To examine the risk of incident breast cancer in women with rheumatoid arthritis (RA), and the risk of RA in women with a history of breast cancer, taking antihormonal treatment for breast cancer into account.Using nationwide Swedish registers, women with new-onset RA diagnosed in 2006–2016 were identified and analysed using a cohort and a case–control design. Each patient with RA was matched on age, sex and place of residence to five randomly selected subjects from the general population. Through register linkages, we collected information on breast cancer, breast cancer risk factors (reproductive history and hormone replacement therapy) and socio-economy. The relative risk of breast cancer after RA was assessed using Cox regression, and the relative risk of RA in women with a history of breast cancer was assessed using conditional logistic regression.The risk of incident breast cancer in women with RA was reduced and the association was not attenuated by adjustment for breast cancer risk factors . The risk of RA in women with a history of breast cancer was similarly reduced . Women with breast cancer treated with tamoxifen  or aromatase inhibitors  did not have an increased risk of RA compared with women with breast cancer treated differently.The decreased occurrence of breast cancer in patients with RA is present already before RA diagnosis; these reduced risks are not readily explained by hormonal risk factors. Adjuvant antihormonal therapy for breast cancer does not seem to increase RA risk. The life-time risk of breast cancer is in the order of 1 woman out of 10. Several studies have reported a 15%–20% reduced risk of breast cancer in women with rheumatoid arthritis (RA), but the reasons behind this decrease remains unknown and unstudied.Previous studies have reported that tamoxifen and aromatase inhibitor treatment of breast cancer may increase the risk of RA.We demonstrate that the risk of breast cancer after rheumatoid arthritis (RA) is indeed reduced, but this association cannot readily be explained by traditional breast cancer risk factors. By studying the future risk of RA in women with breast cancer, we demonstrate an equally pronounced risk reduction before RA diagnosis, again not explained by traditional breast cancer risk factors. These findings suggest that other factors, independent of RA, drive the inverse association between the two diseases.Tamoxifen and aromatase inhibitors do not seem to increase the risk of future RA.With respect to patient counselling, the occurrence of a breast cancer in patients with rheumatoid arthritis (RA) is lower than in the general population, and tamoxifen and aromatase inhibitors appear safe in terms of risk of future RA.With a lifetime risk of close to 1 in 10, breast cancer is the most common cancer among women. Rheumatoid arthritis (RA) is the most common rheumatic disease affecting the joints, and has a marked female predominance. Although the overall risk of malignancies in RA is increased by 10%–15% compared with the general population, large cohort studies have consistently reported decreased occurrence of breast cancer among women with RA.The characteristics and the reason(s) behind the decreased risk of breast cancer in women with RA remain unknown, indeed also virtually unstudied. Hormonal factors such as hormone replacement therapy (HRT),If the observed reduction in the risk of breast cancer in women with RA was attributable to shared risk factors rather than a causal effect of the RA disease or its treatment, then one would expect that the reduced risk of breast cancer would be present already before the onset of RA. So far, the link between history of breast cancer and future risk of RA has been little investigated.The occurrence of RA following breast cancer is clinically and aetiologically important also for other reasons. Five to 10 years of adjuvant antihormonal treatment, for example, tamoxifen or aromatase inhibitors (AI), has become mainstay for oestrogen receptor positive breast cancer. Arthralgia is a common side effect of AI, and to a lesser extent also of tamoxifen. Some studies have suggested that these therapies not only induce arthralgia, but also inflammatory arthritis.Our study therefore had the following aims: first, to examine the risk of breast cancer in women with RA, and to investigate to what extent known breast cancer risk factors may explain the association. Second, to examine the risk of RA in women with a history of breast cancer, and whether antihormonal treatment for breast cancer modifies this association. To address the first aim, we used a cohort design, and to address the second aim, we used a case–control design, both applied to a nationwide population with new-onset RA and to individually matched population referents.Swedish healthcare is public and tax funded. Patients with RA are typically diagnosed and treated by rheumatologists. Sweden has national and virtually complete registers on demographics and health data which can be linked together by the unique personal identity number issued to all Swedish residents. This study was based on linkages between the Swedish Rheumatology Quality Register (SRQ), the National Patient Register (NPR), the Cancer Register, the Prescribed Drug Register, the Total Population Register, the Multigeneration Register and the Causes of Death Register, described elsewhere and in the 10.1136/annrheumdis-2019-216756.supp1Supplementary dataWomen with new-onset RA between 1 January 2006 and 31 December 2016 were identified from two partly overlapping sources, the SRQ and the NPR, using previously devised algorithms . PatientThrough linkage to the Swedish Cancer Register, all incident (1958 or later) cases of breast cancer  in the study population were identified. In the Prescribed Drug Register, we identified all dispensed prescriptions of tamoxifen and tamoxifen-like substances  and AI, respectively, in July 2005 or later  Classification System codes in We included information on educational level , country of birth, number of live births and age at first full-term pregnancy (from the Multigeneration Register), family history in a first-degree relative of breast cancer or ovarian cancer (via linkage to the Multigeneration and Cancer Registers), oral contraceptives and intrauterine devices and HRT (from the Prescribed Drug Register). Age 50 was used as a proxy for menopausal status. Status on all covariates were ascertained at index date. For details and for an assessment of the association between these covariates and the outcome please see SAS V.9.4 was used for all analyses. The study was approved by the Stockholm Ethics Review Board.To assess and characterise the risk of breast cancer in patients with RA, counting from RA diagnosis, we used a matched cohort design where patients with RA were considered exposed, and their population comparators unexposed. Start of follow-up for patients with RA (and for their matched population referents) was set to the date when all RA-defining inclusion criteria were fulfilled. Women with a history of breast cancer at the time of start of follow-up were excluded. End of follow-up was defined as 31 December 2016, death, emigration or breast cancer, whichever occurred first. Relative risks for breast cancer were assessed using Cox regression with follow-up time as the timescale. We first analysed age-adjusted models, and then gradually added more variables. In the full model, adjustments were made for age, calendar year, country of birth, educational level, HRT, oral contraceptives, age at first live birth, number of live-born children, family history of breast or ovarian cancer and previous invasive cancer. The risk of breast cancer was assessed overall, stratified by time since start of follow-up , RA serostatus and age at RA diagnosis . Relative risks were also assessed separately for premenopausal and postmenopausal cancer, and tumour, node, metastases (TNM) cancer stage at diagnosis .To assess the relative risk of RA in women with a history of breast cancer, we used a case–control design, and calculated ORs using conditional logistic regression. Besides the matching variables , the fully adjusted model accommodated country of birth, educational level, age at first live birth, number of live-born children and family history of breast or ovarian cancer. ORs were assessed overall, and stratified by age at RA diagnosis  and RA serostatus. Also, ORs were assessed according to different exposure definitions, that is, time between the breast cancer and RA , premenopausal or postmenopausal breast cancer and TNM cancer stage at diagnosis see .To assess the risk of RA following antihormonal breast cancer treatment, we again used a case–control design. Exposure was defined as at least two dispensings of the antihormonal drug in question, between breast cancer diagnosis and the index date. Also, analyses of cumulative exposure of antihormonal treatment were performed , in these only one dispensing of antihormonal treatment was required. Since the Prescribed Drug Register started in July 2005, we restricted these analyses to women diagnosed with breast cancer from 2003 to 2016. As this would allow some patients receiving antihormonal treatment being misclassified as non-exposed, we performed a sensitivity analysis restricting the study period to July 2005 through December 2016. To avoid the inclusion of occult RA diagnosed shortly after breast cancer diagnosis, and misclassified RA due to acute arthralgia following initiation of antihormonal treatment, in a sensitivity analysis we excluded subjects with <1 year between the breast cancer diagnosis and index date.During 2006–2016, we identified 15 921 incident patients with RA, who were matched with 79 441 subjects from the general population . Mean agDuring a mean follow-up of 5.00 years among patients with RA and 5.04 years among general population comparators, we identified 190 cases of breast cancer among 15 356 patients with RA, and 1191 cases among 75 854 population comparators, resulting in an age-adjusted and calendar year-adjusted HR=0.80 (95% CI 0.68 to 0.93). This estimate was virtually unchanged by further adjustments . The risk was similar among seronegative RA  and seropositive RA , and for all age groups. We noted reduced risks for all TNM stages, and for both premenopausal and postmenopausal breast cancer .At index date, 555 (3.5%) of the 15 921 patients with RA, and 3193 (4.0%) of the controls had a history of breast cancer, age-adjusted OR=0.86 (95% CI 0.78 to 0.94), fully adjusted OR=0.87 , with some overlap (n=184). The risk of RA was not significantly associated with any combination of antihormonal breast cancer treatments; both tamoxifen and AI versus never treated: fully adjusted OR=0.68 (95% CI 0.41 to 1.12); tamoxifen-only versus never treated: OR=0.86 (95% CI 0.62 to 1.20); AI-only versus never treated: OR=0.97 , we noted no trends in risk of RA . For AI,Sensitivity analyses restricting the analysis of risk of RA among women with a history of breast cancer to cancer cases occurring after the Prescribed Drug Register was started (July 2005 to December 2016), and excluding subjects with <1 year between the breast cancer diagnosis and index date, provided results similar to the main analysis see .In this large population-based study, we made a series of important observations. Also in this recent modern cohort of patients followed from RA diagnosis, there was a decreased risk of breast cancer, corresponding to a lifetime risk of 1 in 12.5, instead of 1 in 10 as in the general population.We noted, as has previously been reported,et al, who studied the risk of RA in a cohort of 10 493 women with breast cancer, we did not find a markedly higher risk of RA in AI-treated compared with tamoxifen-treated patients. Although based on relatively small numbers, our upper confidence limits indicate a low probability for clinically significant risk increases overall. However, we cannot rule out an association between RA and tamoxifen/AI among specific subgroups, for example, as defined by hormonal receptor status, which we did not have information on. We did observe a trend towards a higher risk in the beginning of treatment, but then a reduced risk after 2 years of AI treatment. Caprioli et al did not compare the rate of RA among patients with breast cancer to that of the general population. The rate that they observed (4.33 per 1000 person-years) is somewhat lower than population-based age and sex standardised incidence rates reported from Italyet al that included more than 200 000 cases of breast cancer.This is one of the first studies examining the relationship between antihormonal breast cancer treatment, and the risk of RA.We adjusted our models for hormonal risk factors, which had little impact on our results. Whether this is due to residual confounding or a true absence of confounding is difficult to ascertain, but we did observe that these factors were indeed risk factors for breast cancer in our study population . StudiesOur study has some limitations. Although algorithms for identifying incident RA diagnoses in the NPR have been validated and shown to have a positive predictive value close to 90%, misclassification of RA cannot be excluded.The strengths of this study were its large sample size and long follow-up, the use of nationwide registers with high internal validity and coverage and that we could adjust our models for several potentially important confounders.In conclusion, we found a decreased risk of breast cancer in patients with RA, and a similar decrease in risk of RA in patients with a history of breast cancer. We did not find evidence to support that the decreased risk of breast cancer was due to known risk determinants. Thus we were ultimately unable to explain the origins of this association. Antihormonal therapy as used in secondary breast cancer pharmacoprevention does not seem to increase RA risk.


The European Collaborative on Personalized Early Detection and Prevention of Breast Cancer (ENVISION) brings together several international research consortia working on different aspects of the personalized early detection and prevention of breast cancer. In a consensus conference held in 2019, the members of this network identified research areas requiring development to enable evidence-based personalized interventions that might improve the benefits and reduce the harms of existing breast cancer screening and prevention programmes. The priority areas identified were: 1) breast cancer subtype-specific risk assessment tools applicable to women of all ancestries; 2) intermediate surrogate markers of response to preventive measures; 3) novel non-surgical preventive measures to reduce the incidence of breast cancer of poor prognosis; and 4) hybrid effectiveness–implementation research combined with modelling studies to evaluate the long-term population outcomes of risk-based early detection strategies. The implementation of such programmes would require health-care systems to be open to learning and adapting, the engagement of a diverse range of stakeholders and tailoring to societal norms and values, while also addressing the ethical and legal issues. In this Consensus Statement, we discuss the current state of breast cancer risk prediction, risk-stratified prevention and early detection strategies, and their implementation. Throughout, we highlight priorities for advancing each of these areas. Risk-adapted approaches to breast cancer prevention and screening could potentially be more effective than universal approaches, which have important limitations. In this Consensus Statement, representatives of the European Collaborative on Personalized Early Detection and Prevention of Breast Cancer (ENVISION) discuss the current state of breast cancer risk prediction, risk-stratified prevention and early detection strategies, and their implementation. They also present the ENVISION recommendations on priorities for future research in each of these areas with the aim of stimulating and guiding risk-adapted breast cancer prevention and screening programmes. Breast cancer is a biologically and clinically heterogeneous disease, with several recognized histotypes and molecular subtypes that have different aetiologies, profiles of risk factors, responses to treatments and prognoses8. In high-income countries, approximately 75% of breast cancers are diagnosed in postmenopausal women, although around 5–7% are diagnosed in women younger than 40 years of age10.Worldwide, breast cancer is the second most commonly diagnosed cancer, with approximately 2.1 million new diagnoses and almost 627,000 breast cancer-related deaths estimated to have occurred in 2018 , exogenous hormone intake , lifestyle patterns , anthropometric characteristics , a high mammographic breast density and benign breast diseases  are all associated with an increased risk of breast cancerBRCA1 or BRCA2 (BRCA1/2) — may opt to undergo prophylactic bilateral mastectomy; primary chemoprophylaxis with tamoxifen or other selective oestrogen receptor modulators has also been recommended in this group, albeit the uptake is low16. Historically, members of this high-risk group have been identified on an opportunistic basis following self-referral of women with a family history of breast or ovarian cancer, or on the basis of an ancestry associated with an increased prevalence of clinically significant pathogenic variants of BRCA1/2 16. Currently, genetic testing remains somewhat restricted for women with breast cancer; those with triple-negative, bilateral or young-onset disease might be offered a test at diagnosis, but most will be offered testing only if they also have a noted family history of the disease16. The 2019 US Preventive Services Task Force recommendations expand the population in which eligibility for genetic testing should be assessed to include women with a personal or family history of breast, ovarian, tubal or peritoneal cancer, in addition to women who have an ancestry associated with pathogenic BRCA1/2 variants17.Women with pathogenic germline mutations in cancer susceptibility genes — that is, in 22 and have age as the only entry criterion, although the starting and stopping ages (varying from 40 to 74 years) and the frequency of screens  differ between countries. This ‘one-size-fits-all’ approach does not take into account the heterogeneity of the breast cancer subtypes and of the risk in the population. Three decades of mammographic early detection have witnessed an increase in the incidence of early stage cancers with a low-risk tumour biology and an increase in the detection of in situ disease, without a concomitant proportionate decrease in incidence of advanced-stage disease24. Increasingly, calls have been made for a new approach to early detection with a focus on the identification of more consequential cancers and on avoiding the detection of indolent or ultra-low-risk disease25.At present, the mammographic screening programmes used for early detection of breast cancer in most high-income countries are based on the results of trials conducted at least 20–30 years ago27. These programmes require risk assessment of each woman in the population, stratification of the population into several risk groups, assignment of the individuals to a specific risk group and tailoring of prevention and early detection interventions to each risk group28  comprises leading international research consortia working in this specific field  network meeting was attended by 119 delegates from 19 countries: 14 countries in Europe  as well as Israel, the USA, Canada, Malaysia and Australia. Together, the delegates brought diverse expertise in risk-based breast cancer research and health services , with representatives from academia, health-care organizations, industry (information technology support), politics (government representatives) and non-profit organizations (Europa Donna and the Association of European Cancer League).The meeting was held over 3 days. During the first day, presentations covered the latest evidence (‘where we are now’) relating to breast cancer risk prediction, risk stratification for prevention, risk stratification for early detection at the population level and the implementation of such strategies. Each presentation was followed by a discussion session for the delegates to identify gaps in research (‘where do we want to be’). During the second day, through six workshops ), the delegates explored how to meet these gaps (‘how do we get where we want to be’). During the third day, named delegates, in coordination with the presenters, discussants and the facilitators of the workshops, presented recommendation for each of the 18 areas covered in the ENVISION meeting . The presentation of each recommendation was followed by discussion and checking consensus.Each delegate who contributed through presenting the evidence, the workshop discussions and the recommendations presented a written summary. After collating these summaries, all 119 delegates were asked for their feedback.Box 2 Summary of the key recommendations of the ENVISIONAssessment of breast cancer riskRisk-assessment tools should be validated using prospective cohorts in the context in which they will be used and for each population ancestry.Risk-assessment tools that enable better predictions of breast cancer subtype-specific risk and risk in women of non-European descent need to be developed and validated.Discovery research to identify additional genetic variants and new markers is required to improve risk stratification.The trade-off between the accuracy of comprehensive models and their usability at the population level should be evaluated.Algorithm transparency should be ensured, with explicit reporting of the assumptions made.Breast cancer preventionWays to better select high-risk women predisposed to breast cancer of poor prognosis need to be developed.Clinically relevant surrogate markers (reflecting the field defect in breast tissues) that provide early indications of the effectiveness of the preventive measures in reducing incidence of breast cancer of poor prognosis need to be identified.Programmes should incorporate healthy lifestyle recommendations for women at all risk levels.Prevention-specific drug doses, schemes and schedules need to be defined, and rational drug repositioning strategies should be explored.Better and early assessment of the acceptability of new preventive interventions is required.Risk-stratified early detectionDiscovery research is required to identify and validate early detection markers that can differentiate progressive from non-progressive breast cancers.Develop risk-stratified early detection strategies underpinned by understanding of how the natural course of breast cancer, sensitivity of the test  and the probability of overdiagnosis vary according to risk levels.Optimize variables related to risk assessment  and risk stratification (how many risk groups to specify and the risk threshold for each group), thus resulting in a cost-effective, feasible, acceptable and equitably accessible early detection programme.Modelling studies can be used to inform on long-term population outcomes and the optimal design of risk-stratified early detection programmes.Pragmatic randomized study designs, such as randomized health service studies, should be used to generate evidence on the effectiveness of risk-stratified early detection approaches in a given setting.Programme implementationAdopt hybrid effectiveness–implementation research designs to reduce the time lag between generation of evidence on the effectiveness of a programme and its implementation.Shift away from small studies with hypothetical scenarios performed in silos to multidisciplinary research with engagement of all stakeholders to ensure a systems approach to implementation studies in real-world settings.A framework for a learning health-care system should be adopted.The implementation process in a given setting needs to be aligned with health-care organization readiness for change and the social values, preferences and norms.The best ways of communicating risk and supporting behavioural changes in response to risk information need to be identified.BRCA1/2, PALB2, CHEK2 and ATM; mammographic breast density; benign abnormalities in breast biopsy specimens; hormonal, anthropometric and lifestyle factors; family history of the disease; and, potentially, epigenetic markers43. Genome-wide association studies (GWAS) have resulted in the identification of >180 independent common genetic variants that together account for ~20% of the familial relative risk of breast cancer and ~40% of the heritability attributed to all common variants on genome-wide SNP arrays41. Each variant confers a small risk, but their effects can be combined into polygenic risk scores (PRSs) that are predictive of the risk of developing breast cancer, thereby enabling breast cancer risk stratification in the general population46.Breast cancer risk can be predicted using a combination of common genetic variants, mostly single-nucleotide polymorphisms (SNPs); rare coding variants of susceptibility genes, including 44. The relative risks associated with individual SNPs and PRSs vary between breast cancer subtypes, with oestrogen receptor-positive (ER+) disease being more strongly predicted than other forms of the disease44. The current best performing PRS is based on 313 SNPs (PRS313): women in the highest 1% of the risk distribution have an approximately fourfold and threefold greater risk of developing ER+ and ER− breast cancers, respectively, compared with women in the middle quintile (40–60th percentile)44. The risk reflected in the PRSs seems to be independent of other established risk factors — that is, the effects are approximately multiplicative43. PRS313 provides the highest level of breast cancer risk stratification in the population, followed by mammographic breast density and the other risk factors47.The performance of current PRSs has been thoroughly validated in European populations48; for some, the strength of association has been demonstrated to differ between ER+ and ER− disease50. The risk estimates for PTVs of some genes are, however, very imprecise  framework has assessed the strength of evidence between selected putative susceptibility genes and breast cancer and established definitive clinical validity classifications for only 10 of 31 genes commonly tested when evaluating breast cancer risk57 (Table Protein-truncating variants (PTVs) in approximately 12 genes are associated with breast cancer risk58, supporting the principle that an epigenetic field defect renders cells of these tissues susceptible to malignant transformation59. In addition to genetic background61, a large variety of non-genetic factors, including age62 and endocrine disruption64, that are known to modulate breast cancer risk also alter patterns of DNA methylation. On the basis of these insights, one might speculate that epigenetic profiles could predict breast cancer risk.The epigenome consists of various ‘layers’, including non-coding RNAs, histone modification and DNA methylation, and has an essential role in establishing the identity and function of any given cell by determining which genes remain silent and which are transcribed. A plethora of changes in DNA-methylation patterns have been described in breast cancers, and several of these changes are often also present in the non-malignant breast tissue adjacent to the cancer65. First, the vast majority of the studies to date used only blood samples for DNA-methylation analyses. Blood is readily available from participants of several large cohort studies66, but breast cancer is, by definition, an epithelial disease, and hence immune cells in the blood might not be an appropriate surrogate tissue for those of the breast. Second, unlike in germline genetic analyses, the timing of the sample collection for epigenetic analyses is crucial. For example, epigenetic analyses using samples obtained from women during cancer treatment are likely to produce results that reflect treatment effects and not cancer predisposition. Third, unlike PRSs, which are established by combining individual SNPs with risk associations that remain statistically significant after multiple test adjustment, epigenetic risk signatures are reflective of cell programmes; therefore, approaches that a priori select a large number of CpGs for inclusion in the epigenetic signatures are more likely to be appropriate. Fourth, the presence of a cancer can modify the epigenome of a particular surrogate tissue. For example, a higher granulocyte to lymphocyte ratio is detected in the blood of patients with ovarian cancer, which subsequently alters the DNA-methylation signature observed when assessing peripheral blood mononuclear cells67. Thus, validation of risk-predictive signatures in population-based cohorts is important; however, the majority of the existing cohorts do not have appropriate samples available , which makes this validation process prone to producing false-negative results.To date, several groups have attempted to develop epigenetic risk classifiers for breast cancer but with only modest success, which could be due to several reasons70 and a double-strand DNA break-repair phenotype of peripheral blood cells72 have substantial potential to identify women with a high risk of developing breast cancer.Nevertheless, DNA-methylation signatures in easy-to-collect surrogate tissues hold promise, not only in advancing risk-prediction strategies, but also, of equal importance, in providing novel opportunities to monitor the effects of cancer-preventive measures. In addition to epigenetic markers, serum levels of steroid hormones73, the Breast Cancer Surveillance Consortium (BCSC) risk calculator74 and the Individualized Coherent Absolute Risk Estimator (iCARE)77 do not consider explicit genetic models of inheritance and are primarily intended for use in women in the general population. By contrast, genetic models such as Tyrer–Cuzick78 and BOADICEA79 can, in principle, accommodate detailed family history information (including the exact pedigree structure and information on distant relatives) and can, therefore, be applied both at the general population level and in women with a strong family history of breast cancer. These models all vary in terms of the risk factors considered, the study designs and types of data used in their development, and their analytical methods. The validity and clinical utility of these risk-assessment tools must be demonstrated before they are implemented routinely in the clinical setting80.Several breast cancer risk-prediction models are available. Empirical models such as the Gail modelAnalytical validity refers to the accuracy of the test in measuring the underlying genotypes , PRSs  and other lifestyle and hormonal risk factors . Importantly, the analytical validity of comprehensive breast cancer risk-prediction models also depends on having reliable relative risk estimates for the effects of the various risk factors; having precise risk estimates of the associations with individual rare and common genetic variants; as well as estimates of the joint effects of common genetic variants, the joint effects of common and rare genetic variants, and the combined effects of genetic and other risk factors, including a family history of cancer. Clinical validity refers to the accuracy of the tool in predicting the occurrence of breast cancer.76. Data generated by the B-CAST29, BRIDGES30, BCAC81 and CIMBA82 consortia , have limited sample sizes and have varying timescales over which predictions are made, which depend on the follow-up duration of the study.With regard to clinical validity, several validation studies assessing model calibration  or discrimination (the ability of a risk score to discriminate between those who will and those who will not develop the disease) in large independent cohorts have been published29 and BRIDGES30 aim to address these issues by evaluating risk-assessment models in multiple prospective cohorts of women initially without breast cancer in diverse settings. Preliminary results indicate that the iCARE85 and BOADICEA45 models have well calibrated categories of predicted risk and discriminate well between women who develop breast cancer over 5–10 years of follow-up study from those who do not84. As such, these models provide valid risk-prediction tools that can be used in clinical practice.Ongoing studies by B-CAST87. Clinical utility is a multidimensional construct covering effectiveness and cost-effectiveness, as well as the psychosocial, ethical and legal implications of an intervention86. Risk assessment per se does not have inherent clinical utility; the subsequent adoption of a risk-based intervention based on the results of the assessment is what influences the health outcomes88. The use of such a strategy depends on whether the risk-based intervention is appropriate, accessible, practicable and acceptable86. The interactions of these factors and challenges in assessing them are discussed in more detail in later sections of this article , will be required.A large fraction of the unexplained heritability of breast cancer might be attributable to rare variants  not captured on SNP arrays93; parenchymal textual features beyond simple mammographic breast density, such as the co-occurrence matrix and multiresolution spectral features, have been shown to be important94 and might be independently predictive of the development of breast cancer96. Screening programmes provide longitudinal data that can facilitate studies to identify such imaging biomarkers. Potential blood-based biomarkers include microRNAs, tumour-educated platelets and circulating tumour DNA99. However, these markers might be more suitable for short-term early detection than long-term risk prediction (since they are perhaps more likely to reflect the presence of cancer rather than cancer susceptibility), and large longitudinal collections of samples will be required to study them.Other promising approaches to improve breast cancer risk prediction include imaging and blood-based biomarkers. Improved use of mammography or MRI to predict risk is a particularly attractive area of research47. Repeat collection of information on the non-genetic risk factors at a population level raises further complexities in the logistics of risk assessment. The feasibility, clinical utility, costs and cost-effectiveness of risk-based programmes using a comprehensive model versus a model with only PRS need to be evaluated.Comprehensive models incorporating genetic and epidemiological risk factors and mammographic breast density enable more accurate risk stratification in the general population, as well as in carriers of germline pathogenic variants, than is possible with models that consider only PRS100.To enhance the credibility of a given model, and thus confidence in the results, transparency  and validation in relevant settings are essential. The challenge lies in having a consensus on the criteria for sufficient evidence to declare a model as ‘valid’ for a particular application101. In the context of CVD, clinical parameters indicative of risk  can be successfully targeted and subsequently used to monitor preventive actions102. However, mirroring these concepts in the context of cancer has not been possible to date. Cancer development is a multifactorial process that occurs at various stages of life and sometimes decades in advance of diagnosis. Avoiding certain risk factors for breast cancer , as well as adopting healthier lifestyle patterns , can have long-term cancer-preventive effects. Nevertheless, many of the risk factors for breast cancer  are not modifiable, and in many cases the biological mechanism underlying the associated increase in breast cancer risk remains unknown. Notwithstanding, several active strategies have been shown to modify breast cancer risk.In high-income countries that have implemented strategies to prevent or mitigate cardiovascular disease (CVD), cancer has superseded CVD to become the most common cause of death119. However, in order to prevent one breast cancer in the next 20 years, 22 women needed to take tamoxifen daily for 5 years117. The considerable adverse effects of anti-oestrogens and the fact that none of these trials has shown any overall or breast cancer-specific survival benefits or a reduction in the incidence of aggressive, hormone receptor-negative forms of breast cancer make it difficult to judge whether treating healthy women with these drugs is a more effective strategy than reserving them for the adjuvant treatment of only those who actually develop breast cancer. Nevertheless, the US Preventive Services Task Force have judged that serious adverse effects, such as thrombosis and endometrial cancer, are uncommon and the more common toxicities, such as vasomotor symptoms, are reversible and were only marginally more frequent in women on active treatment than in those receiving placebo in the aforementioned RCTs120. Accordingly, several international guidelines recommend the use of anti-oestrogens as chemopreventives for women at increased risk of breast cancer121. Whether improved risk stratification would reduce the number of healthy women who need to take anti-oestrogens in order to achieve the same preventive effect will need to be established in future RCTs.The results of prospective randomized controlled trials (RCTs) evaluating primary prevention of breast cancer using selective oestrogen receptor modulators or aromatase inhibitors have consistently shown a reduced incidence in hormone receptor-positive subtypes of the disease122 with a germline pathogenic BRCA1/2 variant123. Nipple-sparing mastectomies are a safe option for these women, with no known detriment to the risk reduction124. General complications include wound dehiscence, infection, implant loss or flap necrosis, asymmetry and capsular contracture125. For nipple-sparing mastectomies, the overall complication rate has been reported to be 22.3%, and the rate of nipple necrosis was 5.9%126. However, surgery can be associated with other complications and adverse effects, including psychological distress with body image change, and has implications relating to resources. Thus, clinical utility, feasibility and acceptability need to be evaluated in order to set the risk threshold for surgical intervention.Prophylactic bilateral mastectomy is certainly the most effective way of preventing breast cancer and reducing breast cancer-specific deaths in the small minority of women (perhaps 3%)103. Furthermore, the data indicated that women receiving progesterone-containing therapy are more likely to die from breast cancer than women treated only with oestrogens127. Additional evidence for the role of progesterone in breast carcinogenesis comes from the observation that women with germline pathogenic BRCA1/2 variants have elevated levels of luteal phase progesterone compared with those observed in carriers of non-pathogenic BRCA1/2 variants128. This increase in progesterone levels leads to an increase in receptor activator of nuclear factor-κB ligand (RANKL) levels in the breast133, as well as reduced levels of the physiological RANKL antagonist osteoprotegerin129. These effects in turn lead to an expansion of ER− and progesterone receptor-negative mammary stem cells and eventual breast cancer formation134. In mouse models, Brca1/2-mediated breast cancer formation can be prevented by disrupting the progesterone signalling pathway using the competitive progesterone receptor antagonist mifepristone135. In addition, the findings of a case–control study involving women with germline BRCA1/2 mutations indicate that moderate use of dietary supplements containing folic acid and vitamin B12 can be protective against BRCA1/2-associated breast cancer136. Other potential risk-reducing chemotherapeutics include aspirin, metformin, statins or other agents137.In past few years, several new targets of potential preventive interventions for breast cancer have been discovered. In particular, progesterone has an essential role in the development of aggressive breast cancers. A meta-analysis of 58 studies revealed that women receiving a progesterone-containing menopausal hormone therapy not only have a higher incidence of breast cancer than women not receiving such therapy or those receiving oestrogen-only treatments, but also more cancers that had spread beyond the breast134. In postmenopausal women with breast cancer, however, denosumab does not seem to alter the incidence of contralateral breast cancer138. A prevention study of this agent in carriers of pathogenic BRCA1 variants is underway139.To date, clinical trial evidence supporting these chemoprevention strategies is lacking. Denosumab, a fully humanized antagonistic monoclonal antibody targeting RANKL, has been shown to reduce breast epithelial cell proliferation in three premenopausal volunteers+ or luminal B subtypes, need to be identified.Several challenges need to be addressed to advance the field of breast cancer prevention. First, drugs that can reduce the incidence of aggressive breast cancers, for example, of the triple-negative, HER2Second, the required doses and frequency of administration of these potential preventive drugs need to be established. Unlike tamoxifen and aromatase inhibitors, the efficacy and safety of which have been tested in many thousands of women in the adjuvant treatment setting, no such data exist for the most promising novel preventive drugs .BRCA1/2 variants) selectively identifies those women at risk of developing an aggressive cancer that, if not prevented, would likely lead to death.Third, efforts are needed to develop an effective approach to selecting women for whom breast cancer primary or secondary prevention measures will provide survival benefits. None of the current risk-prediction models intended to identify women at an increased risk of developing breast cancer in the absence of a familial predisposition  they can be measured frequently; 2) the dynamics of the molecular biomarkers in individual volunteers might reflect the cancer risk in real time, and thus individual adjustments to preventive measures could be made ad hoc; and 3) unlike many imaging-based markers, they do not require repeated exposure to x-rays , acceptable and better understood by health-care professionals and the public is essential148 , harms  and cost-effectiveness of a screening programme should be estimated to guide decisions on implementation. RCTs should be used to generate the primary evidence on the effectiveness of a new screening programme in reducing cancer-specific mortality149. When modifying currently running programmes, however, questions remain regarding what constitutes supportive evidence 150 and how complete the evidence needs to be before recommendations for implementation can be made151.The Cancer Control Joint Action European Guide on Quality Improvement in Comprehensive Cancer Control152 and MyPeBS in Europe153. While the two trials share a similar design, with intermediate outcome measures (such as stage distribution) as end points, their protocols are adapted to the local health-care settings.Two short-term RCTs evaluating the effectiveness of risk-stratified screening for breast cancer are currently ongoing: WISDOM in the USA152 is a multicentre, pragmatic, adaptive, preference-tolerant RCT comparing risk-based screening to annual screening in women aged 40–74 years. WISDOM is designed to determine whether risk-based screening is as safe as annual mammographic screening , but with less morbidity (measured according to the number of breast biopsies performed) as well as greater acceptability, conductivity to preventive interventions and health-care value152. Women in the risk-based screening arm are receiving a personal risk assessment based on the BCSC risk calculator integrated with a PRS  and testing of a panel of nine susceptibility genes154. Those women are being stratified into four risk groups: highest risk, elevated risk, average risk and lowest risk. Each group is recommended a screening strategy that varies in starting age and the frequency and modality of screening — annual mammography with adjunctive MRI, annual mammography, biennial mammography and deferred screening until the age of 50 years (in the lowest risk group comprising women aged 40–49 years with 5-year absolute risk <1.3%), respectively155.WISDOM153 is a pragmatic, multicentre RCT that is being performed in five countries  to determine if risk-based screening of women aged 40–70 years is non-inferior, in terms of the 4-year incidence of stage ≥II breast cancer, to the standard screening programme currently offered in each participating country (screening every 2–3 years beginning at 40–50 years of age and ending at 69–74 years of age). In MyPeBS, the frequency and modality of screening vary according to the level of risk predicted using PRS313 combined with the BCSC74 or the Tyrer–Cuzick78 risk calculator. The latter calculator is used only in women with more than one first-degree relative with a history of breast or ovarian cancer. In MyPeBS, women are also being classified into four risk groups153, although the risk thresholds differ from those used in WISDOM. However, the lead investigators of both trials are ensuring that data are collected in a similar way and have committed to pooling the data to improve the ability to learn from each study.MyPeBS156. Moreover, the outcomes of screening depend on the screening strategy  and variables relating to the setting 149. Variations in any of these elements can alter the benefit–harm trade-offs. Finding the optimum strategy for a given population requires comparisons of several alternative screening strategies; however, RCTs — particularly of screening strategies that require very large cohorts and long follow-up durations — are inherently limited in their ability to compare more than a few approaches .RCTs of screening interventions provide the strongest evidence of efficacy, although they have certain limitations. In particular, lifetime health effects cannot be observed in RCTs with limited follow-up durations. Thus, the observed benefit–harm trade-offs might not accurately reflect those expected with long-term population screening159. Such modelling studies can precede or follow RCTs of screening interventions. Lifetime health effects can be modelled using empirical data — for example, from RCTs of different approaches to screening, long-term observational studies and clinical registries160. Modelling studies that incorporate data on the population structure and preferences, the natural history and prevalence of disease, life expectancy, the available resources and costs can provide an indication of which screening strategies are likely to be optimal in a given setting160. Thereafter, the most promising strategies could be tested in RCTs. Thus, modelling studies can inform population-screening policies by extrapolating evidence beyond the time horizon of prospective trials and enabling the translation of evidence from one study population to another.Simulations using natural history models and decision analysis models constitute useful tools to study the long-term benefits and harms as well as the cost-effectiveness of various screening strategies161. Modelling approaches have limitations, however. Models present a simplified representation of disease progression and intervention outcomes. Moreover, the accuracy of the results of modelling is dependent on the underlying assumptions and the degree of uncertainty in the input parameters162. Estimating overdiagnosis through simulations is particularly challenging163 and more so in the absence of data on the rates of disease progression for different risk groups.To date, evidence on the effectiveness of risk-stratified screening has come from model-based studies161 risk stratified women using several combinations of risk factors and showed that quinquennial or triennial screening for the low-risk or moderate-risk groups and annual screening for the high-risk group, from 50–74 years of age, would reduce costs, the number of false-positive findings and overdiagnosis, while averting the same number of deaths as biennial screening between the ages of 50 and 69 years. Trentham-Dietz et al.27 used a combination of mammographic breast density and four exemplar relative risk levels for risk stratification and showed that triennial screening of average-risk women with low breast density, starting at 50 years of age, and annual screening of higher-risk women of the same age with high breast density would be cost-effective at a threshold of $100,000 per quality-adjusted-life years gained and would maintain a similar or better balance of benefits and harms than biennial screening of average-risk women. Pashayan et al.26 used the distribution of polygenic risk in the population combined with other risk factors for stratification and showed that, compared with screening women from age 50–69 years triennially, not screening women at lower risk of developing breast cancer would improve the cost-effectiveness and benefit to harm ratio of the breast-screening programme.Thus far, few studies have evaluated the cost-effectiveness and benefit–harm trade-offs of risk-stratified screening for breast cancer. Vilaprinyo et al.When modifying an existing breast cancer screening programme, several considerations need to be taken into account. In particular, agreement should be reached on the framework of expected changes and acceptable trade-offs, whether in benefits, harms, net benefit, equity, cost or opportunity cost, in order to facilitate decisions on whether the evidence is supportive of the adapted programme. The ultimate aim is to implement risk-stratified screening that is justifiable from ethical, legal and societal viewpoints.The policy priorities should be explicit: is the priority to maximize the return on investment or maximize the benefits of screening? That is, will the total number of screens and/or the budget allocated to the screening programme stay the same, but be utilized in a different way to maximize the benefits by focusing on higher-risk groups; or will the screening efforts and resources be increased to enable tailoring of screening to the risk level of each individual?We have identified several key areas for future research to improve early breast cancer detection Box . The evi166. Having the code made open-source and easily accessible will enhance the transparency of the model158.To have confidence in the validity of the outputs of modelling studies, the models have to be well calibrated, the structural assumptions and parameter estimates should be reported clearly and explicitly and the effects of alternative assumptions should be assessed in sensitivity analyses167. Indeed, although modelling, routine monitoring and observational studies can provide helpful evidence, they are not a replacement for randomized health service studies167.In countries with existing breast cancer screening programmes, randomized health service trial designs could be used to evaluate risk-based screening in routine health-care settings. Such trials enable the comparison of a new policy or intervention to the current standard approach within the context of an existing health service168. In a DCE, participants are asked to choose between a series of alternative hypothetical scenarios described in terms of characteristics (or attributes) of the approach and associated levels of, for example, benefit and/or harm. In making these choices, participants are trading off between preferred and less preferred attributes presented in each alternative scenario. Incorporating the choice probability derived from DCEs for each screening approach into decision analytical modelling might facilitate the identification of optimal screening strategies.Trading off benefits and harms of different screening strategies is a fundamentally value-laden activity. Discrete choice experiments (DCEs) provide a quantitative approach to eliciting women’s preferences169. Finally, although risk-stratified screening could potentially reduce overdiagnosis, a major need remains for tests that can differentiate, at diagnosis, tumours with progressive potential in order to reduce overtreatment. At present, no test is available for such differentiation at diagnosis. Biomarker-driven decisions regarding adjuvant therapy have, however, been incorporated into guidelines for the management of women with certain types of breast cancer170, which suggests that such an approach might be viable at diagnosis.In addition to cost-effectiveness analyses, budget-impact analyses will be needed to assess the affordability of a risk-stratified screening programme in a given settingBefore risk-stratified prevention and early detection programmes for breast cancer can be implemented, health-care providers and policymakers would need to plan the resources, build the infrastructure for population-wide risk assessment, develop policies and regulations to protect the public from stigmatization and discrimination, and provide support for informed decision-making of individual women regarding whether or not to participate in the screening programme. Ultimately, these actions are needed to ensure the feasibility and affordability of providing a high-quality risk-stratified screening programme that is accessible to all and is aligned with public values and preferences. There will not be a single predefined way of organizing and delivering such programmes. The optimal approach will be context-specific to account for the idiosyncrasies of the health-care system, as well as the social, economic, cultural and political context Fig. . Here, w171. This state reflects the extent to which those involved in implementing the new approach are primed, motivated and capable of achieving the required changes172. Organizational readiness is a dynamic process with pull and push factors between what is possible owing to constant emergence of new technological opportunities and what resources are available173.Organizational readiness for systems change is widely recognized as being necessary for the successful implementation of complex changes in health-care settings65. In keeping with this concept, the adaptive design of WISDOM enables learning and adaptation of the risk-assessment model and the screening recommendations accordingly over the course of the trial, instead of waiting for certain new discoveries to emerge before starting the trial, or excluding participants of non-European ancestry (for whom limited relevant data are currently available)152. The coverage with evidence development (CED) model174 is a way of developing a ‘learning-based health-care system’. CED provides a mechanism for promising but unproven health technologies to enter practice sooner, through time-limited reimbursement that is conditional on a specific requirement for generation of further evidence on the performance of the new technology.To address the challenge of a constantly changing environment, health-care organizations should embrace an evolutionary approach, rather than espouse a sudden dramatic shift, by adopting a learning organizational culture and building on existing infrastructure171. To ensure the commitment of health-care organizations, the need for a change should be recognized and embedded in a shared vision, with leadership and coalition of all stakeholders175. To achieve a shared vision, the stakeholders have to agree on a framework of values that are aligned with those of the health-care organization. For example, health-care organizations value time-efficiency; therefore, successful implementation would require time-respecting strategies and tools, such as having one test to predict multiple cancers . Overall, vision, skills, incentives, resources and action plans are needed to achieve the systems change that will be required for implementation of risk-stratified prevention and early detection programmes for breast cancer176.Readiness for change requires the commitment and engagement of all stakeholders, resources  and governance177. Key stakeholders in breast cancer prevention and screening include the users and the providers of the service, health-care professionals, policymakers, payers, advocacy groups, researchers and others. Stakeholder engagement would enable the identification of potential misunderstandings among the various stakeholders regarding opposition to, and perspectives on, the implementation of a risk-stratified programme178. Using a multistakeholder approach to reach agreement on what would constitute sufficient evidence to change practice and on guidelines would increase the chances of implementing the research findings within the health-care system152. Such an approach would also help to articulate the values and preferences of the wider community and to build mutual trust, thereby facilitating the implementation of a programme that is accessible and acceptable. Stakeholder analysis179 would be useful to not only identify the key stakeholders, but also their interests and influences, and the level of involvement of each 177.Given the diverse opinions on breast cancer screening among key stakeholders at present and the specific challenges of risk-stratified screening, engagement of all stakeholders is crucial to implementation of new programmes. A stakeholder is a person, group or organization involved in or affected by a decision180 and thus perceive screening as ‘almost always a good idea’181. This attitude is attributable to suboptimal levels of risk literacy among both patients and doctors as well as the limited transparency in the reporting of risks in the media and patient brochures182. Importantly, therefore, women should be transparently informed — for example, using fact boxes184 — about their baseline risks and the benefit to harm ratio of risk-based screening as compared to the existing options of a universal screening approach or no screening185. The development of risk-stratified programmes will need to include consideration of how to update risk assessments as risk-prediction models improve and how to communicate these changes to individuals.Many women overestimate their risk of developing breast cancer187. Indeed, a methodical review of nine systematic reviews, encompassing at total of 36 unique studies, revealed no evidence that providing risk information would have strong, consistent or sustained effects on behaviour186. Changes in health-related behaviour can, however, be facilitated by including elements of interventions to alter the behaviour in question143.Communicating information on breast cancer risk alone is unlikely to result in changes in health-related behaviours, such as smoking or low levels of physical activity188. Nevertheless, knowledge of whether providing risk estimates will promote informed choices regarding screening attendance is lacking, although the evidence base is starting to increase148. More definitive conclusions regarding the behavioural and emotional effects of receiving risk estimates require studies specifically designed to assess these questions , MyPeBS153 and PERSPECTIVE I&I36).Importantly, the available evidence suggests that providing women with their breast cancer risk estimates is unlikely to produce elevated distress189. The level of uptake is one index of the acceptability of a risk assessment. Many studies have addressed the issue of acceptability of risk-stratified screening for breast cancer from the perspective of women190 and of health-care professionals and policymakers191. The available evidence suggests that risk-stratified screening is broadly acceptable to women if it involves the potential for more frequent screening for those deemed to be at high risk193.Acceptability is a complex and poorly defined concept38. Similarly, major reservations surrounding the appropriateness of reducing the frequency of screening for women deemed to be at low risk have been expressed by health-care professionals, policymakers and women themselves194. A few high-quality ongoing studies37 are examining these issues empirically, rather than discussing the issues as hypothetical possibilities195. Further research is needed to determine the feasibility of risk-stratified screening, particularly studies on implementation of screening in a research context, such as PERSPECTIVE I&I36 and PROCAS2 (ref.37).By contrast, a number of concerns exist among professionals working in this area, not least regarding costs and the available evidence base196. Risk-stratified approaches entail (epi)genetic testing for risk assessment. Health-care professionals need not become geneticists to effectively use the (epi)genomic information obtained197; however, they need to be sufficiently versed in (epi)genomics — for example, in understanding the contribution of common and rare coding variants to risk prediction, gene-panel testing and DNA-sequencing modalities and the implications of identifying pathogenic variants with poorly defined cancer risks or genetic variants of uncertain significance (VUS)198. Health-care systems should develop clear guidance related to the reporting of VUS in order to aid health-care professionals in the management of these variants, including descriptions of how patients with VUS should be informed if and when variants are found to confer an additional risk.Effective delivery of risk-stratified prevention and screening services requires health-care professionals to be competent in the use of a risk tool, in interpreting and applying the risk scores and in communicating risk scores effectively to each individual, including discussion of the accuracy of the risk prediction and its future implications196, and have adequate knowledge of screening risk literacy199 and risk-communication skills; they should also have access to structured referral pathways for those women who need more detailed counselling. Accordingly, aspects of genomics and risk-stratified interventions should be integrated across the continuum of training for health-care professionals, from undergraduate education to broad specialty training to continuous professional development programmes. Educational-needs assessments should inform the educational requirements of each medical specialty200.To engage with a new prevention and/or early detection scheme, the health-care professionals involved need to have a clear understanding of the rationale for risk stratification and risk-tailored interventions202. Some of the issues associated with risk-stratified screening will be dependent on the methods by which a programme is implemented202.Ethical, legal and social issues need to be considered at every step of implementation of risk-based interventions, from health-service planning, invitation of participants and consent and sample collection, to risk calculation, communication of results and storage of data203 — autonomy, beneficence, non-maleficence and justice — provide a useful framework to understand the potential implications of risk-based screening, although these principles are more commonly applied to the doctor–patient relationship in the clinical context. Respecting autonomy requires that an individual has adequate knowledge and understanding to decide whether they wish to opt for a given intervention. The capacity of the individual to independently make an informed decision will depend on the information content, the communication tools used and the adequacy of workforce training in conveying the relevant information. Optimizing the balance between providing benefit (beneficence) and the potential for harm  with a risk-based screening programme requires rigorous evaluation. This balance also requires consideration and mitigation of potential unintended harms of such programmes. These unintended harms might include the negative consequences of risk assessment for individuals  or at a society level . Finally, justice relates to the fairness of a programme. Screening programmes have the potential to increase health inequalities, owing to differences in the level of uptake between socioeconomic groups, including those covered under universal health systems206. Risk-based screening programmes might exacerbate these differences201, given their additional complexity and inherent selectivity relative to universal screening. Efforts are needed to mitigate this possibility, for example, through ‘proportionate universalism’207, whereby social inequalities are considered and programme resources are targeted commensurately208. Communication relating to screening and risk assessment has to be accessible and congruent to the literacy and numeracy level of the recipients while also accurately presenting both the potential benefits and risks209. Meeting these requirements will not only avoid misinterpretation of the information provided and subsequent inequitable use of screening services, but also enable each individual to make an informed decision201. In addition, robust legislation is necessary to prevent discrimination and stigmatization, in particular, by insurers and employers. Current approaches vary by country, but can be broadly divided into four categories: moratoria, industry self-regulation, legal limitations to the use of genetic information, and legal bans211. As an example, in the UK, an open-ended code of practice between insurers and the government exists, prohibiting the use of predictive genetic tests except in defined circumstances212.The four principles of bio-ethics promulgated by Beauchamp and Childress213.The time is right to perform implementation research in a real-world setting of risk-stratified prevention and screening for breast cancer, with clearly defined criteria for success . The research should be designed and conducted together with all stakeholder groups, taking into account the ethical, legal and social context as well as factors that affect implementation . The process has to be iterative in a health-care system conducive to learning and adaptation214 ; however, data on effectiveness  are also being collected, and simulation modelling is being performed to assess the efficiency, resource use, costs and cost-effectiveness of risk-based screening at a population level using real-world administrative data. A third type of hybrid design involves the simultaneous study of effectiveness and implementation strategies. This approach enables the demonstration of which implementation strategies work in a given context, as opposed to demonstrating the effects of a particular implementation strategy on the adoption or uptake of an intervention214.To reduce the time lag between obtaining evidence on the effectiveness of a programme and its implementation, studies with hybrid effectiveness–implementation design could be usedBRCA1/2 variants. This approach would require linking of genetic profiles and the outcomes of preventive interventions to cancer registries, training of treating physicians to develop a working knowledge of cancer risk and genetics, and the development of decision aids for patients.The model of evidence-generating health care could be adopted to study the clinical utility of risk stratification in the prevention of breast cancer among carriers of pathogenic Women with a family history of breast cancer constitute a ‘high-impact’ group in which to first pilot national level application of integrated breast cancer risk assessment. In this group, the intervention might not only substantially improve clinical management, but also provide valuable information on how risk-stratified programmes might perform in the general population. Thus, the results of this pilot approach could form the basis on which to build subsequent population-level risk-based interventions.Substantial progress has been made in research focused on estimating an individual woman’s risk of developing breast cancer, applying risk stratification in breast cancer prevention studies, modelling the benefit–harm balance of risk-stratified early detection approaches, and assessing the acceptability and feasibility of implementing risk-based prevention and screening programmes. To translate this progress into improvements in population health outcomes, a systems approach to the evaluation of risk-based programmes is necessary, taking into account the health-care organization’s readiness for change, its openness to learning and adapting, the social context and the need for engagement of all stakeholders.Supplementary Information


This study was undertaken to discover the socioeconomic impact of breast cancer on young women in Ghana.A qualitative exploratory and descriptive design was used to recruit 12 young women from the University of Ghana hospital, 37 Military hospital and Ridge hospital. Individual interviews were conducted face to face and data transcribed verbatim and analysed using content analysis.perceptions and beliefs; economic concerns; and secrecy. Participants perceived that breast cancer was a test of faith, a spiritual disease that is contagious and disgraceful. Mostly, participants stopped work to cater for themselves, and as a result, they encountered financial challenges. Their challenges were compounded with conscious efforts to keep diagnosis secret to avoid being stigmatized.Three themes emerged: Young women living with breast cancer need support physically, economically and socially from healthcare providers, their families and the society at large. Others too might be interested in your job position and once you are no more, they can occupy it like I am at home now. Many participants had strong religious beliefs about the causes of cancer and cancer treatments. Consequently, it was revealed that some participants spent time in prayer camps praying for healing. The common perceptions and beliefs held by participants about breast cancer included; breast cancer being a disgraceful disease, caused by spiritual and evil forces or human enemies.(W10)…all that I know is that we the women our breast is our heart and once they temper with the breast you will not live long. In the beginning, I refused the surgery. Some also believed that the breast of every woman is precious and that breast cancer is disgraceful, deadly and dangerous.(W6)Once people get to know that you have cancer, they shout hey! Because everything that has to do with cancer is deadly so why should people get closer to you. (W8)As for breast cancer, my sister, it's a disgraceful disease. There is nowhere I have not been to just to get healing but look at me here. Some participants perceived that breast cancer is; “deadly, disgraceful, dangerous and a journey but not a destiny” to the sufferer. “…breast cancer is a very dangerous disease because if you joke with it, it will kill you just like that” (W5)(W8)…You need love and affection from loved ones and if such is not given, it can kill you earlier than the disease itself. … (W7)It is all about having a caring man around you who will go through thick and thin with you. Most of the participants narrated that when one gets breast cancer, the person needs love and affection from family and loved ones to survive it. Others believed that an untimely death may occur if love ones, especially partners do not show love and support to breast cancer patients.(W9)…Recently a lady died in our area and I heard she had breast cancer and went to do surgery. One lady said that the surgery is what killed her. Due to some of the beliefs and perceptions participants had about breast cancer, two participants refused to go for surgery after diagnosis. They shared the belief that the breast is the heart of every woman and that once your breast is removed, you will die.4.1.2According to the participants, the perceived spiritual causes of cancer were reflective in the behaviours and attitudes of friends and families in daily interactions with such people.(W5)…my mum believes the disease can be transmitted so she does not allow me to eat with my son. I have separate bowls, spoon, and cup from that of the family. Even when I'm eating and my child comes and I feed him, my mother will take the boy away and will start talking. When I was admitted and I gave my panties to her to wash for me, she threw them away … I knew she was afraid she could be infected. I am sad she is doing that. (W10)… my mother and siblings hate me and do not talk to me. I believe they can do anything to harm me. ……my auntie too envies me because I have my own house, so I believe my condition is spiritual and I realized it is coming from my mother's side. A participant reported that her mother believed breast cancer is a contagious disease and therefore prevented her from feeding her only child. She also said that due to her disease state, she was not allowed to share plates and cutleries with the rest of the family. Instead, she was given her separate sets of kitchen wares4.2This theme has two subthemes which illuminate the employment difficulties and financial challenges participants encountered. Most of the participants reported that they stopped work to concentrate on their health. One participant said she took a year leave from work without pay. Almost all participants complained of huge hospital bills, and also, most of the treatments were not covered by the national health insurance scheme. Due to the financial challenges, one participant could not start the chemotherapy prescribed for her after surgery. Another participant struggled financially to complete subsequent sections of the chemotherapy.4.2.1(W1)I get stressed up and stress is not good so I had to slow down for a while. I finally withdrew from work totally. (W11)My condition has affected my work a lot, my work is a practically oriented one and I have to go up and down with my students to see whether what I asked them to do they are doing it. But now I cannot move around. I feel dissatisfied and uncomfortable with my work output. Most of the participants abandoned their work to take care of themselves. Some participants cited treatment effects and stress as reasons for their inability to work.(W4)…I have asked for leave without pay for a year to recover fully. (W9)…I have stopped work until I am done with chemo and my surgery. I do not have the strength to go to the market. Some participants took leave from work without salary to recover before going back to work.4.2.2(W12)… because of financial challenges, I could not go for chemotherapy. I also realized that it is not just once but involves six cycles so there was no way I could afford it. More so, I was told insurance does not cover the drugs and they are expensive too. (W2)I was told to pay three thousand cedis (about 500 dollars) for the surgery alone and I did not have money so I left…The laboratory investigations alone cost about six hundred ($) not to talk about the medications. Most of the participants complained of financial constraints and the high cost of bills with the treatment of breast cancer. The inability of the national health insurance to cover the full cost of treatment made it difficult for some participants to initiate treatment on time.(W8)I was told if I do not go for the surgery, cancer can kill me but I do not have money to go for the surgery… I have spent all my money on this disease. Now getting the subsequent cycles of the chemo is also difficult. As for the doctors, they do not care whether you have the money or not. Once you complain they will prescribe so if something is worrying me, I am not able to complain again. A participant lamented that she could not finance her surgery because she had spent all her monies taking care of herself. She is unable to complain when in distress because the doctors would not care about her financial status but would prescribe as she complains.4.3Subthemes under this theme include non‐disclosure of diagnosis, selective disclosure, perceived stigma, withdrawal and isolation,4.3.1(W12)I will not even tell my pastor because you cannot trust anyone… if I tell the Pastor and he uses it to preach from the pulpit what will I do, had I known is always, at last, my sister, I don't want to involve anybody in my affairs. (W5)I do not want my colleagues at work to know that I have breast cancer. I am strong and I just want to keep my condition to myself and not even disclose to my closest friend. You know we ladies talk a lot. Most of the participants preferred keeping their diagnosis to themselves because they did not trust people. A participant indicated that she could not tell her Pastor for the fear that the Pastor might use her diagnosis to preach from the pulpit.4.3.2(W9)It is only my husband who is aware I have breast cancer. (W10)Nobody knows about it except a cousin of mine because when I went for the surgery, she came in at some point to help take care of my kids. My husband and my two kids are also aware, I opened up to them. (W11)I have told almost all my family members about my condition except one of my old ladies who is not feeling fine. Some participants selectively informed their partners, children, close family members and a few significant others. Those who disclosed it to their partners and children did that because they trusted them.My siblings are aware of it but for my prayer group members it was my pastor(W3)who told them that I have a tumour but they don't know the details? (W5)My mother, my spiritual father and my boss at work are aware I have this disease. Other participants informed those who were close, trustworthy and could keep a secret. In some cases, the disclosure was partial. According to some participants, the word cancer was not mentioned in their disclosure; however, the close relations only knew they were not well.Some participants did not disclose their breast cancer diagnosis because they perceived they may be stigmatized.4.3.3(W12)I stay in a compound house with other families and if they get to know of my condition, they will not come close to me and they will spread it in the neighbourhoods. (W7)Why should anybody know that I have breast cancer, they will also add their own story and spread it. It will become like a stigma on me and people will not get close to me anymore. The embarrassment or disgrace attached to breast cancer prevented participants from disclosing their diagnosis to some family members and significant others because they perceived they may be stigmatized and isolated.(W9)I stopped going for prayer sessions…, I have not told anyone because they can say I have used my breast for money rituals. You know, rumours spread like wildfire in our area and I cannot be their chewing stick so I decided to keep it a secret because I cannot tolerate it. (W10)I have not told anybody because they will stigmatize me like I am a witch. They will talk as though I have used my breast for money and all sorts of some rituals. Participants believed that apart from the falsified speculations which might spread about their disease state, they also fear that people may lay blame and false accusations on them. For example, a participant said that people could accuse her of sacrificing her body parts like the breast for money rituals.(W3)…at the workplace, it also happens that if anything petty happens to you, they will pass comments like: ‘Oh this person she is sick don't mind her. (W9)I come from a royal family. Among my siblings, I have a good marriage. I would not want to lose the respect people have for us with this deadly disease. Some participants also felt that if they share their diagnosis with people, especially their friends, they would associate every subsequent complaint to breast cancer. One participant believed that she would lose her respect, royalty and be blamed for bringing a bad disease into her Royal family.(W9)If I bring any maid to the house, she might tell people about my condition and I will be stigmatized. …At times I hear people ask why my last born is not going to school and he tells them mummy says I should not go today but the reason cannot be shared. Due to perceived stigma, a participant did not seek support which is affecting the education of her children.4.3.4(W7)I have changed physically and if I continue to stay in the neighbourhood, people will begin to ask questions and I cannot stand it. … when my skin regains its colour, my hair grows and other things reverse after treatment, I will go back but for now, no! I am very sociable and cannot confine myself to the room so I think what I did is the best. Some of the participants narrated that body changes in breast cancer treatment is obvious. To avoid being noticed of the body changes, they relocated to a new neighbourhood.(W3)… I don't go to programmes any longer because of the wound. Now I don't go for weddings, funerals and other social functions because the wound is not healed for me to replace the breast with something. (W11)… How can I go out if I'm not walking? My family is prepared to send me to programmes but I declined because when we get there… and people see me in the wheelchair, it is embarrassing. Other participants who did not relocate also withdrew from social programmes like wedding ceremonies, funerals, church service and other family programmes. They did so either because of their wounds after surgery, too weak and unable to walk or wheelchair‐bound due to cancer metastasis to the spine.(W5)… my doctors said if you are doing chemo you should avoid stressing yourself and avoid public places so that you don't get infections. I know my immune system is down so I don't go for programmes at all. Other participants did not attend programmes to avoid stressing themselves and exposure to infections because their immune system was compromised as a result of chemotherapy.5This study's findings support previous studies that the socioeconomic experiences of young women diagnosed with Breast Cancer are challenging irrespective of race or status. For example, the social disparities in aetiological knowledge of cancers are well documented (McCutchan, Wood, Edwards, Richards, & Brain, The high cost of breast cancer treatments as reported in the study supports several similar findings from different context including low‐ and middle‐income countries (Ekwueme & Trogdon, Culturally in Africa, sick people are expected to be shown sympathy by the family and society but in instances where the sickness has social and spiritual connotations, people hide their sicknesses to ward off social sympathy, prevent stigmatization and social isolation. This is predominant in Africa as reported by Muliira et al. , in theiIt was realized that disclosure was not done because society, especially friends, would associate any ill‐health with their condition and would not receive attention as expected. These findings support that of Al‐Azri et al.  with OmaThe economic burden of breast cancer in young women is higher than any other cancer type because young women diagnosed with breast cancer become less productive due to negative effects of treatment, they take days off from work to access health care, have reduced working hours and pay higher bills for medical attention and counselling (Ekwueme & Trogdon, The high cost of treatment gave participants financial challenges. The national health insurance of Ghana does not cater fully for the cost of treating breast cancer. Participants paid for their laboratory investigations and treatment cost, but this was not the case in the advanced countries. Williams and Jeanetta  reported6Breast cancer in young women comes with a lot of social and economic challenges. The disease puts a lot of financial burden on young women when they are unable to work as a result of negative treatment effects. Society's deleterious beliefs and perceptions about breast cancer make these women perceive they are stigmatized and therefore isolate themselves.7There is a need for healthcare providers to care for breast cancer patients in way that would not communicate further stigmatization within the health facilities. Again, healthcare providers should intensify public education on the risk factors of breast cancer and also demystify the numerous perceptions and beliefs about the disease.No conflict of interest exists.MI: Conceptualization of the study. She is responsible for the selection of the methodology, investigation, resource mobilization and data analysis. She participated in the initial drafting and editing of the manuscript. LAO and LA: Conceptualization, selection of the methodology, supervision and formal analysis of the study. They were also involved in the drafting, reviewing and editing of the manuscript.Ethical approval was gained from the Noguchi Memorial Institute for Medical Research, Ghana, NMIMR‐IRB CPN 111/15‐16.


Women with BC consumed 20.2% less water  and 14% less total fluids than controls . Multiple stepwise logistic regression showed that the differences remained significant both for daily water consumption  and for total daily liquid intake . Low water and liquids intake as a risk factor for BC may be related to the younger age of our subjects. The effect of age on the potential role of water intake in decreasing BC risk should be investigated.Risk and protective factors for breast cancer (BC) include lifestyle, diet, reproduction, and others. Increased risk for colon cancer was linked with low water intake. The link between water consumption and BC was scarcely studied. We investigated the association between water and fluid consumption and the occurrence of BC in a retrospective case–control study in the Shaare Zedek Medical Center, Jerusalem, in 206 women aged 25–65 years . A food frequency questionnaire (FFQ), consumption of water, foods, and beverages, lifestyle, and other risk and protective factors were recorded. The age of women in both groups was comparable ((M ± SD) 52.7 ± 9.8 and 50.6 ± 11.4 years, respectively ( Cancer is one of the main causes of mortality worldwide ,2. In 20Breast cancer is the second most common cancer in the world and the most common cancer among women . The risBy 2050, the incidence rate of breast cancer is estimated to reach 3.2 million . With inBreast cancer was the fifth leading cause of cancer death in 2012 worldwide, with a record of 324,000 deaths in 2012, and in developed countries it was the most common cause of death. Furthermore, breast cancer was the second cause of death in developed countries, second to lung cancer, with 197,000 deaths accounting for 15.4% of all deaths . The morAmong all risk factors, it has been shown that age is the main risk factor for breast cancer . The medWater intake includes, approximately, 20% contribution of water from solid foods and 80% contribution of water from beverages and drinking water ,30,31. IOn average, American adults consume 1.1 L (1138 mL) of water as a beverage per day. Older adults (≥71 years) consume less water than younger adults. Generally, men and women consume comparable amounts of water as a beverage. Overall, adults consume 644 mL/d of tap water  and 502 mL/d of bottled water (44%). Among adults aged 20–50 years, 83% of total water is from beverages, including 37% from plain water, and 17% from moisture in foods. For this age group, soda is an important source of dietary water, accounting for 13% of total water. Coffee and alcohol respectively provide 8.5% and 8% of total water. Among adults aged 51–70 years, 82% of total water comes from beverages, including 32% from plain water, and 18% from moisture in foods. For this age group, soda provides 10% of total water, whereas coffee provides 16% and tea another 9%. Alcohol provides 5% of total water. Among adults aged ≥71 years, 76.0% of total water comes from beverages, including 30% from plain water. In addition, 27% of water comes from moisture in foods. For this age group, soda provides 6% of total water, whereas coffee provides 18% and tea another 7%. Alcohol provides only 2% of total water for this age group. Women aged ≤70 years exceed the Adequate Intake (AI) value, whereas women aged ≥71 years have a shortfall of approximately 603 mL/d. Among adults aged 20–50 years, 40.6% of women fail to meet the Institute of Medicine AI value for total water (3700 mL for men and 2700 mL for women). For adults aged 51–70 years, 44.9% of women fail to meet the AI value for total water. For adults aged ≥71 years, 94.7% of men and 82.6% of women fail to meet the AI value for water [The proposed mechanism for the role of water intake in reducing the risk for colon cancer is through decreasing the gastrointestinal transit time resulting in constipation ,39. ConsMicozzi et al. showed that among 7702 American women, of whom 123 had breast cancer, fewer bowel movements and hard stools were associated with a higher risk for breast cancer . AdditioDespite the high frequency of breast cancer and the potential benefit of water consumption as a simple, non-invasive means for reducing the risk for breast cancer, the role of water intake has been scarcely studied. Stookey et al. published a pilot study of 44 patients with breast cancer, compared with 55 controls, which showed that water drinking appeared to confer a beneficial effect on breast cancer risk. The relative risk for breast cancer associated with low water drinking was 0.21, and the risk estimate represented a 4.7-fold difference in the odds of water drinking between cases and controls . The stuWe conducted a retrospective case-control study in the pre-operative unit of the Shaare Zedek Medical Center, Jerusalem, Israel. This unit care for patients with breast cancer and other related diseases is one of the leading units in Israel. While officially part of the surgical wing, the unit offers a multi-disciplinary approach with experts in oncology, pathology, and more. Over the course of just one day, the women undergo all necessary tests and examinations. This unit’s working profile allowed to interview diagnosed women with breast cancer in-between the medical process during the same day. In addition, interviewing at this time frame assured to include in this research women with new breast cancer diagnoses.Participants ranged in age from 25 to 65 years. The study group included 106 women with newly diagnosed, histologically confirmed breast cancer, scheduled for surgery. The control group consisted of 100 women without breast cancer, recruited from healthy women who escorted the patients and from women who came to the unit for other procedures unrelated to cancer. One hundred and nineteen patients were asked to participate in the study. Of these, 106 signed an informed consent and completed the interview (89% compliance). For the control group, participation was offered to 286 women matched by age, of whom 100 consented and completed the interview (35% compliance).Data collection was conducted from January to December 2015 and was carried out by personal interviews conducted by one of the authors (YK). The interview included a food frequency questionnaire (FFQ) . InformaDescriptive statistics were used to characterize important covariates, including age, nationality, education, BMI, tobacco use, alcohol use, first-degree relatives with history of breast or ovarian cancer, personal history of benign cancer, marital status, number of births, age at menarche and at menopause, reproductive age (between menarche and menopause), contraceptive hormone use, hormonal replacement therapy (HRT) use, constipation, and physical activity.Quantitative variables were compared using the Mann–Whitney test. Categorical variables were compared using the Chi-Square test. Dichotomous variables were defined using the Fisher’s Exact test. Standard deviations were compared using Levene’s Test for Equality of Variances. Equality of means was compared using t tests. Multi-variable analysis was conducted using a multiple stepwise logistic regression model to evaluate the association of water and total fluid consumption with the presence or absence of breast cancer further.® SPSS® Statistics 2020, New York, NY, USA.Covariates with statistical significance were added to the model. All statistical tests were two-sided, with significance defined at 0.05. Statistical analyses were conducted using IBMData on personal, lifestyle, and demographic characteristics are presented in The study and control groups were comparable in age, nationality, BMI, education, number of births, and age at menarche and menopause. Alcohol consumption and a family history of breast and ovarian cancer were more frequent in the breast cancer group. Smoking rates and lack of physical activity showed a trend toward being higher among the group with breast cancer.Data on water and liquid consumption and other nutritional variables are presented in p = 0.02)  .p = 0.018)  .p = 0.003). In a multiple stepwise logistic regression model, the difference in daily water consumption was statistically significant between groups (p = 0.031), as was total daily liquid intake (p = 0.029). Other variables that remained significant in the logistic regression model were fruit and alcohol consumption and first-degree relatives with breast or ovarian cancer.Subjects in the breast cancer group consumed fewer fresh fruits than the control group . These findings support the observation reported in a small-scale study . In contAs a rule, the incidence of breast cancer increases with age. In pre-menopausal women, the weight of nutritional risk factors for breast cancer is generally higher than in post-menopausal women ,49,50. TSeveral studies found reduced risk for colorectal cancer in association with water consumption ,25,26. TThe role of water intake in reducing the risk for breast cancer could be explained by three mechanisms. First, enhancement of gastrointestinal transit time reduces constipation, and it eliminates carcinogens from the gut faster. This mechanism has been proposed as an explanation for the risk reduction for colorectal cancer by increased water intake . Second,Nutritional risk factors for breast cancer that were previously published include low fruit consumption  and highHigh fruit consumption was found in our study to be associated with a low risk for breast cancer. In contrast, increased risk for breast cancer was found for high alcohol consumption.While low fruit consumption and high alcohol consumption are recognized as factors for breast cancer, the evidence for low water consumption is scanty. The innovation in our paper is the finding that low water consumption is associated with an increased risk for breast cancer, particularly in younger women.This study had several limitations. The retrospective design may result in recall bias. However, the study participants in both groups were not aware of the study hypothesis, and the questions regarding water and fluid consumption were embedded among numerous questions on lifestyle and 45 questions on nutritional variables. patients with breast cancer were interviewed within one month of diagnosis, and they were asked to report on their nutritional habits one year earlier, when they were apparently healthy. Data on BRCA were available for only 31 women with breast cancer and 14 in the control group, as this test is not usually offered to women in primary care in Israel. In addition, as women might have been expected to drink more in the summer, answering the questionnaire during the summer months might have resulted in higher reported fluid consumption. However, this might have been counterbalanced with the increased consumption of hot drinks and soups during winter months. To control for possible seasonal drinking differences, the intervention and control groups were interviewed concurrently.Our findings that women with breast cancer consumed less water and total fluids compared with controls may suggest a role for water intake in decreasing breast cancer risk. As water consumption was shown to be associated with decreased risk for colorectal cancer, the potential role of water in decreasing the risk for breast cancer is appealing. Drinking water is convenient, harmless, and beneficial on many aspects of health. The finding of low water and liquid intake as a risk factor for breast cancer in our study may be related to the younger age of the participants. The effect of age on the potential role of water intake in the prevention of breast cancer should be investigated further.