Recommendations on breast cancer screening and prevention in the context of implementing risk stratification: impending changes to current policies

Practice Guideline


Recommendations on breast cancer screening and prevention in the context of implementing risk stratification: impending changes to current policies


J. Gagnon, MSc*, E. Lévesque, LLM*, The Clinical Advisory Committee on Breast Cancer Screening and Preventiona, F. Borduas, MD, J. Chiquette, MD, C. Diorio, PhD, N. Duchesne, MD, M. Dumais*, L. Eloy, MD, W. Foulkes, MBBS PhD*, N. Gervais, MD§, L. Lalonde, MD*, B. L’Espérance, MD*, S. Meterissian, MD CM MSc*, L. Provencher, MD MA, J. Richard, MD*, C. Savard, I. Trop, MD MPH*, N. Wong, MS MS*, B.M. Knoppers, PhD*, J. Simard, PhD


doi: http://dx.doi.org/10.3747/co.23.2961


ABSTRACT

In recent years, risk stratification has sparked interest as an innovative approach to disease screening and prevention. The approach effectively personalizes individual risk, opening the way to screening and prevention interventions that are adapted to subpopulations. The international perspective project, which is developing risk stratification for breast cancer, aims to support the integration of its screening approach into clinical practice through comprehensive tool-building. Policies and guidelines for risk stratification—unlike those for population screening programs, which are currently well regulated—are still under development. Indeed, the development of guidelines for risk stratification reflects the translational aspects of perspective.

Here, we describe the risk stratification process that was devised in the context of perspective, and we then explain the consensus-based method used to develop recommendations for breast cancer screening and prevention in a risk-stratification approach. Lastly, we discuss how the recommendations might affect current screening policies.

KEYWORDS: Breast cancer, screening, prevention, recommendations, clinical practice

INTRODUCTION

Breast cancer is the most common malignancy among Western women and affects approximately 1.67 million women annually worldwide1. In Canada, the age-standardized mortality rate in female breast cancer has fallen by 43% since the mid-1980s. That reduction is likely attributable to a combination of increased mammography screening2 and the use of more effective therapies3,4. Early detection by screening, with or without the use of preventive medications, can reduce the burden of disease but has drawbacks, including overdiagnosis, anxiety related to additional testing, and costs associated with screening59.

By combining genetic and nongenetic risk factors, risk stratification has the potential to identify individuals at increased risk of breast cancer. Stratification of women according to the risk of developing the disease could improve screening and risk-reduction strategies by targeting those most likely to benefit, leading to a more efficient allocation of clinical resources1015. In particular, it could increase coverage of the subpopulation of younger women at high risk for the disease who are missed by standard age-based screening. Indeed, approximately 18% of breast cancers are diagnosed in women less than 50 years of age, a substantial proportion of whom have no pertinent family history. Moreover, because breast cancer in younger women correlates with poor survival16, early detection has the potential for improved survival, less-invasive treatment, and a higher quality of life, thus reducing the burden of disease and the costs of treatment.

Breast cancer tends to aggregate in families. The disease is approximately twice as common in the first-degree relatives of breast cancer patients as in the general population17. Twin and family studies indicate that the observed familial risk is largely the result of inherited susceptibility from the combined effects of multiple genetic variants18,19. Three classes of breast cancer susceptibility alleles, with varying levels of risk and prevalence in the population, have been identified: high-, intermediate-, and low-risk alleles20,21. Mutations in genes such as BRCA1, BRCA2, PTEN, TP53, and probably PALB2 confer a high lifetime risk of the disease, but are relatively rare22. Mutations in intermediate- risk alleles—for example, CHEK2, ATM—confer a risk that is increased by a factor of about 2–4. Yet neither the high-risk nor the intermediate-risk alleles are responsible for most of the genetic risk. Large-scale genome-wide association studies, replication, and custom genotyping efforts have systematically identified almost a hundred common low-risk single-nucleotide polymorphisms17,23,24. Those low-risk alleles explain another significant part of the genetic risk.

Although the risk conferred by individual single- nucleotide polymorphisms is not sufficiently large to be useful when used alone in risk prediction, their joined effect has recently been demonstrated to be able to achieve a degree of risk prediction that is useful within a risk-stratification approach2527. The risk predicted with a genetic profile could be improved by combining family history with lifestyle risk factors, benign breast disease, and breast density2830.

We can expect that new genomic profiling tests, combined with nongenetic risk factors, will be integrated into risk prediction tools to facilitate the identification of individuals at increased risk for cancer. With several major ongoing initiatives recently launched in Canada, the United States, and Europe to accelerate research for the development of personalized approaches in disease prevention and precision medicine3133, risk stratification could become part of clinical practice sooner than expected14,20,22. In that context, several studies have recently evaluated the public interest in, and the acceptability of, population-based risk-stratified screening for breast cancer3436.

In 2013, an international and interdisciplinary research project called perspective [Personalized Risk Stratification for Prevention and Early Detection of Breast Cancer (http://www.genomecanada.ca/medias/pdf/en/Simard.pdf)] was established. A goal of perspective is to develop a comprehensive risk-prediction tool to stratify women into risk levels computed by their individual genomic and other personal risk factors. With the tool, each woman could be assigned a certain risk level (for example, near population risk, intermediate risk, or high risk). As a translational project, perspective also covers the so-called T3 phase of translational genomics, which encompasses the implementation and integration of genomics into routine clinical practice37. That is, the development of policies for the clinical management of women stratified by risk-prediction tools must also be an integral part of risk-stratification research.

Current guidelines address only the management of very high-risk women identified as carriers of a mutation in one of the high-penetrance genes, including BRCA1 and BRCA2, and of women at high risk as identified by a family history3841. However, to apply the specific exclusions, limits, and frequent updates of those guidelines, a high level of specialized knowledge is required. Use of those tools by general practitioners raises an issue of applicability in the context of routine follow-up. In addition, no guidelines address women at high or intermediate risk as identified using a combination of common and low-frequency genetic variants, personal and family history, and breast density. One of the objectives of perspective is to fill that knowledge gap in the Canadian context.

The integration of risk stratification has the potential to substantially change screening and preventive treatment procedures in clinical practice. Population screening programs in many developed countries generally use age as the primary criterion for screening eligibility: routine mammography is recommended at predetermined intervals, starting between the ages of 40 and 50 years, regardless of potential differences in individual risk. The risk-stratification tools developed in the context of perspective could facilitate the establishment of screening schedules in line with risk levels. For instance, screening schedules for women at high risk could include earlier or more frequent mammography, with the possible use of adjunct technologies such as magnetic resonance imaging (mri).

Here, we describe the rationale and the methodology that led to the formulation of recommendations for breast cancer screening and prevention in the context of a risk-stratification approach to be implemented in the province of Quebec. We also discuss how those recommendations might affect screening policies and directions for breast cancer screening and prevention in the near future.

Risk-Stratification Process

Implementing risk-stratification approaches in clinical practice demands consideration of the organizational features of the health care systems in which clinical practices are embedded. Such features might vary from one health care system to another, but they would generally include the particular health care professionals who will be involved in risk stratification, the populations of women to be stratified, the particular process used to offer genomic profiling, and the integration of the genomic information with other validated risk factors and relevant clinical information needed for an individual risk assessment using a comprehensive risk prediction tool—to name but a few. Currently, few of those features can be determined. Notwithstanding such differences, a number of core components of the risk-stratification approach are already known and can therefore form a basis for the development of clinical policies.

First, the genomic profiling test under development will detect common and low-frequency genetic variants that increase cancer risk slightly (specifically, single-nucleotide polymorphisms) or moderately (ATM and CHEK2, for instance). For the purposes of the recommendations, a provisional hypothesis has been formulated that the genes associated with a substantially increased risk (BRCA1, BRCA2, PTEN, TP53, PALB2, for instance) are not included, taking into consideration the attendant costs, technology, counselling needs, and feasibility issues related to implementation of population screening in a public health context. Active discussion is still underway in the perspective project and in the scientific community about the inclusion of those high-risk genes in population screening42.

Second, risk will be estimated using an updated version of boadicea (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm). The boadicea algorithm, which was designed by researchers at the Centre for Cancer Genetic Epidemiology (Cambridge University, U.K.) is a free online algorithm accessible to health professionals worldwide (http://ccge.medschl.cam.ac.uk/boadicea). The current version of this risk-prediction model is designed to compute mutation carrier probabilities in high- and moderate-risk genes (BRCA1, BRCA2, PALB2, CHEK2, ATM) and age-specific risks of breast and ovarian cancer4347. The information taken into account in the current version of boadicea is the age of the individuals included in the pedigree (for example, the woman and her biological family); Ashkenazi Jewish ancestry; country of origin; year of birth; family history of breast, ovarian, and pancreatic cancer, as well as breast cancer and prostate cancer in male relatives; breast tumour pathology (estrogen receptor, progesterone receptor, her2, CK5/6 and CK14 cytokeratin status) in affected relatives; and mutation carrier status.

In the near future, an updated version of boadicea developed in the context of the perspective project will also use the results of a genomic profiling test and breast density. Thereafter, selected lifestyle and hormonal factors will be added if the data are sufficiently conclusive for an evidence-based calculation. The latter factors include age at menarche, parity and age at the first child’s birth, age at menopause (including prophylactic oophorectomy), benign breast diseases, breastfeeding, height, and modifiable factors such as body mass index, use of hormone replacement therapy, and alcohol consumption.

The risk-stratification process—designed to facilitate the development of the recommendations—will involve 3 steps:

  1. Collection of information

    Information about risk factors will be collected from each woman, including medical and familial history, breast density, and results of the genomic profiling test. Note that individual risk can still be estimated even if some risk factors are missing, but the accuracy of the estimation increases with the number of variables used.

  2. Risk evaluation and stratification in a risk level

    The risk evaluation tool (boadicea) will calculate breast cancer risk for 10 years into the future. The risk stratification curves (Figure 1) will then combine the 10-year risk value with the age of the woman to assign her to 1 of 3 specific risk strata: near population risk, intermediate risk, or high risk.

  3. Risk-adapted measures proposal

    Screening and preventive measures adapted to individual risk level will be offered in accordance with the applicable recommendations.

 


 

FIGURE 1 Risk stratification curves. All points forming the outlines of the curves are approximate and were used for illustrative purposes only to facilitate the discussions between experts during development of the recommendations. The exact limits determined by each curve will be finalized after completion of the comprehensive cost–benefit analyses currently underway in the context of the interdisciplinary PERSPECTIVE project (http://www.genomecanada.ca/medias/pdf/en/Simard.pdf).

METHODS

Recommendations applying to clinical practice are frequently the product of consensus-building by experts in a given field. When strong evidence is lacking, the most effective alternative is often to resort to consensus-based processes, in which case professional opinion and expertise become necessary48. Such expertise is needed to discuss and to reach agreement about selected policy issues and has already been used in consensus-building in the context of breast cancer screening, prevention, and treatment. Well-known examples of such an approach include the Saint-Paul de Vence recommendations on breast cancer treatment49, the recommendations of the American Society of Clinical Oncology on pharmacologic intervention to reduce breast cancer50, and the St. Gallen recommendations on breast cancer care51.

A consensus-based process was considered appropriate for investigating the future implementation challenges and opportunities of the new perspective breast cancer risk-stratification approach with relevant practitioners and stakeholders. To maximize future clinical implementation and adoption of such recommendations, a consensus-building exercise with experts involved in breast cancer care and prevention was planned. Steps toward consensus-building included inviting experts to a consensus meeting to help design the new perspective recommendations, asking them to a vote based on a selection of evidence-based answers, and when necessary, debating a given question among themselves to reach consensus.

At the outset, an expert committee called the Clinical Advisory Committee was created to validate all questions and to adopt the final version of the recommendations. The Committee was composed of 16 health professionals involved in breast cancer prevention and care in the province of Quebec, and 1 observer member from the Quebec Breast Cancer Foundation. A wide range of expertise and health care specialties were represented on the committee: genetic counselling, oncology, general practice, radiology, nursing, medical genetics, public health medicine, surgery, and breast cancer research.

The Clinical Advisory Committee supported the research team during the initial policy development phase and identified the most important topics pertaining to stratified screening and preventive measures. From those general topics, the research team developed 69 multiple- choice questions and answers that were supported by international guidelines and evidence from the literature. The committee reviewed the scientific validity of the proposed questions and assessed their compatibility to ensure the feasibility of implementation of any potential recommendations derived from that exercise. The focus was on intermediate- and high-risk women and so had both to ensure optimal integration of the proposed risk-screening policy into the Quebec health care system and to avoid overlap with the current population-based program. Guidelines for the current breast cancer screening program were outside the purview of the perspective project; that program targets all women 50–69 years of age in the province of Quebec and represents the guidelines in use for the near population risk level. Likewise, recommendations for general prevention topics (for example, alcohol moderation) should be applicable to all women, regardless of risk level. The research team also developed communication and decision aids to facilitate implementation and understanding of the risk-stratification approach.

The exact percentage to be attributed to each risk level (for example, 17%–30% for intermediate risk) was not yet available. As a result, a provisional approximation was used to pursue the work. Determination of the exact percentages will be performed later in the project by incorporating results from ongoing cost–benefit studies (that is, identification of the threshold for balance between the benefits and costs in various screening scenarios) and the recommendations of the Clinical Advisory Committee for each risk level. Thus, provisional and approximate risk percentages were set for all 3 risk levels. The percentages used were those developed by the U.K. National Institute for Health and Care Excellence31, because, to the best of our knowledge, it is the only organization that provides screening and prevention guidelines for 3 risk levels; other sources considered only 2 risk levels. Hence, the exact percentage attributed to each risk level was not part of the consensus reached.

On 29 and 30 March 2014, an additional 29 clinical experts in breast cancer care, together with the Clinical Advisory Committee (for a total of 44 participants), attended a 2-day meeting to answer the 69 questions that had been formulated. That group represented 11 different specialties: oncology (n = 1), public health (n = 4), general practice (n = 8), nursing (n = 2), radiology (n = 7), gynecology (n = 2), surgery (n = 7), breast cancer research (n = 1), genetic counselling (n = 5), medical genetics (n = 5), and pathology (n = 2). After a brief overview of the project, the experts answered the 69 questions using an electronic audience response system (anonymous voting). The results obtained after each question were presented to all the experts in a chart format to evaluate the consensus rate. When a consensual position (≥80% of voter agreement) could not be inferred from the initial vote, a discussion ensued, and a new vote was taken when appropriate. In some cases, questions and answers were modified at the request of the experts to propose an alternative consensus. All discussions were audio- recorded. On site, 3 additional questions were drafted to complement the topics that were presented.

After the meeting, results of the voting and audio records of the meeting were analyzed to identify consensus areas. A consensus was considered reached when agreement exceeded 80%. No question created irreconcilable differences after the vote, and the abstention rate was negligible. After the meeting, 2 complementary questions were sent by e-mail, using the SurveyMonkey platform (Palo Alto, CA, U.S.A.), to all 44 experts. A preliminary version of the recommendations was drafted based on the topics that had garnered consensus; it was reviewed by the Clinical Advisory Committee in conjunction with pie charts of all the vote results. An updated version was sent for validation to all 44 experts who attended the consensus meeting. Minor modifications followed. Lastly, the Clinical Advisory Committee approved the final version of the recommendations in December 2014 (Table i), supported by background literature (see the online supplementary material). All work related to the development of the recommendations occurred in French, and the final version was translated into English.

TABLE I Recommendations of the Clinical Advisory Committee


 

RESULTS

A consensus with 80% or more voter agreement was obtained for 32 questions, with each question leading to the development of one or more recommendations reflecting the clear consensus obtained. For questions on which the level of agreement was lower (<80%), recommendations accommodating opposing views and reflecting a “common denominator” on the issue were developed. Overall, 50 recommendations were developed from the answers and discussions recorded at the consensus meeting and were accepted by the Clinical Advisory Committee (Table i).

An updated decision aid for health professionals that summarizes the recommendations was also validated by the Clinical Advisory Committee (Figure 2). Recommendation topics included referral to genetics clinics and breast disease clinics, breast density, screening of women at high and intermediate risk, role of tomosynthesis in screening, clinical breast examination, screening of women with breast implants, preventive lifestyle, chemoprevention, and preventive surgery. Imaging technologies (choice and timing) and clinical breast examinations were the topics that elicited the most controversy and were the most-debated issues.

 


 

FIGURE 2 Decision aid for breast cancer risk stratification. The percentages used here are approximate; they were used to facilitate discussions between experts during the development of the PERSPECTIVE recommendations. The exact percentages will be finalized after completion of the comprehensive cost–benefit analyses currently underway in the context of the interdisciplinary PERSPECTIVE project (http://www.genomecanada.ca/medias/pdf/en/Simard.pdf). “Lifetime risk” represents risk from age 20.
a For these carriers, refer to other applicable recommendations.
bhttp://ccge.medschl.cam.ac.uk/boadicea.

Summary: Key Recommendations

The first important recommendation concerns the collection of breast density data as an important factor for determining disease risk. Participants in the meeting expressed interest in including breast density in the assessment of breast cancer risk and its effect on the detection of breast cancer.

It is well known that dense breasts confer an increased risk of breast cancer52 and reduce the sensitivity of mammography53,54. There is currently strong interest in using breast density to optimize cancer screening. In Ontario, the breast cancer screening program automatically invites women with more than 75% dense tissue to more frequent mammography screenings32. In the United States, approximately 20 states have enacted laws that require women to be informed when their mammogram shows denser breasts55. For example, in the state of California, women showing more than 50% dense tissue in a mammogram must be informed of that observation through a written report56.

Breast density is a parameter that will be used by boad-icea to evaluate the level of risk, and it is assessed by mammography. However, the Clinical Advisory Committee did not recommend that women have a mammogram solely for the purpose of evaluating breast density. Concerns about risks such as radiation or unnecessary biopsies because of false positives were considered potentially more important than the benefit expected from the breast density scores. The recommendations do require, however, that breast density be systematically evaluated when a mammogram is conducted and be documented in the clinical report.

Second, core recommendations focus on screening for women at both the intermediate-risk and high-risk levels:

  • Intermediate risk

    Annual or biennial mammography is recommended starting at age 40. Women with breast density exceeding 75% should undergo annual mammography, and ultrasonography should also be considered as a complement. Chemoprevention is not recommended for women in this group, with the exception of women having atypical hyperplasia or lobular neoplasia.

  • High risk

    Annual mammography is recommended starting between the ages of 30 and 35 years. Annual mri should be considered from age 30. Two recommendations address preventive treatments for this group:

    • ■ For women more than 35 years of age, chemoprevention using one of the two drugs identified for this purpose (tamoxifen for premenopausal and postmenopausal women, and raloxifene for postmenopausal women) should be considered as a primary prevention method.

    • ■ Preventive bilateral mastectomy should be discussed with these women.

Third, experts agreed to adopt a position on clinical breast exams for screening purposes. According to the recommendations, clinical breast exams should be offered to women as a screening measure regardless of risk level. Breast exams are recommended to be conducted at intervals between 6 months and 2 years, in accordance with the risk level and current breast pathologies (for example, lobular neoplasia, atypical hyperplasia) as detailed in the full text of the recommendations.

Finally, a set of recommendations to help lower the incidence of breast cancer through specific lifestyle and behaviours was also adopted. Those recommendations include relevant topics such as alcohol consumption, tobacco use, weight, physical activity, nutrition, breastfeeding, and breast awareness.

DISCUSSION AND CONCLUSIONS

Currently, the breast cancer screening program in the province of Quebec offers mammography every 2 years for women between the ages of 50 and 69 years. Physicians can also prescribe mammography for younger or older women on an individual basis; however, no tool is available to evaluate individual risk and to manage screening frequency. Consequently, access to screening can vary from woman to woman, depending on physician preferences and access to a general practitioner. The recommendations developed in the context of perspective propose refinement in the factors currently considered for breast cancer screening (specifically, age and, less commonly, family history) and more individualized metrics for breast cancer risk in screening policies (which are currently adapted to the average risk of the general population). The proposed refinements include

  • ■ adapting screening frequency;

  • ■ initiating screening at an age adapted to individual risk;

  • ■ using emerging technologies (such as tomosynthesis);

  • ■ introducing additional screening exams (mri, ultrasonography); and

  • ■ considering preventive treatment for all women at high risk (chemoprevention and surgery).

The perspective recommendations will create an impetus for enhancing policies related to breast cancer screening and preventive care for women in the province of Quebec, and will hopefully encourage decision-makers to consider implementing the risk stratification approach to optimize resource allocation.

Three recommendation areas provoked noteworthy debates among the experts attending the consensus meeting and highly benefited from the live exchanges between attendees.

The first pertains to breast density. Concerning the question about whether mammography should be performed solely to estimate risk, many experts expressed concerns that the risks associated with radiation might outweigh the benefits gained for risk estimation. The first vote on this question did not lead to a consensus, and only 41% believed that mammography should not be systematically performed to evaluate the risk of breast cancer. After debate and a second vote on the same question, consensus was reached, with 84% voting that mammography should not be systematically performed only to determine breast density (Figure 3). To the best of our knowledge, no group has ever recommended that mammography be performed solely as a way to assess breast density for risk-evaluation purposes.

 


 

FIGURE 3 Vote results for Question 12: For women not eligible for the Quebec Breast Cancer Screening Program (e.g., <50 years), should mammography be prescribed for the sole objective of obtaining breast density for risk calculation purposes?

Notably, the specific local issue of providing breast density in the mammographic report was discussed. In the province of Quebec, a breast density estimation has to be provided in the report for every mammogram obtained within the screening program. Breast density is classified within 1 of the 4 intervals used by bi-rads (Breast Imaging- Reporting and Data System)57. However, for mammograms performed outside the Quebec screening program, reporting of results is not standardized, and breast density data are not systematically reported. Given that, in 2012, about 27% of Quebec women between 40 and 49 years of age reported having undergone opportunistic mammography in the preceding 2 years (that is, outside the screening program)58, most experts felt that breast density is useful information that should be provided in all mammography reports. A consensus for the systematic provision of breast density information for mammograms performed outside the screening program was obtained with 83%.

The second topic that provoked considerable debate at the consensus meeting was the issue of additional imaging (for example, ultrasonography or mri) for women at high risk. Approval of only 50% was obtained to “offer” complementary exams to all women at high risk; support increased to 86% when the question was whether such exams should merely be “considered” (Figure 4). The distinction between “offering” and “considering” was thought to be important because the former is perceived to allow less flexibility and to be more constraining for health professionals in a clinical setting. Concerns raised by the members about adding mri to the new set of policies included the longer duration of the test, its costs and availability, false positives, and the absence of data on mortality reduction as a result of its use. The choice to use the verb “consider” can be explained by the absence of exact risk interval limits and the differences between current guidelines. Although some guidelines recommend mri for all women with a lifetime risk of breast cancer exceeding 20%–25%, the guidelines from the National Institute for Health and Care Excellence add a second requirement that these women also have a risk exceeding 30% of carrying a mutation of a highly penetrant gene associated with breast cancer (BRCA1/2 or TP53)30,31,33,59. Since the adoption of the perspective recommendations, the International Agency for Research on Cancer has published its recommendations, in which the Working Group evaluated as “inadequate” the strength of evidence supporting mortality reduction by complementary mri screening for carriers of BRCA1 and BRCA2, illustrating the difficulty of adopting a strong position on this issue9.

 


 

FIGURE 4 Vote results for Questions (A) 17 (Should complementary screening imaging be offered, in addition to mammography, to women at the high-risk level?) and (B) 17.1 (Should complementary screening imaging be considered, in addition to mammography, with women at the high-risk level?) Although those questions about complementary exams did not formally target only magnetic resonance imaging (MRI), discussions focused on MRI as the most appropriate complementary imaging approach. Furthermore, MRI was identified as the complementary imaging technique of choice by 75% of the members.

In the third case, vigorous debate attended the position adopted by members about clinical breast exams, because the position taken strays significantly from some current guidelines. Some agencies do not recommend such exams52, but others still advise them60. The low risk and high clinical utility of detecting tumours by routine breast examination substantiate the recommendation for the use of this technique. Benefits were considered to exceed disadvantages associated with clinical exam. The decision was based on clinical experience, expected risks and benefits9, and current opposing guidelines. Recently, a retrospective study concluded that a significant number of cancers would have been missed if clinical breast exams had not been performed61.

As illustrated, consensus-based recommendations for breast cancer screening and prevention can be facilitated by the active involvement of an advisory committee and the collaboration of external clinical experts. The recommendations thus adopted are essential to the subsequent implementation phases of the risk-stratification approach under development. Risk-based management could optimize resources in the health system by targeting women who can benefit the most from those resources. Moreover, the involvement of health professionals in the development of the recommendations presented here will likely foster their adoption into clinical practice. These recommendations supporting management of risk-stratified women could also facilitate the adoption and implementation of the risk-stratification approach by decision-makers.

CONFLICT OF INTEREST DISCLOSURES

We have read and understood Current Oncology’s policy on disclosing conflicts of interest, and we declare the following interests: LL and IT are radiologists at the clinic Léger et associés. ND is member of the medical team at the Clinique radiologie Audet and is also a consultant and shareholder at SonoCiné Inc. The other authors declare that they have no conflicts to disclose.

ACKNOWLEDGMENTS

The development of these recommendations was funded by the Quebec Breast Cancer Foundation. The perspective project is also funded by the Government of Canada (via Genome Canada and the Canadian Institutes of Health Research) and by the Ministère de l’Économie, de la Science et de l’Innovation (via Genome Quebec).

AUTHOR AFFILIATIONS

*Montreal, QC: Centre of Genomics and Policy, Department of Human Genetics, McGill University (Gagnon, Lévesque, Knoppers); Quebec Breast Cancer Foundation [Dumais (observing member)]; Sir Mortimer B. Davis Jewish General Hospital and McGill University Health Centre (Foulkes); Breast Imaging Centre, Centre hospitalier de l’Université de Montréal (Lalonde, Trop); Hôpital du Sacré-Coeur de Montréal and Groupe d’Étude en Oncologie du Québec (L’Espérance); Royal Victoria Hospital and Cedars Breast Clinic of the McGill University Health Centre (Meterissian); Centre Intégré en traitement, recherche et enseignement en Cancer du Sein, Centre hospitalier de l’Université de Montréal (Richard); Sir Mortimer B. Davis Jewish General Hospital and McGill University (Wong);,
Quebec City, QC: Public Health Branch, Capitale-Nationale (Borduas); Centre hospitalier universitaire (chu) de Québec–Université Laval (Chiquette, Duchesne, Provencher); Centre de coordination des services régionaux, Capitale-Nationale (Chiquette); Quebec Breast Cancer Screening Program (Chiquette, Eloy); chu de Québec–Université Laval Research Center and Department of Social and Preventive Medicine, Université Laval (Diorio); Cancer Branch, Ministry of Health and Social Services (Eloy); Deschênes-Fabia Breast Diseases Center (Provencher); chu de Québec–Université Laval (Duchesne); Canada Research Chair in Oncogenetics, chu de Québec–Université Laval Research Centre, and Department of Molecular Medicine, Université Laval (Simard);,
Joliette, QC: Centre hospitalier régional de Lanaudière (Eloy);,
§Rivière-du-Loup, QC: Centre hospitalier du Grand-Portage (Gervais);,
St-Raymond, QC: Centre de santé et de services sociaux de Portneuf (Savard)..

REFERENCES

1. Ferlay J, Soerjomataram I, Ervik M, et al., eds. globocan 2012. Estimated cancer incidence, mortality and prevalence worldwide in 2012 [Web resource]. Lyon, France: International Agency for Research on Cancer; 2013. [Available at: http://globocan.iarc.fr; cited 8 June 2015]

2. Shields M, Wilkins K. An update on mammography use in Canada. Health Rep 2009;20:7–19. [Available online at: http://www.statcan.gc.ca/pub/82-003-x/2009003/article/10873-eng.pdf; cited 8 June 2015]
pubmed  

3. Mariotto A, Feuer EJ, Harlan LC, Wun LM, Johnson KA, Abrams J. Trends in use of adjuvant multi-agent chemotherapy and tamoxifen for breast cancer in the United States: 1975–1999. J Natl Cancer Inst 2002;94:1626–34.
cross-ref  pubmed  

4. Edwards BK, Brown ML, Wingo PA, et al. Annual report to the nation on the status for cancer, 1975–2002, featuring population-based trends in cancer treatment. J Natl Cancer Inst 2005;97:1407–27.
cross-ref  pubmed  

5. Bleyer A, Welch HG. Effect of three decades of screening mammography on breast-cancer incidence. N Engl J Med 2012;367:1998–2005.
cross-ref  pubmed  

6. Independent UK Panel on Breast Cancer Screening. The benefits and harms of breast cancer screening: an independent review. Lancet 2012;380:1778–86.
cross-ref  

7. Cuzick J, Sestak I, Bonnanni B, et al. on behalf of the serm Chemoprevention of Breast Cancer Overview Group. Selective oestrogen receptor modulators in prevention of breast cancer: an updated meta-analysis of individual participant data. Lancet 2013;381:1827–34.
cross-ref  pubmed  pmc  

8. Coldman A, Phillips N, Wilson C, et al. Pan-Canadian study of mammography screening and mortality from breast cancer. J Natl Cancer Inst 2014;106:pii: dju261.
cross-ref  pubmed  

9. Lauby-Secretan B, Scoccianti C, Loomis D, et al. on behalf of the International Agency for Research on Cancer Handbook Working Group. Breast-cancer screening—viewpoint of the iarc Working Group. N Engl J Med 2015;372:2353–8.
cross-ref  pubmed  

10. Howell A, Astley S, Warwick J, et al. Prevention of breast cancer in the context of a national breast screening programme. J Intern Med 2012;271:321–30.
cross-ref  pubmed  

11. Pashayan N, Duffy SW, Chowdhury S, et al. Polygenic susceptibility to prostate and breast cancer: implications for personalised screening. Br J Cancer 2011;104:1656–63.
cross-ref  pubmed  pmc  

12. Hall P, Easton D. Breast cancer screening: time to target women at risk. Br J Cancer 2013;108:2202–4.
cross-ref  pubmed  pmc  

13. Burton H, Chowdhury S, Dent T, Hall A, Pashayan N, Pharoah P. Public health implications from cogs and potential for risk stratification and screening. Nat Genet 2013;45:349–51.
cross-ref  pubmed  

14. Onega T, Beaber EF, Sprague BL, et al. Breast cancer screening in an era of personalized regimens: a conceptual model and National Cancer Institute initiative for risk-based and preference-based approaches at a population level. Cancer 2014;120:2955–64.
cross-ref  pubmed  pmc  

15. Howell A, Anderson AS, Clarke RB, et al. Risk determination and prevention of breast cancer. Breast Cancer Res 2014;16:446.
cross-ref  pubmed  pmc  

16. Fredholm H, Eaker S, Frisell J, Holmberg L, Fredriksson I, Lindman H. Breast cancer in young women: poor survival despite intensive treatment. PloS One 2009;4:e7695.
cross-ref  pubmed  pmc  

17. Collaborative Group on Hormonal Factors in Breast Cancer. Familial breast cancer: collaborative reanalysis of individual data from 52 epidemiological studies including 58 209 women with breast cancer and 101 986 women without the disease. Lancet 2001;358:1389–99.
cross-ref  

18. Peto J, Mack TM. High constant incidence in twins and other relatives of women with breast cancer. Nat Genet 2000;26:411–14.
cross-ref  pubmed  

19. Mucci LA, Hjelmborg JB, Harris JR, et al. on behalf of the Nordic Twin Study of Cancer (NorTwinCan) Collaboration. Familial risk and heritability of cancer among twins in Nordic countries. JAMA 2016;315:68–76.
cross-ref  pubmed  

20. Mavaddat N, Antoniou AC, Easton DF, Garcia-Closas M. Genetic susceptibility to breast cancer. Mol Oncol 2010;4:174–91.
cross-ref  pubmed  

21. Fachal L, Dunning AM. From candidate gene studies to gwas and post-gwas analyses in breast cancer. Curr Opin Genet Dev 2015;30:32–41.
cross-ref  pubmed  

22. Easton D, Pharoah PD, Antoniou AC, et al. Gene-panel sequencing and the prediction of breast cancer risk. N Engl J Med 2015;372:2243–57.
cross-ref  pubmed  pmc  

23. Michailidou K, Hall P, Gonzalez-Neira A, et al. Large-scale genotyping identifies 41 new loci associated with breast cancer risk. Nat Genet 2013;45:353–61.
cross-ref  pubmed  pmc  

24. Michailidou K, Beesley J, Lindstrom S, et al. Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer. Nat Genet 2015;47:373–80.
cross-ref  pubmed  pmc  

25. Mavaddat N, Pharoah PD, Michailidou K, et al. Prediction of breast cancer risk based on profiling with common genetic variants. J Natl Cancer Inst 2015;107:pii: djv036.
cross-ref  pubmed  pmc  

26. Pharoah PD, Antoniou AC, Easton DF, Ponder BA. Polygenes, risk prediction, and targeted prevention of breast cancer. N Engl J Med 2008;358:2796–803.
cross-ref  pubmed  

27. phg Foundation. Stratified Screening for Cancer: Recommendations and Analysis from the COGS Project. Cambridge, UK: phg foundation; 2014. [Available online at: http://www.phgfoundation.org/file/15380; cited 8 June 2015]

28. Darabi H, Czene K, Zhao W, Liu J, Hall P, Humphreys K. Breast cancer risk prediction and individualised screening based on common genetic variation and breast density measurement. Breast Cancer Res 2012;14:R25.
cross-ref  pubmed  pmc  

29. Garcia-Closas M, Gunsoy NB, Chatterjee N. Combined associations of genetic and environmental risk factors: implications for prevention of breast cancer. J Natl Cancer Inst 2014;106:pii: dju305.
cross-ref  pubmed  pmc  

30. Brentnall AR, Harkness EF, Astley SM, et al. Mammographic density adds accuracy to both the Tyrer–Cuzick and Gail breast cancer risk models in a prospective UK screening cohort. Breast Cancer Res 2016;17:147.
cross-ref  

31. Genome Canada. 2012 Large-Scale Applied Research Project Competition [Web page]. Ottawa, ON; n.d. [Available at: https://www.genomecanada.ca/en/programs/large-scale-science/past-competitions/large-scale-research-project-competitions/2012-large; cited 8 June 2015]

32. European Commission. Towards an International Consortium for Personalised Medicine. Brussels, Belgium: European Commission; 2016. [Available online at: http://ec.europa.eu/research/conferences/2016/permed2016/pdf/towards_ic_permed.pdf; cited 9 October 2016]

33. United States, The White House. Fact Sheet: President Obama’s Precision Medicine Initiative [media release]. Washington, DC: Office of the Press Secretary; 2015. [Available online at: http://www.whitehouse.gov/the-press-office/2015/01/30/fact-sheet-president-obama-s-precision-medicine-initiative; cited 8 June 2015]

34. Koitsalu M, Sprangers MA, Eklund M, et al. Public interest and acceptability of the prospect of risk-stratified screening for breast and prostate cancer. Acta Oncol 2016;55:45–51.
cross-ref  

35. Meisel SF, Pashayan N, Rahman B, et al. Adjusting the frequency of mammography screening on the basis of genetic risk: attitudes among women in the UK. Breast 2015;24:237–41.
cross-ref  pubmed  pmc  

36. Evans DG, Donnelly LS, Harkness EF, et al. Breast cancer risk feedback to women in the UK NHS breast screening population. Br J Cancer 2016;114:1045–52.
cross-ref  pubmed  pmc  

37. Schully SD, Khoury MJ. What is translational genomics? An expanded research agenda for improving individual and population health. Appl Transl Genom 2014;3:82–3.
cross-ref  

38. National Comprehensive Cancer Network (nccn). NCCN Clinical Practice Guidelines in Oncology: Breast Cancer Risk Reduction. Ver. 1.2014. Fort Washington, PA: nccn; 2014. [Current version available online at: http://www.nccn.org/professionals/physician_gls/pdf/breast_risk.pdf (free registration required); cited 8 June 2015]

39. U.K. National Institute for Health and Care Excellence (nice). Familial Breast Cancer: Classification and Care of People at Risk of Familial Breast Cancer and Management of Breast Cancer and Related Risks in People with a Family History of Breast Cancer. London, U.K.: nice; 2013.

40. Cancer Care Ontario (cco). Information for Healthcare Providers on the Ontario Breast Screening Program (OBSP). Toronto, ON: cco; 2013.

41. National Breast and Ovarian Cancer Centre. Advice About Familial Aspects of Breast Cancer and Epithelial Ovarian Cancer. 2nd ed. Surry Hills, Australia: Cancer Australia; 2010. [Current version available online at: https://canceraustralia.gov.au/system/tdf/publications/advice-about-familial-aspects-breast-cancer-and-epithelial-ovarian-cancer/pdf/2015_bog_familial_aspects_int.pdf?file=1&type=node&id=2878; cited 8 June 2015]

42. Foulkes WD, Knoppers BM, Turnbull C. Population genetic testing for cancer susceptibility: founder mutations to genomes. Nat Rev Clin Oncol 2016;13:41–54.
cross-ref  

43. Mavaddat N, Rebbeck TR, Lakhani SR, Easton DF, Antoniou AC. Incorporating tumour pathology information into breast cancer risk prediction algorithms. Breast Cancer Res 2010;12:R28.
cross-ref  pubmed  pmc  

44. Cunningham AP, Antoniou AC, Easton DF. Clinical software development for the Web: lessons learned from the boadicea project. BMC Med Inform Decis Mak 2012;12:30.
cross-ref  

45. MacInnis RJ, Bickerstaffe A, Apicella C, et al. Prospective validation of the breast cancer risk prediction model boadicea and a batch-mode version boadiceacentre. Br J Cancer 2013;109:1296–301.
cross-ref  pubmed  pmc  

46. Lee AJ, Cunningham AP, Kuchenbaecker KB, Mavaddat N, Easton DF, Antoniou AC on behalf of the Consortium of Investigators of Modifiers of BRCA1/2 and the Breast Cancer Association Consortium. boadicea breast cancer risk prediction model: updates to cancer incidences, tumour pathology and Web interface. Br J Cancer 2014;110:535–45.
cross-ref  

47. Lee AJ, Cunningham AP, Tischkowitz, et al. Incorporating truncating variants in PALB2, CHEK2, and ATM into the boadicea breast cancer risk model. Genet Med 2016;:[Epub ahead of print].

48. Loblaw DA, Prestrud AA, Somerfield MR, et al. American Society of Clinical Oncology clinical practice guidelines: formal systematic review-based consensus methodology. J Clin Oncol 2012;30:3136–40.
cross-ref  pubmed  

49. Gligorov J, Namer M. Juste dix ans: 5es recommandations francophones de Saint-Paul-de-Vence [editorial, French]. Oncologie 2013;15:565–6.
cross-ref  

50. Visvanathan K, Hurley P, Bantug E, et al. Use of pharmacologic interventions for breast cancer risk reduction: American Society of Clinical Oncology practice guideline. J Clin Oncol 2013;31:2942–62.
cross-ref  pubmed  

51. Harbeck N, Thomssen C, Gnant M. St. Gallen 2013: brief preliminary summary of the consensus discussion. Breast Care (Basel) 2013;8:102–9.
cross-ref  

52. Nelson HD, Zakher B, Cantor A, et al. Risk factors for breast cancer for women aged 40 to 49 years: a systematic review and meta-analysis. Ann Intern Med 2012;156:635–48.
cross-ref  pubmed  pmc  

53. Boyd NF, Guo H, Martin LJ, et al. Mammographic density and the risk and detection of breast cancer. N Engl J Med 2007;356:227–36.
cross-ref  pubmed  

54. Mandelson MT, Oestreicher N, Porter PL, et al. Breast density as a predictor of mammographic detection: comparison of interval- and screen-detected cancers. J Natl Cancer Inst 2000;92:1081–7.
cross-ref  pubmed  

55. Are You DENSE? D.E.N.S.E. State Efforts [Web page]. Woodbury, CT: Are You Dense Advocacy; n.d. [Current version available online at: http://areyoudenseadvocacy.org/dense; cited 8 June 2015]

56. California State Senate. Senate Bill 1538: An Act to Add and Repeal Section 123222.3 of the Health and Safety Code, Relating to Mammograms. Sacramento, CA: California Legislative Information; 2012. [Available online at: http://leginfo.legislature.ca.gov/faces/billNavClient.xhtml?bill_id=201120120SB1538; cited 8 June 2015]

57. D’Orsi CJ, Bassett LW, Berg WA, et al. bi-rads: mammography, 5th edition. In: D’Orsi CJ, Mendelson EB, Ikeda DM, et al. Breast Imaging Reporting and Data System: ACR BI-RADS—Breast Imaging Atlas. Reston, VA: American College of Radiology; 2013.

58. Canadian Partnership Against Cancer (cpac). Breast Cancer Control in Canada: A System Performance Special Focus Report. Toronto, ON: cpac; 2012. [Available online at: https://content.cancerview.ca/download/cv/quality_and_planning/system_performance/documents/breastcancercontrolreppdf?attachment=0; cited 8 June 2015]

59. Saslow D, Boetes C, Burke W, et al. on behalf of the American Cancer Society Breast Cancer Advisory Group. American Cancer Society guidelines for breast screening with mri as an adjunct to mammography. CA Cancer J Clin 2007;57:75–89. [Erratum in: CA Cancer J Clin 2007;57:185]
cross-ref  pubmed  

60. National Comprehensive Cancer Network (nccn). NCCN Clinical Practice Guidelines in Oncology: Breast Cancer Screening and Diagnosis. Ver. 1.2015. Fort Washington, PA: nccn; 2015. [Current version available online at: https://www.nccn.org/professionals/physician_gls/pdf/breast-screening.pdf; cited 8 June 2015]

61. Provencher L, Hogue JC, Desbiens C, et al. Is clinical breast examination important for breast cancer detection? Curr Oncol 2016;23:e332–9.
cross-ref  pubmed  pmc  


aCommittee members are listed in alphabetical order. Supplemental material cited in this article is available at http://www.current-oncology.com. ( Return to Text )

Correspondence to: Emmanuelle Lévesque, Centre of Genomics and Policy, McGill University, 740 Doctor Penfield Avenue, Suite 5202, Montreal, Quebec H3A 0G1. E-mail: emmanuelle.levesque@mcgill.ca

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Current Oncology, VOLUME 23, NUMBER 6, December 2016







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ISSN: 1198-0052 (Print) ISSN: 1718-7729 (Online)