breast cancer subtypes and screening mammography sensitivity · les tumeurs rede -négatif,...

Breast Cancer Subtypes and Screening Mammography Sensitivity

Mémoire

Sue-Ling Chang

Maîtrise en Épidémiologie Maître ès sciences (M.Sc.)

Québec, Canada

© Sue-Ling Chang, 2014

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Résumé Les cancers du sein peuvent être classifiés selon le statut de récepteur d’estrogène (RE), de récepteur de progestérone (RP), de récepteur HER2, ou selon quatre sous-types (Luminal A, Luminal B, HER2-enrichi, Triple-négatif) ayant des propriétés biologiques et cliniques différentes. La sensibilité du dépistage par mammographie pourrait varier selon ces types de cancers mais ceci n’est pas encore clair. L’agressivité de la tumeur, mesurée par le grade histologique pourrait expliquer cette association. Les types de cancers d’intervalle ont été comparés à ceux de cancers détectés par dépistage parmi 1536 cas infiltrants provenant d’un centre de référence de Québec. Les tumeurs RE-négatif, RP-négatif, HER2-positif, Luminal B, HER2-enrichi et TPN étaient tous plus fréquentes chez les femmes avec cancers d’intervalle que chez celles avec cancers détectés par dépistage. À l’exception des tumeurs HER2-positif et HER2-enrichi, le grade histologique expliquait en grande partie la variabilité observée entre les types de cancer et la sensibilité.

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Abstract Breast cancers can be classified according to tumour estrogen (ER) and progesterone (PR) receptors, human epidermal growth factor receptor 2 (HER2), and according to four subtypes (Luminal A, Luminal B, HER2-enriched, Triple-negative), each with different biological and clinical profiles. These tumour types may also influence screening mammography sensitivity but this is still not clear. Tumour aggressiveness, measured by the histological grade, may also play a role in explaining this association. Interval cancer types were compared to screen-detected cancer types in 1536 invasive cases obtained from a reference center in Quebec. ER-negative, PR-negative and HER2-positive, Luminal B, HER2-enriched and TPN tumours were all more frequent in women with interval cancers than in women with screen-detected cancers. Except for HER2-positive and HER2-enriched tumours, histological grade explained most of the variability observed between tumour receptor status, subtypes and sensitivity.

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Table of Contents Résumé......................................................................................................................................................... iii

Abstract .......................................................................................................................................................... v

Table of Contents ......................................................................................................................................... vii

List of Tables ................................................................................................................................................ ix

List of Figures ............................................................................................................................................... xi

List of Abbreviations .................................................................................................................................. xiii

Acknowledgments ........................................................................................................................................ xv

Foreword .................................................................................................................................................... xvii

Introduction .................................................................................................................................................... 1

Literature Review ........................................................................................................................................... 5

2.1 BREAST CANCER INTRINSIC SUBTYPES ....................................................................................................................................... 5 2.1.1 Description of intrinsic breast cancer subtypes ............................................................................................................... 5 2.1.2 Classification of breast cancer subtypes by immunohistochemistry ................................................................................ 8 2.1.3 Section summary ........................................................................................................................................................... 10

2.2 BREAST CANCER TYPES AND AGGRESSIVENESS ........................................................................................................................ 10 2.2.1 Markers of aggressiveness ............................................................................................................................................ 10 2.2.2 Breast cancer types and aggressiveness ...................................................................................................................... 13 2.2.3 Section summary ........................................................................................................................................................... 16

2.3 BREAST CANCER TYPES AND RADIOLOGIC FEATURES ................................................................................................................ 16 2.3.1 Definition and description of radiologic features ............................................................................................................ 17 2.3.2 Breast cancer types and radiologic features .................................................................................................................. 18 2.3.3 Section summary ........................................................................................................................................................... 21

2.4 SCREENING SENSITIVITY ......................................................................................................................................................... 21 2.4.1 Definition ........................................................................................................................................................................ 21 2.4.2 Characteristics of women .............................................................................................................................................. 26 2.4.3 Aggressiveness and sensitivity ...................................................................................................................................... 28 2.4.4 Radiologic features at screening and sensitivity ............................................................................................................ 30 2.4.5 Breast cancer types and sensitivity ............................................................................................................................... 31 2.4.6 Section summary ........................................................................................................................................................... 33

Objectives and Conceptual Framework ...................................................................................................... 37

3.1 OBJECTIVES ........................................................................................................................................................................... 38 3.2 CONCEPTUAL FRAMEWORK ..................................................................................................................................................... 39

Breast Cancer Subtypes and Screening Mammography Sensitivity .......................................................... 41

4.1 RÉSUMÉ ................................................................................................................................................................................. 42 4.2 ABSTRACT .............................................................................................................................................................................. 44 4.3 INTRODUCTION ....................................................................................................................................................................... 45 4.4 MATERIALS AND METHODS ...................................................................................................................................................... 47 4.5 RESULTS ................................................................................................................................................................................ 50 4.6 DISCUSSION ........................................................................................................................................................................... 52

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4.7 REFERENCES ............................................................................................................................... ERREUR ! SIGNET NON DEFINI.

Conclusion ................................................................................................................................................... 65

References ................................................................................................................................................... 69

Appendix ...................................................................................................................................................... 77

APPENDIX A. COMPLETE-CASE RESULTS OF TUMOUR TYPE AND HISTOLOGICAL GRADE OF BREAST CANCERS (N=806) ....................... 78 APPENDIX B. COMPLETE-CASE RESULTS OF TUMOUR TYPE OF INVASIVE INTERVAL BREAST CANCERS RELATIVE TO SCREEN-DETECTED CANCERS (N=858) ....................................................................................................................................................................... 79 APPENDIX C. COMPLETE-CASE RESULTS OF TUMOUR TYPE OF INVASIVE CLINICAL BREAST CANCERS RELATIVE TO SCREENED BREAST CANCERS (N=1536) ..................................................................................................................................................................... 80 APPENDIX D. TUMOUR TYPE OF INVASIVE INTERVAL BREAST CANCERS RELATIVE TO SCREEN-DETECTED BREAST CANCERS, ADJUSTED FOR VASCULAR INVASION (N=858) ................................................................................................................................................ 81 APPENDIX E. COMPLETE-CASE RESULTS OF TUMOUR TYPE OF INVASIVE INTERVAL BREAST CANCERS RELATIVE TO SCREEN-DETECTED BREAST CANCERS, ADJUSTED FOR VASCULAR INVASION (N=858) .................................................................................................... 82

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List of Tables TABLE 1. BREAST CANCER SUBTYPES DETERMINED BY IHC ASSESSMENT OF ER, PR, AND HER2 STATUS. .................................. 9 TABLE 2. FEATURES AND RELATED SCORES TO EVALUATE HISTOLOGICAL GRADE ACCORDING TO THE ELSTON-ELLIS GRADING METHOD. 11 TABLE 3. SUMMARY AND DESCRIPTION OF GRADE 1, 2, AND 3. ................................................................................................. 12 TABLE 4. CHARACTERISTICS OF STUDIES REPORTING ADJUSTED RESULTS FOR THE RELATIONSHIP BETWEEN SUBTYPES AND HISTOLOGICAL

GRADE. ....................................................................................................................................................................... 15 TABLE 5. COMPARISON OF STUDIES EXAMINING BREAST CANCER SUBTYPES AND SENSITIVITY .................................................... 35 Article tables TABLE 1. CHARACTERISTICS OF STUDY POPULATION (N=1536)................................................................................................ 59 TABLE 2. TUMOUR TYPE AND HISTOLOGICAL GRADE OF BREAST CANCERS (N=806) ................................................................... 61 TABLE 3. TUMOUR TYPE OF INVASIVE INTERVAL BREAST CANCERS RELATIVE TO SCREEN-DETECTED BREAST CANCERS (N=858) . 62 TABLE 4. TUMOUR TYPE OF INVASIVE CLINICAL BREAST CANCERS RELATIVE TO SCREENED BREAST CANCERS (N=1536) ............. 63 Appendix tables ADDITIONAL TABLE 1. COMPLETE-CASE RESULTS OF TUMOUR TYPE AND HISTOLOGICAL GRADE OF BREAST CANCERS (N=806) ... 78 ADDITIONAL TABLE 2. COMPLETE-CASE RESULTS OF TUMOUR TYPE OF INVASIVE INTERVAL BREAST CANCERS RELATIVE TO SCREEN-

DETECTED CANCERS (N=858) ...................................................................................................................................... 79 ADDITIONAL TABLE 3. COMPLETE-CASE RESULTS OF TUMOUR TYPE OF INVASIVE CLINICAL BREAST CANCERS RELATIVE TO SCREENED

BREAST CANCERS (N=1536) ........................................................................................................................................ 80 ADDITIONAL TABLE 4. TUMOUR TYPE OF INVASIVE INTERVAL BREAST CANCERS RELATIVE TO SCREEN-DETECTED BREAST CANCERS,

ADJUSTED FOR VASCULAR INVASION (N=858) ............................................................................................................... 81 ADDITIONAL TABLE 5. COMPLETE-CASE RESULTS OF TUMOUR TYPE OF INVASIVE INTERVAL BREAST CANCERS RELATIVE TO SCREEN-

DETECTED BREAST CANCERS, ADJUSTED FOR VASCULAR INVASION (N=858) ................................................................... 82

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List of Figures FIGURE 1. BREAST ANATOMY AND HISTOLOGY. .......................................................................................................................... 5 FIGURE 2. DENDROGRAM FROM HIERARCHICAL CLUSTERING OF 115 TUMOUR SAMPLES. .............................................................. 8 FIGURE 3. TYPICAL HISTOLOGICAL VIEWS OF TUMOURS BY GRADE SCORES RELATIVE TO NORMAL BREAST TISSUE. ...................... 12 FIGURE 4. RADIOLOGIC ABNORMALITIES OF THE BREAST. ......................................................................................................... 17 FIGURE 5. DRAWN REPRESENTATION OF MASS SHAPES AND MARGINS, AND EXAMPLES OF MICROCALCIFICATION MORPHOLOGIES. 18 FIGURE 6. REPRESENTATION OF THE NATURAL HISTORY OF BREAST CANCER: THE NON-DETECTABLE PHASE, THE PRECLINICAL DETECTABLE

PHASE AND THE CLINICAL PHASE. .................................................................................................................................. 22 FIGURE 7. MODIFIED 2X2 TABLE FEATURING RESULTS OF SCREENING MAMMOGRAPHY, ASSESSMENT, AND BREAST CANCER DIAGNOSIS. 23 FIGURE 8. REPRESENTATION OF CASE-CONTROL AND STUDY DESIGN. ...................................................................................... 24 FIGURE 9. 1- SENSITIVITY ODDS RATIOS CALCULATED IN POPULATION AND STUDY SAMPLE. ........................................................ 25 FIGURE 10. REPRESENTATION OF TUMOUR DETECTION BY SCREENING ACCORDING TO LENGTH OF PRECLINICAL PHASE. ............. 26 FIGURE 11. CONCEPTUAL FRAMEWORK OF STUDY. .................................................................................................................. 39 Article figure FIGURE 1. CAUSAL DIAGRAM ILLUSTRATING THE POSSIBLE PATHWAYS BY WHICH BREAST CANCER TYPES MAY INFLUENCE SCREENING

SENSITIVITY. ................................................................................................................................................................ 58

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List of Abbreviations ADJ Adjustment BMI Body Mass Index CCNB1 Cyclin B1 CEP17 Chromosome 17 centromere CI Confidence interval CK Cytokeratins CK2 Cytokeratin 2 CK5/6 Cytokeratins 5 and 6 CMSDF Centre des Maladies du Sein Deschênes-Fabia DCIS Ductal Carcinoma in Situ ER Estrogen Receptor ERBB2 V-Erb-B2 Avian Erythroblastic Leukemia Viral Oncogene Homolog FISH Fluorescent in situ hybridization FOXA1 Forkhead Box Protein 1 GATA3 GATA-Binding Protein 3 GRB7 Growth Factor Receptor-Bound Protein 7 HER1 Epidermal Growth Factor Receptor HER2 Human Epidermal Growth Factor Receptor 2 HRT Hormone Replacement Therapy IC Interval Cancer IDC Invasive Ductal Carcinoma IHC Immunohistochemistry ILC Invasive Lobular Carcinoma INSPQ Institut national de santé publique du Québec KRT5 Cytokeratin 5 KRT6 Cytokeratin 6 KRT17 Cytokeratin 17 LUM Luminal MKI67 Ki-67 MYBL2 Myb-Related Protein OR Odds Ratio PQDCS Programme québécois de dépistage du cancer du sein PR Progesterone Receptor RC Rapport de cotes RE Récepteur d’estrogène RP Récepteur de progestérone SD Screen-Detected Cancer Se Sensitivity SPF S-Phase Fraction TPN Triple-negative WHO World Health Organization XBP1 X-Box Binding Protein

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Acknowledgments I would like to thank foremost my thesis director Dr. Jacques Brisson for graciously accepting me as his student, and offering me an interesting and exciting project. Not having any prior experience in epidemiology, he gave me the opportunity to obtain real-life epidemiology experience by working alongside epidemiologists and breast cancer screening experts, and to participate in two publications. His rigorous approach to research and thinking about epidemiological problems motivated me to improve my own work, and I am certain that all the skills I have gained as his student will help me in my future endeavours. I would be remiss if I didn’t thank Dr. Caroline Diorio for introducing me to the field of molecular epidemiology and for helping me further my knowledge in molecular biology by inviting me to interact with her team. Her knowledge of these fields helped me further understand certain concepts of this present work. I will always be grateful for her encouragement, support, and words of wisdom that she gave me during my studies. Her approachable and welcoming disposition helped me become more at ease with the research environment. I would like to thank Caty Blanchette for her patience and support during my earlier ordeals with SAS and for assembling the database used during this research. In addition, I thank Sylvie Bérubé for helping me understand the CMSDF database. I also would like to extend my gratitude to the members of the PQDCS Evaluation team and other colleagues at the INSPQ notably Isabelle Théberge, Marie-Hélène Guertin, Éric Pelletier, André Langlois and Roxanne Gagnon. Thank you for helping me in various ways throughout this work either by helping me understand epidemiological concepts, working through problems, resolving SAS bugs or simply by extending your friendship. I am also grateful to Daniela Furrer-Soliz for helping me understand immunohistochemistry and some aspects of HER2. On a personal note, I thank my mother Elena, my step-father Serge, and my husband Kayne, for their patience and support throughout this endeavour.

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Foreword This project culminated in the drafting of an article entitled ‟Breast cancer intrinsic subtypes and screening

mammography sensitivity‟ which will be submitted for publication. In this study, I participated in the discussion leading to the formulation of the study objectives and conducted the literature review. I was involved in assembling the data with the support of Sylvie Bérubé who, along with Julie Lemieux, contributed valuable knowledge of the Centre des Maladies du Sein Deschênes-Fabia (CMSDF) database. I was responsible for matching the data from the CMSDF to the database of the Programme Québécois de Dépistage du Cancer du Sein (PQDCS), preparing the data for analyses, conducting the analyses, drafting and editing the article. Éric Pelletier helped me navigate the PQDCS database and also contributed his knowledge of the screening program to the article. François Sanschagrin was responsible for the pathology and laboratory information. Dr. Jacques Brisson supervised my work throughout the entire project.

During my training, I also had the chance to participate in the writing of two other articles that have now been published. I was also closely involved with the data collection of an on-going project of the effect of mammography quality on the sensitivity of mammography screening. These complementary experiences enriched my research training considerably although it does not appear in this document.

1. Fontenoy AM, Langlois A, Chang SL, Daigle JM, Pelletier É, Guertin M, Théberge I, Brisson J. Contribution and performance of mobile units in an organized mammography screening program. Can J Public Health. 2013; 104(3):193-199.

2. Théberge I, Chang SL, Vandal, N, Daigle JM, Guertin M, Pelletier É, Brisson J. Radiologist interpretive volume and breast cancer screening accuracy in a Canadian organized screening program. J Natl Cancer Inst. 2014; 106 (3): 1-9.

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Introduction Sensitivity is the property that enables screening mammography to detect breast cancer early in its preclinical phase which provides an opportunity to advance treatment and thus, reduce mortality. Sensitivity is therefore an important determinant of the disease control value of a screening program.1

Molecular studies have shown that breast cancers can be classified into four unique subtypes by virtue of their distinctive gene-expression profiles (Luminal A, Luminal B, HER2-enriched, and Basal-like)2-5. Luminal A and Luminal B subtypes have gene expression patterns that resemble the gene expression profiles of luminal epithelial breast cells, and are characterized by the expression of the estrogen receptor (ER), progesterone receptor (PR) and genes associated with ER activation.6,7 Luminal B tumours are different from Luminal A in that they also express the human epidermal growth factor receptor 2 (HER2) and HER2-associated genes.3,8-10 In contrast to the luminal subtypes, HER2-enriched tumours lack expression of ER, PR and ER-associated genes. However, like Luminal B, HER2-enriched tumours overexpress HER2 and HER2-associated genes. Lastly, the Basal-like subtype is characterized by the lack of expression of ER, PR, ER-associated genes and HER2 but expresses genes encoding for epithelial cytokeratins (CK) 5, 6, 14, and 17.3 The four breast cancer subtypes have clinical relevancy as they have been shown to have different treatment responses and survival.5,7,8,11 For instance, endocrine therapy such as Tamoxifen is used for Luminal A, while biological therapy like Transtuzumab, is used for HER2-enriched tumours, and a combination of both may be used for Luminal B.5 There are no targeted treatments for Basal-like tumours to date.

Since breast cancers represent different types of tumours with unique biological and clinical characteristics, these differences may also influence the way they appear on a mammogram. For instance, tumour appearance may affect sensitivity if a tumour type has a more conspicuous appearance at screening which would make it more detectable than another that blends in with mammary tissue. The literature suggests that breast tumour types (ER, PR, HER2 and subtype) may differ in radiologic appearance. ER-positive tumours generally tend to occur more frequently as spiculated masses than ER-negative tumours12-21 with only one study not reporting significant findings.22 PR and HER2 were not generally associated with masses. A few studies observed that PR-positive tumours12,20 were more frequent in spiculated masses but most findings were not significant.14,15,17,18,22 HER2-positivivity was not associated with masses.12,13,18,22-26 ER-negative tumours were also more frequent in microcalcifications than ER-positive tumours14,15,19,20,27 but not consistently.16-18,24,26,28 PR-negative tumours also showed frequently microcalcifications20,27 but generally findings were not statistically significant.15,17,18,24,28 Conversely, HER2-positive tumours were more likely than HER2-negative to appear as microcalcifications22,23,25,26,28-32 with few disagreeing studies.18,24 Subtype studies were not consistent.13,31,33-37 Basal-likes were more frequent in ill-defined masses than non-Basal-like subtypes33,34 and this was similarly reported for Triple-negatives when compared to HER-positive and ER-positive tumours.13 However, others reported33 that non-Basal tumours (grouped into one group) were more frequent in spiculated

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masses than Basal-like tumours, another used a non-conventional subtype classification35, and still another did not provide statistics for all comparisons.36 Two studies comparing all subtypes reported that Triple-negative tumours were more frequently masses than Luminal A but no margin descriptors were used.31,37 These studies suggested that HER2-enriched31,37 and Luminal B37 frequently appeared as microcalcifications when compared to other subtypes. An association with Luminal A and architectural distortion is reported which has not been described elsewhere.37

Screening sensitivity may also vary according to tumour aggressiveness. Aggressive cancers progress rapidly through the preclinical phase, therefore, narrowing the window of opportunity to detect them, before they become symptomatic. Conversely, non-aggressive cancers progress slowly (low grade (I)) through the preclinical phase and so, there is greater opportunity to detect them. Tumour receptor status and grade have been extensively studied in the past and generally suggest that ER-positive and PR-positive tumours are more frequently grade I than grade 3 tumours. These findings concur with more recent studies of this subject.38-40 The association of HER2 with grade has been less studied and is less consistent than ER and PR although some suggest HER2-positive tumours are more frequently high grade.38,40-42 Molecular studies revealed that the four subtypes varied in the expression of aggressive genes such as MKI67, CCNB1, and MYBL2 which are known to be associated with cellular proliferation.3,10 Studies examining the association between subtype and grade reporting both crude and adjusted results were consistent7,21,38,43-53 with few disagreeing studies and suggested that compared to Luminal A, Basal-like and HER2-enriched subtypes were strongly associated with high-grade. An association between Luminal B and higher grade was also reported in one study.45

Since breast cancer types vary in radiologic appearance at screening and tumour aggressiveness, it is possible they may also vary in screening sensitivity. To date, studies of tumour types and sensitivity compared the proportion of subtypes in interval cancers to that in screen-detected cancers. In general, ER-negative tumours are more frequent in interval cancers than in screen-detected cancers54-66 with few studies not reporting similar findings.67-69 The evidence for an association of PR status with sensitivity is less consistent than for ER but, in general; studies do not suggest a strong association of PR with sensitivity. While some studies 59,61,62,66 suggest that PR-negative tumours are more frequent in interval cancers than in screen-detected cancers, many do not report significant findings.55,56,58,60,63,64,67-69 Like studies of PR status and sensitivity, studies of HER2 do not suggest an association with sensitivity. Studies of HER2 and sensitivity are inconsistent with a few reporting an association between HER2-positivity and decreased sensitivity55,63,70 but many more not reporting any significant findings. 40,58-61,64,68

There are few studies of tumour subtypes and sensitivity.60,61,68,71 Most suggest that Triple-negative/Basal-like subtypes are found more frequently in interval cancers than in screen-detected cancers but, in these studies, all non-Triple-negative and non-Basal-like are used as comparison groups.60,61,68 Thus, apart from Triple- negative, the relation of other individual subtypes to sensitivity was not examined. Only one small study71 of 277 cases from

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Florence compared interval and screen-detected cancers distinguishing all subtypes; however, this study did not report any significant findings but its statistical power was limited.

Given the goal of screening to reduce breast cancer mortality, it is imperative to understand the factors that may influence screening mammography sensitivity. Since the evidence suggests breast cancer types vary in aggressiveness and in radiological appearance, they may also influence screening sensitivity. Therefore, the main objective of this study is to assess the relation of breast cancer types (including tumour subtypes as well as ER, PR and HER2 status) and screening sensitivity. A second objective is to determine if tumour aggressiveness can explain the variability in sensitivity across tumour type if any such variability is observed.

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Literature Review

2.1 Breast cancer intrinsic subtypes

2.1.1 Description of intrinsic breast cancer subtypes

According to the World Health Organization (WHO), twenty major histological types of breast cancers are known which highlights their rich phenotypic diversity.2 Most of all diagnosed breast cancers, approximately 70-80%, will be classified either as invasive ductal carcinoma (IDC) or invasive lobular carcinoma (ILC).5,72 Invasive breast tumours are those that penetrate all or part of the basement membrane of the epithelial site of origin.73 These tumours are mostly adenocarcinomas that are thought to be derived from mammary epithelial cells of the terminal duct lobular units (Figure 1).73 Invasive cancers represent a mixture of cancers with different biological and clinical profiles.5,72 For instance, two invasive ductal carcinomas will differ in their propensity to metastasize and in their response to treatment.73,74 These observations set the stage for more in-depth characterization of breast cancers to assess if biological differences could also be found at the molecular level.

Figure 1. Breast anatomy and histology. The basic unit in the breast (left) is the terminal duct lobular unit (middle). Cross-section of the terminal duct lobular unit is represented (right) with luminal epithelial cells lining the lumen (triangular-shaped cells in blue). Myoepithelial cells line the basal membrane (elongated pink cells).

Source: Breast development and anatomy75

Given that histological diversity could not explain all the differences in breast cancer behaviour, Perou et al.2 sought to characterize breast cancers at the molecular level. They speculated that breast cancers’ histological diversity could generate an equally rich molecular diversity2 which in turn, could help further understand breast cancer behaviour. In their landmark study2, the authors characterized the gene expression from 8102 human genes and identified 496 discriminating genes that varied little in duplicate samples of the same tumour but exhibited marked variability

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between different tumours in 65 breast cancers obtained from 42 patients. Tumours with similar gene-expression patterns were grouped using a hierarchical clustering method76 (Figure 2) . Based on this method, two distinctive groups of breast cancers emerged based on the expression of the estrogen receptor (ER) and ER-associated genes.2 This finding was compatible with breast cancer biology since estrogen is believed to play a crucial role in breast cancer aetiology.5 Its role in aetiology is consistent with the fact that estrogen binds to the nuclear ER and controls cell proliferation,5,77 moreover, hormone therapy such as Tamoxifen treatment, which targets ER, has been found to increase survival.78,79

The cluster expressing ER (ER-positive) comprised tumours that had a gene expression profile similar to the gene profile of luminal cells found in the normal breast (Figure 1)80 and was aptly named Luminal A subtype.4 Within this same ER-positive cluster, a group of tumours were also found to overexpress HER2 and was named Luminal B to distinguish it from the Luminal A group which did not overexpress this receptor. In the cluster not expressing ER (ER-negative), two groups of tumours were observed which also were differentiated by the expression of HER2. The cluster of ER-negative tumours overexpressing HER2 and HER2-associated genes such as GRB7 was named HER2-enriched.3,4 The role of HER2 in breast cancer can be inferred from the biological therapy with humanized antibody Transtuzumab that target HER2.70 The remaining group of tumours within the ER-negative cluster did not overexpress HER2. However, this group was rich in cells expressing cytokeratins (CK), which are usually expressed in normal breast myoepithelial, or basal cells that underlie the breast luminal cells (Figure 1), and was thus termed Basal-like subtype.4 All of these studies inspired a new molecular taxonomy for breast cancers, 2-4,6,74,81 and the term "intrinsic subtypes" was adopted to reflect each of the subtype’s unique biological properties.3 The four studied intrinsic subtypesab are Luminal A, Luminal B, HER2-enriched, and Basal-like.2-4,6,74,81

Luminal A

The Luminal A subtype has a gene expression pattern resembling the gene expression of the cells of the luminal epithelial layer of the breast and is characterized by the expression of ER, PR and genes associated with ER activation.5,6 In particular, Luminal A breast cancers have high expression of ER and ER-regulated genes such as GATA-binding protein 3 (GATA3), X-box –binding protein (XBP1), and Forkhead box protein A1 (FOXA1), and low expression of proliferative genes such as proliferation associated antigen Ki-67 (MKI67), cyclin B1 (CCNB1), and Myb-related protein 2 (MYBL2). 3,8-10,82 Luminal A is the most frequent tumour subtype representing about 55-65% of

a Perou et al.2 originally also reported a normal-like subtype. However, this last subtype is believed to be laboratory contamination and will not be studied in this

work.3 b Additional studies have been published since alluding to the possible existence of other subtypes. However, this work will focus on subtypes which have been

extensively studied and which have been found to have clinical relevancy.

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total breast cancers diagnosed.5 Patients diagnosed with this subtype are treated with Tamoxifen, and have a better prognosis than all other subtypes with an average 5-year survival of 75-90 %.5,7,8,11

Luminal B

Like the Luminal A subtype, this subtype is associated with the expression of ER, PR and genes involved in ER-regulation. In contrast to Luminal A, the Luminal B subtype also expresses HER2 and HER2-associated genes (ERBB2 and GRB7). In addition, it is also rich in genes associated with proliferation like MKI67, CCNB1, and MYBL2.3,82 This subtype is not very frequent compared to Luminal A, and represents about 7-12% of total diagnosed cancers. Patients diagnosed with this subtype can benefit from Tamoxifen, and possibly Transtuzumab, but the average 5-year survival can range anywhere from 45-90%.5,7,8,11

HER2-enriched

Unlike the Luminal A and B subtypes, the HER2-enriched subtype does not express of ER, PR and ER-associated genes but overexpresses HER2 and HER2-associated genes (ERBB2 and GRB7). Human growth factor receptor 2, or HER2, is a transmembrane receptor tyrosine kinase and the amplification of the gene or protein overexpression is associated with accelerated cell growth and proliferation.77 GRB7 is a gene encoding for growth factor receptor-bound protein 7, which is an adapter protein that interacts with tyrosine kinases, and signalling molecules.83 This subtype highly expresses genes involved in cellular proliferation such as MKI67, CCNB1, and MYBL2.3,82 It is the least common of all subtypes and represents about 6-10% of total breast cancers diagnosed. Although patients diagnosed with this subtype can benefit from targeted therapy such as Transtuzumab, the average 5-year survival is poorer than for Luminal subtypes, and ranges from 20-75%.5,7,8,11

Basal-like

Like the HER2-enriched subtype, Basal-like does not express ER, PR and ER-associated genes. But it also does not express HER2. It is characterized by high level expression of genes KRT5, KRT6, and KRT17 encoding for epithelial cytokeratins 5, 6, and 17.3 This subtype also highly expresses genes involved in cellular proliferation MKI67, CCNB1, and MYBL2.3,82 It represents approximately 10-15% of total breast cancers diagnosed, and also has a poorer prognosis than Luminal subtypes with an average 5-year survival of 30-80%.5,7,8,11 Unlike the other subtypes, women diagnosed with this subtype of breast cancer do not benefit from a targeted therapy.

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Figure 2. Dendrogram from hierarchical clustering of 115 tumour samples.

Columns represent tumour samples while rows are representative of specific genes (genes shown ER, HER2, CK2, HER1). Gene overexpression compared to a reference standard sample is represented in red while low expression of the gene against the standard is in green. A Molecular-signatures specific to each breast cancer subtype is shown (left to right): Luminal A (purple branches), Luminal B (blue branches), and HER2-enriched (pink branches), Basal-like (orange branches) and Normal-like (green branches). B Corresponding immunohistochemistry classification according to ER, PR, and HER2 status is shown at bottom of the dendrogram.

Source: Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study.7

2.1.2 Classification of breast cancer subtypes by immunohistochemistry

Identification of breast cancer subtypes by immunohistochemistry

The use of gene-expression based assays while very informative is both laborious and expensive, and a simpler method to recreate the molecular-derived subtypes was required for routine clinical work. Immunohistochemistry (IHC), a protein-based assay, is a relatively simple laboratory method that is widely used in pathology laboratory and proved a practical alternative to approximate the subtypes.7,84

IHC takes advantage of the capacity of antibodies to bind to very specific antigens.85 Sections of breast tumours are incubated with specific antibodies directed at ER, PR, HER2, and CK5/6 proteins.86 For tumours expressing one of these markers, the specific antibody will bind it and form a complex. A secondary antibody, linked to an enzyme will target this complex.85 A substratec is added and an enzymatic reaction occurs leaving a colour deposit at the site of the complex. Under the microscope, areas that contain bound antibody will appear darker than other areas. By this method, it is then possible to estimate the number of positive staining cells for a specific marker from a section of

c A substrate is a substance that reacts with an enzyme.82

A

B

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tumour. According to current guidelines, if more than 1% of tumour cells are stained then the tumour sample is considered ER- and PR-positive.87,88

To ascertain HER2 receptor status, IHC is also used to assess protein expression. Tumours are classified as HER2-positive if the IHC score is 3+, meaning intense membranous staining of > 30% of tumour cells. 89 Scores of 0 or 1+ are considered HER2-negative.89 Tumours classified, as 2+ are considered equivocal and need to be analyzed by fluorescent in situ hybridization (FISH). FISH is a laboratory procedure that uses fluorescent probes to detect DNA sequences on a chromosome.90,91 These detected areas light up when viewed under a fluorescent microscope and show whether or not there are many copies of the HER2 gene in cancer cells.92 HER2 is considered amplified if on average more than six copies of the HER2 gene are detected per cell, or if more than 2.2 HER2 genes are counted for every copy of chromosome 17 (or CEP 17, the reference gene).89 A result is considered equivocal if on average four to six copies of HER2 are counted per cell, or if 1.8 to 2.2 HER2 genes are counted per copy of chromosome 17.89 If there are less than four copies of HER2 per cell, or if the HER2 to CEP 17 ratio is less than 1.8, then the result is negative.89 Unlike ER, PR, and HER2, assessment of CK 5/6 by IHC to approximate the Basal-like subtype is not routinely performed and is considered insufficiently reproducible for general use.31,34,93 In standard practice, the absence of ER, PR and HER2 receptor expression is considered a proxy for Basal-like, but because it doesn’t include results for cytokeratins, it is called Triple-negative.93-95 In the literature both terms are used depending if cytokeratins were assessed but Triple-negative is the most common terminology.d

Combinations of IHC-derived markers (ER, PR, and HER2) were subsequently validated7 to determine the classification that best matched the original gene expression patterns (Table 1).ef

Table 1. Breast cancer subtypes determined by IHC assessment of ER, PR, and HER2 status. Breast cancer subtypes IHC classification

Luminal A ER + and/or PR + HER2- Luminal B ER + and/or PR + HER2+ HER2 – enriched ER- PR - HER2+ Triple – negative ER- PR - HER2-

d Triple-negative will be used in this work while the term Basal-like will be used when cited in the literature. e Some studies examine tumour in terms of ER, PR and HER2 status separately. In this work, we will use both these individual receptors and the subtypes. For

ease of interpretation, we refer to both these groups as types.

f In this work, we denote HER2-enriched when referring to the subtype and HER2-positive when referring to the individual receptor status.

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2.1.3 Section summary

Molecular studies allowed us to gain a better understanding of breast cancer biology. They allowed classifying breast cancers according to four distinct intrinsic subtypes (Luminal A, Luminal B, HER2-enriched and Triple-negative). These subtypes can be approximated by determining the status of the ER, PR, and HER2 receptors using IHC. Therefore, researchers can now study all breast cancer types meaning in terms of each individual receptor or combine them to reproduce the subtypes. Classifying breast cancers according to types has allowed clinicians to better treat patients, and has paved the way for further studies concerning breast cancer aetiology, detection and progression.8

2.2 Breast cancer types and aggressiveness Aggressiveness can be thought of, as the potential of the cancer to grow and spread. It is a broad term encompassing cellular proliferation, cellular differentiation, and tumour dissemination.96,97 The ability of a tumour to proliferate, differentiate and disseminate is dictated by its aggressiveness, which is a biological characteristic of the tumour.

2.2.1 Markers of aggressiveness

Molecular studies not only showed that breast cancers could be classified according to distinct subtypes but also revealed that they differed in the expression of aggressive genes such as MKI67, CCNB1, and MYBL2 3,82 Aggressiveness in breast cancers can be assessed by evaluating histological grade, determining KI-67 expression and quantifying the S-phase fraction. Determining the histological grade, which measures the degree of cellular differentiation,97,98 is an ideal method to infer tumour aggressiveness since it was reported to correlate well with proliferative genes identified in earlier molecular studies.2 Since proliferative genes MKI67, CCNB1, and MYBL2 encode for cell cycle proteins, the Ki-67 index, which measures the expression of the nuclear protein Ki-67, and the S-phase fraction, which measures the rate of cell turnover or proliferation97 can also be used to infer aggressiveness. Studies of these three markers suggest that the Ki-67 index correlates with the S-phase fraction and the mitotic index, an integral component of the histological grade.99

Histological grade

Differentiation is the process, or is the result of the process, where during development an organ or a body part is modified into a special form or for a specific function.100 Fully differentiated tissue is normal tissue with normal structures and function; all tumours are less differentiated in one of these characteristics.100 The degree of differentiation will be inversely related to the extent to which these characteristics have been lost.100 There is a relationship between the extent of differentiation of a tumour and its biological behaviour for instance; poorly differentiated tumours tend to be more aggressive than well-differentiated tumours.101 The difference in differentiation between the tumours relative to normal tissue can be assessed by the histological grade.5,98 Various methods to evaluate grade have been described based on assessment of cellular, architectural and nuclear structures. Its

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evaluation has been improved over the years by adding standardized criteria to reduce subjectivity and improve concordance.73 Bloom and Richardson first improved the method by adding numerical scoring but clear criteria for cut-offs was still lacking.102,103 Elston and Ellis then modified the Bloom Richardson systemg by establishing criteria, and were able to achieve greater objectivity and concordance.73,102 The method, also known as Nottingham Grading System, is considered reproducible and is recommended internationally as the reference method.98,104-106 Grade is assessed under microscopy for three morphologic features: 1) degree of tubule or gland formation, 2) degree of

nuclear pleomorphism which is the change in size and shape of nuclei98,105 and 3) mitotic count which is used to measure the degree of cellular proliferation by counting the number of mitotic bodies per 10 high power fields of view.98,107 These three features are scored individually on a scale from 1 to 3 (Table 2), and the three scores are then added to obtain a total score ranging from 3 to 9. This total score is used to assign a grade ranging from Grade 1 to Grade 3.73,106 (Table 3)

Table 2. Features and related scores to evaluate histological grade according to the Elston-Ellis* grading method.

Features Score Tubule and gland formation

Majority of tumour (>75%) 1 Moderate degree (10-75%) 2 Little or none (<10%) 3

Nuclear pleomorphism Small, regular, uniform cells 1 Moderate increase in size and variation 2 Marked variation 3

Mitotic count† ≤ 7 mitoses per 10 high power fields

1 8-14 mitoses per 10 high power fields

2 ≥ 15 mitoses per 10 high power fields 3

* Elston-Ellis method 102 † Mitotic count criteria will vary depending on the field diameter of the microscope of the pathologist;

criteria given for 0.50 mm field diameter.108

g Also known as Nottingham Grading System (NGS) or Nottingham modification of the Scarff-Bloom-Richardson grading system.

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Table 3. Summary and description of Grade 1, 2, and 3.

Grade Overall Elston-Ellis Score102

Description

1 (I) 3-5 Well differentiated 2 (II) 6-7 Moderately differentiated 3 (III) 8-9 Poorly differentiated

A grade 1 tumour is considered well-differentiated meaning that it retains features of normal breast tissue (Figure 3, Box B vs. Box A). Tumour cells grow following a slow and organized pattern.109 Grade 1 tumours are not considered aggressive. Grade 2 tumours are moderately differentiated in that they show some tissue changes relative to normal breast tissue (Figure 3, Box C vs. Box A). They are considered moderately aggressive. Grade 3 tumours are poorly differentiated in that the tissue has lost any semblance to normal breast tissue. These tumour cells grow following a rapid and disorganized cell pattern (Figure 3, Box D vs. Box A), and the tumours are considered aggressive.

Normal Breast Grade I Grade II Grade III

Figure 3. Typical histological views of tumours by grade scores relative to normal breast tissue.

Grade I (B) tumour still possesses features of normal tissue (A) and is considered well-differentiated. Grade II (C) tumour shows some tissue changes relative to normal tissue (A). Grade III tumour (D) does not resemble normal tissue, and is considered less differentiated than normal breast tissue (A).

Sources: Diagnosis of breast cancer110 (A) Breast cancer prognostic classification in the molecular era: the role of histological grade. 98 (B, C, D)

Ki-67

Ki-67 is a protein expressed in the nucleus in proliferating cells during all cell cycle phases, except at the resting state (G0).107 The function of the protein is not well known but seems to play a role in cell proliferation.111 The Ki-67 protein can be assessed by IHC but may be difficult to interpret since its expression may be heterogeneous in tumours.99 It is estimated as the percentage of tumour cells positively staining for Ki-67 protein.111 A consensus has yet to be reached on relevant reference values but IHC staining of <10% of tumour cells generally represents a tumour that is low proliferative, 10-20% represents a borderline proliferative tumour, and >20% is considered highly proliferative.112

A B C D

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Although both the Ki-67 and S-phase fraction give an indication of cellular proliferation, the assessment of Ki-67 is less cumbersome than quantifying the S-phase fraction.96

S-phase fraction

S-phase fraction (SPF) is a measure of proliferation and refers to the fraction of cells engaged in DNA synthesis107 and is determined by flow cytometry.96,97 This method allows obtaining information on the number of cells synthesizing DNA and their DNA content113 but the analysis can be hampered by pronounced intratumour heterogeneity.99 Like Ki-67, there is no current agreement on relevant reference values. Tumours with SPF results of <6% are considered low proliferative, 6-10% moderately proliferative, and >10% highly proliferative.112

2.2.2 Breast cancer types and aggressiveness

Molecular studies revealed that breast cancers were heterogeneous diseases and could be classified according to subtypes each with distinctive gene profiles. These subtypes can be reproduced with immunohistochemistry by assessing the status of ER, PR and HER2 receptor expression. Molecular studies also showed that these subtypes had different levels of expression of proliferative genes; hinting that they could also vary in aggressiveness.

ER, PR, HER2 and Histological Grade

The relationship between ER, PR and histological grade is well established and has been the subject of numerous studies dating as far back as 1975.114 In two recent studies,38,39 ER-positive tumours were found to be more frequently Grade I than Grade III. Indeed, Chen et al.38, reported that ER-positive were more frequently Grade I than Grade II and Grade III tumours (90.4% vs. 71.9% vs. 44.2%, p<0.0001, respectively). Similarly, PR-positive tumours were more frequently Grade I (78.9%) than Grade II (69.3%) and Grade III tumours (46.2%), (P<0.0001), respectively. This study had a large sample size and also assessed histological grade according to the recommended Nottingham Grading System. Sarode et al.39 reported similar results despite using a smaller sample size and using lower threshold of positivity for ER and PR (5%) compared to Chen et al. 38 who used 10% as a threshold. They similarly report that ER and PR expression levels decrease with increasing grade, P<0.0001 and P=0.0051, respectively. However, none of these studies adjusted for possible confounders. But even adjusted studies40 reported that ER and PR-positive tumours were inversely associated with high grade compared to ER and PR-negative tumours. However, although this study adjusted for tumour size, vascular invasion, lymph node status and mode of detection no point estimates were provided.

HER2-positive tumours have been generally associated with higher grade 115 but the evidence is not as consistent as ER and PR. In a recent study,38 HER2-positive tumours were more often Grade III than Grade II or Grade I tumours (29.2% vs. 25.5% vs. 4.2%, P<0.0001, respectively). Lesser quality studies also reported similar observations despite not providing quantitative information41 and classifying HER2 2+ as negative without FISH confirmation.42 Moreover, a study adjusting for tumour size, vascular invasion, lymph node status and mode of detection, reported that HER2-

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positivity was associated with higher grade when compared to HER2-negative tumours, but no point estimates were provided.40 On the other hand, Sarode et al.39 reported no statistical difference in mean HER2 amplification ratios between Grades I, II and III tumours (mean FISH ratios 3.3, 5.2, and 4.3, respectively, P-value not provided). However, the authors performed FISH on tumour samples only scoring 2+ and 3+ in IHC. Since this pool of samples will be biased to HER2-positivity, it may explain the non-significance of the results.

Subtypes and Histological Grade

Studies (reporting both crude and adjusted results) examining the association between subtype and grade were consistent. 7,21,38,43-53 Compared to Luminal A, Basal-like and HER2-enriched subtypes were strongly associated with high-grade tumours. An association between Luminal B and higher grade was also reported in one study when compared to Luminal A.45 In studies reporting adjusted results (Table 4), strong associations were reported between grade and subtype, notably for HER2-enriched and Basal-like. In a well-cited study by Carey et al.,7 HER2-enriched tumours and Basal-like were more likely high (III) than low/moderate grade (I/II) (adjusted OR= 6.2, 95% CI= 2.4-16.0 and OR=8.3, 95% CI= 4.4-15.6, respectively), compared to Luminal A but no difference was noted for Luminal B (adjusted OR 1.0, 95% CI= 0.5-1.7). A subsequent study using a larger sample size of 1018 cases, reported that compared to Luminal A, HER2-enriched and Basal-like were more likely high (III) than low/moderate (I/II) grade (adjusted OR=3.6, 95% CI=2.1-6.3 and OR=5.3, 95% CI= 3.5-8.1, respectively) and again no difference was noted for Luminal B (adjusted OR=1.4, 95% CI= 0.8-2.6).46 In a following study that included slightly more cases (1082 cases), results concurred with those of Carey et al.7 and Tamimi et al.46 except for the Luminal B subtype. Luminal B, HER2-enriched and Triple-negative were more likely poorly differentiated than well/differentiated tumours (adjusted OR= 3.1, 95% CI=2.0-4.8, OR 10.7, 95% CI=6.0-19.2, and OR=14.1, 95% CI=8.7-22.7, respectively) compared to Luminal A.45

The difference in these results may be due, at least in part, to the IHC criteria used to determine HER2 positivity since both Carey et al.7 and Tamini et al.46 used a lower threshold (2+ and 3+ are positive), than Onitilo et al. 45 (3+ positive, 2+ negative unless verified by FISH) and did not confirm amplification of the HER2 gene by FISH. Therefore cases that Onitilo et al.45 would have considered HER2-negative, Carey et al.7, and Tamini et al.46, would have considered HER2-positive, and their Luminal B category may represent a group which includes Luminal A, a less aggressive subtype.

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Table 4. Characteristics of studies reporting adjusted results for the relationship between subtypes and histological grade. *

ER, PR, HER2 and S-phase Fraction and Ki-67

The S-phase fraction (SPF) has now been largely replaced by the histological grade to infer tumour aggressiveness, and much of the literature on this topic is not very recent. In a systematic review conducted in 1998116 the authors retrieved 19 articles published in the span of 10 years (1987-1997) examining the association of SPF and hormone receptors. In general, most studies reported that hormone receptor positive (ER and PR) tumours were most likely low SPF tumours, despite using different techniques and cut points, with few studies refuting the findings. In the most recent study in 2001, 117 ER-negative tumours had higher levels of SPF (defined as the third SPF tertile) (62.7%) than ER-positive tumours (27.5%) (P<0.00001). Similarly, PR-negative tumours had higher levels of SPF (55.6%) than PR-positive tumours (26.0%) (P<0.00001). These results agree with past studies. All studies to date have only reported crude results.

Studies examining HER2 and SPF are scarce.118-120 In the most recent study published in 2001, which also included the largest number of cases (295 cases), HER2-positive tended to have a high SPF (defined as ≥6.1%) while HER2-negative tumours tended toward lower SPF (P<0.001). This result concurs with others, and although it is difficult to draw conclusions based on these few studies, results are suggestive of a more aggressive profile for HER2-positive tumours. However, like ER and PR studies, these studies also only reported crude results.

Author Year Subtypes IHC Thresholds N Adjusted OR (95% CI)†

Grade III vs. I/II

Adj. Grade method

Carey et al.7‡ 2006

Luminal A Luminal B HER2-enriched Basal-like

ER+, PR+ if >5% stained HER2+ if ≥10% stained Cytokeratin+ if any stained

255 100 33 100

1.0 (Referent) 1.0 (0.5 – 1.7) 6.2 (2.4 – 16.0) 8.3 (4.4 – 15.6)

Age, race, stage

Nottingham I-III

Tamimi et al.46§ 2008

Luminal A Luminal B HER2-enriched Basal-like

ER+, PR+ if >10% stained HER2+ if >10% stained (2+, 3+) Cytokeratin + if any stained

730 46 64 132

1.0 (Referent) 1.4 (0.8 – 2.6) 3.6 (2.1 – 6.3) 5.3 (3.5 – 8.1)

Age Nottingham I-III

Onitilo et al.45ǁ 2009

Luminal A Luminal B HER2-enriched TPN

ER+, PR+ if >20% stained HER2+ if >10% stained or 3+ FISH if 2+

781 116 85 152

1.0 (Referent) 3.1 (2.0 – 4.8) 10.7 (6.0 – 19.2) 14.1 (8.7 – 22.7)

Age Not available

* OR= odds ratio, CI=confidence interval, Adj=adjustments. † Bold results are statistically significant. ‡ Luminal A: ER+ and/or PR+ HER2-; Luminal B: ER+ and/or PR+ HER2+; HER2-enriched: ER- PR- HER2+; Basal-like: ER- PR- HER2- CK5/6+ and/or

HER1+ § Luminal A: ER+ and/or PR+ HER2-; Luminal B: ER+ and/or PR+ HER2+; HER2-enriched: ER- PR- HER2+; Basal-like: ER- PR- HER2- CK5/6+ ǁ Luminal A: ER+ and/or PR+ HER2-; Luminal B: ER+ and/or PR+ HER2+; HER2-enriched: ER- PR- HER2+; TPN: ER- PR- HER2-

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Studies have also focused on ER, PR, HER2 and Ki-67. In a recent literature review conducted in 2005111, the majority of studies (9 of 12 studies) suggested that ER and PR-positivity were associated with lower levels of Ki-67. The results for HER2-positivity and Ki-67, however, were less consistent than ER and PR. In five studies, three suggested an association between HER2-positivity and high Ki-67 expression. According to the author, discordances in results may be due mostly to differences in laboratory protocols between studies.111

Subtypes and S-phase fraction and Ki-67

Given the infrequent use of the SPF as a routine proliferative marker, there is a paucity of literature examining SPF and subtypes. However, there is some evidence to suggest that higher levels of SPF are more frequent in HER2-enriched and Triple-negative subtypes than in Luminal subtypes. In the only study retrieved, Del Casar et al.43 reported in 2008, luminal tumours (Luminal A and Luminal B tumours) had more frequently lower SPF values (<7.69%) than Basal-like and HER2-enriched tumours (P=0.03). However, there was a considerable amount of missing data for SPF that exceeded 35% and the results were limited to a crude analysis; therefore, they need to be interpreted carefully.

There were more studies of subtypes and Ki-67 but comparing results is difficult due to different definitions of subtypes used and lack of standardized Ki-67 cut-off.39,48,49,51 In the study classifying subtypes according to recommended criteria using ER, PR, and HER2 receptor status,51 Luminal A tumours were more frequent in the low (≤ 5%) and middle (5-20%) Ki-67 category while Luminal B, Triple-negative, and HER2-enriched tumours were more frequent in the high (>20%) Ki-67 category (P<0.0001).


Aggressiveness when assessed by histological grade, SPF, and Ki-67 seems to vary by receptor status and subtype. In general, ER-positive and PR-positive tumours are less aggressive than their negative counterparts while HER2-positive tumours are more aggressive than HER2-negative tumours. Luminal A seems to be the least aggressive subtype when compared to Luminal B, HER2-enriched and Basal-like/Triple-negative. Luminal B seems to be moderately aggressive; it is more aggressive than Luminal A but less aggressive than HER2-enriched and Basal-like/Triple-negative tumours. Conversely, compared to luminal tumours, HER2-enriched and Basal-like/Triple-negative are very aggressive.

2.3 Breast cancer types and radiologic features Since breast cancer subtypes have unique biological properties, these differences may influence the radiological appearance of the tumour on the screening mammogram.

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2.3.1 Definition and description of radiologic features

A standardized lexicon is used by radiologists to describe features of suspected breast lesions on a mammogram, and depending on the lesion, or radiologic feature, it will be described according to its shape, margins, and morphology. The main radiologic features observed are masses, calcifications, architectural distortion and focal asymmetric density (Figure 4).121

Masses

A mass represents a cluster of cells that has volume and occupies space.122 On a radiological image, it generally appears as a circular-like opacity on a mammogram (Figure 4, first box). Masses are typically described in terms of shape (round, oval, lobulated, or irregular) and margins (circumscribed microlobulated, obscured, indistinct, or spiculated) (Figure 5).121

Calcifications

Calcifications represent mineralization of cellular debris and degenerative tumour cells16 and are considered an important tumour feature. Microcalcifications may represent one the earliest mammographic detectable changes in breast carcinomas in asymptomatic women.16,26,34,123 Calcifications may appear as opaque tiny circular shapes and are often described in terms of morphology for instance, round, amorphous, pleomorphic, fine-branching or casting or clustered (Figure 5).121

Mass Microcalcifications Architectural Distortion Focal Asymmetric Density

Figure 4. Radiologic abnormalities of the breast. From left to right, a breast mass (A), microcalcifications (B), architectural distortion (C), and focal asymmetric density (D). Source: Breast abnormalities typically discovered by mammogram.122

D B A C

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Masses Microcalcifications

Figure 5. Drawn representation of mass shapes and margins, and examples of microcalcification morphologies.

Source: The Abnormal Mammogram in Holland-Frei Medicine 124

Architectural Distortion and Focal Asymmetric Density

Architectural distortion refers to a distortion or warping of breast tissue.122 On a mammogram, architectural distortion will have the appearance of spicules (stellate lesion) without an accompanying mass (Figure 4, box C).122 Fibroglandular tissue is relatively symmetrical in both breasts but in focal asymmetric density an area of obscure tissue occurs in only one view (Figure 4, box D).122

2.3.2 Breast cancer types and radiologic features

The notion that tumour appearance at mammography may be related to tumour biology has been of interest for some time with the earliest study published in 1983 by Broberg et al.19 Several studies have subsequently followed examining variation of radiologic features of tumours according to their ER, PR, HER2 receptor status and their subtype classification.

ER, PR, HER2 and radiologic features

Masses

In general, studies looking at ER, PR, and HER2 receptor status and radiologic features suggest that ER-positive tumours (invasive/DCIS) more frequently present as spiculated masses than do ER-negative tumours. This was a relatively consistent finding despite obtaining radiologic features from diagnostic mammograms,12-15 a mix of screening and diagnostic mammograms,16 and unspecified mammograms.17-20 A single study published in 199115 adjusted for possible confounders (age and tumor stage) and agreed with crude results, and reported that ER-positive tumours were more likely than ER-negative tumours to present as spiculated masses than other features

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(circumscribed masses, focal density, no lesion), (OR=1.30, 95% CI=1.00-1.68). One study22 disagreed and reported no significant results. However, quantitative results and information on laboratory methods were not provided to compare findings.

The relation between PR and masses was less evident than ER. A few studies reported that PR-positive tumours were more frequently than PR-negative tumours to appear as spiculated masses12,20 than circumscribed and non-visible masses;20 and compared to non-spiculated masses;12 but in others no significant findings were reported.14,15,17,18,22

There were no studies reporting an association with HER2-positivivity and masses.12,13,18,22-26

Calcifications

Studies of ER and microcalcifications generally suggest that ER-negative tumours (invasive or invasive/DCIS) appear more frequently with microcalcifications than ER-positive tumours.14,15,19,20,27 But this is not always consistent, as some studies reported that ER-positive tumours appear more frequently with microcalcifications than ER-negative26, and others found no association between ER status and microcalcifications.16-18,24,28 Discordances in results may be in part related to laboratory variability and differences in test cut-offs which tended to vary between studies.

In general, studies do not suggest an association between PR status and microcalcifications. Few reported an association with PR-negative tumours (invasive or invasive/DCIS) and microcalcifications,20,27 while others reported that PR-positive tumours appear frequently with microcalcifications.14,26 The majority of studies did not report any significant differences between receptor status and microcalcifications.15,17,18,24,28

Unlike PR, the relation between HER2 and calcifications was more consistent in the literature. Generally, compared to HER2-negative tumours, HER2-positive tumours (invasive or invasive/DCIS) tended to appear with microcalcifications22,23,25,26,28-32 and few studies did not report any significant findings between HER2 receptor status and microcalcifications.18,24 Unfortunately, the study by Ildefonso et al.18 did not provide method information, and Månsson et al.24 did not provide numerical information to compare studies.

Architectural distortion and focal asymmetric density

The relation between ER, PR, and HER2 and architectural distortion and focal asymmetric density has not been as studied as other radiologic features. There is some evidence that suggests that hormone receptor-negative tumours (ER-negative, PR-negative) appear more frequently as architectural distortions or focal asymmetric densities than hormone receptor-positive tumours.15,18,19 More studies are needed to be able to draw some definitive conclusions concerning ER, PR, HER2 and these features.

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Subtypes and radiologic features

The relation between subtypes and radiologic features has not been extensively studied and there is still a paucity of data. Nevertheless, there is some evidence to suggest a difference in radiologic appearance amongst subtypes.

In studies comparing Basal-like tumours to non-Basal tumours,33,34 Luck et al.33 reported that Basal-like tumours were more likely to appear as ill-defined masses than non-Basal tumours (61% vs. 49%, P<0.001). Wang et al.34 also similarly reported that Basal-like were more frequently indistinct masses than non-Basal tumours (36% vs. 9%, P=0.035). In Luck et al.33, non-Basal tumours appeared also more frequently as spiculated masses than Basal tumours (49% vs. 15%, P<0.001) which is in disagreement with Wang et al.34 who did not find any significant differences between the two subtypes (P=0.48). The results for architectural distortion also differed between the two studies. Wang et al.34 reported that Basal-like tumours appeared more frequently as architectural distortions than non-Basal tumours (33% vs. 12%, P=0.02), but this was not significant in Luck et al.33(P=0.302). One possible contributing factor that may explain the disagreeing findings between both studies is the type of mammograms used to obtain radiologic features. Luck et al.33 included only screening mammograms from screen-detected cancers while Wang et al.34 included only diagnostic mammograms. Screening mammograms of screen-detected cancers may over represent radiologic features that are more conspicuous while diagnostic mammograms may represent cancers that were missed at screening such as interval cancers; therefore, the tumours may have less visible features.

There were few studies that included all subtypes.31,35,36 However, Taneja et al.35 used a subtype classification based on mucin and E-cadherin that is not standard classification, and Tamaki et al.36 did not provide statistics for all comparisons. Taneja et al.35, reported that compared to Luminal subtypes (defined as ER+PR+, mucin+, nuclear BRCA+, HER2-, p53-), Basal tumours (defined as ER-PR-, HER2-, p53+) were more frequent as ill-defined masses (47% vs. 26%, P=0.001). This observation is similar to the findings obtained by Luck et al.33 and Wang et al. 34 despite using different comparison groups and subtype definitions. Taneja et al.35 also reported significantly more spiculated lesions in Luminal subtypes than in Basal and HER2a and HER2b subtypes. Ko et al.31 also reported a higher proportion of masses in Triple-negative tumours (49%) than in Luminal A (45%) and HER2-enriched tumours (11%), (P<0.0001). However, because no margin descriptors were used in the analyses it is difficult to compare to others. In a study of young premenopausal women, Yang et al.13 reported that compared to HER2-positive and ER-positive tumours, Triple-negatives were overrepresented in masses with circumscribed, obscured, and indistinct margins (P<0.0001) which is in agreement with Luck et al.33 and Wang et al.34 In addition, one study31 found that focal asymmetry was more frequent in Triple-negatives (22%) than in Luminal A (8%) and HER2-enriched tumours (6%), (P=0.0030). In this same study, calcifications were overrepresented in HER2-enriched tumours when compared to Triple-negative and Luminal A tumours, (P<0.0001).

A recently published study37 is the first to provide results adjusted for race, age, stage, tumour size and histology. The authors report that Luminal A are more likely than Triple-negatives to appear as architectural distortion (OR=4.3, 95%

21

CI=1.3-14.1) than other features, a finding not described elsewhere and contrary to Wang et al.34 Luminal B and HER2-enriched subtypes were also more likely than Luminal A to appear with, rather than without calcifications (OR=2.8, 95% CI=1.7-4.8 and OR=3.1, 95% CI=1.7-5.5, respectively) which is in agreement to crude findings in Ko et al.31 Lastly, Triple-negatives were more likely than Luminal A to appear as a mass (OR=2.5, 95% CI = 1.4-4.4) but like Ko et al. 31 no margin descriptors were used and HER2-enriched was less likely to manifest as a mass (OR =0.51, 95% CI = 0.3-0.9)


Studies examining tumour types (ER, PR, and HER2 and subtypes) in relation to radiologic features suggest that certain types present more frequently with certain radiological appearances. ER-positive tumours and to a much lesser extent Luminal A, appear more often as spiculated masses. Conversely, ER-negative tumours and Basal-like/Triple-negative subtypes are more likely to appear as masses with indistinct or ill-defined margins. Studies also suggest an association with HER2-positive tumours and microcalcifications. There are fewer studies of the HER2-enriched subtype but like HER2-positive tumours, the evidence seems to suggest an association with microcalcifications. Results for Luminal B are scarce but a recent study suggests a possible association between this subtype and microcalcifications. This is biologically plausible given the HER2-positive component of this subtype.

Architectural distortion and focal asymmetric density do not seem to be associated with tumour types and there are few studies of this subject. However, a recently published article reported a strong association between architectural distortion and Luminal A which has not been reported elsewhere.

The fact that tumour types may appear differently on mammograms may have implications for screening since features more conspicuous than others may facilitate the detection of the tumour. This means that some tumour types may not be as easily detected by screening mammography as others which may impact the ability of screening to reduce breast cancer mortality.

2.4 Screening Sensitivity

2.4.1 Definition

The end-goal of breast cancer screening is to detect and then treat the cancer early in order to reduce breast cancer mortality. For screening to reach its end-goal the test should have a high sensitivity.5 Screening mammography sensitivity is defined as the capacity of the test to detect breast cancers among asymptomatic women who are in the preclinical stage of the disease (Figure 6). Therefore, identifying factors that may interfere with sensitivity is imperative to optimize early-disease detection.125

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Non-detectable phase Preclinical detectable phase Clinical phase

Lead time

Sojourn time

T0 T1 T2 Time

Figure 6. Representation of the natural history of breast cancer: the non-detectable phase, the preclinical detectable phase and the clinical phase.

Lead-time (red arrow, dark green box) is the period of time between detection at screening (dashed black arrow) and the time where cancer would have been diagnosed in the absence of screening (bold black line). Sojourn time (green arrow) is the period that a tumour spends in the preclinical detectable phase, and may be detected by screening.

Adapted from IARC Handbooks of Cancer Prevention: Breast Cancer and Screening73

Sensitivity is the ability of the screening test to designate people in the preclinical detectable phase of the disease as positive. It is the proportion of individuals with detectable pre-clinical cancer whom the screening test labels as positive1 (see Eq. 1). Screen-detected cases are labelled "true positives" while cases with a negative result are deemed "false-negatives".1

Direct estimation of sensitivity at a population-level is not possible since it is impossible to know the number of women who are in the preclinical detectable phase of the disease126 at screening unless a perfect diagnostic test i.e. 100% sensitivity, is applied to all women participating in screening. Such a test does not exist.1 Therefore, true sensitivity can never be known but estimates, or measures of sensitivity, can be obtained.127h Measures of sensitivity are calculable with observable data with some assumptions. Observable data include interval cancers, which are cancers detected in a determined time period following a normal screening (a predetermined inter-screening interval) and represent the failure of screening.128 In theory, interval cancers may represent a false-negative result from a previous screen or a cancer that was not in the detectable preclinical period at screening but became clinical in the specified inter-screening interval. We can use data on interval cancers to estimate sensitivity by assuming that they were all in

h In this work, theoretically we will be estimating measures of sensitivity. To be coherent with the literature, we will simply refer to these as sensitivity for ease of

understanding.

Sensitivity = Number of women with preclinical breast cancer who are detected at screening (Eq. 1) Total number of women who have preclinical breast cancer

Detection at screening

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the detectable preclinical phase at the time of screening.126 This assumption carries some disadvantages as some false-negatives are not included in the calculation of sensitivity since they may not become detectable in the prescribed interval period following the initial screen; thereby, overestimating sensitivity.126 It also includes clinical cancers that were not in their preclinical detectable phase at the time of the screen; thereby, underestimating sensitivity.126 However, because of the long preclinical period of most breast cancers, this second group of breast cancers are thought to be relatively rare. In other words, measured sensitivity assumes that screen-detected and interval cancers make up the totality of women who had detectable preclinical disease at the time of screening and together form the denominator in Eq.1 (or M1 in Figure 7). This concept is best illustrated in a table such as the one below (Figure 7), which has been modified to include the results of the investigative episode i.e. positive or negative assessment. This method of estimating sensitivity is also known as the detection methodi and is the most commonly used in the literature.128

i Sensitivity can also be estimated using the proportional incidence method, which is 1- (observed interval cancers during time t /expected incidence in the

absence of screening). However, obtaining the number of interval cancers in the absence of screening is difficult and the method of detection is generally the method used in the literature.127

Screening Mammography

Results

Breast Cancer Diagnosis

Yes No

Abnormal

Positive assessment a

b N1 Negative

assessment c1

Normal ----- c2 d N0

M1

M0

T Sensitivity (Eq.2) = 𝒂/(𝒂+ 𝒄𝟏 + 𝒄𝟐)

Specificity (Eq. 4)

= 𝒅/(𝒃+ 𝒅)

(Eq. 3) = 𝒂/𝑴𝟏 (Eq .5) = 𝒅/𝑴𝟎

Figure 7. Modified 2x2 table featuring results of screening mammography, assessment, and breast cancer diagnosis.

Cell ‟a” represents screen-detected cancers meaning cases with an abnormal screening result and correctly confirmed positive on assessment (or true-positives). Cell ‟c1” represents interval cancers which are cases with an abnormal screening result deemed negative at assessment, and then become symptomatic (also false-negatives) in the interval following the index screen. Cell ‟c2” represents interval cancers cases with a normal screening result but later becoming symptomatic (also false-negatives) in the interval following the screen. Screening sensitivity by the detection method is calculated as the proportion of screen-detected cancers (a) among screen-detected and interval cancers (a+c1+c2) or a/M1. Cell ‟b” represents women with an abnormal test result at screening but negative at assessment, and who do not have cancer (also false-positives). Cell ‟d” represents women with a negative test result at screening and who do not have cancer (also true-negatives). Specificity is the proportion of women who are given a correct normal result at screening (d) among all women who do not have breast cancers (b+d) or d/M0. Adapted from Sensibilité et spécificité du dépistage du cancer du sein par mammographie : mesures directes et indirectes. 127

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Sensitivity (Se) can be estimated in absolute terms but it may also be pertinent to obtain relative sensitivities in order to compare the sensitivities between two exposure groups. Then characteristics of women, tumours, or radiologists that may influence sensitivity can be identified. For example, it may be interesting to compare the screening sensitivity of women with dense versus non-dense breasts because density has been shown to be associated with sensitivity. In population-based programs, where all cancers (screen-detected and interval cancers) can be ascertained, relative sensitivity can be calculated with advanced regression models such as log-Binomial or Poisson regression with robust variance estimation.129 In many cases, logistic regression is used to produce sensitivity odds ratio which is a more familiar method.

In the present study as in all other studies in this area, we will use a design that is similar to that of a case-control study. We will produce an adjusted ratio of the odds for interval cancers versus screen-detected cancers between the two tumour groups. Such an odds ratio can be interpreted as the ratio of the odd of lack of sensitivity (1-Se)/Se in one tumour group to the same odd in another tumour group used as referent. The odds ratio is then an estimate of the “lack of sensitivity” odds ratio.

If we juxtapose the design of this study against the design of a classical case-control study as in Figure 8 (left), interval cancers in this study are considered the ‟cases” and screen-detected cancers are considered ‟controls” (or non-cases) (right). Therefore, we can consider this study similar to a case-control study, and because of this equality, we are able to derive estimates which are related to sensitivity. In a population-based study, we can derive 1-Se odds ratios as in the equations given in Figure 9 (Left) (Eq.6, 7, and 8). If a study sample is derived from a well-defined population (Figure 9, right), and there is no selection bias, the resulting 1-Se odds ratios can be considered a population estimate (Eq. 9).

Classical case-control design Present study design

E+ E-

Case a b

Control c d

ER- ER+

IC a b

SD c d

Figure 8. Representation of case-control and study design. E+: exposed; E-: non-exposed; IC: interval cancer; SD: screen-detected cancer; ER+: estrogen-positive receptor; ER-: estrogen-negative receptor.

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Population Study Population

ER- ER+

IC A B N1

SD C D N0

M1 M0 T

ER- ER+

IC f1A f1B f1N1

SD f0C f0D f0N0

𝐎𝐝𝐝𝐬𝐄𝐑− (𝟏 − 𝐒𝐞𝟏) = 𝐀𝐂

(Eq. 6)

𝐎𝐝𝐝𝐬𝐄𝐑+ (𝟏 − 𝐒𝐞𝟐) = 𝐁𝐃

(Eq. 7)

𝐎𝐝𝐝𝐬 𝐫𝐚𝐭𝐢𝐨 (𝟏 − 𝐒𝐞) = 𝐀𝐂�

𝐁𝐃�

= 𝐀𝐃𝐁𝐃

(Eq. 8)

𝐎𝐝𝐝𝐬 𝐫𝐚𝐭𝐢𝐨 (𝟏 − 𝐒𝐞) = 𝒇𝟏𝑨

𝒇𝟏𝑩�𝒇𝟎𝑪

𝒇𝟎𝐃�= 𝐀𝐃

𝐁𝐃 (Eq. 9)

Figure 9. 1- Sensitivity odds ratios calculated in population and study sample. IC: interval cancer; SD: screen-detected cancer; ER+: estrogen-positive receptor; ER-: estrogen-negative receptor.

Sensitivity can vary with tumour aggressiveness and radiologic features (appearance of the tumour on a mammogram). Aggressiveness can be linked to sensitivity because it is related to the sojourn time which is the period during which a tumour is detectable by screening but has not yet been diagnosed clinically (Figure 6).73 The probability that a case is detected by screening mammography will depend on the location of the tumour during the detectable preclinical phase.130 Aggressive tumours will tend to progress rapidly through the detectable preclinical phase (short sojourn time). Thus, they are less likely to be detected by screening before becoming clinical. As such, we would expect more aggressive tumours to be detected in the interval following an index screening and before the subsequent one rather than at screening (Figure 10). Conversely, non-aggressive tumours progress slowly and will tend to have a longer detectable preclinical phase (longer sojourn time) increasing their likelihood of being detected at screening (Figure 10).

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Radiologic features, or the tumour appearance, at screening mammography may also affect screening sensitivity. Tumours that have more conspicuous features on the screening mammogram may be more easily detected by radiologists. Therefore, screen-detected cancers may be expected to have a more overt appearance on the mammogram at screening. Conversely, if the tumour has a conformation or shape that seems to blend in with the background mammary tissue, looks benign, or is difficult to discern, it may more easily missed at screening because the lesion may not be visible to the radiologist or may be misinterpreted as normal or benign. Therefore, interval cancers may be expected to be less conspicuous or be non-visible at screening compared to screen-detected tumours.

2.4.2 Characteristics of women

Screening sensitivity may vary according to a number of factors that have been the subject of various studies in the past such as characteristics of women undergoing screening, characteristics of radiologists interpreting the mammograms, characteristics of centers, and image quality.131 In the present work, we discuss characteristics of women as they represent potential confounding factors in the study, and should be the only ones associated with subtypes.

Breast density

Breast density is the relative proportion of fibroglandular breast tissue that appears radiodense at mammography,132 and its association with screening sensitivity is well known. Previous studies have reported that screening sensitivity

Figure 10. Representation of tumour detection by screening according to length of preclinical phase.

At a first screening (or incident screening) tumours with longer preclinical phases (less aggressive) (blue) will tend to be detected than tumours with shorter preclinical phases (aggressive) (red). Following the first screening, aggressive incident tumours may become clinical (interval cancer) before the subsequent screening (dashed red). Less aggressive tumours that develop in the interval are slow-growing and may not become clinical, and will likely be detected at the subsequent screening before ever showing symptoms (dashed blue). Adapted from Screening in Chronic Disease.1

Time

First screening Second screening

Interval between two consecutive screenings

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tends to decrease with increasing breast density.133-136 This is biologically plausible since dense tissue may obscure breast tumours and decreases the ability to detect them. 135 In one of the more recent studies examining the association between density and sensitivity published in 2010, Chiu et al.137 reported that crude sensitivity (Se) in dense breasts (Tabár IV, V) is lower than in non-dense breasts (Tabár I-III) (Se= 62.8%, 95% CI=47.2-78.3% vs. Se=82.0%, 95% CI=75.2-88.8%, respectively) which is in agreement with past studies. The same associations were reported when results were stratified by women age.

Age

The association of age and sensitivity has also been extensively studied due to its close relationship with breast density. Breast density decreases with age as breast tissue is replaced with fatty tissue.5 Since fatty tissue is radiolucent, it facilitates screen detection of tumours. Similarly to breast density, the relation between age and sensitivity, is well established. As age increases there is a corresponding increase in sensitivity.133,135,136,138,139 In a large study by Kolb et al.133 including 11,130 asymptomatic women undergoing screening, crude sensitivity for women younger than 49 years was estimated at 58.0% compared to 82.7% for women 50 years or older. In adjusted results, an increase in sensitivity with age was still apparent although the results were somewhat attenuated compared to crude results. In one of the most recent study on this topic grouping seven registries from the Breast Cancer Screening Consortium, adjusted sensitivity increased with age from 68.6% (95% CI=60.2-75.9%) in women 40 to 44 years of age, to 75.1% (95% CI= 70.3-79.4%) in women 55 to 59 years of age, and to 83.3% in women aged 80 to 89 years.139 Results of this study had been adjusted for breast density, HRT use and registry.

Hormone replacement therapy (HRT)

Hormone replacement therapy (HRT) refers to the use of estrogen (or analogues), with or without progesterone, primarily for treating menopausal symptoms.140 Literature shows that HRT may be associated with a decrease in screening sensitivity by potentially increasing breast density5 but uncertainty remains. In a systematic review141 that included six studies from 1996-2000, in the first year following screening, all studies reported a reduction in sensitivity among HRT users ranging from 6% to 25% relative to the sensitivity estimated for non HRT users. These studies varied in age at screening, definitions of screen-detected and interval cancers, screening interval and time since last screening. Newer data also suggests a decrease in sensitivity with HRT use for instance in one of the most recent studies, published in 2004,138 after adjusting for age, likelihood of previous screening, screening center, body mass index, and previous surgery, adjusted 1-year sensitivities for current, past, and never users was 83.0 (95% CI=77.4-87.6%), 84.7 (95% CI=73.9-91.6%) and 92.1 (95% CI=87.6-95.0). A subsequent study comparing HRT use among interval cancer and screen-detected cancers, while adjusting for age, family history, symptoms, previous mammogram, time since screening, density, and tumour characteristics, also reported that HRT use was more frequent in interval cancers than screen-detected cancers. In the first models that did not adjust for breast density and tumour characteristics, the first and subsequent round ORs were respectively 1.99 (95% CI=1.38-2.86) and 2.29

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(95% CI=1.37-3.81). This effect was slightly attenuated when density was added to the multivariate model but remained significant for the first round (OR = 1.54, 95% CI=1.04-2.27) and subsequent round (OR = 1.97, 95% CI=1.16-3.34). The effect was slightly increased when tumour morphology, size and grade was added to the models and remained significant for the first round (OR = 1.72, 95% CI=1.15-2.58) and subsequent round (OR = 2.03, 95% CI=1.16-3.54). The direction of these newer results are in line with past studies and suggest that current HRT use may be associated with a reduction in screening sensitivity.

Body mass index (BMI)

Overweight and obesity (defined by the body mass index (BMI)) has been identified as a putative determinant of sensitivity. BMI is thought to increase the fatty tissue of the breast, thereby, possibly facilitating cancer detection. However, there are few studies on this subject and the available literature do not all agree. In an early study by Elmore et al.142 after adjusting for various characteristics (age group, breast density, menopause status, HRT use, symptoms, family history, biopsy and surgery history, and time since last mammogram), BMI was found not to be associated with sensitivity. A subsequent study by Banks et al.140 reported a lower adjusted (included age, previous screening, screening centre, previous breast surgery, menopausal status, and HRT use) sensitivity in women with low BMI (< 25 kg/m2) (Se=85.7%, 95% CI= 81.2-89.3%) compared to high BMI women (≥25 kg/m2) (Se=91.0%, 95% CI= 87.5-93.6%). Similarly, Kerlikowske et al.143 also reported a lower adjusted (included age, race, and mammography registry) sensitivity in low BMI women (< 25 kg/m2) compared to high BMI women (≥25 kg/m2) in the first year of screening (Se= 79.9%, 95% CI= 76.3-82.7% vs. Se=86.1%, 95% CI= 83.5-88.1%, respectively), in the second year of screening (Se= 84.0%, 95% CI= 79.3-87.6% vs. Se=89.0%, 95% CI= 83.5-91.2%, respectively), and in the third year of screening (Se= 91.0%, 95% CI= 86.9-93.7% vs. Se=92.6%, 95% CI= 89.8-94.4%, respectively). Elmore et al.142 was the only study that adjusted for breast density which may explain the discrepant results. Indeed, this adjustment may have been inappropriate as breast density may be considered an intermediate variable in the pathway between BMI and sensitivity, and adjusting for this variable may have attenuated the effect of BMI on sensitivity.

2.4.3 Aggressiveness and sensitivity

Cancers that progress slowly are considered less aggressive than those progressing rapidly. Because aggressive cancers progress rapidly through the preclinical phase they may be missed by screening, and be diagnosed as an interval cancer. Non-aggressive cancers on the other hand will progress slowly which offers more opportunity for detection. Given these distinct behaviours, interval cancers may harbour biological characteristics that are typical of a more aggressive cancer than screen-detected cancers Understanding these biological differences, may provide additional information on why certain cancers are missed by screening mammography.

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S-Phase Fraction and Ki-67 and Sensitivity

The relation between SPF, Ki-67 and sensitivity has been less examined than the histological grade, and there is a paucity of data. In a narrative review that examined significant differences between interval – and screen-detected tumours59 for a period spanning 1983 to 2005, one study reported results for SPF and sensitivity.144 In this study, interval cancers were found to have higher SPF (>6.0%) than screen-detected cancers (63% vs. 38%, P=0.0006).

In terms of Ki-67, six studies55,58,63,64,67,68 have reported results for Ki-67 and sensitivity. Past studies55,64,67 have reported higher levels of Ki-67 in interval cancers than in screen-detected cancers despite differences in Ki-67 cut-off, and definition of screen and interval cancers, and this is consistent with more recent studies.58,63 For instance, Collett et al.58 report that interval cancers are more likely to have higher Ki-67 (>25%) expression than screen-detected cancers (OR=2.2, 95% CI=1.0-4.9), P<0.04). Using a different threshold of positivity, Musolino et al.63 also report that true interval cancers have higher Ki-67 (>15%) expression than screen-detected cancers (adjusted OR=2.4, 95% CI= 1.2-4.5), P<0.001). Lowery et al.68 on the other hand did not report significant findings. In their study, using a positive cut-off of 14%, no significant differences between interval and screen-detected cancers in terms of Ki-67 expression (P=0.67). However, this study did not provide adjusted results. Other additional factors that may have led to the divergent result is the small sample size (lack of power), and the fact that women self-reported the mode of detection which could have led to misclassification of detection status (biased to the null). In addition, the women from this study were obtained from a family cancer registry and the cancers may have been different than those obtained among regular screening participants since screen-detected cancers had a greater proportion of grade III cancers (33%) than interval cancers (21%).

Histological Grade and Sensitivity

Histological grade is related to the sojourn time which is the period where a tumour is detectable by screening.73 Grade III tumours, which are more aggressive and thus, have a shorter sojourn time, will tend to pass quickly through the detectable preclinical phase and become clinical before they can be detected. It expected that interval cancers will be overrepresented in this pool of cancers. On the other hand, screen-detected cancers have a longer sojourn time and are expected to be less aggressive and have a lower grade. The relation between histological grade and sensitivity has been the subject of various studies since grade is a common marker that can be easily obtained from pathology reports. Despite differences in studies, they generally suggest that interval cancers are more frequently high-grade than screen-detected cancer. 57,60-65,69,70 These results are fairly robust since findings are similar in studies reporting crude and/or adjusted results. In one instance, the study by Van der Vegt et al.59 may not have had sufficient power to detect a statistical significant difference, although the point estimate was still relevant, as they reported that true interval cancer was associated with poor grade (OR = 2.0, 95% CI=0.5-7.4). However, other studies did not report significant results.58,68 As stated earlier, Lowery et al.68 included high risk women, thus the study sample may have contained an excess of aggressive cancers, and mode of detection was self-reported which could have

30

contributed to some misclassification. In both instances, estimates would have been biased toward the null. Collett et al.58 may not have had sufficient power to detect differences given the small sample size.

A recent study in 2012,63 suggests that true interval cancers are more likely to be grade III than screen-detected cancers (adjusted OR=1.8, 95% CI=1.2-3.8, P<0.001) which is in line with studies that have been conducted in the past.

2.4.4 Radiologic features at screening and sensitivity

Studies of radiologic features and sensitivity have been examined previously in the context of interval cancer revision, and not necessarily to estimate a measure of sensitivity. Therefore, the literature on this subject is thin.

In a study by Warren et al.,145 the authors reported actual crude sensitivity estimates for each radiologic feature studied. Radiologic features were obtained from screening and diagnostic mammograms in women aged 50-64 years that participated in the Breast Screening Frequency Trial (BSFT) randomized control trial. Women in the study arm were invited to receive three annual screens after a prevalence screen while women in the control arm underwent a prevalence screen and a subsequent screen three years later, as per the regular screening program. Crude sensitivity estimated for well-defined, poorly defined and spiculated masses was 83%, 90% and 91%, respectively. Microcalcifications with suspicious features and comedo-type had sensitivities of 80% and 97%, respectively. Features such as parenchymal deformity/stellate lesion (or architectural distortion) and asymmetric density had sensitivities of 81% and 77%, respectively. Sensitivity in this study was defined as the proportion of features that led to a cancer diagnosis on first appearance for example, for 12 cases (8 screen-detected cases and 4 interval cancers) with well-defined masses, 10 cases has well-defined masses present only at the first diagnostic mammogram, and sensitivity was calculated as 10/12 = 83%. Since sensitivity is defined and calculated differently than standard definition it is difficult to understand the meaning of the estimated measure. In addition, the authors pooled all screen-detected and interval cancers from the study and control arms which could have led to misclassification of modes of detection for instance, a given cancer may have been considered screen-detected in the study arm but an interval cancer in the control arm. Therefore, the results of the study have to be interpreted cautiously.

Although Meeson et al.146 compared screen-detected cancers to false-negatives (included only missed interval cancers), they reported that asymmetric densities were more frequent in false-negatives than in screen-detected cases which is in line with the sensitivity results obtained by Warren et al.145 This particular type of radiologic feature may be difficult for radiologists to interpret.

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2.4.5 Breast cancer types and sensitivity

ER, PR, HER2 and Sensitivity

The relation between ER, PR or HER2 and sensitivity has been intensely studied, attested by the number of studies published since 1987. Many of the studies examining ER have also examined PR since both receptors are linked.7 In general, studies suggest that ER-negative tumours are more frequent in interval cancers than in screen-detected cancers.54-66 However, there are a few studies that refuted these findings.67-69

The evidence for PR and sensitivity is less consistent than for ER. Some studies 59,61,62,66 report that like ER-negative tumours, PR-negative tumours occur more frequently in interval cancers than in screen-detected cancers but there are many studies that disagree with this observation.55,56,58,60,63,64,67-69

Differences in results in both ER and PR studies may be attributed to various factors. Some studies included high-risk women68; therefore, may not be no comparable women participating in screening. Moreover, only few studies accounted for possible confounders.58,61-64,69 While the majority of studies defined interval cancers as those emerging 24-months following an index screen, others had a lengthier interval of 36 months,55,56 or a shorter interval of 12 months.67,68 Likewise, some screen-detected cancers were defined as those diagnosed within 3-months64, or 6-months69 of the index screen. Therefore, a screen-detected cancer would have been considered an interval cancer in another study. Furthermore, some studies counted only true interval cancers54-56,61,63 which would have excluded some interval cancers included in other studies. Lastly, changes in laboratory protocols may have also contributed to differences in results for instance, the positivity threshold for ER and PR changed over time (>10 % cells stained vs. current ≥ 1% cells stained) and differed across studies.

Studies examining the relation between the HER2-positive tumour type and sensitivity are also not consistent and only a few reported an association between HER-positivity and sensitivity55,63,70 while the remaining studies did not report any significant findings40,58-61,64,68 Differences in studies could be attributable to a) insufficiently powered studies since this tumour type is not very frequent (range of sample sizes across studies: n=9 to n=59), b) not accounting for possible confounders since the majority of studies reported crude results, c) using different definitions for screen-detected cancer and interval cancer, and d) laboratory variability. According to Anttinen et al.70 this last factor is a major source of variability between studies concerning HER2. Although, there are now guidelines published to reduce testing variability,89 past studies used different HER2 positivity cut-offs and had not yet developed the methods to confirm equivocal case status like FISH.

Two recent publications demonstrate the variability of results. Musolino et al.63 reported that HER2-positive tumours were more likely true interval cancers than screen-detected cancers (OR=3.4, 95% CI=1.7-7.1), after adjusting for tumour size and age. Rayson et al.61 on the other hand did not report significant results. This was a nested case-control study that included women aged 40-69 years, and matched screen-detected cases 2:1 to true interval cases

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for 5-year age range at diagnosis, screening interval, and time period (before or after October 2001 which was the date HER2 testing was introduced in Nova Scotia). The sample size for HER2-positive cases in each of the age and interval strata was limited, indeed, when results were stratified by age and screening interval, the number of HER2-positive cases were very small (40-49 years n=15; 50-69 years, 1-year interval, n=6, and 50-69 years, 2-year interval, n=28) with respective univariate ORs: 0.85 (95% CI=0.25-2.93), 1.98 (95% CI=0.31-12.7), and 1.14 (95% CI=0.60-2.15). The overall univariate OR was 1.14 (95% CI =0.60-2.15) while the multivariate odds ratio accounting for matching variables was not presented. By comparison, Musolino et al.63 had more HER2-positive cases i.e. 59 cases (study was based on women aged 50-69 years).

Subtypes and Sensitivity The relation between subtypes and sensitivity has been gaining some interest with a few studies published since 2010 60,61,68,71 (Table 5). Because breast cancer subtypes have clinical relevancy with respect to sensitivity of screening mammography, it is important to understand if sensitivity varies according to subtype.

In the first study published by Domingo et al.60 the authors reported that Triple-negatives were more frequent in true interval cancers than in screen-detected cancers (28.1% vs. 7.5%, P=0.028). Similarly, in the multivariate analysis, compared to other subtypes (category comprises Luminal A, Luminal B, and HER2-enriched), Triple-negatives were more likely to be true interval cancers and interval cancers than screen-detected cancers (adjusted OR=4.70, 95% CI=1.42-15.60 and OR=8.85, 95% CI=2.03-38.62, respectively). However, the classification for Luminal A and B is not clear in this study, the authors classified Luminal A as ER and PR positive while Luminal B were ER positive only; therefore, the Luminal subtypes may not be directly comparable to others. But in agreement with the overall adjusted results of the study, Rayson et al.61 reported that compared to non-Triple-negatives, Triple-negatives were more likely to be true interval cancers than screen-detected cancers (adjusted OR=2.01, 95% CI=1.04-3.90) although results were not adjusted for confounders. Likewise, Lowery et al.68 also reported that compared to non-Triple-negatives, Triple-negatives were more frequent in interval cancers than in screen-detected cancers although the finding was not significant (P=0.26). However, this last study had a relatively small sample size (15 Triple-negative cases), did not adjust for confounders, and used data from high-risk women (60% of participants) who were registered in a familial cancer genetics registry which may not be comparable to regular screening participants. Indeed, when data was stratified by family history, Triple-negatives were found to be significantly overrepresented in interval cancers than in screen-detected cancers (P=0.02). In addition, women self-reported their mode of detection which may have contributed to some misclassification of interval and screen-detected cancers. All three studies focused solely on Triple-negatives and do not provide results for other subtypes individually. Grouping Luminal A, B and HER2-enriched together may not be appropriate as they may be each differently be associated with sensitivity i.e. HER2-enriched is

33

considered an aggressive subtype which could be associated with interval cancers while Luminal A represents a non-aggressive cancer that is expected to make up the majority of the screen-detected pool.

A recent population-based study71 comparing sensitivity for all subtypes individually did not report any significant differences, after adjusting for potential confounders. Compared to Luminal A, Luminal B-HER2 negative (adjusted OR=1.45, 95% CI=0.68-3.07), Luminal B-HER2 positive (adjusted OR =1.30, 95% CI = 0.48-3.54), Triple-negative (adjusted OR= 3.16, 95% CI =0.81-12.26), and HER2-enriched (adjusted OR = 1.09, 95% CI = 0.26-4.55) were not associated with interval cancers. However, this may have been due to the small sample sizes for some subtypes (134 Luminal A, 79 Luminal B-HER2 negative, 34 Luminal B-HER2 positive, 14 Triple-negative, and 16 HER2-enriched cases) which can also be inferred from the wide confidence intervals of some results. Still though, the association for Triple-negative and sensitivity may still be biologically relevant even if not statistically significant given the result (OR=3.16). The authors in this study also use Ki-67 expression to classify Luminal A and Luminal B which limits comparisons to other studies.


Screening mammography sensitivity is the ability of the test to detect all preclinical breast cancer cases present at the time of screening. Identifying factors that may influence screening sensitivity is critical as they may affect the test’s ability to early-detect breast cancers, and thus, undermine the goal to reduce breast cancer mortality. The characteristics of women such as age, breast density, HRT use, and BMI represent one level of factors that influence sensitivity. These studies have been studied extensively in the past and in general, increasing age, decreasing breast density, higher BMI, and no HRT use seem to be associated with better sensitivity. These factors will be considered in the present study as they represent potential confounders.

Literature also suggests that aggressiveness is another factor associated with sensitivity. According to the studies, interval cancers have more aggressive features than screen-detected cancers. They tend to have greater Ki-67 expression and be less differentiated than screen-detected cancers. They also seem to have a greater SPF although there is not sufficient data to confirm this observation.

Sensitivity may also vary according to a tumour’s radiological feature although this has not been extensively studied. There is some evidence, although thin, that some tumour features are better detected than others. For example, poorly defined, spiculated masses and comedo-type microcalcifications have better sensitivities compared to asymmetric density. However, this observation needs to be confirmed with additional studies.

Studies suggest that sensitivity may vary according to tumour receptor status (ER, PR, and HER2). However, the evidence is more consistent for ER which suggests ER-negative tumours are more frequent in interval than screen-

34

detected cancers. The evidence is not as consistent for PR and HER2. Further studies that take into account some of the shortcomings of published literature may aid in clarifying these relationships.

Subtypes may also affect sensitivity but the literature is still scarce on this subject, and published works have focused essentially on TPN. The available data suggest that sensitivity may be poorer for Triple-negatives compared to all other subtypes. In the only study to date assessing sensitivity in all subtypes, no significant findings were reported although this may have been limited by lack of power. Therefore, additional studies are necessary to be able to draw more definitive conclusions on this subject.

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Table 5. Comparison of studies examining breast cancer subtypes and sensitivity

Author Year, Country

Program Study period Age

Subtypes IC True IC

SD Statistical analysis Outcome

Results Adj. Comments

Domingo et al, 60 2010 Spain

Barcelona 1995-2008 50-69 y

Non-TPN† TPN

99 19

25 9

107 8

Logistic regression OR (95% CI) IC vs. SD OR (95% CI) True IC vs. SD

Non-TPN TPN Non-TPN TPN

1.0 (Referent) 4.70 (1.42 – 15.60) 1.0 (Referent) 8.85 (2.03 – 38.62)

Age at screening, TNM, screening round

IC: 24 months following normal screen

Lowery et al. 68 2011 US

Cancer Genetics Network Population-based 1999-2000 <50, ≥50 y

TPN ‡ Non-TPN

9 34

6 44

Fisher’s Test IC vs. SD Stratified by age Stratified by family history

TPN

21% IC vs. 12% SD, P=0.26

<50 y 18% IC vs. 6% SD, P=0.60

≥50 y 24% IC vs. 15% SD, P=0.50

History positive 32% IC vs. 0 SD, P=0.02

History negative 13% IC vs. 18% SD,P=0.73

Age, family history


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Table 5. Comparison of studies examining breast cancer subtypes and sensitivity (continued)

Author Year, Country

Program Study period Age

Subtypes IC True IC

SD Statistical analysis Outcome

Results Adj. Comments

Rayson et al.61 2011 Canada

Nova Scotia Breast Screening Program Population-based 1991-2004 40-69 y

Non-TPN§ TPN

92 23

167 21

Logistic regression OR (95% CI) True IC vs. SD

Non-TPN TPN

1.0 (Referent) 2.01 (1.04 – 3.90)

None Multivariate OR not shown; IC: 24 months following normal screen

Caldarella et al. 71 2012, Italy

Florence Population-based 2004-2005 50-69 y

Lum A ǁ Lum B-HER2- Lum B-HER2+ HER2-enriched TPN

25 22 9 4 6

109 57 25 12 8

Logistic regression OR (95% CI) IC vs. SD

Lum A Lum B-HER2- Lum B-HER2+ HER2-enriched TPN

1.0 (Referent) 1.45 (0.68 – 3.07) 1.30 (0.48 – 3.54) 1.09 (0.26 – 4.55) 3.16 (0.81 – 12.26)

Age at diagnosis, density, histotype, pT, pN


IC: interval cancers; SD: screen-detected cancers; y: years; Adj: adjustment; Lum: Luminal; TPN: triple-negative; NA: not available; IHC: immunohistochemistry; OR: odds ratio; CI: confidence interval; ER+: estrogen receptor positive. ER-: estrogen receptor negative; PR+: progesterone receptor positive; PR-: progesterone negative; HER2+: HER-positive; HER2-: HER2-negative. † Non-TPN includes Luminal A (ER+ and PR+); Luminal B (ER+ only); HER2-enriched (ER-PR-HER2+). TPN (ER-PR-HER2-). ‡ No details provided for non-TPN group; TPN (ER-PR-HER2-). § No details provided for non-TPN group; TPN (ER-PR-HER2-). ǁ Luminal A: ER+PR+HER2-, Ki-67<14%; Luminal B-HER2- : ER+PR+HER2-, Ki-67≥14%; Luminal B-HER2+: ER+PR+HER2+; HER2-enriched: ER-PR-HER2+; TPN: ER-PR-HER2-.

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Objectives and Conceptual Framework

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3.1 Objectives This study proposes to examine if breast cancer types (receptor status and subtypes) influence screening mammography sensitivity. We also hypothesize that the effect of breast cancer types on screening may be mediated by tumour aggressiveness. Therefore, we aim to examine these relationships by first assessing the total effect of tumour type on screening sensitivity. Secondly, we will assess the direct effect of types on screening sensitivity by adjusting for histological grade, as a surrogate for tumour aggressiveness. The study’s conceptual framework is presented in Figure 11 which illustrates the main study variables in relation to the proposed objectives. In addition, other potential intermediate pathways are represented but will not be subject to analysis in the present study.

Briefly, this project proposes to answer the following research questions:

1. Does screening sensitivity vary among different breast cancer types as determined by ER, PR, and HER2 receptor status as well as tumour subtype (Luminal A, Luminal B, HER2-enriched, and Triple-negative)?

2. Can observed differences in sensitivity be explained by tumour aggressiveness as gauged by the histological grade?

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3.2 Conceptual Framework

Figure 11. Conceptual framework of study. Primary objective is to determine if breast cancer types influence screening sensitivity. The assessment of this pathway is the total effect of cancer types on sensitivity which includes the pathways A, B, and C, or Total Effect = A+B+C. Secondary objective is to determine if the A pathway mediated by the histological grade is important in explaining the variability observed in sensitivity. In other words, we assess if grade is an intermediary factor in the type and sensitivity association. One method to do this is to adjust for the histological grade which blocks the A pathway. Therefore, other pathways potentially explaining the effect of types on sensitivity are remaining pathways B+C.

Breast cancer types

Sensitivity

Radiologic features

Grade

C

A

B

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Breast Cancer Subtypes and Screening Mammography Sensitivity

Sue-Ling Chang (1,2,3), Jacques Brisson (1,2,3)

1. Direction de l’analyse et de l’évaluation des systèmes de soins et services, Institut national de santé publique du Québec (INSPQ), Québec, Québec

2. Centre de recherche du Centre hospitalier universitaire de Québec,

3. Département de médecine sociale et préventive, Université Laval, Québec, Québec

Corresponding author : Dr. Jacques Brisson

Hôpital St-Sacrement

CHU de Québec, 1050

Chemin Sainte-Foy, Québec, QC G1S 4L8

Tel : 418-682-7392

Fax : 418-682-7949

E-mail : [email protected]

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4.1 Résumé Objectifs : L’objectif principal de cette étude est de déterminer si la sensibilité de la mammographie de dépistage varie selon le statut de récepteur de la tumeur ER, PR, HER2 et les sous-types de cancer du sein (Luminal A, Luminal B, HER2-enrichi, Triple-négatif (TPN)) en comparant des cancers d’intervalles avec des cancers détectés par dépistage. Aussi, cette étude vise à déterminer si la variabilité de la sensibilité pourrait être due à l’agressivité de la tumeur Méthodes : Cette étude a été conduite parmi toutes les 1536 femmes âgées entre 50-71 ans diagnostiquées avec un cancer du sein infiltrant entre janvier 2003 et décembre 2007 au Centre des Maladies du Sein Deschênes-Fabia (CMSDF) au Québec. Le statut de dépistage a été établi en jumelant la base de données du CMSDF avec la base de données du Programme québécois de dépistage du cancer du sein (PQDCS). Les caractéristiques des tumeurs et des femmes ont été extraites de la base de données du CMSDF. La régression logistique a été utilisée pour estimer les rapports de cotes en ajustant pour les caractéristiques des femmes. Résultats : Durant les années 2003-2007, 596 cancers détectés par dépistage, 262 cancers d’intervalle, et 678 cancers cliniques (hors dépistage) ont été diagnostiqués au CMSDF. Les types de cancer du sein étaient fortement associés au grade histologique. Les tumeurs RE-négatif, RP-négatif, et HER2-positif étaient plus fréquemment de grade III que de grade I/II (RC = 25,0, IC 95% = 15,0 – 41,8, RC = 8,3, IC 95% = 5,5 –12,5, et RC = 4,3, IC 95% = 2,5 – 7,2, respectivement). Également, comparé au sous-type Luminal A, le sous-type Luminal B (RC = 6,8, IC 95% = 3,4 –13,3), HER2-enrichi (RC = 18,3, IC 95% = 7,5 – 44,7) et TPN (RC = 49,7, IC 95% = 24,9 – 99,3) étaient plus fréquemment grade III que grade I/II. Les types de tumeur étaient associés à la sensibilité de dépistage. Les tumeurs RE-négatif, RP-négatif, et HER2-positif étaient plus fréquentes chez les cancers d’intervalle que chez les cancers détectés par dépistage (RC = 2,7, IC 95% = 1,8 – 4,0, RC = 1,8, IC 95% = 1,3 – 2,5, et RC = 2,4, IC 95% = 1,4 – 3,9, respectivement). Comparé au sous-type Luminal A, le sous-type Luminal B, HER2-enrichi et TPN étaient tous plus fréquents chez les cancers d’intervalle que chez les cancers détectés par dépistage (RC = 2,0, IC 95% = 1,1 – 3,9, RC = 4,6, 95% IC = 2,1 – 10,1, et RC = 2,8, IC 95% = 1,7 – 4,7, respectivement). Tous les RC se sont atténués lorsque le grade histologique a été ajouté aux modèles, à l’exception des tumeurs de type HER2-positif et HER2-enrichi. Les types de cancers du sein sont aussi fréquents parmi les cancers diagnostiqués chez les femmes qui participent au dépistage que chez les femmes dont le cancer a été diagnostiqué hors dépistage. Conclusion : La sensibilité de la mammographie de dépistage varie selon le type de cancer du sein. Alors que la mammographie serait meilleure pour détecter les cancers ER-positif, PR-positif, et les Luminal A, elle est moins efficace pour détecter les cancers ER-négatif, PR-négatif, et les sous-types HER2-enrichis et les TPN. L’influence du type de tumeur sur la sensibilité de dépistage s’expliquerait en grande partie par

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l’agressivité de la tumeur. Conséquemment, pour maximiser la réduction de la mortalité par dépistage, des stratégies qui visent à améliorer la détection des cancers plus agressifs devraient être envisagées.

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4.2 Abstract Background: The aims of this study were to determine if screening mammography sensitivity varies according to breast cancer receptor status ER, PR, and HER2 and subtype (Luminal A, Luminal B, HER2-enriched, Triple-negative (TPN)) by comparing interval with screen-detected cancers, and to assess if the variability in sensitivity can be explained by tumour aggressiveness. Methods: The study was carried out among 1536 women aged 50-71 years newly diagnosed with an invasive breast cancer January 2003 to December 2007 at the Deschênes-Fabia Breast Centre (CMSDF) in Quebec City, Canada. Screening status was ascertained by linking the CMSDF registry data to the Quebec Breast Screening Program (PQDCS) database, and tumour and women characteristics were obtained from the CMSDS registry. Screening sensitivity was assessed by comparing tumour type and subtype of interval cancers to that of screen-detected cancers. Logistic regression was used to adjust for women characteristics. The effect of tumour aggressiveness was assessed by adjusting for histological grade in the models. Results: During 2003-2007, 596 screen-detected, 262 interval cancers, and 678 clinical cancers were diagnosed at the CMSDF. Tumour type was strongly associated with grade. ER-negative, PR-negative and HER2-positive tumours were all more likely to be grade III than grades I/II (OR = 25.0, 95% CI = 15.0 to 41.8, OR = 8.3, 95% CI = 5.5 to 12.5, and OR = 4.3, 95% CI = 2.5 to 7.2, respectively). Similarly, compared to Luminal A, Luminal B (OR = 6.8, 95% CI = 3.4 to 13.3), HER2-enriched (OR = 18.3, 95% CI = 7.5 to 44.7) and TPN (OR = 49.7, 95% CI = 24.9 to 99.3) were more likely grade III than grade I/II. Tumour type was also associated with screening sensitivity. ER-, PR-negative, and HER2-positive were more frequently interval cancers than screen-detected cancers (OR = 2.7, 95% CI = 1.8 to 4.0, OR = 1.8, 95% CI = 1.3 to 2.5, and OR = 2.4, 95% CI = 1.4 to 3.9, respectively). Luminal B, HER2-enriched and TPN subtypes were all more frequent in interval than screen-detected cancers (OR = 2.0, 95% CI = 1.1 to 3.9, OR = 4.6, 95% CI = 2.1 to 10.1, and OR = 2.8, 95% CI = 1.7 to 4.7, respectively) compared to Luminal A. ORs attenuated when models were adjusted for histological grade, except for HER2-positive and HER2-enriched tumours. Tumour types were not associated with participation in screening. Conclusion: Screening sensitivity varies by tumour receptor status and subtype. While screening mammography is better at detecting ER-positive, PR-positive and Luminal A subtype tumours, it is less effective in detecting ER-negative, PR-negative tumours, and more aggressive subtypes such as HER2-enriched and TPN. The influence of tumour types on screening sensitivity can be explained mostly by tumour aggressiveness. In order to make further gains in mortality reduction, strategies aiming at optimizing the detection of aggressive tumour types should be prioritized.

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4.3 Introduction The main objective of mammography screening is to avert breast cancer deaths.1,2 To reach this goal, mammography needs to have a high sensitivity.1 Because of imperfect sensitivity, some cancers present at screening will remain undetected and will not benefit from screening. Some of these undetected cancers will be diagnosed in the interval between screens. Interval cancers may be due in part to tumor-level factors such as tumor aggressiveness and type of mammographic change induced by a tumour. For instance, because of tumour aggressiveness, some tumours initially undetected at screening develop rapidly and are diagnosed in the inter-screening interval3,4 while other less aggressive tumours may remain undiagnosed until the next screen when they have another possibility to be detected by mammography. Moreover, some radiologic features of tumours on the screening mammogram such as spiculated masses and linear calcifications are more easily identified than others displaying more subtle signs of malignancy such as distortions, focal asymmetric densities, amorphous calcifications and well circumscribed masses.5 Thus, radiologic features of some tumours may not be conspicuous enough to prompt suspicion from the radiologist and these tumours may then be missed at screening only to be diagnosed in the inter-screening interval or later. Up to now studies interested in screening sensitivity have compared receptor status (ER (estrogen receptor) ±, PR (progesterone receptor) ±, and HER2 (human epidermal growth factor receptor 2) ±) of screen-detected cancers to that of interval cancers. If a given type of tumour is overrepresented in screen-detected cancers compared to intervals cancers, then this suggests that screening sensitivity may be greater for this tumour type. Conversely, if a type is more frequent among interval cancers, this would suggest that sensitivity is lower for this type. Numerous studies have been published on tumour receptors, and there is wide consensus that ER-negative tumours are more frequent in interval than in screen-detected cancers3,6-17 with only a few studies not reporting similar findings.4,18-20 Thus, sensitivity appears lower for ER-negative than ER-positive tumours. Studies of PR and HER2 are less consistent than those of ER with fewer studies reporting an association for PR-negative6-9 and HER2-positive11,14,21 tumours and sensitivity. Other studies do not report significant results for PR-negative3,4,10-14,18,20 and HER2-positive3,8-10,13,17,20 tumours and sensitivity. Since molecular studies have confirmed that breast cancer can be classified according to distinct subtypes, estrogen, progesterone and HER2 receptors can be used as surrogates to approximate molecular subtypes 22-

24, there is also interest in comparing subtypes in interval and screen-detected cancers. There are few studies published in this area 8,13,20,25 and most report that Triple-Negative (TPN) tumours are more frequent in interval than in screen-detected cancers.8,13,20 Since all these studies focused on TPN and did not provide separate estimates for the remaining subtypes, it is not known if some other subtypes are similarly more frequent in

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interval cancers. A recent study by Caldarella et al.25 is the first to provide information for all subtypes separately, and reported a lack of association to sensitivity for all subtypes. The present study aims to help clarify whether screening mammography sensitivity varies according to breast cancer subtype by comparing interval with screen-detected cancers while adjusting for known potential confounding factors. Secondly, we assess if observed differences in sensitivity can be explained by differences in tumour aggressiveness as measured by histological grade. Lastly, in order to assess whether differences in screening sensitivity may affect subtype distribution of breast cancers in a population where screening is offered, subtype distributions of cancers diagnosed among screened (screen-detected and interval cancer) and non-screened (clinical) women are compared. .

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4.4 Materials and Methods Study population

The study was carried out among women aged 50-71 years newly diagnosed with an invasive breast cancer between January 2003 to December 2007 at the Deschênes-Fabia Breast Centre (Centre des Maladies du Sein Deschênes-Fabia, CMSDF) in Quebec City, Canada. This center which is the only breast center in Quebec City maintains a comprehensive registry with detailed information on all CMSDF breast cancer patients including breast cancer risk factors, characteristics of disease at diagnosis, and treatment information.26 A total of 1536 eligible invasive breast cancer cases were identified from the CMSDF registry during the study period.

The PQDCS is an organized population-based breast cancer-screening program that provides biannual screening mammography to all women aged 50-69 years. Eligible women are identified by the Quebec public health insurance program (RAMQ) and invited to participate in screening via a personalized letter. Women participating in the program receive two-view (cradio-caudal and medio-lateral) bilateral mammography, which is offered in designated private or public screening centers. Following an abnormal screening result, women have an assessment at accredited reference centers such as the CMSDF, or one of their choosing. The CMSDF is also the only designated center in Quebec City to evaluate women who have an abnormal screen in the context of the Quebec breast cancer-screening program (PQDCS). Therefore, almost all women from Quebec City and surroundings pursue their assessments for abnormal screening mammograms at the CMSDF.

Following Ethics Committee procedures, authorization by the Director of Professional Services (DPS) of the hospital was obtained for use of CMSDF data. PQDCS participants provide written consent at screening for use of their data for evaluation purposes.

Classification of cancers by mode of detection

Screening status of the 1536 CMSDF patients was ascertained by linking the CMSDF registry data to the PQDCS screening database. Breast cancers in women diagnosed at the CMSDF who could be matched to the PQDCS screening database were classified as screen detected if the diagnosis occurred within 6 months following an abnormal screening mammogram. Cancers diagnosed in the 6-24 months following an abnormal screen and those diagnosed within 24 months following a normal screen were considered interval cancers. Screen-detected cases and interval cancer cases are classified as “screened” cases.

The CMSDF patients who could not be linked to the PQDCS screening database were considered “clinical” cancers. For the purposes of the study, cancers diagnosed in screened women with a personal history of

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breast cancer, breast reduction or augmentation mammoplasty, or were symptomatic at screening also were classified as clinical (140 cases) cancers since these women may have different medical follow-ups than women participating in screening.

Data collection

Demographic data

Characteristics of women were extracted from the CMSDF registry and included age at diagnosis (years), age at first birth (years), family history (first degree) (none/yes), hormone replacement therapy (HRT) use (none (never)/yes (ever)), and body mass index (BMI; kg/m2). Breast density data (%) was obtained from the PQDCS database for women who had participated in screening. Missing values were replaced with an indicator variable.

Pathology data and tumour classification

Tumour characteristics for each case was abstracted from the CMSDF data base and included tumour size (mm), number of positive lymph nodes tumour stage (I, II, III, IV), vascular invasion (no/yes), histological grade (I, II, III), and ER (positive/negative), PR (positive/negative) and HER2 (negative/positive) status. Histological grade was defined according to the Nottingham scoring system (also modified Bloom-Richardson grading system as proposed by Elston-Ellis) expressing three degrees of differentiation (Grade I: well-differentiated; Grade II: moderately differentiated and Grade III: poorly differentiated).26,27 ER, PR, and HER2 receptor expression status was ascertained by immunohistochemistry (IHC). ER and PR were considered positive if ≥1% of cells were stained. HER2 was considered overexpressed if more than 30% of tumour cells were intensely stained, or were given an IHC score 3+. IHC scores of 0 and 1+ were considered HER2-negative. An IHC score of 2+ were considered equivocal, and HER2 gene amplification was carried-out by fluorescent in situ hybridization (FISH). HER2 was considered amplified when the gene amplification ratio was greater than 2.2, not amplified if less than 1.8, and equivocal if 1.8-2.2.27

Tumours types were classified according to receptor status: ER-positive and ER-negative, PR-positive and PR-negative, and HER2-positive and HER2-negative, and also classified according to “subtypes” by combining ER, PR, and HER2 receptors obtained in IHC as surrogates for gene expression profiles22 and recommended by the IMPAKT 2012 Working group28: Luminal A: ER and/or PR positive, HER2-negative; Luminal B: ER and /or PR positive, HER2-positive; TPN: ER, PR, and HER2-negative; HER2-enriched: ER and PR-negative, and HER2-positive; and Unclassified: ER, PR results combined with equivocal HER2 results. Missing values were replaced with an indicator variable.

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Statistical analysis

For our main analyses, tumour type of interval cancers was compared to that of screen-detected cancers. Unconditional multivariate logistic regression was used to compute odds ratios (ORs) with 95% confidence intervals. The computed odds ratio can be viewed as a measure of the lack of sensitivity. If Se refers to sensitivity then lack of sensitivity is 1-Se and (1-Se)/Se is its odds (O). The odds ratio estimated by the model is the ratio of this odds for a given tumour subtype to the odds for the reference type. An odds ratio greater than 1.0 for a tumour type means that sensitivity for this tumour type is poorer than it is for the reference tumour type. Variables included in multivariate models include age at diagnosis in years (50 – 54, 55 – 59, 60 – 64, 65 –71), age at first birth in years (nulliparous, <20, ≥20 –24, ≥25 –29, ≥30 –34, ≥35), family history (none, yes), hormone therapy use (none, yes), breast density in percentage (<25%, 25 – 49%, 50 – 75%, >75%), and BMI in kg/m2 (<20.0, 20.0 – 24.9, 25.0 – 29.9, 30.0 – 34.9, ≥35.0). These potential confounding variables were determined a priori by review of literature. We arranged study variables in a causal graph (Figure 1) using a priori knowledge of possible relationships between subtypes, histological grade, and sensitivity. Histological grade could be viewed as an intermediate variable through which tumour receptors/subtype could affect sensitivity and thus, was not considered a confounding variable. To determine whether histological grade explains the relation of tumour type to sensitivity, grade (I, II, and III) was added to the adjusted logistic models above. To assess the association of tumour types (receptors and subtype) with histological grade, we used unconditional logistic regression. In this analysis, grade III cancers were compared to grade I/II (combined) cancers for each tumour receptor status/subtype. An odds ratio greater than 1.0 means that differentiation is poorer for this receptor status/subtype compared to the reference type. We adjusted the ORs for the same covariates as in the main analyses. Finally, we used unconditional logistic regression to compute ORs and 95% CIs to compare tumour types of clinical cancers to that of cancers diagnosed among screened women (screened-detected and interval cancers). In this instance, an odds ratio greater than 1.0 means that this tumour type is more frequent in clinical cancers than in cancers occurring in screened women. We adjusted the ORs for the same covariates as in the main analyses except for breast density which was not available for clinical cancers. All analyses were conducted with SAS version 9.2 (SAS, Cary, USA). All statistical tests were two-sided, and P-values <0.05 were considered statistically significant.

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4.5 Results Characteristics of screen-detected, interval and clinical cancers Of the total 1536 breast cancers studied, 596 were screen-detected, 262 were interval cancers, and 678 were clinical cancers diagnosed outside the screening program. Distributions of women and tumour characteristics by cancer detection status are presented in Table 1. There was a greater proportion of women with HRT use history in women with screened cancers than in clinical cancers (65.2% vs. 51.5%). As expected, women with very dense breasts were more frequent in interval- than in screen-detected cancers. Clinical cancers had larger tumours, and a greater proportion of women with more advanced disease (high number of positive nodes, and late stage) than cancers diagnosed among women screened.

Association between histological grade and breast cancer types among screened women

ER, PR, HER2 receptor status is strongly associated with histological grade (Table 2). ER-negative, PR-negative and HER2-positive tumours were more likely grade III (OR = 25.0, 95% CI = 15.0 to 41.8, OR = 8.3, 95% CI = 5.5 to 12.5, and OR = 4.3, 95% CI = 2.5 to 7.2, respectively) than grades I/II combined. There is a strong association with subtype and grade. Compared to Luminal A, Luminal B (OR = 6.8, 95% CI = 3.4 to 13.3), HER2-enriched (OR = 18.3, 95% CI = 7.5 to 44.7) and TPN (OR = 49.7, 95% CI = 24.9 to 99.3) were more likely grade III than grade I/II cancers. The associations were not affected much by confounding as crude results changed negligibly with adjustment.

Association between breast cancers types and sensitivity

ER, PR, and HER2 receptor status and breast cancer subtype were associated with screening sensitivity (Table 3). ER- and PR-negative, and HER2-positive were more frequent among interval than screen-detected cancers (OR = 2.7, 95% CI = 1.8 to 4.0, OR = 1.8, 95% CI = 1.3 to 2.5, and OR = 2.4, 95% CI = 1.4 to 3.9, respectively). Luminal B, HER2-enriched and TPN subtypes occurred more frequently in interval than screen-detected cancers (OR = 2.0, 95% CI = 1.1 to 3.9, OR = 4.6, 95% CI = 2.1 to 10.1, and OR = 2.8, 95% CI = 1.7 to 4.7, respectively).

Association between breast cancers types, sensitivity, and histological grade

In agreement with our postulated causal graph, histological grade explained much of the relation of tumour type to sensitivity (Figure 1). Irrespective of tumour receptor status and subtype when histological grade was included in the models (Model 2, Table 3), all ORs were attenuated (percent reductions for ER-negative = 48%; PR-negative = 33%; HER2-positive=33%; Luminal B=30%; HER2-enriched=39%; and TPN=50%) and all, except HER2-positive and HER2-enriched tumours, lost statistical significance. Even after adjustment, the

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association of HER2-enriched and sensitivity remained relatively strong compared to Luminal A (adjusted OR = 2.8, 95% CI = 1.2 to 6.5). Similarly, compared to HER2-negative, HER2-positive tumours remained associated with sensitivity but to a lesser extent than the HER2-enriched subtype (adjusted OR = 1.6, 95% CI = 1.0 to 2.8).

Association between breast cancer types and screening

Tumour receptor status was not associated with participation in screening (Table 4). There were no significant differences found between screened and clinical cancers in terms of ER- and PR-negative and HER2-positive tumour status (OR = 1.0, 95% CI = 0.7 to 1.4, OR = 1.1, 95% CI = 0.8 to 1.4, and OR = 1.0, 95% CI = 0.7 to 1.4, respectively). Adjusting for potentially confounding variables did little to change the crude point estimates which fluctuated near unity.

Results for subtypes were similar to those obtained for receptor status. No significant differences were found between screened and clinical cancers in terms of Luminal B, HER2-enriched, and TPN subtypes (Luminal B: OR = 0.9, 95% CI = 0.5 to 1.4, HER2-enriched: OR = 1.1, 95% CI = 0.6 to 1.8, TPN: OR = 0.8, 95% CI = 0.6 to 1.3) compared to Luminal A.

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4.6 Discussion Our results suggest that sensitivity is poorer for ER-negative, PR-negative and HER2-positive tumours. Likewise, compared to the Luminal A subtype, sensitivity appears poorer for Luminal B, HER2-enriched and TPN tumours. Adding histologic grade in the multivariate models attenuated several of the observed relations of tumour types to sensitivity and suggests that these may affect sensitivity through their effect on aggressiveness. However, even after adjustment for grade, HER2-positive and HER2-enriched tumours were still associated with more frequent interval cancers than other tumour types. According to our findings, receptor status and subtypes does not vary between women participating and not participating in screening Our results suggest that screening mammography performs poorly for TPN when compared to Luminal A tumours. This finding is in line with a recent study by Caldarella et al.25 although in that study the results were not significant (OR = 3.16 (95% CI = 0.81–12.26). However, that study may have been insufficiently powered as sample sizes were relatively small (SD Luminal A (n) =109, IC Luminal A (n) = 25 vs. SD TPN (n) = 8, IC TPN (n) = 6). Studies comparing TPN to all other subtypes combined (Luminal A, Luminal B and HER2-enriched in one category) also reported more interval cancers among TPN.8,13,20 Our analysis also suggests that sensitivity varies greatly for Luminal A, Luminal B and HER2- enriched. However, this is in disagreement with the study by Caldarella et al.25 which is the only other study that provided an adjusted point estimate for all subtypes separately. In that study, compared to Luminal A, Luminal B and HER2-enriched are not associated with interval cancers (adjusted ORs for Luminal B and HER-2 enriched, OR = 1.45 (95% CI = 0.68 to 3.07) and OR = 1.09 (95% CI = 0.26 to 4.55, respectively). However, this study classified the Luminal subtype based on a Ki-67 cut-off which is still subject to debate.28 This classification would tend to move tumours that we considered Luminal A into Luminal B. Hence, this approach would decrease the number of Luminal A and increase the number of Luminal B cases but would add less aggressive tumours to the Luminal B group thus reducing the difference in aggressiveness between Luminal A and B subtypes. Moreover, the HER2-enriched sample was somewhat smaller than ours (n=16 vs. n=33). The association between receptor status, subtype and histological grade generated estimates of great magnitude. To the best of our knowledge, we provide for the first time adjusted results confirming that ER-negative, PR-negative and HER2-positive tumours are strongly associated with grade III tumours. Moreover, we also report that compared to Luminal A, HER2-enriched and TPN are strongly associated with grade III rather than grade I/II tumours which is in agreement with the few other studies of this relation.24,29,30 These results confirm the intrinsic aggressive nature of these subtypes, and explain their overrepresentation in interval cancers. However, less is known about the aggressive potential of Luminal B. This study suggests that

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compared to Luminal A, Luminal B tumours tend to be grade III rather than grade I/II which has also been reported in one30 but not two other studies 24,29. In the latter, HER2 equivocal cases are considered positive which may have contributed to misclassification since some cases of Luminal A may have been included with Luminal B which would tend to reduce any difference between the two subtypes. Histological grade appears to explain much of the relation of receptor status or subtype to sensitivity. This is plausible because histological grade is related to the sojourn time, which is the preclinical period during which a tumour is detectable by screening.31 Aggressive tumours i.e. grade III, will progress rapidly through the detectable pre-clinical period (short sojourn time)32 and will be less likely to be detected by screening before becoming clinical. Conversely, non-aggressive tumours i.e. grade I, will progress slowly through the detectable preclinical phase (long sojourn time), and so, will have more opportunities to be detected by screening. Since subtypes vary in terms of aggressiveness it is possible that tumour type influences sensitivity.31 We tested this theory, by adding histological grade to our main models which attenuated almost all previous association between receptor status, subtype and sensitivity. Therefore, receptor status, subtype may affect screening sensitivity through tumour aggressiveness. However, this is valid provided that there are no unmeasured confounders between receptor status, subtypes and sensitivity, and grade and sensitivity.33 To the best of our knowledge we have not seen these associations reported elsewhere. Interestingly, we found that, although grade seems to be an important variable in the receptor status, subtype-sensitivity relationships, it does not entirely explain the lower sensitivity for HER2-positive and HER2-enriched tumours. The ORs for both these tumours remained significant even after adjustment for grade. We offer that HER2-positive and HER2-enriched tumours may influence sensitivity through their radiologic features at screening. Recently, when compared to Luminal A, HER2-enriched was found to be associated with calcifications (OR=2.8, 95% CI= 1.7 to 4.8).34 Since the interpretation of these lesions on screening mammograms can prove challenging35 it may offer an explanation as to why these tumours are more frequent in interval cancers. These tumours may have an affinity for a less conspicuous calcification shape or distribution. Because screening will inevitably detect some indolent cancers that may have never become symptomatic or be fatal in the woman’s lifetime,36,37 these cancers are thought to be overdiagnosed. Since Luminal A were overrepresented among screen-detected cancers and were less likely to have grade III tumours, we hypothesized that this subtype could potentially represent an indolent subtype. Therefore, in an overdiagnosis scenario, we would expect to find an excess of indolent cancers like the Luminal A subtype in screened cancers (combination of screen-detected and interval cancers) when compared to clinical cancers. Our results

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suggest that overdiagnosis of invasive breast cancer, if present, is not substantial since we did not find significant differences in receptor tumour status and subtype distribution between screened and clinical cancers. Studies evoking the notion of subtypes in overdiagnosis are few 38 and although we did not find an excess of Luminal A cases among the screened, we agree with Broukaert et al.38 that if overdiagnosis is present, cases would probably come from this subtype pool representing three quarters of diagnosed invasive breast cancer in this cohort. Our study has several strengths. We were able to obtain detailed information on women characteristics allowing us to adjust for a multitude of potentially confounding variables thereby reducing our risk of residual confounding. In previous studies, we noted adjustments for age and tumour size. According to our causal framework, tumour size is a consequence of screening and we did not include it in our analyses.39 We also classified subtypes according to recent guidelines28 which provide recommendations for the evaluation of ER and PR (HER2 guidelines were published in October 2013) and subtype classification based only on the expression status of ER, PR, and HER2 to identify clinically relevant subtypes. In addition, all specimens were handled in the same laboratory conditions (tissue-sample handling, tissue processing, fixation time and technicians) thereby reducing subtype misclassification and laboratory errors. In addition, we provided estimates for all tumour types individually and compared each subtype relative to Luminal A. We did not limit our comparisons to a dichotomous group (TPN vs. non-TPN). Our study also has some limitations, which should be considered. Our results are based on data from a single-institution. Therefore, we are limited in making population-level inferences such as obtaining actual sensitivity estimates for subtypes. In addition, given the nature of our study (retrospective, cases from a reference center, single-institutional analysis), it is subject to selection bias. Bias would arise if the population referred to the breast center is based on both screen detection and tumour type. This was unlikely to occur as tumour type is unknown at the time of referral.40 We were unable to classify interval cancers into ‟true” interval cancers which some argue allow for a more precise interpretation of the subtype-sensitivity association.7 However, true interval cancers have been reported to account for 65-75% of interval cancers7 and those missed due to interpretive failures account for 10% - 36%.3 This means that the majority of interval cancers can be expected to be true interval cancers. It would also suggest that, had we been able to classify interval cancers as true-negative or missed cancers, associations could have been stronger than the ones we observed. However, our results are comparable to others that have included only true interval cancers in their analyses. It would have been interesting to obtain radiologic features at screening according to receptor status and subtypes. Since breast cancers represent different types of tumours with unique biological and clinical

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characteristics, these differences may also influence the way they appear on a mammogram. A tumour’s radiological appearance may influence sensitivity as tumours with conspicuous features at screening will be more easily detected than those with less evident features. In addition to grade, this offers another potential pathway for tumours to affect screening sensitivity. In summary, our results confirm that screening sensitivity varies by tumour receptor status and subtype. In particular, screening mammography is better at detecting the Luminal A subtype than all other subtypes, and is poorer at detecting Luminal B, HER-enriched and Triple-negatives. We have shown that these differences in screening sensitivity for various tumour receptors and subtypes are due mostly to differences in aggressiveness, and more aggressive breast cancer types tend to have poorer sensitivity. However, other factors such as radiological features may also explain the poor sensitivity reported for HER2-positive tumours and HER2-enriched subtype, and this needs to be further clarified. Future studies with larger sample sizes to confirm these associations are needed. The findings in this study suggest that breast screening needs to be improved in order to maximize the early detection of aggressive breast cancers.

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4.7 References 1. Li CIF. Breast Cancer Epidemiology. Springer; 2009. 2. Morrison AS. Screening in chronic disease. Vol 7. 1st edition ed. New York: Oxford University Press;

1985. 3. Porter PL, El-Bastawissi AY, Mandelson MT, et al. Breast tumor characteristics as predictors of

mammographic detection: comparison of interval- and screen-detected cancers. J Natl Cancer Inst. Dec 1 1999;91(23):2020-2028.

4. Gilliland FD, Joste N, Stauber PM, et al. Biologic characteristics of interval and screen-detected breast cancers. J Natl Cancer Inst. May 3 2000;92(9):743-749.

5. Majid AS, de Paredes ES, Doherty RD, Sharma NR, Salvador X. Missed breast carcinoma: pitfalls and pearls. Radiographics. Jul-Aug 2003;23(4):881-895.

6. Caumo F, Vecchiato F, Strabbioli M, Zorzi M, Baracco S, Ciatto S. Interval cancers in breast cancer screening: comparison of stage and biological characteristics with screen-detected cancers or incident cancers in the absence of screening. Tumori. Mar-Apr 2010;96(2):198-201.

7. Kirsh VA, Chiarelli AM, Edwards SA, et al. Tumor characteristics associated with mammographic detection of breast cancer in the Ontario breast screening program. J Natl Cancer Inst. Jun 22 2011;103(12):942-950.

8. Rayson D, Payne JI, Abdolell M, et al. Comparison of clinical-pathologic characteristics and outcomes of true interval and screen-detected invasive breast cancer among participants of a Canadian breast screening program: a nested case-control study. Clin Breast Cancer. Mar 2011;11(1):27-32.

9. van der Vegt B, Wesseling J, Pijnappel RM, et al. Aggressiveness of 'true' interval invasive ductal carcinomas of the breast in postmenopausal women. Mod Pathol. Apr 2010;23(4):629-636.

10. Collett K, Stefansson IM, Eide J, et al. A basal epithelial phenotype is more frequent in interval breast cancers compared with screen detected tumors. Cancer Epidemiol Biomarkers Prev. May 2005;14(5):1108-1112.

11. Crosier M, Scott D, Wilson RG, Griffiths CD, May FE, Westley BR. Differences in Ki67 and c-erbB2 expression between screen-detected and true interval breast cancers. Clin Cancer Res. Oct 1999;5(10):2682-2688.

12. Crosier M, Scott D, Wilson RG, Griffiths CD, May FE, Westley BR. High expression of the trefoil protein TFF1 in interval breast cancers. Am J Pathol. Jul 2001;159(1):215-221.

13. Domingo L, Sala M, Servitja S, et al. Phenotypic characterization and risk factors for interval breast cancers in a population-based breast cancer screening program in Barcelona, Spain. Cancer Causes Control. Aug 2010;21(8):1155-1164.

14. Musolino A, Michiara M, Conti GM, et al. Human epidermal growth factor receptor 2 status and interval breast cancer in a population-based cancer registry study. J Clin Oncol. Jul 1 2012;30(19):2362-2368.

15. Frisell J, Eklund G, Hellstrom L, Somell A. Analysis of interval breast carcinomas in a randomized screening trial in Stockholm. Breast Cancer Res Treat. 1987;9(3):219-225.

16. Wang H, Bjurstam N, Bjorndal H, et al. Interval cancers in the Norwegian breast cancer screening program: frequency, characteristics and use of HRT. Int J Cancer. Nov 2001;94(4):594-598.

17. Alexander FE, Anderson TJ, Hubbard AL. Screening status in relation to biological and chronological characteristics of breast cancers: a cross sectional survey. J Med Screen. 1997;4(3):152-157.

18. Chiarelli AM, Edwards SA, Sheppard AJ, et al. Favourable prognostic factors of subsequent screen-detected breast cancers among women aged 50-69. Eur J Cancer Prev. Jan 23 2012.

19. Cowan WK, Angus B, Gray JC, Lunt LG, al-Tamimi SR. A study of interval breast cancer within the NHS breast screening programme. J Clin Pathol. Feb 2000;53(2):140-146.

20. Lowery JT, Byers T, Kittelson J, et al. Differential expression of prognostic biomarkers between interval and screen-detected breast cancers: does age or family history matter? Breast Cancer Res Treat. Aug 2011;129(1):211-219.

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21. Anttinen J, Kuopio T, Nykanen M, Torkkeli H, Saari U, Juhola M. Her-2/neu oncogene amplification and protein over-expression in interval and screen-detected breast cancers. Anticancer Res. Sep-Oct 2003;23(5b):4213-4218.

22. Perou CM, Sorlie T, Eisen MB, et al. Molecular portraits of human breast tumours. Nature. Aug 17 2000;406(6797):747-752.

23. Sorlie T, Perou CM, Tibshirani R, et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci U S A. Sep 11 2001;98(19):10869-10874.

24. Carey LA, Perou CM, Livasy CA, et al. Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study. Jama. Jun 7 2006;295(21):2492-2502.

25. Caldarella A, Puliti D, Crocetti E, et al. Biological characteristics of interval cancers: a role for biomarkers in the breast cancer screening. J Cancer Res Clin Oncol. Feb 2013;139(2):181-185.

26. Bérubé S, Provencher L, Robert J, et al. Quantitative exploration of possible reasons for the recent improvement in breast cancer survival. Breast Cancer Res Treat. 2007;106(3):419-431.

27. MSSS Direction québecoise du cancer. Protocole pour l'examen des spécimens provenant de patients atteints d'un carcinome infiltrant et micro-infiltrant du sein. Québec: Direction québécoise du cancer, MSSS; 2012.

28. Guiu S, Michiels S, Andre F, et al. Molecular subclasses of breast cancer: how do we define them? The IMPAKT 2012 Working Group Statement. Ann Oncol. 2012;23(12):2997-3006.

29. Tamimi RM, Baer HJ, Marotti J, et al. Comparison of molecular phenotypes of ductal carcinoma in situ and invasive breast cancer. Breast Cancer Res. 2008;10(4):R67.

30. Onitilo AA, Engel JM, Greenlee RT, Mukesh BN. Breast cancer subtypes based on ER/PR and Her2 expression: comparison of clinicopathologic features and survival. Clin Med Res. Jun 2009;7(1-2):4-13.

31. Vainio H, Bianchini F. Breast cancer and screening: International Agency for Research on Cancer (IARC) Handbooks of Cancer Prevention. Vol 7. Lyon, France: IARC Press; 2002.

32. Tabar L, Chen HH, Fagerberg G, Duffy SW, Smith TC. Recent results from the Swedish Two-County Trial: the effects of age, histologic type, and mode of detection on the efficacy of breast cancer screening. J Natl Cancer Inst Monogr. 1997(22):43-47.

33. Cole SR, Hernán MA. Fallibility in estimating direct effects. Int J Epidemiol. 2002;31(1):163-165. 34. Killelea BK, Chagpar AB, Bishop J, et al. Is there a correlation between breast cancer molecular

subtype using receptors as surrogates and mammographic appearance? Ann Surg Oncol. Oct 2013;20(10):3247-3253.

35. Hoff SR, Samset JH, Abrahamsen A-L, Vigeland E, Klepp O, Hofvind S. Missed and true interval and screen-detected breast cancers in a population based screening program. Acad Radiol. 2011;18(4):454-460.

36. Moynihan R, Doust J, Henry D. Preventing overdiagnosis: how to stop harming the healthy. BMJ. 2012;344.

37. Elmore JG, Fletcher SW. Overdiagnosis in breast cancer screening: time to tackle an underappreciated harm. Ann Intern Med. 2012;156(7):536-537.

38. Brouckaert O, Schoneveld A, Truyers C, et al. Breast cancer phenotype, nodal status and palpability may be useful in the detection of overdiagnosed screening-detected breast cancers. Ann Oncol. 2013.

39. Rothman KJ, Greenland S, Lash TL. Modern Epidemiology. Wolters Kluwer Health/Lippincott Williams & Wilkins; 2008.

40. Hernán MA, Hernandez-Diaz S, Robins JM. A structural approach to selection bias. Epidemiology. 2004;15(5):615-625.

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Figure 1. Causal diagram illustrating the possible pathways by which breast cancer types may influence screening sensitivity.

Breast cancer types

Sensitivity

Radiologic features

Grade

59

Table 1. Characteristics of study population (N=1536) Screen-detected

(n=596) Interval

(n=262) Screened

(n=858) Clinical

(n=678) Women characteristics No. (%) No. (%) No. (%) No. (%) Mean age at diagnosis, y (±SD) 58.9 (5.5) 59.0 (5.1) 58.9 (5.4) 59.8 (6.7) Age at diagnosis, y 50 – 54 143 (24.0) 57 (21.8) 200 (23.3) 194 (28.6) 55 – 59 193 (32.4) 92 (35.1) 285 (33.2) 159 (23.5) 60 – 64 141 (23.7) 73 (27.9) 214 (24.9) 129 (19.0) 65 – 71 119 (20.0) 40 (15.3) 159 (18.5) 196 (28.9) Age at first birth, y Nulliparous 137 (24.0) 62 (25.5) 199 (24.4) 145 (22.9) <20 35 (5.5) 17 (7.0) 43 (5.3) 35 (5.5) ≥20 – 24 183 (32.0) 83 (34.2) 266 (32.6) 183 (29.0) ≥25 – 29 166 (29.0) 52 (21.4) 218 (26.8) 176 (27.9) ≥30 – 34 50 (8.7) 21 (8.6) 71 (8.7) 66 (10.4) ≥35 10 (1.8) 8 (3.3) 18 (2.2) 27 (4.3) Missing 24 19 43 46 Family history None 420 (72.2) 187 (73.0) 607 (72.4) 458 (69.3) Yes 162 (27.8) 69 (27.0) 231 (27.6) 203 (30.7) Missing* 14 6 20 17 Hormone therapy use None 228 (38.9) 64 (25.3) 292 (34.8) 315 (48.5) Yes 358 (61.1) 189 (74.7) 547 (65.2) 335 (51.5) Missing* 10 9 19 28 Breast density, % <25 63 (10.6) 11 (4.2) 74 (8.6) --- 25 –49 256 (43.0) 80 (30.5) 336 (39.2) 50 –75 205 (34.4) 118 (45.0) 323 (37.6) >75 72 (12.1) 53 (20.2) 125 (14.6) Mean BMI, kg/m2 (±SD) 26.4 (5.0) 25.7 (5.0) 26.2 (5.0) 26.1 (5.4) BMI, kg/m2 <20.0 31 (5.6) 22 (9.1) 53 (6.6) 54 (8.6) 20.0 – 24.9 208 (37.2) 99 (44.7) 307 (38.3) 241 (38.3) 25.0 – 29.9 214 (38.3) 78 (32.1) 292 (36.4) 209 (33.2) 30.0 – 34.9 67 (12.0) 32 (13.2) 99 (12.3) 81 (12.9) ≥35.0 39 (7.0) 12 (4.9) 51 (6.4) 44 (7.0) Missing* 37 19 56 49

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Table 1. Characteristics of study population (continued) Screen-detected

(n=596) Interval

(n=262) Screened

(n=858) Clinical

(n=678) Tumour characteristics No. (%) No. (%) No. (%) No. (%) Mean tumour size, mm (±SD) 15.5 (11.4) 24.7 (15.6) 18.3 (13.5) 24.1 (18.0) Tumour size, mm <10.0 165 (27.7) 24 (9.2) 189 (22.0) 110 (16.2) 11.0 – 14.9 158 (26.5) 33 (12.6) 191 (22.3) 108 (15.9) 15.0 – 19.9 108 (18.1) 46 (17.6) 154 (18.0) 110 (16.2) ≥20.0 165 (27.8) 159 (60.7) 324 (37.8) 350 (51.6) Number of positive nodes 0 421 (73.3) 135 (52.3) 556 (66.8) 351 (55.7) 1–3 113 (19.7) 70 (27.1) 183 (22.0) 180 (28.6) >4 40 (7.0) 53 (20.5) 93 (11.2) 99 (15.7) Missing* 22 4 26 48 Tumour stage I 391 (66.3) 84 (32.7) 475 (56.1) 260 (39.0) II 149 (25.3) 120 (46.7) 269 (31.8) 264 (39.6) III 44 (7.5) 52 (20.2) 96 (11.3) 115 (17.3) IV 6 (1.0) 1 (0.4) 7 (0.8) 27 (4.1) Missing* 6 5 11 12 Vascular invasion No 479 (82.0) 167 (65.2) 646 (76.9) 466 (71.8) Yes 105 (18.0) 89 (34.8) 194 (23.1) 183 (28.2) Missing* 12 6 18 29 Histological grade I 244 (43.8) 66 (26.5) 310 (38.5) 194 (31.0) II 235 (42.2) 98 (39.4) 333 (41.3) 268 (42.8) III 78 (14.0) 85 (34.1) 163 (20.2) 164 (26.2) Missing* 39 13 52 52 Estrogen receptor Positive 526 (89.1) 195 (75.6) 721 (85.0) 552 (82.6) Negative 64 (10.9) 63 (24.4) 127 (15.0) 116 (17.4) Missing* 6 4 10 10 Progesterone receptor Positive 411 (69.8) 144 (56.0) 555 (65.6) 415 (62.2) Negative 178 (30.2) 113 (44.0) 291 (34.4) 252 (37.8) Missing* 7 5 12 11 HER2 status Negative 463 (91.7) 204 (84.0) 667 (89.2) 513 (87.5) Positive 42 (8.3) 39 (16.1) 81 (10.8) 73 (12.5) Missing* 91 19 110 92 Tumour subtypes Luminal A 412 (81.6) 153 (63.5) 565 (75.7) 433 (74.1) Luminal B 29 (5.7) 19 (7.9) 48 (6.4) 36 (6.2) HER2-enriched 13 (2.6) 20 (8.3) 33 (4.4) 36 (6.2) Triple-negative 40 (7.9) 41 (17.0) 81 (10.9) 64 (11.0) Unclassified 11 (2.2) 8 (3.3) 19 (2.6) 15 (2.6) Missing* 91 21 112 94 Y = years; SD = standard deviation; BMI = body mass index. * Variables with missing information were excluded from percentage calculation.

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Table 2. Tumour type and histological grade of breast cancers (N=806)*

Grade I/II (n=643)‡

Grade III (n=163)‡

Crude OR (95% CI)

Adjusted OR (95% CI) Model 1†

Tumour type No. (%) No. (%) Estrogen receptor Positive 607 (94.4) 75 (46.0) 1.0 (Referent) 1.0 (Referent) Negative 32 (5.0) 87 (53.4) 22.0 (13.7 – 35.2) 25.0 (15.0 – 41.8) Missing 4 (0.6) 1 (0.6) Progesterone receptor Positive 478 (74.3) 46 (28.2) 1.0 (Referent) 1.0 (Referent) Negative 160 (24.9) 116 (71.2) 7.5 (5.1 – 11.1) 8.3 (5.5 – 12.5) Missing 5 (0.8) 1 (0.6) HER2 receptor Negative 520 (80.9) 121 (74.2) 1.0 (Referent) 1.0 (Referent) Positive 39 (6.1) 38 (23.3) 4.2 (2.6 – 6.8) 4.3 (2.5 – 7.2) Missing 84 (13.1) 4 (2.5) Subtype Luminal A 490 (76.2) 52 (31.9) 1.0 (Referent) 1.0 (Referent) Luminal B 27 (4.2) 20 (12.3) 7.0 (3.7 – 13.3) 6.8 (3.4 – 13.3) HER2-enriched 12 (1.9) 18 (11.0) 14.1 (6.5 – 31.0) 18.3 (7.5 – 44.7) Triple-negative 14 (2.2) 65 (39.9) 43.7 (23.0 – 83.3) 49.7 (24.9 – 99.3) Unclassified 15 (2.3) 3 (1.8) 1.9 (0.5 – 6.7) 2.1 (0.5 – 7.9) Missing 85 (13.2) 5 (3.1) * OR=odds ratio, CI=confidence interval. † Model 1: adjusted for age at diagnosis, age at first birth, family history, hormone therapy use, breast density, and BMI (body mass index). ‡ 52 missing outcome data not included in analyses.

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Table 3. Tumour type of invasive interval breast cancers relative to screen-detected breast cancers (N=858)* Screen-detected

(n=596) Interval

(n=262) Crude OR

(95% CI) Adjusted OR (95% CI)

Model 1† Adjusted OR (95% CI)

Model 2‡ Tumour type No. (%) No. (%) Estrogen receptor Positive 526 (88.3) 195 (74.4) 1.0 (Referent) 1.0 (Referent) 1.0 (Referent) Negative 64 (10.7) 63 (24.1) 2.7 (1.8 – 3.9) 2.7 (1.8 – 4.0) 1.4 (0.8 – 2.3) Missing 6 (1.0) 4 (1.5) Progesterone receptor Positive 411 (69.0) 144 (55.0) 1.0 (Referent) 1.0 (Referent) 1.0 (Referent) Negative 178 (29.9) 113 (43.1) 1.8 (1.3 – 2.5) 1.8 (1.3 – 2.5) 1.2 (0.8 – 1.7) Missing 7 (1.2) 5 (1.9) HER2 receptor Negative 463 (91.7) 204 (84.0) 1.0 (Referent) 1.0 (Referent) 1.0 (Referent) Positive 42 (8.3) 39 (16.1) 2.1 (1.3 – 3.4) 2.4 (1.4 – 3.9) 1.6 (1.0 – 2.8) Missing 91 (15.3) 19 (7.3) Subtype Luminal A 412 (69.1) 153 (58.4) 1.0 (Referent) 1.0 (Referent) 1.0 (Referent) Luminal B 29 (4.9) 19 (7.3) 1.8 (1.0 – 3.2) 2.0 (1.1 – 3.9) 1.4 (0.7 – 2.7) HER2-enriched 13 (2.2) 20 (7.6) 4.1 (2.0 – 8.5) 4.6 (2.1 – 10.1) 2.8 (1.2 – 6.5) Triple-negative 40 (6.7) 41 (15.7) 2.8 (1.7 – 4.4) 2.8 (1.7 – 4.7) 1.4 (0.8 – 2.6) Unclassified 11 (1.9) 8 (3.1) 2.0 (0.8 – 5.0) 1.7 (0.6 – 4.4) 1.5 (0.5 – 4.0) Missing 91 (15.3) 21 (8.0) * OR=odds ratio, CI=confidence interval. † Model 1: adjusted for age at diagnosis, age at first birth, family history, hormone therapy use, breast density, and BMI (body mass index). ‡ Model 2: adjusted for age at diagnosis, age at first birth, family history, hormone therapy use, breast density, BMI (body mass index), and grade.

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Table 4. Tumour type of invasive clinical breast cancers relative to screened breast cancers (N=1536)*

Screened (n=858)

Clinical (n=678)

Crude OR (95% CI)


Adjusted OR (95% CI) Model 2‡

Tumour type No. (%) No. (%) Estrogen receptor Positive 721 (84.0) 552 (81.4) 1.0 (Referent) 1.0 (Referent) 1.0 (Referent) Negative 127 (14.8) 116 (17.1) 1.2 (0.9 – 1.6) 1.2 (0.9 – 1.7) 1.0 (0.7 – 1.4) Missing 10 (1.2) 10 (1.5) Progesterone receptor Positive 555 (64.7) 415 (61.2) 1.0 (Referent) 1.0 (Referent) 1.0 (Referent) Negative 291 (33.9) 252 (37.2) 1.2 (0.9 – 1.4) 1.2 (1.0 – 1.5) 1.1 (0.8 – 1.4) Missing 12 (1.4) 11 (1.6) HER2 status Negative 667 (77.7) 513 (75.7) 1.0 (Referent) 1.0 (Referent) 1.0 (Referent) Positive 81 (9.4) 73 (10.8) 1.2 (0.8 – 1.6) 1.2 (0.8 – 1.7) 1.0 (0.7 – 1.4) Missing 110 (12.8) 92 (13.6) Subtype Luminal A 565 (65.9) 433 (63.9) 1.0 (Referent) 1.0 (Referent) 1.0 (Referent) Luminal B 48 (5.6) 36 (5.3) 1.0 (0.6 – 1.5) 1.0 (0.7 – 1.7) 0.9 (0.5 – 1.4) HER2-enriched 33 (3.9) 36 (5.3) 1.4 (0.9 – 2.3) 1.4 (0.8 – 2.3) 1.1 (0.6 – 1.8) Triple-negative 81 (9.4) 64 (9.4) 1.0 (0.7 – 1.5) 1.1 (0.8 – 1.6) 0.8 (0.6 – 1.3) Unclassified 19 (2.2) 15 (2.2) 1.0 (0.8 – 1.5) 1.1 (0.5 – 2.2) 1.0 (0.5 – 2.0) Missing 112 (13.1) 94 (13.9) * OR=odds ratio, CI=confidence interval. † Model 1: adjusted for age at diagnosis, age at first birth, family history, hormone therapy use, and BMI (body mass index). ‡ Model 2: adjusted for age at diagnosis, age at first birth, family history, hormone therapy use, BMI, and grade (body mass index).

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Conclusion In summary, this study suggests that screening mammography sensitivity varies by breast tumour type. In terms of tumour receptor status, the results suggest that ER-positive, PR-positive and HER2-negative tumour types have a better sensitivity than ER-negative, PR-negative and HER2-positive tumours. Sensitivity also varies by breast cancer subtypes. Notably, Luminal A tumours have a better sensitivity than Luminal B, HER2-enriched and Triple-negative tumours. We show for the first time this reduction in sensitivity for HER2-enriched, and also for Luminal B, which, to our knowledge, has not been published elsewhere. We sought to gain some understanding into the underlying mechanism that could potentially explain how tumour types influence sensitivity. We previously hypothesized that tumours could affect sensitivity by way of the tumour’s aggressiveness. The results from the present work suggest that the effect of tumour type on sensitivity is mediated to a large extent by aggressiveness. We are the first to examine the impact of aggressiveness of the relationship of tumour type and sensitivity. We also conducted sensitivity analyses to compare complete-case analyses versus the use of a missing indicator variable, and tested if vascular invasion could be as important as the histological grade in the breast cancer type and sensitivity relationship (Appendix A-E). The analyses showed that the results obtained in this study are robust as there were no important differences between our treatment of missing variables and using complete cases. Furthermore, grade better explained the association between breast cancer types and sensitivity than vascular invasion. Our results also suggest very strong associations between type and grade. Compared to the Luminal A, Luminal B, HER2-enriched and Triple-negatives were strongly associated with grade III tumours. We confirm studies published previously but provide better adjusted estimates. Of note, we report an aggressive profile for Lumina B, compared to Luminal A tumours, which has not been reported elsewhere. Since sensitivity varies by breast cancer type, this may have implications for the effect of screening on mortality reduction since sensitivity is worse for more aggressive breast cancers. Screening may allow greater relative reduction in mortality for Luminal A tumours than for the other subtypes in part because of these differences in sensitivity. To maximize the detection of rapidly progressing interval cancers, one potential option is to reduce the period between two screenings, for instance, reduce the biannual screening requisite to an annual screening. The benefit of that scenario is that we increase the opportunity to detect interval cancers which we know are associated with types of breast cancers that are more aggressive. However, these aggressive cancer types are not frequent, and this option would expose women to greater negative effects of screening such as an increase in false-positives, in overdiagnosis, and in radiation exposure. Another approach is to study risk

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factors for the breast cancer types. Additional research could help identify women at risk for certain types of cancers in order to propose different screening options for these women for example, propose early screening to younger aged women, recommend an alternate screening schedule (annual vs. biannual), or suggest an alternate screening technology. The results of the present study are interesting and could inspire additional work. For instance, the present study presents results from cases obtained at the Centre des maladies du sein Deschênes-Fabia de Québec (CMSDF). This is a world-class reference center for breast cancer and we have a good representation of most cases that arise in the Quebec City area. Although it is very close to a population-based study, we may not have ascertained all interval cancers. Thus, we were unable to obtain actual sensitivity estimates for tumours with different receptor status and different subtypes. A population-based follow-up study could therefore be conducted ascertaining all cancer cases diagnosed in screening participants of the province of Québec following a reference screening year. Such a study could be done with PQDCS data. The challenge for this type of study would be to retrieve all pathology data for all tumours and to have sufficient study power. The study design would need to maximize the number of HER2-enriched cases because this is the group where greater uncertainty remains as to differences in sensitivity compared to tumours of other subtypes especially Luminal A. To date there are no studies reporting estimates of sensitivity or sensitivity ratios for each breast cancer type. Given that sensitivity is high (exceeding 70%), lack of sensitivity odds ratios and sensitivity odds ratios will be poor estimates of their respective proportion ratios.

The main objective of this study was to examine the association between breast cancer types and sensitivity. At the onset, we hypothesized that histological grade was in the causal path and we considered the variable as an intermediate. Since the effect of this intermediate on the association type-sensitivity was of interest, we adjusted for this variable to isolate the direct effect and compared the results to the unadjusted model eliminating the indirect effect. However, literature on causal methods does not recommend this method since we have to make the assumption that there are no neglected confounders in the type-grade relationship, and grade-sensitivity relationship. Although we included all known potential confounders to minimize the risk of residual confounding, a possibility remains that residual confounding is not completely avoided. A hypothetical confounder between the mediator (grade) and sensitivity would not bias the overall estimates in a model that does not adjust for grade since it is a collider variable which essentially blocks the path of the confounder. However, once grade is adjusted, the path opens and confounding ensues. The results from this study therefore, provide preliminary information that should be followed-up with methods that better quantify the direct and indirect effects individually. To date, no studies have been published which explore the impact of the mediator grade on the total effect of tumour type on sensitivity.

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In the present study, tumour aggressiveness (grade) was considered as a potential intermediate in the type and sensitivity relationship. However, another potential interesting pathway is the one mediated by tumour radiologic features. Radiologic features could affect sensitivity because tumour type appears to affect the appearance of the cancer on the screening mammogram. According to this literature review, the radiologic appearance of tumours at screening could also influence sensitivity and there is evidence that the appearance of a tumour on the mammogram varies by breast cancer type. Since grade did not completely attenuate the effect of HER2 positivity on sensitivity, a part of the remaining effect may go through this other pathway. To date there are no studies that have explored the breast cancer types, radiologic features, and sensitivity relationship. In addition, better conducted studies of subtypes and radiologic features should be conducted since many studies were of poor quality.

In this study, we prioritized the histological grade as a proxy measure for aggressiveness because it is a well-known, validated, and extensively studied measure. It is assessed in all tumours. Therefore, data are available for most tumours. Another possible measure of aggressiveness that correlates with histological grade and that could be explored is Ki-67 expression, which is a protein expressed during the cell cycle. Ki-67 expression is prioritized since it is more frequently performed in laboratories than the S-phase fraction, and is also being used sometimes to further classify Luminal A and Luminal B. Ki-67 might be an even better measure of the rapidity of tumour progression because it is a more direct measure of cellular replication compared to grade which also focuses on differentiation. Therefore, future studies may replicate the analyses in this present study, and use Ki-67 as a measure for aggressiveness. Because Ki-67 is not routinely performed like the histological grade, the test may have to be performed retrospectively on tumour samples to minimize missing data. The results could be compared to those obtained with grade. The end-goal of breast cancer screening mammography is to reduce breast cancer mortality. To fully realize that goal, screening sensitivity must be optimal in order to early detect all breast cancers present at screening. According to this study, screening mammography may not be able to detect all types of breast cancers. Moreover, the types of cancers not detected by mammography are ones which tend to have an aggressive nature. This means that mortality reduction may only be achievable for certain types of breast cancers. From a public health perspective, it will be critical then to continue exploring different technologies and strategies to optimize cancer detection. Since we report that the type of breast cancer can influence sensitivity, this also has implications from a breast cancer screening evaluation perspective. Breast cancer tumour types will now need to be taken into account in the analyses when evaluating program performance.

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Appendix

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Appendix A Additional Table 1. Complete-case results of tumour type and histological grade of breast cancers (N=806)*

Grade I/II (n=643)§

Grade III (n=163)§

Crude OR (95% CI)

Adjusted OR (95% CI)†

Tumour type No. (%) No. (%) Estrogen receptor ‡ Positive 607 (95.0) 75 (46.3) 1.0 (Referent) 1.0 (Referent) Negative 32 (5.0) 87 (53.7) 22.0 (13.7 – 35.2) 25.2 (14.4 – 43.8) Progesterone receptor ‡ Positive 478 (74.9) 46 (28.4) 1.0 (Referent) 1.0 (Referent) Negative 160 (25.1) 116 (71.6) 7.5 (5.1 – 11.1) 8.4 (5.4 – 12.9) HER2 receptor ‡ Negative 520 (93.0) 121 (76.1) 1.0 (Referent) 1.0 (Referent) Positive 39 (7.0) 38 (23.9) 4.2 (2.6 – 6.8) 4.1 (2.3 – 7.1) Subtype ‡ Luminal A 490 (87.8) 52 (32.9) 1.0 (Referent) 1.0 (Referent) Luminal B 27 (4.8) 20 (12.7) 7.0 (3.7 – 13.3) 6.5 (3.2 – 13.1) HER2-enriched 12 (2.2) 18 (11.4) 14.1 (6.5 – 31.0) 16.7 (6.2 – 45.1) Triple-negative 14 (2.5) 65 (41.4) 43.7 (23.0 – 83.3) 45.6 (22.1 – 94.2) Unclassified 15 (2.7) 3 (1.9) 1.9 (0.5 – 6.7) 2.8 (0.7 – 11.1) * OR=odds ratio, CI=confidence interval. † Model adjusted for age at diagnosis, age at first birth, family history, hormone therapy use, breast density, and BMI. ‡ Numbers in these categories do not sum to the total because of missing data. § 52 missing outcome data not included in analyses.

79

Appendix B Additional Table 2. Complete-case results of tumour type of invasive interval breast cancers relative to screen-detected cancers (N=858) *

Screen-detected (n=596)

Interval (n=262)

Crude OR (95% CI)



Tumour type No. (%) No. (%) Estrogen receptor § Positive 526 (89.2) 195 (75.6) 1.0 (Referent) 1.0 (Referent) 1.0 (Referent) Negative 64 (10.9) 63 (24.4) 2.7 (1.8 – 3.9) 2.6 (1.7 – 4.1) 1.3 (0.7 – 2.2) Progesterone receptor § Positive 411 (69.8) 144 (56.0) 1.0 (Referent) 1.0 (Referent) 1.0 (Referent) Negative 178 (30.2) 113 (44.0) 1.9 (1.3 – 2.6) 1.9 (1.3 – 2.6) 1.2 (0.8 – 1.8) HER2 receptor § Negative 463 (91.7) 204 (84.0) 1.0 (Referent) 1.0 (Referent) 1.0 (Referent) Positive 42 (8.3) 39 (16.1) 2.1 (1.3 – 3.4) 2.2 (1.3 – 3.9) 1.6 (0.9 – 2.8) Subtype § Luminal A 412 (81.6) 153 (63.5) 1.0 (Referent) 1.0 (Referent) 1.0 (Referent) Luminal B 29 (5.7) 19 (7.9) 1.8 (1.0 – 3.2) 2.2 (1.1 – 4.3) 1.3 (0.6 – 2.7) HER2-enriched 13 (2.6) 20 (8.3) 4.1 (2.0 – 8.5) 3.8 (1.5 – 9.4) 3.0 (1.1 – 8.3) Triple-negative 40 (7.9) 41 (17.0) 2.8 (1.7 – 4.4) 2.9 (1.7 – 4.9) 1.3 (0.7 – 2.5) Unclassified 11 (2.2) 8 (3.3) 2.0 (0.8 – 5.0) 1.4 (0.4 – 4.4) 1.1 (0.3 – 3.9) * OR=odds ratio, CI=confidence interval. † Model 1: adjusted for age at diagnosis, age at first birth, family history, hormone therapy use, breast density, and BMI. ‡ Model 2: adjusted for age at diagnosis, age at first birth, family history, hormone therapy use, breast density, BMI, and grade. § Numbers in these categories do not sum to the total because of missing data.

80

Appendix C Additional Table 3. Complete-case results of tumour type of invasive clinical breast cancers relative to screened breast cancers (N=1536) *

Screened (n=858)

Clinical (n=678)

Crude OR (95% CI)



Tumour type No. (%) No. (%) Estrogen receptor § Positive 721 (85.0) 552 (82.6) 1.0 (Referent) 1.0 (Referent) 1.0 (Referent) Negative 127 (15.0) 116 (17.4) 1.2 (0.9 – 1.6) 1.3 (0.9 – 1.7) 1.0 (0.7 – 1.4) Progesterone receptor § Positive 555 (65.6) 415 (62.2) 1.0 (Referent) 1.0 (Referent) 1.0 (Referent) Negative 291 (34.4) 252 (37.8) 1.2 (0.9 – 1.4) 1.2 (0.9 – 1.5) 1.0 (0.7 – 1.3) HER2 status § Negative 667 (89.2) 513 (87.5) 1.0 (Referent) 1.0 (Referent) 1.0 (Referent) Positive 81 (10.8) 73 (12.5) 1.2 (0.8 – 1.6) 1.3 (0.9 – 1.9) 1.2 (0.8 – 1.8) Subtype § Luminal A 565 (75.7) 433 (74.1) 1.0 (Referent) 1.0 (Referent) 1.0 (Referent) Luminal B 48 (6.4) 36 (6.2) 1.0 (0.6 – 1.5) 1.1 (0.7 – 1.8) 1.0 (0.6 – 1.6) HER2-enriched 33 (4.4) 36 (6.2) 1.4 (0.9 – 2.3) 1.7 (1.0 – 3.0) 1.5 (0.8 – 2.7) Triple-negative 81 (10.9) 64 (11.0) 1.0 (0.7 – 1.5) 1.1 (0.8 – 1.7) 0.8 (0.5 – 1.3) Unclassified 19 (2.5) 15 (2.6) 1.0 (0.5 – 2.1) 1.4 (0.6 – 3.2) 1.3 (0.6 – 3.1) * OR=odds ratio, CI=confidence interval. † Model 1: adjusted for age at diagnosis, age at first birth, family history, hormone therapy use, and BMI. ‡ Model 2: adjusted for age at diagnosis, age at first birth, family history, hormone therapy use, BMI, and grade. § Numbers in these categories do not sum to the total because of missing data.

81

Appendix D Additional Table 4. Tumour type of invasive interval breast cancers relative to screen-detected breast cancers, adjusted for vascular invasion (N=858) *


Interval (n=262)

Crude OR (95% CI)



Tumour type No. (%) No. (%) Estrogen receptor Positive 526 (88.3) 195 (74.4) 1.0 (Referent) 1.0 (Referent) 1.0 (Referent) Negative 64 (10.7) 63 (24.1) 2.7 (1.8 – 3.9) 2.7 (1.8 – 4.0) 2.5 (1.6 – 3.8) Missing 6 (1.0) 4 (1.5) Progesterone receptor Positive 411 (69.0) 144 (55.0) 1.0 (Referent) 1.0 (Referent) 1.0 (Referent) Negative 178 (29.9) 113 (43.1) 1.8 (1.3 – 2.5) 1.8 (1.3 – 2.5) 1.7 (1.3 – 2.4) Missing 7 (1.2) 5 (1.9) HER2 receptor Negative 463 (91.7) 204 (84.0) 1.0 (Referent) 1.0 (Referent) 1.0 (Referent) Positive 42 (8.3) 39 (16.1) 2.1 (1.3 – 3.4) 2.4 (1.4 – 3.9) 2.1 (1.3 – 3.5) Missing 91 (15.3) 19 (7.3) Subtype Luminal A 412 (69.1) 153 (58.4) 1.0 (Referent) 1.0 (Referent) 1.0 (Referent) Luminal B 29 (4.9) 19 (7.3) 1.8 (1.0 – 3.2) 2.0 (1.1 – 3.9) 1.9 (1.0 – 3.7) HER2-enriched 13 (2.2) 20 (7.6) 4.1 (2.0 – 8.5) 4.6 (2.1 – 10.1) 3.7 (1.7 – 8.2) Triple-negative 40 (6.7) 41 (15.7) 2.8 (1.7 – 4.4) 2.8 (1.7 – 4.7) 2.8 (1.7 – 4.7) Unclassified 11 (1.9) 8 (3.1) 2.0 (0.8 – 5.0) 1.7 (0.6 – 4.4) 1.5 (0.5 – 4.0) Missing 91 (15.3) 21 (8.0) * OR=odds ratio, CI=confidence interval. † Model 1: adjusted for age at diagnosis, age at first birth, family history, hormone therapy use, breast density, and BMI. ‡ Model 2: adjusted for age at diagnosis, age at first birth, family history, hormone therapy use, breast density, BMI, and vascular invasion.

82

Appendix E Additional Table 5. Complete-case results of tumour type of invasive interval breast cancers relative to screen-detected breast cancers, adjusted for vascular invasion (N=858) *


Interval (n=262)

Crude OR (95% CI)



Tumour type No. (%) No. (%) Estrogen receptor § Positive 526 (89.2) 195 (75.6) 1.0 (Referent) 1.0 (Referent) 1.0 (Referent) Negative 64 (10.9) 63 (24.4) 2.7 (1.8 – 3.9) 2.6 (1.7 – 4.1) 2.3 (1.4 – 3.6) Progesterone receptor § Positive 411 (69.8) 144 (56.0) 1.0 (Referent) 1.0 (Referent) 1.0 (Referent) Negative 178 (30.2) 113 (44.0) 1.9 (1.3 – 2.6) 1.9 (1.3 – 2.6) 1.7 (1.1 – 2.4) HER2 receptor § Negative 463 (91.7) 204 (84.0) 1.0 (Referent) 1.0 (Referent) 1.0 (Referent) Positive 42 (8.3) 39 (16.1) 2.1 (1.3 – 3.4) 2.2 (1.3 – 3.9) 1.9 (1.1 – 3.3) Subtype § Luminal A 412 (81.6) 153 (63.5) 1.0 (Referent) 1.0 (Referent) 1.0 (Referent) Luminal B 29 (5.7) 19 (7.9) 1.8 (1.0 – 3.2) 2.2 (1.1 – 4.3) 1.9 (1.0 – 3.9) HER2-enriched 13 (2.6) 20 (8.3) 4.1 (2.0 – 8.5) 3.8 (1.5 – 9.4) 2.7 (1.1 – 6.9) Triple-negative 40 (7.9) 41 (17.0) 2.8 (1.7 – 4.4) 2.9 (1.7 – 4.9) 2.7 (1.6 – 4.7) Unclassified 11 (2.2) 8 (3.3) 2.0 (0.8 – 5.0) 1.4 (0.4 – 4.4) 1.1 (0.3 – 3.8) * OR=odds ratio, CI=confidence interval. † Model 1: adjusted for age at diagnosis, age at first birth, family history, hormone therapy use, breast density, and BMI. ‡ Model 2: adjusted for age at diagnosis, age at first birth, family history, hormone therapy use, breast density, BMI, and vascular invasion. § Numbers in these categories do not sum to the total because of missing data.

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