Faculté de Médecine
«Menopause, breast cancer and menopausal treatments»
Docteur Caroline Antoine-Moussiaux
Thèse soumise à la Faculté de Médecine de l’Université Libre de Bruxelles en vue de l’obtention du grade de Docteur en Sciences Médicales.
Promoteur: Professeur Serge Rozenberg
Membres du Jury:
• Président: Professeur Christian Melot • Secrétaire: Professeur Serge Rozenberg
• Professeur Yves Coppieters’t Wallant • Professeure Joëlle Desreux
• Professeure Anne Gompel • Professeure Axelle Pintiaux • Professeure Caroline Verhoeven
TABLE OF CONTENTS
REMERCIEMENTS (Acknowledgments in French)... 8
LIST OF ABBREVIATIONS ... 14
LIST OF TABLES ... 18
LIST OF FIGURES ... 18
RESUME (French abstract)... 19
ABSTRACT... 20
OUTLINE OF THE THESIS... 21
Part 1. INTRODUCTION ... 22
1.A. Breast cancer incidence and mortality rates ... 22
1.B. Breast cancer risk and protective factors (this part of the introduction is submitted as two review articles) ... 23
1.B.1 Lifestyle-related breast cancer risk and protective factors ... 27
Overweight and obesity...33
Weight changes ...37
Hyperinsulinaemia...39
Hyperglycaemia...39
High circulating levels of insulin growth factor-1 ...39
Diabetes ...40
Tobacco ...41
Alcohol ...42
Menopausal hormone therapy ...43
Oral contraception ...43
Night-shift work ...44
Breastfeeding...45
Age at first birth ...46
Physical activity ...46
Dietary factors ...47
Diagnostic radiation ...50
Medications ...51
1.B.2 Unchangeable breast cancer risk and protective factors... 57
Age ...61
Gender ...61
Race/ethnicity ...61
Height ...62
Endogenous sex hormones ...62
Age at menarche ...63
Age at menopause ...64
Exposure to ionizing radiation ...64
Mammographic density ...65
Benign breast diseases...67
In situ breast carcinoma...68
Personal history of invasive breast cancer...68
Family history of invasive breast cancer ...69
Gene mutations...69
Bone mineral density...71
Others ...71
1.B.3 Conclusions on breast cancer risk and protective factors... 73
1.C. Menopausal hormone therapy: definition, indications and historical perspective... 75
1.C.1 History of menopausal hormone therapy... 75
1.C.2 Definition of menopausal hormone therapy ... 77
1.C.3 Current indications for menopausal hormone therapy... 78
Menopausal symptoms ...78
Genitourinary syndrome of menopause...78
Others ...80
1.C.4 Actual guidelines on use of menopausal hormone therapy ... 81
1.D. Menopausal hormone therapy and breast cancer risk... 88
1.D.1 Women’s Health Initiative studies ... 88
1.D.2 The “Million Women Study” ... 91
1.D.3 The E3N study... 93
1.D.4 Other studies... 96
1.D.5 Tibolone... 100
1.D.6 Comments and summary on breast cancer risk associated with menopausal hormone therapy and tibolone use... 102
1.E. Non-hormonal therapies for menopausal symptoms... 115
1.E.1 Vasomotor symptoms ... 115
Non-hormonal drugs...115
Complementary and alternative medicine ...118
Other alternatives...121
1.E.2 Genitourinary syndrome of menopause ... 122
Vaginal moisturisers and lubricants ...122
Fractional microablative carbon dioxide vaginal laser and low-energy dynamic quadripolar radiofrequency vaginal treatment ...122
1.E.3 Conclusions on non-hormonal therapies for menopausal symptoms ... 123
Part 2. OWN RESEARCH... 124
2.A. Objectives of the research ... 124
2.B. Published articles ... 125
2.B.1 Published articles on the analysis of the changes in breast cancer incidence and sales of menopausal hormone therapy... 125
Study 2: Update of the evolution of breast cancer incidence in relation to hormone replacement therapy
use in Belgium...126
Study 3: Systematic review about breast cancer incidence in relation to hormone replacement therapy use...127
Study 4: Menopausal hormone therapy use in 17 European countries during the last decade ...128
Study 5: Menopausal hormone therapy use in relation to breast cancer incidence in 11 European countries ...129
2.B.2 Published article on the impact of menopausal hormone therapy on breast cancer prognostic factors ... 130
Study 6: Influence of HRT on prognostic factors for breast cancer: a systematic review after the Women's Health Initiative trial...130
2.B.3 Published articles on the medical support for climacteric symptoms in breast cancer patients... 131
Study 7: Safety of hormone therapy after breast cancer: a qualitative systematic review ...131
Study 8: Safety of alternative treatments for menopausal symptoms after breast cancer: a qualitative systematic review ...132
Study 9: A survey among breast cancer survivors: treatment of the climacteric after breast cancer...133
Study 10: Treatment of climacteric symptoms in breast cancer patients: a retrospective study from a medication databank...134
Part 3. GENERAL DISCUSSION... 135
3.A. The influence of menopausal hormone therapy on breast cancer... 135
3.A.1 Trends in breast cancer incidence and sales of menopausal hormone therapy ... 135
3.A.2 The influence of menopausal hormone therapy on breast cancer characteristics and mortality ... 142
Menopausal hormone therapy use and breast cancer characteristics ...142
Menopausal hormone therapy use and breast cancer mortality...149
3.B. The safety and prevalence of use of menopausal treatments in breast cancer patients .. 153
REMERCIEMENTS (Acknowledgments in French)
Je tiens à remercier toutes les personnes qui ont participé à l’élaboration et à la réalisation de ce travail :
Le Professeur Serge Rozenberg, successivement promoteur de mon travail de fin d’études de médecine, de gynécologie et de ma thèse de doctorat, pour ses idées, sa rigeur, son soutien et sa patience exceptionnels.
Madame Lieveke Ameye, biostatisticienne au Data Centre de l’Institut Jules Bordet, sans la précieuse collaboration de laquelle ce travail n’aurait tout simplement pas pu aboutir.
Madame Marianne Paesmans, directrice du Data Centre de l’Institut Jules Bordet, pour son aide et ses remarques judicieuses lors de nos réunions « statistiques ».
Madame Mary Stevens, pour les multiples corrections linguistiques apportées aux articles publiés.
Madame Anne Bormans, bibliothécaire à l’Institut Jules Bordet, pour sa merveilleuse efficacité.
Madame Jean Wright, pour les corrections linguistiques et stylistiques apportées à ce manuscrit.
IMS Health®, l’Institut National d’Assurance Maladie Invalidité, EPC-Familia et les Registres du Cancer belge, autrichien, danois, finlandais, norvégiens, suédois, allemand, irlandais, néerlandais, suisse et britannique pour leur collaboration et les données fournies.
La Fondation Vésale, le Fond IRIS Recherche et les Amis de l’Institut Jules Bordet pour les bourses ayant permis la réalisation de ces travaux.
Mon mari, Stephan, qui depuis presque 20 ans, m’écoute, me conseille, m’encourage et m’assiste dans la réalisation de mes objectifs.
Mes enfants, Nathan et Léa, pour leurs encouragements, leur patience et leur bon sens.
Mes amis et particulièrement Janet, Marie et Samantha pour leur soutien indéfectible, leur optimisme et leurs nombreuses paroles de réconfort.
Le Docteur Benjamin Fishler, Monsieur Thierry Melchior, Madame Aloyse Van Der Stegen et Madame Martine Benoît pour m’avoir guidée et permis d’arriver au bout de ce long chemin.
Mes collègues et particulièrement les Docteurs Christine Gilles, Maxime Fastrez, Valérie Albert, Aurélie Joris et Virginie Liénart pour leur soutien moral.
Mes beaux-parents, Yannic et Rafael, pour leur présence chaleureuse.
CURRICULUM VITAE Personal information
Name and first name Antoine-Moussiaux Caroline Date and place of birth October 5th 1977, Brussels
Nationality Belgian
Professional address Department of Obstetrics and Gynaecology, CHU Saint-Pierre, Free University of Brussels, Rue Haute 322, 1000 Brussels, Belgium
E-mail address caroline_antoine@stpierre-bru.be
College education
2014 International Course of IOF & ISCD, Osteoporosis: Essentials of Densitometry, Diagnosis and Management, Leuven
2010 Inter-university diploma in Colposcopy and Cervico-Vaginal Pathology, Amiens, France
2009 Inter-university diploma in Gynaecology of Childhood and Adolescence, Lille, France
2003–2005 Free University of Brussels, Graduate Diploma in Gynaecology-Obstetrics (la plus grande distincion pour l’ensemble de la formation)
1996–2003 Free University of Brussels, Faculty of Medicine (grande distinction pour l’ensemble des doctorats)
Work Graduation Gynaecology and Obstetrics:
«Traitement de la ménopause et cancer du sein: Pronostic, innocuité et prévalence»; supervised by Prof. S. Rozenberg (la plus grande distinction)
Final work of medical school:
«Facteurs pronostiques du cancer du sein détecté sous traitement hormonal de substitution: Méta-analyse qualitative et étude rétrospective de cas»; supervised by Prof. S. Rozenberg (la plus grande distinction)
Professional activities
2014–present Deputy Head of Clinic, Department of Gynaecology-Obstetrics, Saint-Pierre University Hospital Centre, Brussels
2013–present Scientific collaborator, Department of Gynaecology-Obstetrics, Saint-Pierre University Hospital Centre, Free University of Brussels
2009–present Assistant chargé d’exercices (ASHU), Department of Gynaecology-Obstetrics, Saint-Pierre University Hospital Centre, Free University of Brussels
2009–present Member of the Belgian Menopause Society
Grants
2011 Vesalius Fund Grant for the research project: «Biphosphonates and Breast Cancer: Meta analysis and Retrospective cohort study within medication databanks»
2011 Iris Research Grant for the research project: «Menopause Hormone Therapy use and Breast cancer: Retrospective cohort studies within medication databanks» 2008 Vesalius Fund Grant for the research project: «Risk profile evaluation of women
who may benefit from hormone therapy»
2005 Vesalius Fund Grant for the research project: «Traitements du climatère et interactions avec le tamoxifène»
Publications in international peer-reviewed journals
First author
Antoine C, Ameye L, Paesmans M, de Azambuja E, Rozenberg S. Menopausal hormone therapy use in relation to breast cancer in 11 European countries. Maturitas 2016;84:81-88.
Ameye L, Antoine C, Paesmans M, de Azambuja E, Rozenberg S. Menopausal hormone therapy use in 17 European countries during the last decade. Maturitas. 2014;79:287-291.
Antoine C, Ameye L, Paesmans M, Rozenberg S. Treatment of climacteric symptoms in breast cancer patients: A retrospective study from a medication databank. Maturitas. 2014,78:228-232.
Antoine C, Ameye L, Paesmans M, Rozenberg S. Systematic review about breast cancer incidence in relation to hormone replacement therapy use. Climacteric. 2014 Apr;17(2):16-32.
Antoine C, Ameye L, Paesmans M, Rozenberg S. Update of the evolution of breast cancer incidence in relation to hormone replacement therapy use in Belgium. Maturitas 2012 Aug;72(4):317-23.
Antoine C, Ameye L, Moreau M, Paesmans M, Rozenberg S. Evolution of breast cancer incidence in relation to hormone replacement therapy use in Belgium. Climacteric. 2011 Aug;14(4):464-71.
Caroline Antoine, Jean Vandromme, Maxime Fastrez, Birgit Carly, Fabienne Liebens and Serge Rozenberg. A survey among breast cancer survivors: Treatment of the climacterium after breast cancer. Climacteric 2008;11(4):322-8.
Caroline Antoine, Fabienne Liebens, Birgit Carly, Ann Pastijn and Serge Rozenberg. Safety of alternative treatments for menopausal symptoms after breast cancer: a qualitative systematic review. Climacteric 2007;10:23-26.
C Antoine, F Liebens, B Carly, A Pastijn, S Neusy and S Rozenberg. Safety of hormone therapy after breast cancer: a qualitative systematic review. Human Reproduction, Vol. 22,No. 2,616-622,February 2007.
Caroline Antoine, Fabienne Liebens, Birgit Carly, Ann Pastijn and Serge Rozenberg. Influence of HRT on prognostic factors for breast cancer: a systematic review after the Women’s Health Initiative trial. Human Reproduction, Vol. 19, No. 3, 741-756, March 2004.
Last author
Serge Rozenberg, Birgit Carly, Fabienne Liebens, Caroline Antoine. Risks of osteoporosis associated with breast cancer treatment: The need to access to preventive treatment. Maturitas 2009, Volume 64, 1-3.
Co-author
Rozenberg S, Antoine C, Vandromme J, Fastrez M. Should we abstain from treating women with endometriosis using menopausal hormone therapy, for fear of an increased ovarian cancer risk? Climacteric. 2015 Aug;18(4):448-52.
Rozenberg S, Antoine C, Carly B, Pastijn A, Liebens F. Improving quality of life after breast cancer: prevention of other diseases. Menopause Int. 2007 Jun;13(2):71-4.
Deniz G, Antoine C, Liebens F, Carly B, Pastijn A, Rozenberg S. Treatment of premature menopause in breast cancer patients. Acta Chir Belg. 2007 Jun; 107(3): 263-6.
Serge Rozenberg, Caroline Antoine, Jean Vandromme, Birgit Carly, Ann Pastijn, Sarah Neusy and Fabienne Liebens. Management of the menopause in breast cancer patients. EJC Supplements, Vol 2, No 9 (2004) 81-83.
National publications
Rozenberg S, Vandromme J, Antoine C. Reactualisation of hormonal treatment at the menopause in 2011. Rev Med Brux. 2011 Sep;32(4):239-42.
Oral communications at international scientific congresses (first author)
«Menopausal hormone therapy use in 17 European countries during the last decade». 10th European Menopause and Andropause Society congress, 20-22 May 2015, Madrid, Spain.
«Menopausal hormone therapy use in relation to breast cancer incidence in 11 European countries». 10th
European Menopause and Andropause Society congress, 20-22 May 2015, Madrid, Spain.
«Osteoporosis prevention after breast cancer». 2nd World Congress on Controversies, Debates & Consensus in
Bone, Muscle & Joint Diseases, 21-24 November 2013, Brussels, Belgium.
«Osteoporosis therapy and breast cancer». 10th Congress of the ESG, 18-21 September 2013, Brussels, Belgium.
«Osteoporosis therapy in breast cancer patient». 10th Congress of the ESG, 18-21 September 2013, Brussels,
Belgium.
«Evolution of the breast cancer incidence in relation to hormone replacement therapy use in Belgium». 13th World Congress on Menopause, 8 – 11 June 2011, Rome, Italy.
«La mort de l’hormonothérapie substitutive, pour ou contre?». Symposium Aging and Anti-Aging, February 7th
2009, Luxembourg.
«A survey among breast cancer survivors: Treatment of the climacterium after breast cancer». 12th World
Congress on the Menopause, 19 – 23 May 2008, Madrid, Spain.
«Influence of hormone replacement therapy on prognostic factors for breast cancer: a systematic review after the Women’s Health Initiative Trial». 7th European Congress on Menopause, 3 – 7 June 2006, Istanbul, Turkey. «Treatment of menopausal symptoms after breast cancer: a systematic review». 7th European Congress on
Oral communications at national scientific meetings (first author)
«Non hormonal medical treatment of vasomotor symptoms». Belgian Menopause Society Symposium, November 14th , Brussels.
«A chaque âge sa contraception? La périménopause». Colloque FLCPF, September 25th 2015 – Mons.
«Women and lung cancer: the influence of reproductive factors?». Belgian Menopause Society Symposium, September 19th 2009, Brussels.
«Le Cancer du sein et la ménopause». CUMG: First Symposium 2004-2005, November 27th 2004, Brussels.
«Hormone Replacement Therapy Regimens and Breast Cancer Risk». 24th Belgian Menopause Society
Symposium, November 8th 2003, Brussels.
Posters presented at international scientific congresses
Antoine C, Ameye L, Paesmans M, Rozenberg S. Systematic review about breast cancer incidence in relation to hormone replacement therapy use. 10th European Menopause and Andropause Society congress, 20-22 May 2015, Madrid, Spain.
Antoine C, Ameye L, Paesmans M, Rozenberg S. Treatment of climacteric symptoms in breast cancer patients: A retrospective study from a medication databank. 10th European Menopause and Andropause Society congress,
20-22 May 2015, Madrid, Spain.
Caroline Antoine, Fabienne Liebens, Birgit Carly, Ann Pastijn et Serge Rozenberg: Study protocol: treatment of the climacterium after breast cancer and interactions with tamoxifen. 7th European Congress on Menopause, 3
– 7 june 2006 Istanbul Turkey.
Posters presented at national scientific meetings
Caroline Antoine, Fabienne Liebens, Birgit Carly, Ann Pastijn et Serge Rozenberg: Influence of HRT on prognostic factors for breast cancer: a systematic review after the Women’s Health Initiative trial. 26th Belgian
LIST OF ABBREVIATIONS
AARP American Association of Retired Persons ACE Angiotensin Converting Enzyme
ACS American Cancer Society AI Aromatase Inhibitors
AI/AN American Indian/Alaska Natives
AMBER African American Breast Cancer Epidemiology and Risk API Asian/Pacific Islanders
AR Attributable Risk
ATM gene Ataxia Telangectasia Mutated gene BARD1 BRCA1 Associated RING Domain protein 1 BBD Benign Breast Diseases
BC Breast Cancer
BCE Black Cohosh Extract BMD Bone Mineral Density BMI Body Mass Index
BRCA1 Interacting Protein C-terminal helicase 1 CAM Complementary and Alternative Medicine CCB Calcium Channels Blockers
CCMHT Continuous CMHT CDH1 Cadherin1
CEE Conjugated Equine Estrogens CHD Coronary Heart Diseases CI Confidence Interval cm Centimetre
CMHT Combined MHT CO2 Carbon dioxide
CS Cancer du Sein
CYP2D6 Cytochrome P450 isoenzyme 2D6 CYP3A4 Cytochrome P450 isoenzyme 3A4 DCIS Ductal Carcinoma In Situ
DFS Disease-Free Survival DHEA DeHydroEpiAndrosterone
DHEAS DeHydroEpiAndrosterone Sulphate DNA Deoxyribo Nucleic Acid
DQRF Dynamic Quadripolar RadioFrequency DXA Dual-energy X-ray Absorptiometry
E3N cohort study Etude “Epidémiologique de femmes de la mutuelle générale de l’Education Nationale” cohort study
EMAS European Menopause and Andropause Society EPCAM EPithelial Cell Adhesion Molecule
EPIC European Prospective Investigation into Cancer and Nutrition
EPIC-PANACEA European Prospective Investigation into Cancer and Nutrition-Physical Activity, Nutrition, Alcohol, Cessation of smoking, Eating out of home And obesity
EPT Estrogen Progestin Therapy ER- Estrogen Receptor-Negative ER+ Estrogen Receptor-Positive ET Estrogen Therapy
EU European Union
FDA Food and Drug Administration FFTP First Full-Term Pregnancy FIT Fracture Intervention Trial g Grams
GABA gamma-aminobutiric acid GEE Generalized Estimating Equations GSM Genitourinary Syndrome of Menopause Gy Gray
HER2 Human Epidermal growth factor Receptor 2 HERS Heart and Estrogen/progestin Replacement Study HL Hodgkin’s Lymphoma
HORIZON-PFT Health Outcomes and Reduced Incidence With Zoledronic Acid Once Yearly–Pivotal Fracture Trial
HABITS trial Hormonal Replacement After Breast Cancer – Is It Safe? trial HOT Study HRT Opposed by low-dose Tamoxifen Study
HR Hazard Ratio
HR- Hormone Receptor-negative HR+ Hormone Receptor-positive HRT Hormone Replacement Therapy HT Hormone Therapy
IARC International Agency for Research on Cancer IDC Invasive Ductal Carcinoma
IGF Insulin Growth Factor IGF-1 Insulin Growth Factor 1 IL-6 Interleukin-6
ILC Invasive Lobular Carcinoma IMS International Menopause Society kg Kilograms
LIBERATE trial Livial Intervention following Breast cancer: Efficacy, Recurrence, And Tolerability Endpoints trial
LIFT trial Long-term Intervention on Fractures with Tibolone trial LNG LevoNorGestrel
LNG-IUS LevoNorGestrel IntraUterine system m2 Square Meter
mcg Micrograms mg Milligrams
MHT Menopausal Hormone Therapy MI Myocardial Infarction
mm Millimetre
MPA MedroxyProgesterone Acetate MRN complex Mre11 complex MWS Million Women Study NA Not Available
NAMS North American Menopause Society
NCCAM National Institutes of Health Centre for Complementary and Alternative Medicine NETA Norethisterone Acetate
NHS II Nurses’ Health Study II NHS Nurses’ Health Study
NSAID Non-Steroidal Anti-Inflammatory Drugs OC Oral Contraception
OR Odds Ratio OS Overall Survival
PAR Population Attributable Risk
PAR% Population Attributable Risk Percentage PI Prediction Interval
PLCO Cohort Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial Cohort POF Premature Ovarian Failure
PR- Progesterone Receptor-Negative PR+ Progesterone Receptor-Positive
PREDIMED trial Prevention with Mediterranean Diet trial QOL Quality Of Life
RCT Randomized Controlled Trial RR Relative Risk
SCMHT Sequential CMHT SD Standard Deviation
SEER data Surveillance, Epidemiology and End Results data SERM Selective Estrogen Receptor Modulator
SMR Standardized Mortality Ratio
SNRI Serotonin and Norepinephrine Reuptake Inhibitor SSRI Selective Serotonin Reuptake Inhibitor
THM Traitement Hormonal de la Ménopause TNBC Triple-Negative Breast Cancer TNF-α Tumour Necrosis Factor-alpha TSEC Tissue Selective Estrogen Complex UK United Kingdom
US United States
VEGF Vascular Endothelial Growth Factor VITAL VITamin D and OmegA-3 TriaL VMS VasoMotor Symptoms
VTE Venous Thrombo-embolic Events WHI Women’s Health Initiative
LIST OF TABLES
Table 1. Breast cancer risk and protective factors: attributable risk (as a percentage)... 25 Table 2. Confirmed lifestyle and related risk and protective factors for breast cancer ... 28 Table 3. Putative mechanisms of action of some modifiable risk factors for breast cancer and protective factors in postmenopausal women ... 32 Table 4. Some medications that have been studied and their effect on primary breast cancer risk... 52 Table 5. Confirmed unchangeable risk and protective factors for breast cancer... 58 Table 6. The governing principles on Menopausal Hormone Therapy of the International Menopause Society ... 82 Table 7. The clinical guidelines on menopausal hormone therapy of the North American Menopause Society ... 83 Table 8. The position statement on menopausal hormone therapy from the European Menopause and Andropause Society ... 86 Table 9A. Results and limitations of the main studies on breast cancer risk associated with combined menopausal hormone therapy... 107 Table 9B. Results and limitations of the main studies on breast cancer risk associated with estrogen only menopausal therapy... 110 Table 9C. Results and limitations of the main studies on breast cancer risk associated with tibolone... 113
LIST OF FIGURES
RESUME (French abstract)
ABSTRACT
OUTLINE OF THE THESIS
Part I of the thesis is an exhaustive review of the literature on current knowledge on: • The breast cancer risk and protective factors
• The current indications for menopausal hormone therapy
• The risk of breast cancer associated with menopausal hormone therapy • The non-hormonal alternative therapies for menopausal symptoms
The review aims to put in context menopausal hormone therapy as a risk factor for breast cancer, to review current data on the risk of breast cancer associated with menopausal hormone therapy and on prescribed alternative therapies to menopausal hormone therapy.
Part II of the thesis presents our own research.
It aims to contribute to the analysis of the influence of menopausal hormone therapy on breast cancer and to the improvement of the quality of life of breast cancer patients.
Part III of the thesis critically comments on our findings in a more general perspective and defines the needs for future research.
Part IV of the thesis presents the conclusions.
Part 1. INTRODUCTION
1.A. Breast cancer incidence and mortality rates
World-wide, breast cancer (BC) is the most common cancer in women, constituting more than 25% of the total number of new cancer cases diagnosed in 2012 [Ferlay et al. 2015]. Breast cancer incidence estimates for Belgium were the highest in the world, followed by Denmark and France [Ferlay et al. 2013]. In women, it is the first cause of death by cancer in less developed regions, including Africa, Asia (with the exception of Japan), Latin America, the Caribbean, Melanesia, Micronesia and Polynesia, and the second cause of death in women, by cancer, after lung cancer, in more developed regions, i.e. Europe, North America, Australia, New Zealand and Japan [Ferlay et al. 2015].
Similarly, in Belgium, in 2013, BC ranked as the most frequent tumour in women, accounting for 35% of all malignancies [Cancer burden in Belgium 2004–2013, Belgian Cancer Registry, Brussels 2015]. The incidence rates of BC are similar in the three regions of Belgium and have remained stable over time (data on BC incidence are available for the Flemish Region since 1999 and for the whole of Belgium since 2004). In the Flemish Region, the incidence slightly increased in 2001 (this increase was attributed to the implementation of the screening program) and then slightly decreased, remaining stable over time [Cancer burden in Belgium 2004–2013, Belgian Cancer Registry, Brussels 2015]. However, the risk pattern varied with age: the incidence rates remained stable during the years 2004–2013 in women aged 25–49 and 50–69 years, but increased by 2% annually in the group of women aged 70 years or more [Cancer burden in Belgium 2004–2013, Belgian Cancer Registry, Brussels 2015]. In 2012, BC was the leading cause of death by cancer in women in Belgium (20% of all cancer deaths). However, over time, mortality rates decreased by 2% annually [Cancer burden in Belgium 2004–2013, Belgian Cancer Registry, Brussels 2015].
1.B. Breast cancer risk and protective factors (this part of the introduction is submitted as two review articles)
BC has numerous risk factors. Some are well established while others are still being studied. One should distinguish those risk factors that cannot be changed (e.g. being a woman, age, personal or family history of BC, genetics, etc.) from modifiable risk factors such as those related to lifestyle (e.g. body mass index (BMI), alcohol consumption, bearing children, use of oral contraception (OC), MHT, etc.). Some risk factors may also be influenced by the environment, such as age at menarche, having children or the age at first child, and cannot be modified at any time. Genetic and environmental factors probably influence other risk factors such as breast density [Boyd et al. 2002; Greendale et al. 2003; Boyd et al. 2005]. Personal and family history of BC, and having atypical hyperplasia or a genetic predisposition have a more pronounced impact on BC risk than do the behavioural factors which have a moderate impact on this risk [Wilson et al. 2013]. Nevertheless, the high prevalence of behavioural risk factors may become important at the population level [Singletary 2003; Cancer Research UK, http://www.cancerresearchuk.org/health-professional/cancer-statistics/statistics-by-cancer-type/breast-cancer/risk-factors, accessed July 2016].
prevalence of the risk factor in the population [Rothman and Greenland 1998]. Therefore, the PAR% may vary across different populations and calendar times [Rothman and Greenland 1998]. Moreover, most studies have used different designs and approximations to evaluate the attributable risk of risk factors and some risk factors are highly correlated (e.g. alcohol and tobacco) and not easily distinguishable. The PAR% reported by studies may therefore be variable.
Table 1. Breast cancer risk and protective factors: attributable risk (as a percentage)
RISK FACTOR POPULATION ATTRIBUTABLE RISK
PERCENTAGE (PAR%)
Lifestyle-related risk factors 26–53.5%
Overweight and obesity 5.1–22.8%
Recent MHT use 3.2–19.4%
Delayed first birth
(≥ 30–35 years versus younger)*
1–9.8%
Alcohol consumption
(≥ 6–35g/day (≥ 0.5–3 drinks/day)*
2–9%
Inadequate physical activity** 3–7.6%
Night-shift work 4.6%
Breastfeeding < 6 months 3.1%
Unchangeable risk factors 37.2–57.3%
Early age at menarche (≥ 14 years versus younger)*
8.6–19.8%
Later age at menopause
(≥ 48–52 years versus younger)*
7.4–16.6%
History of benign breast disease 14.1–15.4%
Height ≥ 162 cm 6.5%
Family history of breast cancer 3.64–6.2%
Adapted from Hamajima et al. 2002; Boyd et al. 2005; Sprague et al. 2008; Barnes et al. 2011; Parkin. 2011d; Parkin et al. 2011; Schütze et al. 2011; Hayes et al. 2013; Wilson et al. 2013; Dartois et al. 2016; Shield et al. 2016; Tamimi et al. 2016; Engmann et al. 2017.
*Variable from one study to another.
1.B.1 Lifestyle-related breast cancer risk and protective factors
Table 2. Confirmed lifestyle and related risk and protective factors for breast cancer
RISK FACTOR RELATIVE RISK (95% CONFIDENCE INTERVAL)
Postmenopausal obesity
(BMI ≥ 35 kg/m2 versus normal weight)
1.58 (95% CI 1.40–1.79)
Age at first full term pregnancy (≥ 31 years versus < 22 years)
1.46 (95% CI 1.18–1.81)
Alcohol consumption (≥ 30 g/day versus none)
1.43 (95% CI 1.02–2.02)
X-ray fluoroscopy for tuberculosis (versus general population)
1.29 (95% CI 1.1–1.5)
Menopausal hormone therapy*
(CEE + MPA for ≥ 5 years versus placebo)
1.26 (95% CI 1.00–1.59)
Hormonal contraception
(current and recent users versus never users)
1.20 (95%CI 1.14–1.26)
Physical activity
(highest versus lowest level of activity)
0.88 (95% CI 0.85–0.90)
Breastfeeding
(ever breastfeeding versus no breastfeeding)
0.78 (95% CI 0.74–0.82)
Multiparity
(≥ 5 children versus no children)
0.65 (95% CI 0.53–0.80)
Figure 1. Relative risks of confirmed lifestyle risk and protective factors for breast cancer
The columns in red represent the relative risk of each risk factor and the columns in green represent the relative risk of each protective factor. The black line represents the 95% confidence interval. Adapted from Boice et al. 1991; Clavel-Chapelon et al. 2002; Rossouw et al. 2002; Zhang et al. 2007; Lacey et al. 2009; Chowdhury et al. 2015; Neuhouser et al. 2015; Pizot et al. 2016; Mørch et al. 2017.
Figure 2. Breast cancer and lifestyle risk and protective factors for postmenopausal women
Table 3. Putative mechanisms of action of some modifiable risk factors for breast cancer and protective factors in postmenopausal women
FACTOR PUTATIVE MECHANISMS OF ACTION
Risk factors
Obesity Aromatisation of androgens into estrogens in fat tissue, high insulin and IGFs levels, production of leptin, cytokines and other growth factors (e.g. IL-6, TNF-α, VEGF), reduction of the levels of ghrelin.
Diabetes type 2 Increased circulating concentrations of insulin, IGFs and endogenous sex hormones (estrogens and androgens).
Tobacco Direct DNA damage or by acting as an endocrine disruptor, interfering with estrogen metabolism.
Alcohol Increase of estrogen serum levels, acts as a co-carcinogen (increasing the permeability of cell membranes to carcinogens, i.e. alcohol may act as a solvent for carcinogens contained in tobacco smoke), is mutagenic through acetaldehyde, inhibits detoxification of carcinogens, activates pro-carcinogens, induces oxidative stress and affects folate metabolism.
Night-shift work Suppression of nocturnal melatonin production by the pineal gland, subsequent to nocturnal light exposure, resulting in a decreased level of 6-sulfatoxymelatonin and an increase of circulating estrogen levels.
Protective factors
Breastfeeding Shorter exposure to endogenous sex hormones and post-lactational glandular involution and apoptosis.
Physical activity Lowers adiposity, circulating sex hormone levels, insulin resistance, adipokines, and chronic inflammation.
Overweight and obesity
Being overweight or obese after menopause increases the risk of BC [van den Brandt et al. 2000; Key et al. 2003; Ahn et al. 2007; Suzuki et al. 2009; Parkin & Boyd 2011; Cheraghi el al 2012; Ritte et al. 2012; Collaborative Group on Hormonal Factors in Breast Cancer 2012; Neuhouser et al. 2015]. It was estimated that as much as 5.1–22.8% of cases of BC could be attributed to overweight and obesity [Parkin & Boyd 2011; Hayes et al. 2013; Dartois et al. 2016; Engmann et al. 2017].
BC-specific mortality (RR 2.25, 95% CI 1.51–3.36 for obesity grades 2 and 3) [Neuhouser et al. 2015]. Two meta-analyses reported similar findings on BC-specific mortality [Chlebowski et al. 2002; Protani et al. 2010].
After the menopause, fat tissue represents an important source of estrogens (through aromatisation of androgens into estrogens) [Key et al. 2003]. The estrogen increase may contribute to the greater BC risk associated with a higher BMI among postmenopausal women. To illustrate this hypothesis, BC risk associated with a high BMI is substantially reduced after adjustment for serum estrogen concentrations (RR associated with a 5 kg/m2 increase in BMI of 1.19 (95% CI 1.05–1.34) versus 1.02 (95% CI 0.89–1.17) when adjusted for free estradiol concentration) [Key et al. 2003]. Alternatively, high levels of insulin and insulin growth factors (IGF) may increase the risk of BC in obese, postmenopausal women [Singletary 2003; Lukanova et al. 2004; Gunter et al. 2009; Fowke et al. 2010; Park et al. 2014]. Adipose tissue may also produce pro-inflammatory cytokines (e.g. Interleukin-6 (IL-6), Tumour Necrosis Factor-alpha (TNF-α)) and pro-angiogenic factors (e.g. Vascular Endothelial Growth Factor (VEGF)) that may contribute to BC initiation and progression [Lu et al. 2011; Park et al. 2014]. Ghrelin is an orexigenic hormone, inversely correlated to BMI, produced in multiple tissues [Au et al. 2016]. It has been shown to inhibit aromatase expression and to suppress macrophage-derived inflammatory factors [Au et al. 2016]. Obese women have reduced levels of ghrelin, which therefore favour aromatase activity as well as the production of pro-inflammatory factors [Au et al. 2016]. Leptin levels sharply increase in obese women and may enhance the expression of aromatase, alter the immune environment, induce BC growth and activate the migration and motility of BC cells [Geisler et al. 2007; Park et al. 2014; Picon-Ruiz et al. 2017]. Potential mechanisms of action of postmenopausal obesity on BC risk are presented in Figure 3.
that obesity in premenopausal women was associated with an increased risk of ER- BC and triple-negative BC (TNBC) [Picon-Ruiz et al. 2017]. The presence of confounding factors cannot be excluded.
The influence of BMI on premenopausal BC risk is still poorly understood. The decrease of BC risk in premenopausal women with a high BMI has been related to more frequent anovulatory cycles, with a subsequent decrease of sexual hormones [Potischman et al. 1996]. However, this hypothesis has been contradicted by other studies: in the Nurses’ Health Study II (NHS II), the decreased risk of BC in obese premenopausal women was not related to menstrual cycle characteristics [Michels et al. 2006]. A re-analysis of seven prospective studies, analysing endogenous sex hormone levels, reported that obese premenopausal women may be more often exposed to an environment rich in estrogens [Key et al. 2013]. Alternatively, it has been reported that premenopausal white women with a high BMI had low circulating levels of IGF-1, while obese black premenopausal women may have higher levels of IGF-1 [Lukanova et al. 2004; Fowke et al. 2010]. The risk of BC may therefore be different in black and white women [Fowke et al. 2010]. A recent meta-analysis reported that, in most studies, BC risk was decreased in obese white and black premenopausal women but was probably increased in obese premenopausal Asian women [Amadou et al. 2013b]. Finally, the heterogeneity of obesity (central or peripheric), and therefore of insulin resistance, may also explain the discrepant results observed in premenopausal women [Pichard et al. 2008].
Some studies reported that greater body fatness in childhood and adolescence was associated with decreased pre- and postmenopausal BC risk and therefore with a long-term protective effect on BC risk [Ahn et al. 2007; Baer et al. 2010; Fagherazzi et al. 2013; Keinan-Boker et al. 2016; Xue et al. 2016; Shawon et al. 2017]. It was reported that the decrease might be stronger in women with later age at menarche [Ahn et al. 2007]. Conversely, it was reported that BC risk increased with birth weight (RR 1.15, 95% CI 1.09–1.21) [Xue & Michels 2007; Dartois et al. 2016; Xue et al. 2016]. This increased risk could be limited to premenopausal women [Dartois et al. 2016; Xue et al. 2016].
Figure 3. Potential mechanisms of action of post-menopausal obesity on breast cancer risk
Weight changes
2016]. In the Nurses’ Health Study (NHS), important weight gain from age 18 was associated with increased risk of BC and, more specifically, postmenopausal BC (HR 1.37, 95% CI 1.28–1.47 per 30 kg weight change) [Rosner et al. 2017]. Weight gain during the postmenopausal years was also associated with increased postmenopausal BC risk. Weight loss over 5 kg was associated with decreased postmenopausal BC risk (HR 0.81, 95% CI 0.68–0.97). The authors estimated that 14% of cases of postmenopausal BC in the NHS were attributable to long-term weight change [Rosner et al. 2017]. The European Prospective Investigation into Cancer and Nutrition-Physical Activity, Nutrition, Alcohol, Cessation of smoking, Eating out of home And obesity (EPIC-PANACEA) study was the only one to report an association between weight gain and BC diagnosed before or at age 50 (i.e. premenopausal BC) (HR 1.37, 95% CI 1.02–1.85) but not with BC diagnosed after age 50 [Emaus et al. 2014]. In this study, no association was found between BC risk and weight loss [Emaus et al. 2014]. Some studies reported that the risk of postmenopausal BC was increased by weight gain only in women who were not currently using MHT [Feigelson et al. 2004; Lahmann et al. 2005; Ahn et al. 2007; Cordina-Duverger et al. 2016]. The risk may be higher for ER+ PR+ BC (HR 1.5, 95% CI 1.36–1.65 per 30 kg weight change), although this association was not found to be statistically significant in all studies [Ahn et al. 2007; Vrieling et al. 2010; Emaus et al. 2014; Cordina-Duverger et al. 2016; Rosner et al. 2017].
understand the mechanisms involved.
Hyperinsulinaemia
Insulin exerts mitogenic and anti-apoptotic effects on normal and malignant breast epithelial cells [Goodwin et al. 2002]. In non-diabetic pre- and postmenopausal women, hyperinsulinaemia may be an independent risk factor for BC (HR 2.22, 95% CI 1.39–3.53) [Del Giudice et al. 1998; Gunter et al. 2009; Kabat et al. 2009]. Furthermore, a high fasting insulin blood concentration may also be associated with poor outcomes (HR 2.1, 95% CI 1.2– 3.6; HR 3.3, 95% CI 1.5–7.0, respectively, for distant recurrences and deaths) in women with early stage BC, regardless of their BMI category [Goodwin et al. 2002]. Nevertheless, in a recent meta-analysis, including only studies with a prospective design, no evidence of an association between serum insulin and BC was found [Autier et al. 2013]. Its authors suggested that the increased risk of BC previously associated with hyperinsulinaemia could be due to inadequate control for adiposity [Autier et al. 2013]. Some authors reported that the increased BC risk associated with insulin disappeared in MHT users [Key et al. 2003; Lahmann et al. 2004; Li et al. 2006a; Gunter et al. 2009; Arnold et al. 2016].
Hyperglycaemia
Boyle et al. (2013) recently conducted a meta-analysis, including only prospective studies, evaluating the association between glucose serum levels and BC risk [Boyle et al. 2013]. They found no association between high glucose serum levels and BC risk in non-diabetic, postmenopausal women (RR 1.11, 95% CI 1.00–1.23). However, the studies varied in several factors, e.g. not all studies adjusted their results for adiposity, many studies were based on a single blood sample, and serum glucose levels of comparison groups were variable [Boyle et al. 2013]. Further research is needed to better understand whether high glucose serum levels have an impact on BC risk or whether the risk is linked to the associated hyperinsulinaemia or adiposity.
High circulating levels of insulin growth factor-1
case cohort study of women enrolled in the WHI observational study (WHIOS), levels of total IGF-1 or free IGF-1 were not associated with BC risk [Gunter et al. 2009].
Acromegaly represents a good human model to understand the consequences of a continuous and prolonged exposure to high growth hormone and IGF-1 concentrations [Boguszewski & Ayuk. 2016]. However, the consequences of the excessive secretion of growth hormone, IGF-1 and IGF-binding protein 3 on cell cycle regulation may be difficult to predict and research findings remain conflicting [Boguszewski & Ayuk. 2016; Dal et al. 2018]. In 2014, the clinical practice guideline on acromegaly, published by the Endocrine Society, concluded that the impact of acromegaly and its control on neoplasia risk and mortality was still controversial [Katznelson et al. 2014]. Recently, a small case-control study reported that BC was significantly more common in patients with acromegaly (p = 0.02) [Wolinski et al. 2017]. On the contrary, a Danish nationwide cohort study reported that BC risk was not increased in patients with acromegaly compared to national rates (standardized incidence ratio 1.1 (95%CI 0.5-2.1)) [Dal et al. 2018]. However, the number of cases in this cohort was very small (n=9) and the meta-analysis conducted by the same authors, including their study, yielded to the opposite conclusion: BC risk was increased in patients with acromegaly (standardized incidence ratio 1.6 (95%CI 1.1-2.3)) [Dal et al. 2018].
Poor reproducibility between IGF assays and possible reporting bias may have led to diverging views regarding the importance of the IGF system in BC [Horne et al. 2016]. Acromegaly is a rare disease and most studies included small numbers of patients and had no statistical power to adjust for confounding factors [Boguszewski & Ayuk. 2016]. The heterogeneity of the control populations may be another potential source of bias [Boguszewski & Ayuk. 2016]. Finally, overall cancer incidence in the meta-analysis was more pronounced in single-centre studies suggesting possible selection bias [Dal et al. 2018].
Diabetes
association between diabetes and BC risk may be related to changes in circulating concentrations of insulin, IGFs and endogenous sex hormones (estrogens and androgens) [Larsson et al. 2007]. However, in a recent report from the WHI, diabetes did not appear to increase BC risk after adjustment for BMI and abdominal obesity (HR 1.02, 95% CI 0.93– 1.11) [Gong et al. 2016].
Regarding cancer mortality, some authors have reported an increased risk of BC mortality in diabetic women (HR 1.38, 95% CI 1.20–1.58)) [Liao et al. 2011; De Bruijn et al. 2013]. In the WHI, women with diabetes were more likely to die from invasive cancer in general (HR 1.46, 95% CI 1.34–1.60) and particularly from colorectal cancer (HR 1.44, 95% CI 1.06–1.96) compared to non-diabetic women [Gong et al. 2016].
Obesity may be a strong confounder for the association between diabetes and BC [Boyle et al. 2012; Gong et al. 2016]. Other potential confounding factors are the type of diabetes and the use of anti-diabetic medications [De Bruijn et al. 2013]. The association between diabetes and BC still needs to be confirmed in studies adjusted for all these confounding factors.
Tobacco
current and former active smokers (HR 1.11, 95% CI 1.06–1.16; HR 1.09, 95% CI 1.06–1.12, respectively) [Macacu et al. 2015].
The possible effects of alcohol and tobacco on BC may be confounded since the average alcohol consumption reported by ever smokers is greater than that reported by never smokers in developed countries [Hamajima et al. 2002]. The results of studies analysing the association between smoking and BC should therefore be adjusted for alcohol consumption. The impact of environmental tobacco smoke exposure on BC risk is still not clearly established [Lee & Hamling 2016]. An association with increased BC risk may exist (HR 1.20, 95% CI 1.07–1.33) but study weaknesses (e.g. mainly case–controls studies, no adjustment for confounding factors, small numbers of cases) and possible publication biases limit the interpretation of available data [Dossus et al. 2014; Macacu et al. 2015; Lee & Hamling 2016].
It is possible that tobacco smoke affects BC risk through direct deoxyribonucleic acid (DNA) damage or by acting as an endocrine disruptor, interfering with estrogen metabolism [Dossus et al. 2014]. Genetic variations in carcinogen-metabolizing enzymes may also modify the risk of BC associated with cigarette smoking or passive cigarette smoke exposure [Anderson et al. 2012a; Cotterchio et al. 2014].
Alcohol
Alcohol may have an effect through the estrogen pathway but may also act as a co-carcinogen (increasing the permeability of cell membranes to carcinogens, i.e. alcohol may act as a solvent for carcinogens contained in tobacco smoke), be mutagenic through acetaldehyde, inhibit detoxification of carcinogens, activate pro-carcinogens, induce oxidative stress and affect folate metabolism [Zhang et al. 2007; Allen et al. 2009]. The risk of cancer for alcohol drinkers may be modulated by genetic factors [Bagnardi et al. 2013].
The possible additive risk of the combination of alcohol and MHT has been reported in both the NHS and the WHI study (RR 1.84, 95% CI 1.37–2.46 for women who consumed more than 10 g/day of alcohol and currently use MHT compared with women who were both non-drinkers of alcohol and never-users of MHT) [Chen et al. 2002; Zhang et al. 2007]. However, this additive risk has not been reported in the EPIC cohort [Tjønneland et al. 2007].
Menopausal hormone therapy
Much of the available evidence supports a causal link between MHT and BC. This will be discussed in a separate chapter (1.D. Menopausal hormone therapy and breast cancer risk).
Oral contraception
the Norwegian Women and Cancer study reported that BC risk increased with the cumulated dose of estrogens (RR 1.49 (95%CI 1.11-1.99) for 100 mg or more) (p for trend = 0.002) [Dumeaux et al. 2003]. They could not conclude whether the progestin compound influenced the BC risk due to lack of statistical power, especially for the pills of new generation [Dumeaux et al. 2003]. A case–control study showed an increased BC risk when using a moderate-dose (30–35 mcg) and high-dose (50 mcg) estrogen OC (OR 1.6, 95% CI 1.3–2.0; OR 2.7, 95% CI 1.1–6.2, respectively) but not when using a low-dose (20 mcg) estrogen OC (OR 1.0, 95% CI 0.6–1.7) [Beaber et al. 2014]. A recent nationwide prospective cohort study in Denmark assessed the risk of BC associated with contemporary hormonal contraception, using registry-based data and reported an increased risk of BC among current and recent (discontinuation within the previous 6 months) users of hormonal contraception compared to never users (RR 1.20, 95% CI 1.14–1.26) [Mørch et al. 2017]. This corresponds to approximately one extra BC for every 7960 women using hormonal contraception for 1 year. The risk increased with duration of use and persisted in long-term users (≥ 5 years) at least 5 years after discontinuation. After adjustment for multiple testing, there was no significant difference between combined OC regimens. Current and recent use of progestin-only products was also associated with an increased risk of BC [Mørch et al. 2017]. This study was based on registry data and confounding factors could not be excluded. Oral contraception use has been associated with both ER+ and ER- BC [Althuis et al. 2004; Ritte et al. 2013a; Beaber et al. 2014].
Night-shift work
The International Agency for Research on Cancer (IARC) and the World Health Organization (WHO) recognize night-shift work as a probable carcinogen [Straif et al. 2007]. Some meta-analyses reported that BC risk was associated with night-shift work or circadian disruption (RR 1.14, 95% CI 1.08–1.21) [Megdal et al. 2005; He et al. 2015]. An increased risk of BC may be seen in night-shift workers only after 20–30 years and not for shorter periods of time [Kolstad 2008; Vistisen et al. 2017]. Some others did not confirm this association [Kamdar et al. 2013; Koppes et al. 2014; Travis et al. 2016]. It was estimated that 4.6% of BC cases diagnosed in the UK, in 2010, may be attributed to night-shift work and circadian disruption [Parkin 2011e].
2008]. However, other confounding factors (e.g. BMI, tobacco and physical activity) could not be excluded, the definition of night-shift work varied considerably in the different studies, and most of them were case–control studies [Megdal et al. 2005; Kolstad 2008; Kamdar et al. 2013; He et al. 2015]. Moreover, it has been shown that night workers may have different lifestyle habits [Kolstad 2008; Jia 2013]. Additional, well-conducted and large-scale epidemiological studies are needed.
Breastfeeding
Breastfeeding has been associated with a reduced risk of BC (OR 0.78, 95% CI 0.74–0.82) [Bernier et al. 2000; Collaborative Group on Hormonal Factors in Breast Cancer 2002; Chowdhury et al. 2015; World Cancer Research Fund/American Institute for Cancer Research. Continuous Update Project Findings & Reports, 2017]. This reduced BC risk may be limited to women who breastfed for more than 12 months [Bernier et al. 2000; Collaborative Group on Hormonal Factors in Breast Cancer 2002; Chowdhury et al. 2015]. In the collaborative reanalysis of individual data from 47 epidemiological studies in 30 countries, the RR of BC decreased by 4.3% (95% CI 2.9–5.8; p < 0.0001) for every 12 months of breastfeeding [Collaborative Group on Hormonal Factors in Breast Cancer 2002]. Based on data from the Collaborative Group on Hormonal Factors in Breast Cancer (2002), Parkin (2011) estimated that, in 2010, 3.1% of female BC cases in the UK could be attributed to breastfeeding for fewer than 6 months [Parkin 2011b]. Possible biological mechanisms are shorter exposure to endogenous sex hormones (which are reduced during lactation-induced amenorrhea) and post-lactational glandular involution and apoptosis (which contribute to decrease the proliferation rate and enhance the cellular differentiation) [Bernier et al. 2000; Chowdhury et al. 2015; Lambertini 2016]. However, these results mostly came from case– control studies, possibly affected by recall biases, with an important heterogeneity in the definition of breastfeeding and with possible confounding factors [Bernier et al. 2000; Chowdhury et al. 2015]. A recent meta-analysis also suggested that the findings might have been influenced by a publication bias: trials with statistically significant results were possibly more likely to be published [Chowdhury et al. 2015].
either ER+ PR+ or ER- PR- BC [Ritte et al. 2013a]. In the Nurses Health Studies, breastfeeding appeared more strongly inversely associated with basal-like tumours (7 months or more versus never HR 0.65 (95%CI 0.49-0.87)), though heterogeneity across molecular subtypes of BC was not significant (p for heterogeneity = 0.27) [Sisti et al. 2016].
Parity
I considered childbearing as a lifestyle factor since a woman may choose to have children or not. However, some women do not choose to not have children but are forced to it through infertility. Breast cancer risk is reduced in women who have had one or more children (RR 0.92, 95% CI 0.88–0.96 for each full-term pregnancy) compared to women who have none [Clavel-Chapelon et al. 2002; Collaborative Group on Hormonal Factors in Breast Cancer 2002; Falkenberry & Legare 2002; Olson et al. 2005; Lacey et al. 2009]. In the collaborative reanalysis of individual data from 47 epidemiological studies in 30 countries, the RR for BC decreased by 7.0% (95% CI 5.0–9.0; p < 0.0001) with each birth [Collaborative Group on Hormonal Factors in Breast Cancer 2002]. The risk reduction related to each birth seems to affect essentially ER+ PR+ BC (RR 0.89, 95% CI 0.84–0.94) [Althuis et al. 2004; Ma et al. 2006; Ritte et al. 2013a; Lambertini et al. 2016]. However, in the Nurses Health Studies, parity was not associated with any BC molecular subtypes [Sisti et al. 2016].
Age at first birth
The risk of BC increases with increasing age at first birth (RR 1.03, 95% CI 1.01–1.04 per year) [Armstrong et al. 2000; McPherson et al. 2000; Clavel-Chapelon et al. 2002; Falkenberry & Legare 2002; Singletary 2003; Ma et al. 2006]. This increased risk may be limited to ER+ PR+ BC (RR 1.47, 95% CI 1.15–1.88 for a FFTP at 35 years or more compared to a FFTP at 19 years or less) and may be higher for lobular cancer (RR 1.23, 95% CI 1.17–1.29 for each 5 years of age at FFTP) than for all other BC subtypes [Althuis et al. 2004; Ma et al. 2006; Reeves et al. 2009; Ritte et al. 2013a; Sisti et al 2016]. It has been estimated that 1–9.8% of BC could be attributed to a delayed first birth [Hayes et al. 2013; Dartois et al. 2016; Tamimi et al. 2016].
Physical activity
[Pizot et al. 2016]. Risk protection increases with increasing amounts of physical activity with no threshold effect [Lynch et al. 2011; Pizot et al. 2016]. It was estimated that 3–7.6% of BC cases could be attributed to inadequate physical exercise (less than 30 minutes of moderate physical activity, 5 days per week) [Parkin 2011c; Hayes et al. 2013; Wilson et al. 2013]. Data regarding the impact of the type of physical activity (occupational or non-occupational), adiposity, and menopausal status are conflicting [Lynch et al. 2011; Pizot et al. 2016]. In their meta-analysis, Pizot et al. (2016) reported that the type of physical activity, adiposity and menopausal status did not alter the decrease in BC risk linked to physical activity. In their systematic review, Lynch et al. (2011) reported that the decrease of BC risk was greater for non-occupational physical activity, in leaner and postmenopausal women. Differences between these two analyses may arise from their methodology (Pizot et al. (2016) conducted a meta-analysis combining all of the RRs in order to obtain a global result; Lynch et al. (2011) conducted a descriptive systematic review) and from the variability in the included studies (Pizot et al. (2016) did not include case–control studies and included more recent data). The meta-analysis of Neilson et al. (2017) evaluated the association between BC risk and, solely, recreational physical activity [Neilson et al. 2017]. They analysed case–control and cohort studies and reported a decreased BC risk associated with moderate-vigorous physical activity among pre- and postmenopausal women. This association was weaker among cohort studies and when the results were adjusted for non-recreational physical activity [Neilson et al. 2017]. They reported a possible publication bias: studies showing no association between physical activity and BC risk may have been less often published [Neilson et al. 2017]. High levels of physical activity compared to low levels seem to be associated with a reduced risk for BC regardless of the hormonal receptor status [Lynch et al. 2011; Pizot et al. 2016; Neilson et al. 2017]. The preventive effect of physical activity on BC risk could be lost in women using MHT (RR 0.78, 95% CI 0.70–0.87; RR 0.97, 95% CI 0.88–1.07 for, respectively, never-users and ever-users of MHT) [Pizot et al. 2016].
It is likely that physical activity is associated with a decreased BC risk via multiple interrelated biologic pathways that may involve adiposity, circulating sex hormone levels, insulin resistance, adipokines, and chronic inflammation [Lynch et al. 2011; Oh et al. 2017].
Dietary factors
Evidence of an association between BC risk and dietary factors is lacking.
with the lowest (RR 1.29, 95% CI 1.06–1.56) [Li et al. 2016]. Nevertheless, when looking at the study design, the BC risk reduction was significant only in case–control studies and not in cohort studies (RR 1.07, 95% CI 0.98–1.17; RR 2.12, 95% CI 1.17–3.84, respectively in cohort and case–control studies) [Li et al. 2016]. A descriptive meta-analysis reached the same conclusion [Mourouti et al. 2015]. Meta-analyses of only prospective cohort studies, including the data of the EPIC cohort, found no association between fat intake and BC risk [Alexander et al. 2010; Cao et al. 2016]. In the WHI randomized, controlled dietary modification trial, BC risk in postmenopausal women was not reduced by a low-fat diet [Prentice et al. 2006]. Some studies suggested that the effect might become significant only when fat intake is very high (> 370 mg/day) [Thiébaut et al. 2007; Li et al. 2016] or when considering ER+ PR+ BC [Sieri et al. 2014].
Limited evidence suggests that a Mediterranean diet with unrestricted fat intake may decrease BC risk [Bloomfield et al. 2016]. The Prevention with Mediterranean Diet (PREDIMED) trial, the only trial reporting cancer outcomes, found a lower risk for BC in women whose diet was a Mediterranean diet supplemented with extra-virgin olive oil compared to the control group (HR 0.32, 95% CI 0.13–0.79) [Toledo et al. 2015]. Nevertheless, the trial was initially designed to assess the impact of a Mediterranean diet on cardiovascular events in women aged 60–80 years and at high risk of cardiovascular disease. The number of BC cases was very small and therefore the results should be confirmed in larger trials [Toledo et al. 2015]. Pooled analyses of 13 studies found similar BC incidences at the highest and the lowest levels of adherence to the Mediterranean diet (RR 0.96, 95% CI 0.90–1.03) [Bloomfield et al. 2016]. Another meta-analysis found a decreased BC risk associated with the highest adherence score to the Mediterranean diet (RR 0.93, 95% CI 0.87–0.99) but, when looking at the study design, this effect was limited to the case–control studies (RR 0.90, 95% CI 0.85–0.95; RR 0.99, 95% CI 0.89–1.12 for, respectively, case–control studies and cohort studies) [Schwingshackl & Hoffmann 2015]. This was confirmed by yet a third meta-analysis [Farsinejad-Marj et al. 2015]. The definition of the Mediterranean diet varies considerably from one study to another [Bloomfield et al. 2016]. The studies included in each meta-analysis, and therefore its results, may then vary according to the selected definition.
Fruits and vegetables are important sources of fibre, vitamins and other biologically active
vegetables (RR 0.89, 95% CI 0.80–0.99) [Aune et al. 2012a]. A pooled analysis of 20 studies reported no association between fruit and vegetable intake and overall BC risk (RR 0.98, 95% CI 0.93–1.02) [Jung et al. 2013]. These two meta-analyses did not include the same studies and residual, confounding factors could not be excluded [Aune et al. 2012a; Jung et al. 2013]. Inconsistent findings may be also partly explained by the different groups of fruits and vegetables analysed in each study and by the way the consumption was measured [Aune et al. 2012a; Jung et al. 2013; Mourouti et al. 2015]. Some studies suggested that an association between BC risk and fruit or vegetable consumption could be limited to ER- PR- tumours [Jung et al. 2013; Emaus et al. 2016] or to women with a high intake of fruit or vegetables during adolescence [Farvid et al. 2016a].
Dietary fibre intake may reduce BC risk (RR 0.93, 95% CI 0.89–0.98) [Zhang et al. 2011;
Aune et al. 2012b; Ferrari et al. 2013]. This link could be stronger with high levels of fibre intake [Aune et al. 2012b]. The main food sources of fibre are vegetables, fruit, cereals and legumes [Ferrari et al. 2013]. It remains controversial whether one source of fibre may be better than another [Zhang et al. 2011; Aune et al. 2012b; Ferrari et al. 2013]. A meta-analysis of prospective studies did not report any difference between sources of fibre [Aune et al. 2012b]. Adolescent or early adulthood dietary fibre intake could be of greater importance than adult intake [Liu et al. 2014; Farvid et al. 2016b]. The real impact of fibre intake remains difficult to evaluate, partly because foods high in fibre also contain other biologically active constituents that could contribute to modifying BC risk [Farvid et al. 2016b].
Consumption of large quantities of meat may increase BC risk (HR 1.11, 95% CI 1.04–1.18)
[Taylor et al. 2007; Inoue-Choi et al. 2016]. The increase in BC risk may be caused mainly by the consumption of red and/or processed meat, as shown in a recent meta-analysis of prospective studies (HR 1.10, 95% CI 1.02–1.19; HR 1.08, 95% CI 1.01–1.15, respectively) [Guo et al. 2015]. However, adjustment for other dietary patterns may minimize this association and a large number of analyses for multiple dietary regimens may lead to significant findings by chance [Inoue-Choi et al. 2016].
et al. 2016a]. Additional well-designed cohort or interventional studies will then be needed to confirm the aforementioned associations [Guo et al. 2015].
Diagnostic radiation
Gamma and X-radiations are classified by the IARC as causes of BC [IARC Monographs Volume 75 (2000)]. Diagnostic radiation includes X-rays and nuclear medicine [Parkin & Darby 2011]. In the UK, in 2010, diagnostic radiation was estimated to be responsible for 0.1% of BC [Parkin & Darby 2011].
BC screening. The estimated reduction in BC mortality was 23% for women aged 50–69 years, including women who took up the invitation and women who did not accept the invitation. The overdiagnosis in screened women was estimated to be 6.5% (range 1–10%) compared to unscreened women, and radiation-induced BC death was estimated to occur in 1–10 per 100,000 screened women. The estimated radiation-induced BC death was estimated to be smaller by, at least, a factor 100 than the estimates of death from BC prevented by mammography screening [Lauby-Secretan et al. 2015].
The RR of BC in female tuberculosis patients repeatedly exposed to X-ray fluoroscopy for mass screening was 1.29 (95% CI 1.1–1.5) compared to the general population [Boice et al. 1991]. The risk decreased with increasing age at first exposure (significant RR of 2.26 and 1.72 for women aged 15–19 years at first exposure and 20–24 years, respectively; 95% CI not reported) [Boice et al. 1991]. The risk increased with time since first exposure (significant RR of 1.46, 1.37 and 1.65 for women aged 20–29 years since last exposure, 30–39 years and 40– 49 years, respectively; 95% CI not reported) [Boice et al. 1991]. The RR of BC for 1 Gray (Gy) of radiation exposure by fluoroscopy in tuberculosis patients at a latency period of 10 years was estimated to be 1.61 (95% CI 1.30–2.01) [Boice et al. 1991].
Medications
Table 4. Some medications that have been studied and their effect on primary breast cancer risk
MEDICATION EFFECT ON PRIMARY BC RISK (RR (95% CI))
Protective effect with high level of evidence
Raloxifene* 0.28 (95% CI 0.17–0.46)1
Tamoxifen** 0.62 (95% CI 0.54–0.72)2
Anastrozole 0.47 (95% CI 0.32–0.68)3
Exemestane 0.35 (95% CI 0.18–0.70)3
Possible protective effect (postmenopausal women)***
Metformin 0.75 (95% CI 0.57–0.99)
Bisphosphonates 0.68 (95% CI 0.59–0.80)
Lipophilic statins 0.82 (95% CI 0.70–0.97)
NSAID 0.86 (95% CI 0.81–0.92)
Vitamin D 0.97 (95% CI 0.93–1.00)
Adapted from Cauley et al. 2001; Cuzick et al. 2003; Cauley et al. 2006; Goss et al. 2011; Chlebowski et al. 2012; Liu et al. 2012; Luo et al. 2012; Bauer et al. 2013; Cuzick et al. 2014.
*FDA, but not EMA, approved for BC prevention in postmenopausal women with osteoporosis or at high risk of BC [https://www.cancer.gov/about-cancer/treatment/drugs/raloxifenehydrochloride].
1In older osteoporotic postmenopausal women. In women at high risk of BC, Raloxifene is less effective than
Tamoxifen in preventing invasive BC (RR 1.24 (95%CI 1.05-1.47)) [Vogel et al. 2010].
**FDA, but not EMA, approved for BC prevention in all women at high risk of BC [https://www.cancer.gov/about-cancer/treatment/drugs/tamoxifencitrate].
2In women at high risk of BC.
3In post-menopausal women at high risk of BC.
Raloxifene is a selective estrogen receptor modulator (SERM) with anti-estrogenic effect on
breast and endometrial tissue and estrogenic effect on bone, lipid metabolism and blood clotting [Cummings 1999]. It is the only medication used in a part of the general population with a proven effect on BC risk. In older osteoporotic postmenopausal women, raloxifene reduces the risk of all BC by 72% (RR 0.28, 95% CI 0.17–0.46) and the risk of ER+ BC by 84% (RR 0.16, 95% CI 0.09–0.30) [Cauley et al. 2001]. The risk of ER- BC is not modified by raloxifene (RR 0.88, 95% CI 0.26–3.0) [Cummings et al. 1999]. The risk reduction may be greater in women with higher circulating estradiol levels and with a positive family history of BC [Lippman et al. 2006]. Raloxifene also reduces BC risk in older postmenopausal women with osteopenia [Kanis et al. 2003].
In postmenopausal women at high risk for BC, raloxifene effectively reduces BC risk, but to a lesser extent than tamoxifen [Vogel et al. 2010]. This point concerns women at high BC risk and will not be developed here.
Raloxifene reduces BC risk by competing with endogenous estrogens to bind to estrogen receptors on breast tissue [Cummings et al. 2002]. However, it has also been reported that raloxifene may prevent BC by modulating the IGF pathway and the circulating leptin level [Torrisi et al. 2001; Eng-Wong et al. 2003].
The US Food and Drug administration (FDA), but not the European Medicines Agency (EMA), approves raloxifene for the prevention of BC in postmenopausal women with osteoporosis or at high risk of BC [https://www.cancer.gov/about-cancer/treatment/drugs/raloxifenehydrochloride].
