance and weight of advocacy in the lives of these men. Self-advocacy is defined as “a means for patients to exert control over complex treatment decisions and uncertain health outcomes, address their unmet needs, and improve their healthcare experience” . In a quThere were high expectations of the men in this study to maintain their employment, causing some men to carry a heavy burden when they had to stop or limit working due to treatment, with participants noting the need to maintain routine and normalcy as well as their professional identity. These themes match those identified in a systematic review of returning to work after breast cancer and other studies including multiple types of cancer , 36, 37.The experience of a decrease in occupational performance led to changes in role fulfillment in these men, such as being a husband, partner, or father. Although the desire to fulfill the expectations of these roles was still present, the demands exceeded their ability to perform these tasks physically. Societal stigmas in the environment pushed the men to challenge concepts of their identity and body image. This effect impacted occupations, as some men reported embarrassment in social occupations with people who were not aware of their diagnosis to avoid further questioning. Social participation is another area frequently addressed by oncology occupational therapists , 31, 40.The diagnosis of cancer provoked mortal salience, the recognition of the inevitability of death, for these participants. The men reported an abundance of conflicting feelings. The sense of death's imminence prompted many of the participants to reevaluate their lives and make changes in their routines, habits, values, and beliefs. Although cancer is associated with alterations in future expectations, cancer survivors demonstrate resilience and continue to demonstrate positive social well-being and social growth .Trust, communication, and respect are foundations of client- or patient-centered care  leading Our results concerning the ability to fulfill required and desired roles were consistent with findings from a previous qualitative study of women with breast cancer and men with bowel cancer highlighting the importance of social, emotional, and physical support in maintaining a sense of self-worth –19, 30. The robust sample size of 24 provided a significant amount of data for a comprehensive understanding of the lived experience of the participants. This study is the first of its kind to examine the occupations of men with breast cancer. Triangulation through the data collection and analysis process decreases bias and increases trustworthiness.Convenience sampling through support groups is a significant limitation of this study. Men involved in the support groups were not fully representative of the entire population of male breast cancer. Bias in the results is evident in the fact that every participant in this study was involved in advocacy and support groups. The study does not reflect the experiences of men not involved in advocacy and support related to a breast cancer diagnosis. Participants discussed their path to advocacy involvement and data does not provide insight into why some men do not go into advocacy and support groups. Self-selection limits generalizability of the study.Participants in this study were at various stages of the cancer survivor trajectory. This study does not reflect the different experiences associated with different stages of the breast cancer treatment and survivorship timeline. Additional research is needed to explore the specific relationship between disease sequelae and occupational performance, changes in occupational performance overtime for cancers survivors, and the efficacy of occupational therapy to address changes.The aim of this research study was to better understand how men experience changes in occupation when diagnosed with breast cancer. The lived experiences shared by the men in this study provide insight into the physical, emotional, and social challenges they faced from diagnosis through treatment and into the survival phase. Participation in meaningful occupations were altered for all participants by the experience of male breast cancer. Participants discussed ways of adapting, such as seeking out needed support in their environment or engaging in new occupations such as becoming involved in advocacy groups. Evidence from this study supports that a sense of self, identity, and ability to interact with the social environment strengthened engagement in meaningful occupations. The lived experiences of the men in our study were like the lived experiences of women with breast cancer, men with prostate cancer, and bowel cancer survivors , 30, 35.All health care providers must maintain a client-centered approach that provides space for the unique experiences of each client and not fall into stereotyping which may stigmatize or marginalize the client. Occupational therapy has the ability promote engagement in meaningful occupations and therefore promote overall health and well-being , 33, 39


Globally, breast cancer is the leading cause of cancer deaths, accounting for 15.5% of female cancer deaths in 2020. Breast cancer is also the leading cause of female cancers in South Africa. The rapid epidemiological transition in South Africa may have an impact on the trends in breast cancer mortality in the country. We therefore evaluated the trends in the breast cancer mortality in SA over 20 years (1999–2020).Joinpoint regression analyses of the trends in crude and age-standardized mortality rates (ASMR) of breast cancer among South African women were conducted from 1999 to 2018 using mortality data from Statistics South Africa. Age–period–cohort regression analysis was then conducted to evaluate the independent effect of age, period, and cohort on breast cancer mortality, and analysis was stratified by ethnicity.The mortality rate of breast cancer  increased at around 1.4% per annum : 1.4%, 95% CI:0.8–2.0, P-value< 0.001). Young women aged 30–49 years  had increased breast cancer mortality. The risk of breast cancer mortality increased among successive birth cohorts from 1924 to 1928 but decreased among recent cohorts born from 1989 to 1993. In 2018, the breast cancer mortality rate among Blacks  was around half of the rates among the non-Blacks. .Contrary to the trends in high- and middle-income countries, breast cancer mortality increased in South Africa especially among young women. Breast cancer prevention programs should be intensified and should also target young women. The marked disparity in ethnic burden of breast cancer should be considered during planning and implementation of interventions. Globally, breast cancer is the leading cause of cancer deaths, accounting for 15.5% of female cancer deaths in 2020 . By law, it is mandatory for all deaths in South Africa to be reported to the Department of Home Affairs (DHA) . Causes The population denominators for calculating the mortality rates were the mid-year population estimates of women (≥15 years) stratified by ethnicity and 5-year age group, as obtained from published data of Stats SA from 2002 to 2018. The annual mid-year population estimates for 1999–2001 were obtained by assuming the constant inter-census rate and increment between two South African population census of 1996 and 2001.The vital registration methodology and records of South Africa have been internationally adjudged to be comprehensive . JoubertEthical approval for the conduct of this study was obtained from the Human Research and Ethics Committee  of the University of the Witwatersrand (clearance certificate number: M190544). Anonymized data with no risk of re-anonymization were utilized.Data were imported into Stata version 16  statistical software for statistical analysis. Data validation and data cleaning were done. Descriptive statistics such as frequency and mean (± standard deviation) were analyzed. The annual proportion of breast cancer in relation to all women and gynecological cancer mortality was calculated.The annual crude mortality rate (CMR) was calculated by dividing the annual breast cancer mortality among women aged ≥15 years by the mid-year female population (≥15years). The calculation was stratified by ethnicity  from 1999 to 2018.Age-specific mortality rate was also calculated by dividing the cumulative age-stratified mortality of each 5-year age group  by cumulative age-stratified mid-year population of each age category. The annual age-standardized mortality rates (ASMR) were calculated using the direct method of standardization, and the Segi world standard population was the weighted population.ia is the age-specific rate of the i th 5-year age group and iw is the corresponding number of persons (or the weight) in the same 5-year age group i of the Segi world standard population.where The standardized rates were stratified by ethnicity. All rates were expressed per 100,000 women.A joinpoint regression analysis of the trends in the overall cancer mortality of breast cancer (stratified by ethnicity and age groups) was performed with the Joinpoint Regression software, version 4.9.0.1 . The Joinpoint Regression software fit a Poisson regression in which ln(rate) is the outcome and the year of occurrence is the explanatory variable. Log-linear modeling with four maximum joinpoints and 4,499 Monte Carlo permutation tests were conducted for each of the trends in ASMR.The equation of the joinpoint trend is: –24where β = coefficient of the calendar year, ln = natural logarithm, and C = constant (or intercept)The annual percent change (APC) of the cancer rates between a previous calendar year “X” and the next calendar year “X+1” isFrom Eq. (i),where e = 2.7The APC is equivalent to the Average Annual Percent Change (AAPC) if there are no joinpoints. However, when there are joinpoints, the segmental APC  was calculated and the AAPC was iteratively calculated as a weighted average of all the segmental APCs. Conventionally, a positive or negative AAPC (or APC) with P-value<0.05 was taken as a statistically significant increased or decreased trend. If the P-value of the AAPC was >0.05, the trend is taken as a non-significant increased or decreased trend. If the AAPC is between -0.5 and + 0.5 with P-value >0.05, the trend is reported as stable.A–P–C modeling has been used by social scientists, demographers, and epidemiologists to assist in understanding the impacts of age, period, and birth cohort on the trends in prevalence of social, demographic, or disease outcome or rates. This modeling technique assists to disentangle the effect of chronological age (age effect), from “period effect”  and “cohort effect”  –29.Arithmetically, the relationship between age, period, and birth cohort is given asAge = period (year of event) – cohort (year of birth). (or birth cohort = period – age) …(iii)However, the A–P–C model assumes a Poisson distribution of the mortality rates (dependent variable) with age, period, and birth cohort as the covariates/independent variables.The general equation of the A–P–C model is expressed asY is the breast cancer mortality; X1, X2, and X3 are the age period and birth cohort with their corresponding effect estimates of α, β, and γ, respectively; α0 is the intercept; and ε is the residual.where Indeed, the natural logarithm of the mortality rates in Eq. (iv) becomes a linear or additive function of age, period, and birth cohort as expressed thus:whereE[Mij] represents the expected mortality rate at 5-year age group i  and period j ; ijD and ijP are the number of deaths and corresponding population size in the i age group and the j period, respectively.iα represents the age effect in the age group I; jβ denotes the period effect during a j period, kγ corresponds to the cohort effect among the thk (k =i+j–1) birth cohort, and μ is the intercept.cancer.gov) with accompanying R Studio codes (https://github.com/CBIIT/nci-webtools-dceg-age-period-cohort) as developed by Rosenberg et al. to produce estimable parameters of the A–P–C of the trends in breast cancer mortality. The webtool utilized the weighted least squares estimator (The above arithmetic equation (iii) of the relationship between age, period, and cohort shows a perfectly linear relationship or linear dependency with inherent problem of collinearity when all of age, period, and birth cohort are added as covariates during the Poisson regression modeling of mortality rates. Therefore, reliable unique estimates for each of age, period, or cohort will ordinarily be difficult to obtain from the regression model because the covariate matrix will not be full-rank. This phenomenon is known as “identification” problem. Multiple methods have been proposed to circumvent the identification problems, but each has its merits and demerits . The metstimator .Before the A–P–C analysis, data of breast cancer mortality were further prepared. Age was categorized into 5-year age groups from 15 to 75 years , and the year of mortality  was also categorized into 5-year categories from 1999 to 2018 . A Lexis matrix was then formed with age category of the mortality data as columns and the corresponding period as rows . The corresponding population at risk was also calculated for each age group and period. The above A–P–C data preparation was done for each of breast cancers and then stratified by ethnic groups . These data were then imputed in turn into the A–P–C webtool .Several estimates are obtainable from the A–P–C regression modeling webtool . HoweverDuring the 20-year period from 1999 to 2018, 4,386,517 deaths were reported among South African women who were 15 years and older. Of these female mortalities, around 8.24%  were cancer-related mortalities. Deaths due to breast and gynecological cancers constituted around 37.39%  of the cancer mortalities among women in the country. Breast cancer  was responsible for around 41.27% of breast and gynecological deaths. The proportion of breast and gynecological cancer deaths due to breast cancer appears to be stable during the study period Table 1.Mortality from breast cancer increased from 1,848 in 1999 to 3,790 in 2018 Table 1.The ASMR of breast cancer was second highest behind cervical cancer Figure 2Joinpoint regression analysis of breast ASMR showed two trends: the first was a steep rise in ASMR at around 5.9% per annum from 1999 to 2004  and then a slow increase at 0.5% per annum from 2004 to 2018  Table 2.Blacks followed by Whites had the highest annual number of breast cancer deaths throughout the study Table 2.In 2018, the mean age at death from breast cancer in South Africa was 59.98 ± 15.67 years and had been between 59 and 60 years during the study period (1999–2018) Table 2.In 2018, the age-specific death rates of breast cancer increased with increasing age. Breast cancer mortality rates were lower than cervical cancer rates from 15 years till 60–64 years and then became the highest afterward to reach a peak at 75 years and above , other women aged 30 years and older generally had an increased annual mortality rate of breast cancer  from 1999 to 2018  between 2004 and 2018, whereas women aged 70 years and older had stable trends during a similar period 9.Joinpoint regression modeling of the age-specific death rates of breast cancer revealed that Black teenagers  and young women aged 20–24 years  respectively had nearly stable trends and a non-significant decline in breast cancer mortality rates from 1999 to 2018. All Black women aged 25 years and older had increased breast cancer death rates   whereas there was a non-statistically significant rise in mortality rates among women aged 35–44 years , 50–54 years , 60 years and older , Indian/Asian aged 45–49 years   had non-statistically significant increased rates whereas women aged 45–49 and 55 years and older  had statistically significant increased mortality rates  of breast cancer mortality trends over the study period (1999–2018) was around 1.47% per annum (95% CI: 0.91%–2.04%). Table 3.The overall local drift of breast cancer is<0  for women younger than 25 years, and women older than 24 years had positive local drifts, with women aged 30–39 years and 75 above having drifts >2%  of overall and ethnic breast cancer mortality increased with age, portraying a J-curve with a steep increase in risk from 70 years  and then increased  by 9% from 2004–2008 to 2009–2013 . Subsequently, there was a 5% reduction in risk from 2009–2013 to 2014–2018  Table 3.The cohort RR of breast cancer mortality among those born during 1924–1928  was the least, and the risk increased among successive cohorts to a peak RR among those born between 1984 and 1988 . Afterward, there was a decline in risk among successive birth cohorts to 1.57 among birth cohorts from 1999 to 2003 Table 3.To our knowledge, this is the first study in SSA to utilize both joinpoint and A–P–C regression modeling techniques to evaluate the national trends in breast cancer mortality, stratified by ethnicity. This temporal trend analysis over 20 years (1999–2018) in South Africa is necessary to evaluate the impact of previous interventions and guide prioritization of health resources.The mortality rate of breast cancer in South Africa  was slightly lower than the average rates in Southern Africa , 31.As reported globally, we observed a significant period effect on the trends of breast cancer mortality in South Africa , 28. TheIn line with previous studies, we found that there was a strong age effect on the breast cancer mortality trends as there was increased risks and rates with increasing age , 28, 42.In comparison with postmenopausal breast cancer, the premenopausal breast cancer type is usually more aggressive, advanced-stage at diagnosis, triple-negative, and with worse prognosis , 48. RemNotably, South African women aged 50–59 years had nearly stable mortality trends (AAPC = 0.5%). Similarly, women aged 50–69 years had the lowest AAPC in Sub-Saharan Africa  and in all other global regions from 1990 to 2017 . This paThe increased mortality rate of breast cancer among South African women older than 70 years may be associated with increasing life expectancy and comorbid factors , 48, 50.We reported a rise in RR of breast cancer mortality among South African birth cohorts from 1924 to 1988 0.5 to 1.64) and a subsequent decline among recent cohorts from 1988 to 2003. A decline in cohort mortality risks around 1920 and 1960 in USA and East Asia, respectively, was previously reported , 51, 52. to 1.64 We observed that ethnic disparity in breast cancer mortality in South as Blacks had around half the breast cancer mortality rates of Colored, Whites, and Indian/Asians. In contrast, Blacks had higher breast cancer mortality rates as compared with Whites in USA , 59, 60.Our analysis showed that breast cancer mortality RR increased among successive Black and Colored cohorts from 1924 to 2003 and Blacks had the highest mortality risk among recent cohorts (1974–2003). Historically, Blacks had protective breast cancer risk factors such as increased prevalence of late menarche, early age at first birth (Black South African culture supports early/teenage pregnancy), high parity, prolonged breastfeeding practices, and high-fiber diet , 27, 60.The earliest White and Indian/Asian birth cohorts had relatively high mortality RR, which was nearly stable until 1969–1973 when the RR among Whites slightly increased whereas that of Indian/Asian cohorts declined. The increased mortality risk among the recent White cohorts may be driven by modifiable factors such as obesity, smoking, alcohol consumption, and use of hormonal contraceptives, whereas the decline among Indian/Asians is similar to the cohort trends in East Asia and America that was attributable to improved awareness, screening, and improved healthcare , 52, 62.The period effect of breast cancer mortality from 1999 to 2018 was noted among Blacks and Coloreds, with rapid drifts of 4.6% and 2.5% per annum, respectively. The improved socioeconomic status and shift in reproductive behaviors without commensurate access to screening and oncological care among Blacks and Coloreds led to increased breast cancer mortality from 1999 to 2018. Nonetheless, a reduced acceleration among Blacks (APC: 5.0% vs. 3.0%), in the later period (2004–2018), may be attributed to some improvement in public reproductive health and oncological services , 52, 57.The period effect of breast cancer mortality was not statistically significant among Whites and Indian/Asians, and they had low net drifts . Indeed, Whites and Indian/Asians had access to private health facility with optimum oncological facilities that are comparable with healthcare services in HICs , 57. ThuBlacks had the youngest average age at death (56 years) followed by Coloreds (60.6 years), Indian/Asian (63.9 years), and White (67.4 years), suggesting that worst survival or more premenopausal deaths occurred among them. The observed rise in breast cancer mortality among the Whites in the later years may be occurring at old age. Indeed, the CMR of breast cancer was around thrice the ASMR among Whites, suggesting that majority of the deaths occurred in the elderly. Strikingly, women aged 25–39 years generally had the highest rise in breast cancer mortality. Remarkably, deaths from premenopausal breast cancer (<45 years) increased whereas postmenopausal breast cancer deaths declined among Coloreds, possibly suggesting increased modifiable risks and poor access to screening and early care among young Coloreds. The negative drifts among Whites aged 50–69 years and Indian/Asians aged 40–59 years may suggest that women of the two ethnic groups commenced screening at 40–50 years according to international guidelines , 47, 69.We utilized national mortality data that have been adjudged to be of high quality to comprehensively evaluate the trends in breast cancer mortality, based on the A–P–C and joinpoint regression models to unmask cues and information toward control of breast cancer in South Africa , 20.One limitation of this study was the missing information on the stage and histological types of the cancers that can further improve the interpretation of our results , 70. FurIn conclusion, we found that a significant age period cohort effect was observed for breast cancer mortality trends. There was a breast cancer rise of around 1.5% per annum from 1999 to 2018, largely driven by a rapid rise in deaths among young women (in the last 10 years of the study). The breast cancer mortality risk increased from the early cohorts but started decreasing among the recent cohorts born from 1989 to 2003. The period effect from screening and expansion of healthcare services after multiracial democracy in 1994 only led to minimal reduction in deaths of breast cancer, especially among women aged 50–59 years. The breast cancer mortality rate among Blacks was around half of the rates among the non-Blacks. Each of the four ethnic groups had differential trends and burden on account of peculiar socioeconomic, cultural, screening behavior, access to optimum care, awareness, and sexual and reproductive behavior. The identified disparities and trends are very useful for designing targeted intervention.The South African government launched the national breast program in 2017 to promote prevention and early detection and prompt optimum treatment of breast . Such inSince we found that cohort effect is a major driver of breast cancer mortality trends in the country, primary prevention should target all the known risk factors of breast cancer such as reduction of obesity, promoting breastfeeding, and reproductive behaviors. Breast cancer prevention should be part of the social marketing for promoting the cessation of tobacco smoking and alcohol consumption , 28. IntPublicly available datasets were analyzed in this study. This data can be found here: The Statistics South Africa website.The studies involving human participants were reviewed and approved by Human Research and Ethics Committee  of the University of the Witwatersrand (Clearance certificate number: M190544). Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.Conceptualization and study design: GO, EM, EL, OCE; data acquisition: GO, EM, EL; data management and data analysis: GO; data interpretation: GO, EM, EL, OCE; writing original draft: GO; critical review of manuscript and acceptance on the manuscript submission: GO, EM, EL, OCE; supervision of the project: EM, EL, OCE. All authors contributed to the article and approved the submitted version


Dense breast notification (DBN) legislation aims to increase a woman’s awareness of her personal breast density and the implications of having dense breasts for breast cancer detection and risk. This information may adversely affect women’s breast cancer worry, perceptions of risk, and uncertainty about screening, which may persist over time or vary by sociodemographic factors. We examined short- and long-term psychological responses to DBN and awareness of breast density (BD).In a predominantly Hispanic New York City screening cohort (63% Spanish-speaking), ages 40–60 years, we assessed breast cancer worry, perceived breast cancer risk, and uncertainties about breast cancer risk and screening choices, in short (1–3 months)- and long-term (9–18 months) surveys following the enrollment screening mammogram (between 2016 and 2018). We compared psychological responses by women’s dense breast status (as a proxy for DBN receipt) and BD awareness and examined multiplicative interaction by education, health literacy, nativity, and preferred interview language.In multivariable models using short-term surveys, BD awareness was associated with increased perceived risk (odds ratio (OR) 2.27, 95% confidence interval (CI) 0.99, 5.20 for high, OR 2.19, 95% CI 1.34, 3.58 for moderate, vs. low risk) in the overall sample, and with increased uncertainty about risk  and uncertainty about screening choices  in Spanish-speaking women. DBN was associated with decreased perceived risk among women with at least some college education , while those with a high school education or less experienced an increase . There were no associations observed between DBN or BD awareness and short-term breast cancer worry, nor with any psychological outcomes at long-term surveys.Associations of BD awareness and notification with breast cancer-related psychological outcomes were limited to short-term increases in perceived breast cancer risk dependent on educational attainment, and increases in uncertainty around breast cancer risk and screening choices among Spanish-speaking women.The online version contains supplementary material available at 10.1186/s13058-022-01584-2. High mammographic breast density (BD)—relatively large opaque white areas of mostly fibroglandular tissue on a mammogram—not only raises breast cancer risk but also makes it more difficult for radiologists to detect breast cancer on a mammogram , 2. ThesIn addition to structural factors such as healthcare access and coverage of costs for supplemental testing, any effect of DBN on breast cancer screening behavior is contingent upon increasing women’s awareness of breast density and its implications as well as women’s cognitive and emotional appraisal of this information . A recenIn a longitudinal study within a majority Hispanic immigrant screening cohort , we specThe New York Mammographic Density (NY MaDe) Study is a study of breast cancer risk factors and screening in a mammography cohort of women in Northern Manhattan, New York City, and has been previously described , 16, 17.n = 607 for short term and 626 for long term).We extracted clinical mammography reports since January 2013 to obtain the dense breast status of their screening mammograms post-implementation of New York’s DBN (in 2013). In accordance with New York State legislation, the recruiting mammography clinic provided women with dense breasts the state-mandated additional DBN text along with their clinical mammography results, provided in both English and Spanish [The Columbia University Medical Center institutional review board approved this study, and all women provided written informed consent prior to data collection.For breast density status, as described previously , we retrWe considered the following covariates obtained from the baseline interview based on prior predictors of BD awareness in this cohort : 5-year For descriptive analyses, we compared participant characteristics across survey waves using chi-squared or t tests. For multivariable analyses, we first determined the most appropriate models for the outcome data, which contained multiple answer choices. We used binary logistic regression to assess high versus low for breast cancer worry due to small cell sizes when disaggregated. We then tested the validity of the proportional odds assumption for all other psychological outcomes to see if it was appropriate to treat these outcomes as ordinal variables. This assumption held only for the uncertainty measures, so cumulative logistic regression was used. We then used multinomial logistic regression for perceived absolute and comparative risk. We modeled each psychological outcome separately for each wave using the appropriate models described above. To isolate the impact of DBN of baseline mammogram from women’s baseline psychological characteristics, we adjusted for the corresponding psychological factor reported at baseline  (base model). To this, Model 1 added separate sets of covariates specific to each outcome variable Table . These cp < 0.05.As sensitivity analyses, to test the robustness of our findings to analysis specifications, we also estimated the average population association of DBN or awareness with psychological factors in the smaller sample of women that responded to each question across all waves using generalized estimating equations (GEE) models that included interaction for survey wave when appropriate. We also assessed the use of other proxies for notification status or awareness, including a four-level variable representing each combination of density and awareness, a variable representing the number of times a women has had mammographically dense breasts since 2013 prior to baseline, and the use of the dense status of the mammogram just prior to baseline. Finally, we assessed for interaction between DBN and BD awareness for each outcome and each wave using a cross product term and in stratified analyses. We used the same statistical approach to examine whether associations of DBN or awareness with psychological outcomes varied by educational attainment (high school or less vs. some college or more), health literacy (continuous), nativity (US-born vs. non-US-born), and preferred language of interview (English vs. Spanish). All analyses were conducted in SAS 9.4  using a significance level of We observed no statistically significant differences in sociodemographic and breast cancer-related characteristics between women who completed the baseline survey and those who completed each follow-up survey or all 3 surveys (data not shown) and therefore present the population characteristics of women who responded to the short-term survey in Table Adjusting for baseline psychological factors, only perceived absolute risk was associated with short-term awareness Table . FurtherSensitivity analyses using the 4-level combination of DBN and awareness variables and stratification by DBN status yielded similar results. We also found similar results when we used the dense breast status of the last mammogram prior to the baseline mammogram, and when we used the number of dense breast mammograms since DBN implementation, instead of the baseline mammogram, as a proxy for notification status (data not shown). We observed similar findings when estimating the population average of the psychological factors in response to density or awareness using GEE models . We observed increased short-term uncertainty about breast cancer risk  align with the content of the mandated DBN text in the New York State legislation , 5. ThisThe limited body of empirical literature to date has not established a large or consistent effect of notification on emotional or cognitive psychological outcomes although unlike this study, the majority of prior research was small qualitative studies immediately after reading DBN text, or examined cross-sectional associations, and focused on BD knowledge and awareness , 18, 28.We ascertained DBN status using BI-RADS data for dense and non-dense breast classification levels retrieved from medical records, which provides an accurate measure of women’s eligibility for DBN. However, we did not assess whether women who had mammographically dense breasts at their baseline mammogram received, read, or absorbed the notification information. We also did not have a clear assessment of women who were newly made aware of breast density to see the impact of notification. Although we were able to use medical records to see how many times women had dense breasts on their mammogram in the past, this only accounted for mammograms done at the recruiting facility. Finally, a full exploration of multiplicative interaction with education and our 4-level combination density and awareness variable was impossible due to sparse cell size at this level. Our study was strengthened by the use of an ethnically and racially diverse cohort with a range of education levels, allowing us to explore effect modification by education and language. We were also strengthened by our use of validated constructs for psychological outcomes, and that we assessed these psychological outcomes in the same women at multiple timepoints.In a predominantly Hispanic screening cohort, awareness of breast density, regardless of one’s own dense breast status, appears to increase one’s perceived risk of breast cancer for a short time after undergoing mammography, but was otherwise not associated with emotional or cognitive psychological factors such as worry or long-term changes. Women with lower educational attainment had increased perceived absolute risk if they were eligible for dense breast notification, and women with a dominant language of Spanish showed increased short-term uncertainty about breast cancer risk and screening options if they had BD awareness. Taken together, these findings suggest that women with lower educational attainment or with language barriers or lower acculturation are at greater risk for short-term uncertainty among breast cancer choices with BD awareness and perhaps could specifically benefit from outreach clarifying the implications of breast density on screening choices.Additional file 1.Table S1. Average population association of dense breast notification (DBN) or breast density (BD) awareness with psychological factors.


Breast cancer and heart failure share several known clinical cardiovascular risk factors, including age, obesity, glucose dysregulation, cholesterol dysregulation, hypertension, atrial fibrillation and inflammation. However, to fully comprehend the complex interplay between risk of breast cancer and heart failure, factors attributed to both biological and social determinants of health must be explored in risk-assessment. There are several social factors that impede implementation of prevention strategies and treatment for breast cancer and heart failure prevention, including socioeconomic status, neighborhood disadvantage, food insecurity, access to healthcare, and social isolation. A comprehensive approach to prevention of both breast cancer and heart failure must include assessment for both traditional clinical risk factors and social determinants of health in patients to address root causes of lifestyle and modifiable risk factors. In this review, we examine clinical and social determinants of health in breast cancer and heart failure that are necessary to consider in the design and implementation of effective prevention strategies that altogether reduce the risk of both chronic diseases Cardiovascular disease (CVD) and cancer are the two leading causes of death in the United States in 2020 . ClassicTraditional clinical risk factors for HF in women are well established. Modifiable clinical HF risk factors that may also increase risk for breast cancer include diabetes, obesity, hypertension, hyperlipidemia, and atrial fibrillation  9). Ine. Ine9). 2 higher BMI above 25 kg/m2 in postmenopausal women  . In anotDysregulation in cholesterol metabolism is another traditional cardiovascular risk factor that is associated with breast cancer. Some studies have demonstrated an association between high-density lipoprotein cholesterol (HDL-C) and breast cancer risk . In a stThere is growing mechanistic evidence that links hypercholesterolemia with breast cancer. 27-hydroxycholesterol is an endogenous oxysterol that has activity as a selective estrogen receptor modulator . It is gp < 0.04). This risk was highest in the first 3 months after incident AF, but remained beyond 1 year  and cancer, with inflammation contributing to the development of both in part through the production of reactive oxygen species. Elevation in C-reactive protein levels and increased NLRP3 inflammasome activation have also been reported in AF . Whetherd 1 year . Atrial d 1 year . Women wd 1 year .As described above, immune dysregulation and inflammation are common final pathways that link traditional HF risk factors to breast cancer development. Obesity can lead to a chronic low-grade inflammation which leads to accumulation of pro-inflammatory adipose tissue macrophages, increased levels of aromatase, estrogen biosynthesis, and increased risk for estrogen-dependent breast cancer after menopause . Some inPoverty and inequality form the backbone of underlying social risk factors that contribute to social determinants of health (SDOH). These are primary concerns for healthcare providers who must consider community-level factors that influence health outcomes. Thriving in a society involves addressing a complex association between personal, environmental, economic, and social factors that impact overall health. There are multiple SDOH assessment tools which have been developed to comprehensively evaluate these outcomes. SDOH screening tools must be better integrated into healthcare delivery schema in cardio-oncology. Several social risk factors derived from these tools are known to contribute to both cancer and HF, including socioeconomic status, neighborhood disadvantage, food insecurity, an inadequate healthcare system , and social isolation , 57. TheThere is a known association between socioeconomic characteristics and risk for both breast cancer and HF. Across racial and ethnic groups, increasing socioeconomic status is inversely correlated with breast cancer incidence in population studies . Low socSocioeconomic factors also predict outcomes from HF admissions. Those patients with adverse social factors in a Medicare dataset were 3-fold as likely to die within 90 days of discharge for a HF hospitalization as those without any social risk factors . In a stThere is a linear relationship between number of socioeconomic risk factors and higher risk of HF hospitalization, cardiovascular events, and mortality . Prevent> 20% below poverty) and inner-city disadvantage have shown an association with risk of later stage breast cancer diagnosis . FGF-23 has been correlated with increased myocardial fibrosis on cardiac MRI and a strong predictor of mortality and first HF hospitalization, especially in patients with HF with preserved ejection fraction . FurtherFrailty and deterioration resulting from undernutrition has also been shown in patients with HF . InterveThere are well-documented disparities in breast cancer survival and HF by socioeconomic status, access to health insurance, and preventive care. Lack of adequate health insurance leads to high out of pocket medical costs, inability to pay for medications, lack of a primary care physician to perform screening studies, and provide subspeciality referral. The difficulty in navigating screening and treatment for HF or cancer is exacerbated by poverty, lack of insurance, and not having an established continuity clinic. Other socioeconomic factors such as lower education, health literacy, and higher stress levels were associated with lower HF clinic use . PatientPrevention is a large component in the management of both HF and breast cancer. It has been demonstrated that decreased cancer screening rates are associated with delayed diagnosis and treatment and poorer health outcomes . In a stFinally, the importance of social networks and connections for both breast cancer and HF patients has been well-established. High levels of social support have been shown to be protective for physical and mental health and quality of life , 89. In One prospective study of HF patients found that 6% of patients experienced severe social isolation; even after controlling for depression, these patients had >3.5 times increased risk of death 68% increased risk of hospitalization, and 57% increased risk of emergency department visits compared to those who did not report social isolation . In anotTo address the underlying factors that promote both HF and breast cancer, a multi-faceted approach is needed that focuses on SDOH and in turn clinical risk factors . A singuThe newer concept whereby HF promotes cancer development is supported by both epidemiological and mechanistic data. In an initial case-control study, HF was associated with nearly 70% higher risk of incident cancer after adjusting for comorbidities . This asAnimal studies have provided important insights into the association between CVD and cancer. The initial hallmark study evaluated the effect of HF induced by a large anterior MI in mice prone to developing precancerous intestinal tumors . Mice wiIn a separate breast orthotopic cancer mouse model, pressure overload induced cardiac hypertrophy from transverse aortic constriction led to greater tumor growth and more metastases . Tumor gThe interplay between risk factors associated with breast cancer and HF is very complex. Traditional cardiovascular risk factors, such as obesity, glucose dysregulation, hypertension, cholesterol dysregulation, atrial fibrillation and inflammation, are also closely linked with the development of breast cancer. HF itself has been shown to increase tumor growth and cancer development. Overarching social factors that lead to development of these cardiovascular risk factors, and in turn to breast cancer and HF, must simultaneously be addressed in order to comprehensively develop approaches for prevention of both chronic illnesses . PovertyNA, AS, and AB contributed to concept and design of the review and wrote sections of the the manuscript. NA and AB created the figure. All authors contributed to manuscript revision, read, and approved the submitted version.SS has received research grants from the National Institutes of Health , Actelion, AstraZeneca, Corvia, Novartis, and Pfizer; and has received personal fees from Abbott, Actelion, AstraZeneca, Amgen, Aria CV, Axon Therapies, Bayer, Boehringer-Ingelheim, Boston Scientific, Bristol-Myers Squibb, Cardiora, Coridea, CVRx, Cyclerion, Cytokinetics, Edwards Lifesciences, Eidos, Eisai, Imara, Impulse Dynamics, Intellia, Ionis, Ironwood, Lilly, Merck, MyoKardia, Novartis, Novo Nordisk, Pfizer, Prothena, Regeneron, Rivus, Sanofi, Shifamed, Tenax, Tenaya, and United Therapeutics. The remaining 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.