Cohort Profile: The Breast Cancer Prospective Family Study Cohort (ProF-SC)

For breast cancer, like most other common diseases, having a family history of the disease is associated with an increased risk. There is large heterogeneity in absolute and relative breast cancer risks associated with family history, depending on the age of the woman, the age(s) at diagnosis of her affected relative(s) and the genetic relationship(s). Women with one affected first-degree relative are on average at 2-fold increased risk of breast cancer relative to women with no first-degree family history, and this increases to 4-fold for women with three or more affected first-degree relatives 1 . Under a multiplicative risk model, the underlying risk distribution must be highly skewed, and most women in the population are well below average risk; see Figure 1 , which illustrates the difference between women unselected for familial or genetic risk (blue line) and women enriched for familial/genetic risk (dotted red line). Given that epidemiological studies make inference about risk for the controls, almost all existing knowledge about risk factors is not relevant to ‘women at average risk’, but to women at lower than average risk. It is not known if this knowledge applies to women at increased, if not high, risk. To find evidence relevant to women across the full continuum of risk, with the potential for targeted risk modification and prevention, we have established and genetically-characterised a large prospective family-based cohort enriched for familial risk. Comparison of the theoretical distribution of familial risk profile (FRP) for women from the general population (blue line) and for those affected with either early-onset breast cancer or unaffected but with a strong family history of breast cancer, equivalent to a 3-fold increased risk (dotted red line), under a multiplicative, multifactorial, polygenic model. For details see 18,47 . Over the past two decades, an increasing number of genetic risk factors have been identified. 2,3 Nevertheless, the majority of women with a family history of breast cancer, even those with a strong family history, do not have causal mutations in the known genes, and large genome-wide association studies (GWAS) and now next-generation sequencing efforts are identifying additional genetic risk factors. 4–10 Epidemiological evidence suggests that some environmental factors modify breast cancer risk for women with a family history. Most epidemiology studies, however, record only first-degree family history as a binary factor (e.g. 1,11,12 ), which does not capture the potential importance of disease in second-degree and more distant relatives, 13–15 and rarely take into account the importance of age at diagnosis of affected relatives. The few studies that do 16,17 suggest greater environmental and genetic heterogeneity in risk. One approach to studying gene-environment interactions is to consider a woman’s underlying familial risk profile (FRP), representing her inherent lifetime risk due to familial determinants. A woman’s FRP can be predicted from her multi-generational family history including the number of affected relatives and her relationship with each affected relative, their age(s) at diagnosis, and if known, her genetic risk status (including causal variants and markers associated with risk) and the genetic risk status of her relatives. It is not well recognised that there must be very large variation in FRP. Given the increased risks associated with having a family history, mathematical models predict that, as a group, women in the top 25% of FRP must be at least 20 times more likely to develop breast cancer than women in the bottom 25% of FRP. 18,19 Nevertheless, unlike matching on age to control for its strong effect on cancer risk, epidemiological studies rarely match well by design or analysis on FRP, even though cases and controls differ greatly by FRP, especially in the upper tail. Environmental and genetic effects may have different effects in women with increased FRP. Studies of such ‘gene-environment interactions’ for which controls are better matched to cases for FRP, and even for mutations in specific genes—either by design or by analyses that use good predictors of FRP—might be more informative, especially if both cases and controls are over-sampled for increased familial risk. They also have greater validity if they are prospective. 18,19 Few prospective studies of families exist. They include the Minnesota Breast Cancer Family Study (544 families), established in the 1950s, 20–23 and the USA-based Sisters Study (50 844 unaffected sisters of affected women aged 35–74 years). 24 Family-based cohorts are also important for novel behavioural, psychosocial and health care utilization research, such as attitudes and practices regarding screening and risk reduction, and for the translation of primary, secondary and tertiary prevention findings into clinical practice. 25–28 In the mid-1990s,when two major susceptibility genes, BRCA1 and BRCA2 , were discovered, the Breast Cancer Family Registry (BCFR), 29 and the Kathleen Cuningham Foundation Consortium for research into Familial Breast cancer (kConFab) 30 (in 2001 the kConFab FUP started 31 ) were established. Importantly, both the BCFR and the kConFab were designed from the outset so that they could generate cohorts from which data could be pooled; they used the same baseline questionnaire and have conducted regular active follow-up of families. In mid-2014, a systematic follow-up of both the BCFR and kConFab FUP was completed as part of an NIH-funded grant to study the following aims using a prospective family study cohort (ProF-SC) (CA159868): (i) estimate age-specific absolute risks of breast cancer; (ii) estimate relative risks associated with modifiable factors and test whether these associations vary by FRP; and (iii) develop and internally validate comprehensive clinical breast cancer risk assessment models for women across the spectrum of breast cancer risk. The ProF-SC includes all female participants in the BCFR or kConFab FUP who were enrolled before 30 June 2011 and completed a baseline questionnaire. A total of 31 640 women from 11 171 families, 11.4% of whom are Ashkenazi Jewish, completed the same baseline questionnaire. The BCFR recruited families from six sites; one in Australia, one in Canada and four in the USA. The Australian, Canadian and Northern Californian sites recruited population-based case families using cancer registries. kConFab and the Australian BCFR recruited cases unselected for family history, over-sampling for early age at diagnosis, whereas the other two population-based sites used a two-stage sampling scheme, over-sampling for early age at diagnosis and/or having a family history or other predictors of a genetic predisposition. The Northern California site over-sampled racial/ethnic minority families. The New York, Philadelphia, Utah, Canadian and Australian sites recruited multiple-case families through family cancer clinics and community outreach. kConFab recruited multi-generational, multiple-case families through cancer family clinics in Australia and New Zealand. 30,31 The eligibility criteria for recruitment of families evolved over time and were intended to maximise the number of living potentially high-risk women, including known BRCA1 and BRCA2 mutation carriers, whether or not they had been diagnosed with breast cancer. Although ascertainment issues sometimes require separate analyses of population-based and clinic-ascertained families for retrospective studies, for prospective studies all unaffected family members can be combined into a single cohort because all families are being followed using the same methods and their members have been studied using the same protocol at baseline. A family cohort is in contrast to conventional cohort studies in which the vast majority of incident cases do not have a family history, at least not for first- or second-degree relatives. A large proportion of the ProF-SC cohort was affected at baseline, which also facilitates studies on risk factors for subsequent primary breast cancer, including contralateral disease. Table 1 describes the baseline characteristics of ProF-SC, illustrating wide variation in demographics, family history and other risk factors. Table 2 summarises the distribution of the incident breast cancer cases diagnosed since baseline. There is a wide distribution in age at diagnosis, with cases diagnosed before age 50 years accounting for 34% in the sub-cohort of women unaffected at baseline and 28% in the sub-cohort of women affected at baseline, respectively. For both these sub-cohorts, a high proportion of incident cases have been confirmed through pathology records (78% and 71%, respectively) and a high proportion have DNA available (88% and 95%, respectively). Baseline characteristics of ProF-SC participants, by breast cancer status at baseline and by loss to follow-up a Includes refusals and not located. Baseline characteristics of ProF-SC participants, by breast cancer status at baseline and by loss to follow-up a Includes refusals and not located. Prospectively ascertained breast cancer cases among ProF-SC participants Prospectively ascertained breast cancer cases among ProF-SC participants The family-based design facilitates follow-up primarily through tracing and updates of vital status using multiple informants, thereby increasing the validity of the cohort’s data on outcomes and family cancer history. 32 Since baseline, there has been regular contact with families through BCFR and kConFab newsletters and websites. Vital and cancer statuses have been updated through phone interviews, mailed questionnaires, clinic visits and linkages to cancer registries. In addition, there have been systematic updates of risk factor and clinical outcomes data (see below for details). High participation at follow-up is a critical issue for the validity of cohort studies, and we have demonstrated that this can be achieved by using a family-based design with multiple contacts typically available for each cohort member. Of the 31 640 women in the cohort, after an average of 9 years of follow-up, 11% were no longer living, 5% no longer wished to participate in follow-up and 14% have been lost to follow-up. Table 1 shows that baseline characteristics are similar for those lost to follow-up or no longer participating in active follow-up and those who have remained active. For those lost to follow-up and/or who dropped out of active follow-up, we have information on vital status, including cancer history, for 63% from their participating relatives. For all ProF-SC members, the BCFR and kConFab have collected detailed family history, demographic and risk factor data and biospecimens, regardless of their breast cancer history. For all women with breast cancer, pathology records, archived tumour tissue and self-reported information on cancer treatment have been sought ( Table 3 ). Overview of measurements made for ProF-SC participants Baseline Annual follow-up 10-year follow-up ProF-SC follow-up Baseline 10-year follow-up ProF-SC follow-up Every 3 years a Baseline Follow-up as new family mutations are identified At diagnosis After identified through personal or family report Linkage with cancer (Australia, California, Canada) and national death registries Pathology report; pathology material Treatment questionnaire Linkage with cancer registries and linkage with National Death Index Baseline Annual follow-up 10-year follow-up ProF-SC follow-up Baseline 10-year follow-up ProF-SC follow-up Every 3 years a Baseline Follow-up as new family mutations are identified At diagnosis After identified through personal or family report Linkage with cancer (Australia, California, Canada) and national death registries Pathology report; pathology material Treatment questionnaire Linkage with cancer registries and linkage with National Death Index a kConFab FUP only. Overview of measurements made for ProF-SC participants Baseline Annual follow-up 10-year follow-up ProF-SC follow-up Baseline 10-year follow-up ProF-SC follow-up Every 3 years a Baseline Follow-up as new family mutations are identified At diagnosis After identified through personal or family report Linkage with cancer (Australia, California, Canada) and national death registries Pathology report; pathology material Treatment questionnaire Linkage with cancer registries and linkage with National Death Index Baseline Annual follow-up 10-year follow-up ProF-SC follow-up Baseline 10-year follow-up ProF-SC follow-up Every 3 years a Baseline Follow-up as new family mutations are identified At diagnosis After identified through personal or family report Linkage with cancer (Australia, California, Canada) and national death registries Pathology report; pathology material Treatment questionnaire Linkage with cancer registries and linkage with National Death Index a kConFab FUP only. Pedigree information includes age at diagnosis of all cancers (except non-melanoma skin cancer) and deaths for first- and second-degree relatives of all participants (not just probands). This provides the most comprehensive description of family history of any epidemiological breast cancer study. The BCFR and kConFab used the same baseline questionnaire to collect data on menstrual and reproductive history, medical history and behavioral factors. The BCFR conducted a systematic follow-up beginning in 2007, and collected updated information on personal and family history of cancer, breast and ovarian surgeries and breast cancer risk factors collected at baseline. New items of interest were added, including screening behaviours such as use of magnetic resonance imaging (MRI), use of non-steroidal anti-inflammatory drugs (NSAIDs) and knowledge and understanding of genetic test results. The most recent systematic follow-up of the BCFR, conducted in 2011–14, updated some risk factor data in addition to family history and pedigree information. kConFab FUP surveyed participants every 3 years, using questionnaires that cover the same content as the BCFR follow-up questionnaires, with the exception of diagnostic radiation. At baseline, depending on relationship to the proband, most women were asked by the BCFR and kConFab to provide either a blood or a buccal sample. As a result, for 83% of ProF-SC there are banked DNA and plasma samples, and for an additional 2% there is DNA from buccal samples. There are no major differences between women who gave blood and those who did not with regard to the characteristics in Table 1 (data not shown). Screening for germline BRCA1 and BRCA2 mutations and other known or putative susceptibility variations in other genes has been undertaken by the BCFR and kConFab, as previously described. 29,33,34 The cohort includes 1508 (844 BRCA1 , 658 BRCA 2, 6 both BRCA1 and BRCA2 ) female carriers from the BCFR, and 1233 (670 BRCA1 , 561 BRCA2, 2 both BRCA1 and BRCA2 ) female carriers from kConFab. We have collected pathology reports for 74% of prospectively ascertained (incident) cases to date. The BCFR collected self-reported treatment data using a validated questionnaire addressing stage and the type of initial breast cancer treatments (surgery, radiation treatment, endocrine treatment and chemotherapy). 35,36 The Australian, Canadian and Utah sites of the BCFR regularly link to population-based cancer registries to validate cancers reported during follow-up. Linkage to death registries in Australia and Canada has been used to update vital status and related information (date and cause of death) as well as the National Death Index for the USA-based sites. To empirically evaluate the differences in breast cancer risk estimates from different constructs of family history, we compared standard ways of defining family history with estimates using full family history pedigrees ( Table 4 ). For the more than 18 000 women unaffected at baseline, we compared family history as typically defined by cohort studies [any affected first-degree relative(s); yes/no] with that of the number of affected first-degree relatives, and with the more comprehensive family history measure of FRP based on the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) 47 model (10-year predicted risk). We fitted an age-adjusted proportional hazards model and found that all measures predicted risk. As we compare binary categorical, ordered categorical and continuous constructs of family history, the χ 2 statistics (based on the change in log likelihood which allows comparisons across constructs) showed that the BOADICEA score was clearly the best predictor of risk (χ 2 = 523 for BOADICEA vs χ 2 = 18 for ever/never family history) in that it captures more information on risk. After fitting the BOADICEA score, the strengths of the associations with the other two predictors were approximately halved, whereas the association with the BOADICEA score was virtually unchanged. Therefore, there is also scope for the BOADICEA model to be improved as a measure of FRP. Associations of family history measures as predictors of age-adjusted breast cancer incidence for the sub-cohort of 17 403 women in ProF-SC who were unaffected at baseline a Each row represents a separate age-adjusted model; rows 4 and 5 report models in which two constructs of family history are simultaneously fitted. Associations of family history measures as predictors of age-adjusted breast cancer incidence for the sub-cohort of 17 403 women in ProF-SC who were unaffected at baseline a Each row represents a separate age-adjusted model; rows 4 and 5 report models in which two constructs of family history are simultaneously fitted. Figure 2 shows the predicted remaining lifetime risk based on BOADICEA for the sub-cohort of women unaffected at baseline. This illustrates the large range in risk and therefore why ProF-SC can be used to develop risk models which consider modification of risk by underlying FRP for women across the risk continuum. Remaining lifetime risks according to BOADICEA based on baseline characteristics, including family history, for the sub-cohort of 17 403 women in ProF-SC who were unaffected at baseline. These results suggest that the range of risk across Prof-SC participants is large, which will be essential for prospectively validating many of the retrospective findings from our families, including the importance of biomarkers that change over the life course (such as DNA repair phenotype, telomere length, oxidative stress and DNA methylation markers) in high-risk women. 37,38 We have also investigated environmental modifiers of risk for carriers of BRCA1 and BRCA2 mutations using retrospective data, and found a positive association with smoking 39 but no association with alcohol intake, 40 oral contraceptive use 41,42 or medical diagnostic radiation. 43 These studies suggest that it might be misleading to extrapolate findings about cancer risk factors from studying the general population to BRCA1 and BRCA2 mutation carriers or other sub-populations of women at increased familial/genetic risk. We are currently working to prospectively validate these finding using ProF-SC, with the aim of identifying modifiable risk factors for women across the full spectrum of risk. 44 A key goal of ProF-SC is to validate and extend risk assessment models that predict breast cancer risk and are used in clinics and elsewhere. Most models, such as the BCRAT or Gail model, 45 have been developed for average risk populations and do not incorporate extensive data on family history of breast cancer or BRCA1 and BRCA2 mutation status. Exceptions are the International Breast Cancer Intervention Study (IBIS, or the Tyrer-Cuzick model) 46 and the BOADICEA. 47 Using data from the New York site of the BCFR, we have observed large discordances across models, 48,50 for example predictions from the model were to the observed number of than predictions using BCRAT even for the women to be at average risk (e.g. those with no family history and no BRCA1 or BRCA2 Using data from the Australian site of the BCFR, we have that BOADICEA is well and has good and at the As a family-based cohort over-sampled for increased familial risk has many strengths (i) on so that be and/or for a in to have the same as a cohort unselected for risk; (ii) the cohort a large range of risk; (iii) to environmental and genetic modifiers of risk for women at than average risk; and better through having multiple family a however, family studies can be because additional of protocol and to be also has to be to that information is not to other family These however, can be through study and and we that the of a family cohort its and that this design be research on environmental modifiers across the risk For information on to with the ProF-SC cohort in use of the data and and also with the BCFR, see For to kConFab see in a ProF-SC is a prospective cohort study of 31 640 women from 11 171 families ascertained through population-based and sampling and who cover the full spectrum of familial risk. The study is designed to use pedigree and genetic data to predict the underlying familial risk profile (FRP) of each and if risk associations differ according to FRP, thereby targeted risk modification and in and families were from the Canada and At baseline this cohort of women over the age of 18 years 18 unaffected and affected with breast cancer, of whom are BRCA1 or BRCA2 mutation The most recent follow-up was completed in and family cancer from multiple 5% have and 14% were lost to follow-up. Over on average 9 years, we have identified and women with incident breast cancers among those at baseline who were unaffected and respectively. cancer family were sought from all participants who were the same baseline epidemiology questionnaire. have been collected from and 2% have DNA available through buccal samples, of participants and used for extensive genetic For with the ProF-SC cohort, see and This was by an from and from the National Cancer The content of this does not the or of the National Cancer or any of the in the BCFR, does of or by the or the is an Australian National Breast Cancer Foundation kConFab is by from the National Breast Cancer the National and and the Cancer the Cancer of New and Australia, and the Cancer Foundation of is an the and in at and the of We like to the of the ProF-SC data and and and We also like to other who have been in the analyses and/or the cohorts and We the kConFab research and the and of the Australian and New Family Cancer and the kConFab for the and the follow-up and and especially the many families enrolled in the BCFR and kConFab. of

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