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Figure 1.
Assembly of Analysis Cohorts
Assembly of Analysis Cohorts

aAfter exclusion of women in the preceding categories.

Figure 2.
Estimated Cumulative Risks of Breast and Ovarian Cancer in Mutation Carriers
Estimated Cumulative Risks of Breast and Ovarian Cancer in Mutation Carriers

Kaplan-Meier estimates of cumulative risks of breast and ovarian cancers. In the breast cancer analysis, women were censored at risk-reducing bilateral mastectomy. In the ovarian cancer analysis, women were censored for risk-reducing salpingo-oophorectomy. Number at risk indicates the number of women who remained at risk at the end of the 10-year age category (eg, in panel A, there were 138 women with BRCA1 mutations still at risk of breast cancer at the end of the age 50-60 years period). The earliest follow-up started at age 18 years.

Table 1.  
Numbers of Mutation Carriers and Incident Cancers Per Study Group Eligible for Each of the Analyses and Other Summary Statistics
Numbers of Mutation Carriers and Incident Cancers Per Study Group Eligible for Each of the Analyses and Other Summary Statistics
Table 2.  
Breast and Ovarian Cancer Incidence Rates Per 1000 Person-Years, Kaplan-Meier Estimates of the Cumulative Risks, and Standardized Incidence Rates by 10-Year Age Groups
Breast and Ovarian Cancer Incidence Rates Per 1000 Person-Years, Kaplan-Meier Estimates of the Cumulative Risks, and Standardized Incidence Rates by 10-Year Age Groups
Table 3.  
Contralateral Breast Cancer Incidence Rates Per 1000 Person-Years and Kaplan-Meier Estimates of the Cumulative Risks of Contralateral Breast Cancer by Time Since First Breast Cancer, Overall and Stratified by Age at First Breast Cancer
Contralateral Breast Cancer Incidence Rates Per 1000 Person-Years and Kaplan-Meier Estimates of the Cumulative Risks of Contralateral Breast Cancer by Time Since First Breast Cancer, Overall and Stratified by Age at First Breast Cancer
Table 4.  
Hazard Ratio Estimates for Breast and Ovarian Cancer Associated With Family History of Breast or Ovarian Cancer in First- and Second-Degree Relatives and Corresponding Cumulative Risk Estimates
Hazard Ratio Estimates for Breast and Ovarian Cancer Associated With Family History of Breast or Ovarian Cancer in First- and Second-Degree Relatives and Corresponding Cumulative Risk Estimates
Table 5.  
Hazard Ratio Estimates for Breast and Ovarian Cancer Associated With Mutation Location and Corresponding Cumulative Risk Estimates
Hazard Ratio Estimates for Breast and Ovarian Cancer Associated With Mutation Location and Corresponding Cumulative Risk Estimates
Supplement.

eAppendix. Supplementary Methods and Results

eFigure 1. Estimated cumulative risk of breast cancer in mutation carriers with censoring at oophorectomy

eFigure 2. Study-specific breast and ovarian cancer standardised incidence rate estimates (with associated 95% confidence intervals)

eFigure 3. Estimated cumulative risks of breast and ovarian cancer in mutation carriers, by breast and ovarian cancer family history (FH)

eFigure 4. Estimated cumulative risks of breast and ovarian cancer in mutation carriers, by mutation location

eFigure 5. Age-specific breast cancer incidence estimates (with associated 95% confidence intervals) by year of birth (breast cancer analysis cohort)

eTable 1. Number of samples from each study

eTable 2. Completeness of follow-up and sources of information for censoring endpoints, for the samples included in the breast cancer analysis

eTable 3. Breast cancer incidence rates per 1000 person-years, Kaplan-Meier estimates of the cumulative risks and Standardised Incidence Rates when censoring for risk-reducing salpingo-oophorectomy, by 10-year age groups

eTable 4. Breast cancer incidence rates per 1000 person-years and Kaplan-Meier estimates of the cumulative risks, considering only invasive breast cancer

eTable 5. Breast cancer incidence rates per 1000 person-years and Kaplan-Meier estimates of the cumulative risks, by 10-year age groups, by study groupings

eTable 6. Breast cancer incidence rates per 1000 person-years and Kaplan-Meier estimates of the cumulative risks, by 10-year age groups, by study ascertainment type: family clinic vs population-based studies

eTable 7. Contralateral breast cancer incidence rates per 1000 person-years and Kaplan-Meier estimates of the cumulative risks, by 10-year age groups, overall and stratified by age at unilateral breast cancer (UBC)

eTable 8. Contralateral breast cancer incidence rates per 1000 person-years and Kaplan-Meier estimates of the cumulative risks when censoring for risk-reducing Salpingo-oophorectomy, by 10-year age groups and time since first breast cancer diagnosis

eTable 9. Hazard Ratio estimates for breast and ovarian cancer associated with family history of breast or ovarian cancer in first degree relatives

eTable 10. Hazard Ratio estimates for breast cancer associated with family history of breast cancer in first and second degree relatives, stratified by presence of ovarian cancer family history

eTable 11. Hazard Ratio estimates for ovarian cancer associated with family history of ovarian cancer in first and second degree relatives, stratified by presence of breast cancer family history

eTable 12. Hazard Ratio estimates for breast cancer associated with family history of ovarian cancer in first and second degree relatives, stratified by presence of breast cancer family history

eTable 13. Hazard Ratio estimates for ovarian cancer associated with family history of breast cancer in first and second degree relatives, stratified by presence of ovarian cancer family history

eTable 14. Sensitivity analyses: hazard ratio estimates for breast cancer associated with mutation location, adjusted for family history of breast cancer in first and second degree relatives or by excluding the Ashkenazi mutations (BRCA1: c.68_69delAG and c.5266dupC; BRCA2: c.5946delT)

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Original Investigation
June 20, 2017

Risks of Breast, Ovarian, and Contralateral Breast Cancer for BRCA1 and BRCA2 Mutation Carriers

Author Affiliations
  • 1Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, England
  • 2Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, England
  • 3Centre for Epidemiology and Biostatistics, Melbourne School of Population Health, University of Melbourne, Melbourne, Australia
  • 4Division of Cancer Medicine, Peter MacCallum Cancer Centre, Melbourne, Australia
  • 5Department of Medicine, St Vincent’s Hospital, University of Melbourne, Parkville, Australia
  • 6Sir Peter MacCallum Department of Oncology, University of Melbourne, Parkville, Australia
  • 7Department of Epidemiology, Netherlands Cancer Institute, Amsterdam, the Netherlands
  • 8Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands
  • 9Mathematics Institute, University of Warwick, Coventry, England
  • 10Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, Australia
  • 11Inserm U900, Paris, France
  • 12Institut Curie, Paris, France
  • 13Mines ParisTech, Fontainebleau, France
  • 14PSL Research University, Paris, France
  • 15Department of Dermatology, University of Utah School of Medicine, Salt Lake City, Utah
  • 16Department of Epidemiology, Columbia University, New York, New York
JAMA. 2017;317(23):2402-2416. doi:10.1001/jama.2017.7112
Key Points

Question  What are the breast and ovarian cancer risks for BRCA1 and BRCA2 mutation carriers and are they related to family history of cancer and mutation position?

Findings  From a prospective cohort of 9856 mutation carriers, mainly ascertained through cancer genetic clinics, the cumulative breast cancer risk to age 80 years was 72% for BRCA1 and 69% for BRCA2 carriers. The cumulative ovarian cancer risk to age 80 years was 44% for BRCA1 and 17% for BRCA2 carriers. Cancer risks differed by cancer family history and mutation position.

Meaning  These findings provide cancer risk patterns based on BRCA status using prospective data. Family history and mutation position are important additional variables in risk assessment.

Abstract

Importance  The clinical management of BRCA1 and BRCA2 mutation carriers requires accurate, prospective cancer risk estimates.

Objectives  To estimate age-specific risks of breast, ovarian, and contralateral breast cancer for mutation carriers and to evaluate risk modification by family cancer history and mutation location.

Design, Setting, and Participants  Prospective cohort study of 6036 BRCA1 and 3820 BRCA2 female carriers (5046 unaffected and 4810 with breast or ovarian cancer or both at baseline) recruited in 1997-2011 through the International BRCA1/2 Carrier Cohort Study, the Breast Cancer Family Registry and the Kathleen Cuningham Foundation Consortium for Research into Familial Breast Cancer, with ascertainment through family clinics (94%) and population-based studies (6%). The majority were from large national studies in the United Kingdom (EMBRACE), the Netherlands (HEBON), and France (GENEPSO). Follow-up ended December 2013; median follow-up was 5 years.

Exposures  BRCA1/2 mutations, family cancer history, and mutation location.

Main Outcomes and Measures  Annual incidences, standardized incidence ratios, and cumulative risks of breast, ovarian, and contralateral breast cancer.

Results  Among 3886 women (median age, 38 years; interquartile range [IQR], 30-46 years) eligible for the breast cancer analysis, 5066 women (median age, 38 years; IQR, 31-47 years) eligible for the ovarian cancer analysis, and 2213 women (median age, 47 years; IQR, 40-55 years) eligible for the contralateral breast cancer analysis, 426 were diagnosed with breast cancer, 109 with ovarian cancer, and 245 with contralateral breast cancer during follow-up. The cumulative breast cancer risk to age 80 years was 72% (95% CI, 65%-79%) for BRCA1 and 69% (95% CI, 61%-77%) for BRCA2 carriers. Breast cancer incidences increased rapidly in early adulthood until ages 30 to 40 years for BRCA1 and until ages 40 to 50 years for BRCA2 carriers, then remained at a similar, constant incidence (20-30 per 1000 person-years) until age 80 years. The cumulative ovarian cancer risk to age 80 years was 44% (95% CI, 36%-53%) for BRCA1 and 17% (95% CI, 11%-25%) for BRCA2 carriers. For contralateral breast cancer, the cumulative risk 20 years after breast cancer diagnosis was 40% (95% CI, 35%-45%) for BRCA1 and 26% (95% CI, 20%-33%) for BRCA2 carriers (hazard ratio [HR] for comparing BRCA2 vs BRCA1, 0.62; 95% CI, 0.47-0.82; P=.001 for difference). Breast cancer risk increased with increasing number of first- and second-degree relatives diagnosed as having breast cancer for both BRCA1 (HR for ≥2 vs 0 affected relatives, 1.99; 95% CI, 1.41-2.82; P<.001 for trend) and BRCA2 carriers (HR, 1.91; 95% CI, 1.08-3.37; P=.02 for trend). Breast cancer risk was higher if mutations were located outside vs within the regions bounded by positions c.2282-c.4071 in BRCA1 (HR, 1.46; 95% CI, 1.11-1.93; P=.007) and c.2831-c.6401 in BRCA2 (HR, 1.93; 95% CI, 1.36-2.74; P<.001).

Conclusions and Relevance  These findings provide estimates of cancer risk based on BRCA1 and BRCA2 mutation carrier status using prospective data collection and demonstrate the potential importance of family history and mutation location in risk assessment.

Introduction

The optimal clinical management of women with BRCA1 and BRCA2 mutations depends on accurate age-specific cancer risk estimates. These can be used to estimate the absolute risk reduction from preventive strategies and to inform decisions about the age at which to commence cancer screening.1

Based on retrospective studies,2-11 cumulative breast cancer risk estimates to age 70 years range from 40% to 87% for BRCA1 and from 27% to 84% for BRCA2 carriers. The corresponding ovarian cancer risks vary from 16% to 68% for BRCA1 and from 11% to 30% for BRCA2 carriers. Risk estimates from these studies had wide confidence intervals. Differences in sampling (population-based/high-risk families), population and mutation characteristics, analytic methods, and other genetic and lifestyle/hormonal factors are possible explanations for the variation in risk estimates.12

Because BRCA1 and BRCA2 mutations are rare in the population, most retrospective penetrance estimates have been derived from family-based studies. Typically, mutation screening has been performed among affected women, selected on the basis of young age at diagnosis or cancer family history. Cancer risks are then estimated using the known or inferred genotypes of the relatives. Estimates from such retrospective, family-based studies are prone to bias if analyses are not correctly adjusted for the ascertainment process or if there are inaccuracies in family history.

Prospective cohort studies, in which mutation carriers are recruited on the basis of their mutation status and followed over time, may avoid these issues. Because the precision of risk estimates depends on the number of prospective incident cancers, a very large sample with long follow-up is required. Prospective penetrance estimates have been based on small samples (<64 breast cancers, 31 ovarian cancers) and are imprecise.13-15 The purpose of this study was to estimate age-specific risks of breast, ovarian, and contralateral breast cancer using data from a large prospective cohort.

Methods
Participants

We used prospective cohort data on carriers of pathogenic BRCA1 and BRCA2 mutations recruited through 3 consortia, the International BRCA1/2 Carrier Cohort Study (IBCCS), the Breast Cancer Family Registry (BCFR), and the Kathleen Cuningham Foundation Consortium for Research Into Familial Breast Cancer (kConFab) (eAppendix in the Supplement). All centers in these consortia obtained written informed consent from study participants and local ethical review committees approved protocols.

Briefly, for the IBCCS, data were available from 7666 female carriers recruited between 1997 and 2011 from 18 European cancer genetics centers and the Quebec province of Canada. The majority were from large national studies in the United Kingdom, the Netherlands, and France. All centers conducted active follow-up through questionnaires. In addition to the active follow-up in all studies, passive follow-up through linkage with cancer, pathology, and death registries was obtained in countries where this is available (cancer/death registries in Denmark, the Netherlands, Sweden, and the United Kingdom; pathology registries to collect information on preventive surgeries in Denmark and the Netherlands), together with medical record validation of self-reported cancer diagnoses and preventive surgeries.

The BCFR is a family cohort that includes data on 1570 mutation carriers recruited from 6 sites in Australia, Canada, and the United States. Families were followed up regularly through annual approaches to probands and 5-year systematic follow-up of families collecting epidemiological and demographic data from all participants.

The kConFab study included 620 mutation carriers from multiple-case families ascertained through family cancer clinics in Australia and New Zealand since 1997. Participants were systematically followed up using a questionnaire mailed every 3 years.

The end of follow-up was December 2013.

Eligibility and Censoring

For each of the 3 analyses (breast cancer risk, contralateral breast cancer risk, and ovarian cancer risk), we defined a different group eligible at baseline (Figure 1). Age at baseline was defined as age at study recruitment or age at the genetic test, whichever was more recent.

Breast Cancer Risk

Women were included in the estimation of first breast cancer risk if at completion of the baseline questionnaire they had not been diagnosed as having any cancer (excluding nonmelanoma skin cancer) nor undergone risk-reducing bilateral mastectomy (with mastectomy: n = 304 BRCA1; n = 148 BRCA2) (eAppendix in the Supplement). Women were followed up from baseline until the first of the following: age 80 years; death; completion of last follow-up questionnaire or last record linkage (if conducted), whichever happened last; risk-reducing bilateral mastectomy; or diagnosis of any first cancer (excluding nonmelanoma skin cancer). Women diagnosed as having breast cancer (invasive or noninvasive [ductal carcinoma in situ]) during follow-up were considered as affected. Because information on cancers was partly self reported, tumor phenotype–specific data were not available other than for invasiveness. Therefore, all types of breast cancer were included in the analysis. Additional analyses were performed in which (1) affected women were considered to be only those diagnosed as having invasive disease and (2) women were censored at the age of risk-reducing salpingo-oophorectomy (eAppendix).

Ovarian Cancer Risk

Women were included in the ovarian cancer analysis if at baseline they had not been diagnosed as having ovarian cancer nor undergone risk-reducing salpingo-oophorectomy (with oophorectomy: n = 1808 BRCA1; n = 969 BRCA2). Women with a history of breast or nonmelanoma skin cancer were included in the analysis but women with other cancers were not. Women were followed up from baseline until the first of the following: age 80 years; death; completion of last follow-up questionnaire or last record linkage (whichever happened last); risk-reducing salpingo-oophorectomy (or salpingectomy or removal of ovaries for other reasons); or any cancer diagnosis (excluding breast and nonmelanoma skin cancer). Only women diagnosed as having invasive ovarian (or fallopian tube or peritoneal) cancer during follow-up were considered affected.

Contralateral Breast Cancer Risk

Women were included in the contralateral breast cancer analysis if they were diagnosed as having a first breast cancer before the date of their last follow-up questionnaire (or record linkage) and had not been diagnosed as having any other cancer (including contralateral breast cancer) nor undergone risk-reducing bilateral mastectomy before study entry. Only asynchronous contralateral breast cancer was considered, for which there had to be an interval of at least 1 year between first and second breast cancers. Eligible women entered follow-up at their baseline questionnaire date or 1 year after their first breast cancer diagnosis date (whichever was later) and were followed up until the first of the following: age 80 years; death; date at last follow-up; risk-reducing bilateral mastectomy; or any cancer. Women diagnosed as having asynchronous contralateral breast cancer during follow-up were assumed to be affected.

Statistical Analysis

Annual incidences of breast, ovarian, and contralateral breast cancer per 1000 person-years were estimated for 10-year age intervals using standard cohort analysis. Kaplan-Meier analysis was used to estimate cumulative risks. Standardized incidence ratios (SIRs) for breast and ovarian cancer relative to population-specific incidences were also estimated (eAppendix in the Supplement).

We used Cox-regression to compare cancer risks for BRCA1 mutation carriers with risks for BRCA2 carriers across all age groups and by attained age. To test for heterogeneity by country, we carried out Cox regression estimating hazard ratios (HRs) for each country (n=6) compared with the baseline (United Kingdom); a χ2 (n − 1) degree-of-freedom test was carried out on the estimated HRs to test for heterogeneity. The contralateral breast cancer analysis was stratified by age at first breast cancer (<40 years, 40-49 years, or ≥50 years) and Cox regression was used to compare risks between age groups. We evaluated cancer risks by extent of self-reported family history of breast or ovarian cancer separately (eAppendix in the Supplement). Women were classified by the number of cancers in first- or second-degree relatives (0, 1, or ≥2). Separate categories for women with cancers of unknown type among relatives and for those with unknown family history (missing data) were defined, and separate HRs were estimated for these categories. A test for trend was performed using Cox regression by including a continuous variable in the model representing the number of breast or ovarian cancers in female first- or second-degree relatives (taking values of 0, 1, 2, 3, etc). Separate variables were derived for the number of breast cancers and number of ovarian cancers in relatives. We also evaluated differences in breast and ovarian cancer by mutation position (based on base-pair location) using Cox regression. Mutations were grouped into regions based on differences in breast and ovarian cancer risks previously reported in retrospective studies.16-18 Mutations in BRCA1 were grouped into 3 regions (5′ to c.2281, c.2282 to c.4071, c.4072 to 3′). For BRCA2, mutations were grouped in 3 regions using both the narrow and broad definitions of the ovarian cancer cluster region16 (OCCR; broad definition: 5′ to c.2830, c.2831 to c.6401, c.6402 to 3′; narrow definition: 5′ to c.3846, c.3847 to c.6275, c.6276 to 3′; see eAppendix). For all analyses, a robust variance approach that clustered observations on family membership was used to adjust standard errors for the fact that the cohort included multiple women from the same family.19 Analyses were stratified by country (United Kingdom, France, the Netherlands, Australia, United States, or other) and birth cohort (before 1940, 1940-1949, 1950-1959, 1960-1969, 1970-1979, or 1980 or later). Proportionality was evaluated using Schoenfeld residuals, which was met for all analyses. Analyses were carried out in Stata version 13 (Stata Corp). Statistical tests were considered significant based on 2-sided hypothesis tests with P < .05.

Results

A total of 9856 participants including 6036 BRCA1 and 3820 BRCA2 mutation carriers were available at baseline. The majority of women were ascertained through family clinics (94%), and the remainder (6%) were recruited from studies that used population-based ascertainment. Figure 1 and eTable 1 in the Supplement summarize the baseline cohort study sample (N = 9856) and the assembly of the eligible prospective cohorts for each analysis. Table 1 summarizes the characteristics of the eligible women included in the prospective analyses. Information on follow-up completeness is summarized in eTable 2 in the Supplement. All studies conducted active follow-up with questionnaires, but the mean interval between questionnaires varied across studies (1.6 to 8.7 years) (eTable 2). In addition, in countries with registry information, active follow-up was complemented with passive follow-up through record linkage. On average, 7% of women in the cohort were lost to follow-up, but this varied among studies (0% to 13%) (eTable 2).

The breast cancer analysis was based on 3886 eligible BRCA1 and BRCA2 mutation carriers (median age at study entry, 38 years; interquartile range [IQR], 30-46 years). The ovarian cancer analysis was based on data from 5066 women (median age at study entry, 38 years; IQR, 31-47 years) and the contralateral breast cancer analysis was based on 2213 women (median age at start of follow-up, 47 years; IQR, 40-55 years). During follow-up, among the eligible women, 426 were diagnosed as having breast cancer (483 censored for risk-reducing bilateral mastectomy), 109 were diagnosed as having ovarian cancer (1508 censored for risk-reducing salpingo-oophorectomy), and 245 were diagnosed as having asynchronous contralateral breast cancer. The age-specific cancer incidences, SIRs, and cumulative risks are shown in Table 2.

Breast Cancer Risks

For BRCA1 carriers, the breast cancer incidences per decade of age increased from 21 to 30 years to 31 to 40 years but then remained at 23.5 to 28.3 per 1000 person-years for ages 31 to 70 years (P = .97 for trend). The peak incidence occurred in the 41- to 50-year age group (28.3 [95% CI, 23.1-34.7] per 1000 person-years). A similar pattern was seen for BRCA2 carriers, with peak incidence in the 51- to 60-year age group (30.6 [95% CI, 22.8-41.1] per 1000 person-years) and incidences of 21.9 to 30.6 per 1000 person-years across ages 41 to 80 years (P = .57 for trend). The estimated SIRs decreased with increasing age in both BRCA1 carriers (P<.001 for trend) and BRCA2 carriers (P<.001 for trend). The cumulative risk of breast cancer by age 80 years was 72% (95% CI, 65%-79%) for BRCA1 carriers and 69% (95% CI, 61%-77%) for BRCA2 carriers (Figure 2). While the cumulative risks for BRCA1 and BRCA2 carriers to age 80 years were similar, the cumulative risks to age 50 years were higher for BRCA1 carriers (P = .03).

The cumulative risk estimates for breast cancer by age 80 years when censoring at risk-reducing salpingo-oophorectomy were 70% (95% CI, 60%-80%) for BRCA1 carriers and 75% (95% CI, 67%-83%) for BRCA2 carriers (eTable 3 and eFigure 1 in the Supplement). From an analysis that excluded known in situ breast cancers, the corresponding risk estimates were 68% (95% CI, 60%-76%) for BRCA1 carriers and 63% (95% CI, 54%-72%) for BRCA2 carriers (eTable 4 in the Supplement).

There were no significant differences in the estimated breast cancer incidences by country for either BRCA1 carriers (P = .32 for heterogeneity) or BRCA2 carriers (P = .43 for heterogeneity) (eTable 5 and eFigure 2 in the Supplement). The estimated breast cancer risks were similar when analyses were carried out separately for women identified through family clinics and women who were relatives of mutation carriers identified through populationwide screening of breast cancer cases (eTable 6 in the Supplement).

Ovarian Cancer Risks

There was an increase in ovarian cancer incidence with age up to 61 to 70 years for both BRCA1 and BRCA2 carriers. The incidences were higher for BRCA1 carriers (HR comparing BRCA1 vs BRCA2, 3.6; 95% CI, 2.2-5.9; P < .001). The SIRs did not vary with age for either gene (BRCA1: overall SIR, 49.6 [95% CI, 40.0-61.5]; P = .86 for trend; BRCA2: 13.7 [95% CI, 9.1-20.7]; P = .23 for trend). The ovarian cancer cumulative risk to age 80 years was 44% (95% CI, 36%-53%) for BRCA1 carriers and 17% (95% CI, 11%-25%) for BRCA2 carriers (Table 2 and Figure 2).

Contralateral Breast Cancer Risks

The estimated incidence of contralateral breast cancer for BRCA1 carriers varied between 23 and 28 per 1000 person-years for the period up to 20 years after the first breast cancer diagnosis (Table 3; eTable 7 in the Supplement). The cumulative risk of contralateral breast cancer 20 years after the first breast cancer diagnosis was 40% (95% CI, 35%-45%). The HR for contralateral breast cancer declined with increasing age at the first breast cancer diagnosis (for women with first breast cancer at age 40-50 years, HR, 0.81 [95% CI, 0.58-1.12], and for women with first breast cancer at age >50 years, 0.71 [95% CI, 0.45-1.11], relative to women with first breast cancer at age <40 years).

For BRCA2 carriers, the estimated contralateral breast cancer incidence varied between 13 and 18 per 1000 person-years during the years after the first breast cancer diagnosis. The cumulative risk of contralateral breast cancer at 20 years after the first breast cancer diagnosis was 26% (95% CI, 20%-33%) and was lower than for BRCA1 carriers (HR comparing BRCA2 vs BRCA1 carriers, 0.62; 95% CI, 0.47-0.82; P = .001). The HR for contralateral breast cancer when first breast cancer diagnosis was between ages 40 and 50 years was 0.73 (95% CI, 0.41-1.26), and when the first breast cancer diagnosis was at age greater than 50 years, the HR was 0.76 (95% CI, 0.43-1.36) compared with a first breast cancer before age 40 years.

When women were censored at the age of risk-reducing salpingo-oophorectomy, the contralateral breast cancer risks at 20 years after the first breast cancer were 38% (95% CI, 31%-45%) for BRCA1 carriers and 34% (95% CI, 25%-45%) for BRCA2 carriers (eTable 8 in the Supplement).

To investigate potential survival bias, the analysis was repeated after excluding women whose first breast cancer diagnosis occurred more than 5 years prior to study recruitment. The estimated cumulative risk of contralateral breast cancer at 20 years after the first breast cancer diagnosis was 41% (95% CI, 32%-53%) for BRCA1 and 21% (95% CI, 15%-50%) for BRCA2 carriers.

Breast and Ovarian Cancer Risks by Family History

The estimated cumulative breast and ovarian cancer risks by family history are shown in Table 4 and eFigure 3 in the Supplement. Breast cancer risk estimates for both BRCA1 and BRCA2 carriers increased with the number of first- and second-degree relatives diagnosed as having breast cancer (P<.001 for trend for BRCA1; P=.02 for BRCA2) (Table 4). For women with 2 or more first- or second-degree relatives diagnosed as having breast cancer compared with those with no family history of breast cancer, the HR for breast cancer was 1.99 (95% CI, 1.41-2.82) for BRCA1 carriers (cumulative risk estimates to age 70 years: 73% [95% CI, 65%-80%] vs 53% [95% CI, 39%-69%]) and the HR for breast cancer was 1.91 (95% CI, 1.08-3.37) for BRCA2 carriers (cumulative risks to age 70 years: 65% [95% CI, 56%-74%] vs 39% [95% CI, 25%-56%]) (Table 4).

There was no significant difference in ovarian cancer risk for BRCA1 carriers with family history of ovarian cancer compared with those without (HR, 1.37; 95% CI, 0.89-2.11) (Table 4; eFigure 3 in the Supplement). A similar pattern was observed for BRCA2 carriers, but the number of events for women with ovarian cancer family history was small (n = 5). Results were similar when family history of cancer was restricted to first-degree relatives (eTable 9 in the Supplement) or when analyses were stratified by the presence of family history of breast or ovarian cancer (eTables 10-13 in the Supplement). For BRCA1 mutation carriers, the risk of breast cancer was lower for women with a family history of ovarian cancer compared with those with no family history of ovarian cancer (HR, 0.71 [95% CI, 0.51-0.99] in women with a family history of breast cancer; HR, 0.38 [95% CI, 0.21-0.70] in those without) (eTable 12).

Breast and Ovarian Cancer Risks by Mutation Position

BRCA1 mutations located outside the region bounded by positions c.2282 to c.4071 were associated with a significantly higher breast cancer risk compared with mutations within the region (HR, 1.46; 95% CI, 1.11-1.93; P = .007) (Table 5; eFigure 4 in the Supplement), but there was no significant difference in ovarian cancer risk. There was no significant difference in the breast or ovarian cancer risks for either the BRCA1 c.68_69delAG or c.5266dupC mutations compared with BRCA1 mutations in the same region (Table 5). BRCA2 mutations outside the OCCR were associated with a significantly higher breast cancer risk compared with mutations within the OCCR (based on the narrow OCCR definition: HR, 1.70 [95% CI, 1.18-2.46]; P = .005; based on the broad OCCR definition: HR, 1.93 [95% CI, 1.36-2.74]; P < .001) (Table 5), but there was no significant difference in ovarian cancer risk. There was no significant difference in breast cancer risk for BRCA2 c.5946delT mutation carriers compared with other OCCR BRCA2 mutations (HR, 0.73; 95% CI, 0.35-1.54; P = .41). The associations by mutation position remained significant after adjusting for family history of breast cancer and after excluding carriers of the BRCA2 c.5946delT mutation from the OCCR (eTable 14 in the Supplement).

Discussion

This study estimated age-specific risks of breast, ovarian, and contralateral breast cancer for BRCA1 and BRCA2 mutation carriers using data from a prospective cohort. Because the study mainly included unaffected women identified by mutation screening based on cancer family history, early age at onset of a family member, or both, the overall estimates are relevant to mutation carriers identified through clinical testing. However, the wide range of family histories represented allowed an examination of the relationship between family history and cancer risk. The results indicate that family history is a strong risk factor for mutation carriers and that cancer risks vary by mutation location, suggesting that individualized counseling should incorporate both family history profiles and mutation location.

The cumulative risk of developing breast cancer by age 80 years was 72% for BRCA1 mutation carriers and 69% for BRCA2 mutation carriers, respectively. For ovarian cancer, the cumulative risks by age 80 years were 44% for BRCA1 carriers and 17% for BRCA2 carriers. Breast cancer incidence for carriers increased rapidly with age in early adulthood then plateaued to remain relatively constant throughout the remaining lifetime. The age at which this plateau was reached was 31 to 40 years for BRCA1 carriers and 5 to 10 years later for BRCA2 carriers. The incidence during the plateau was similar for both groups of mutation carriers. This is consistent with the model for genetic risk of breast cancer based on twin data,20 in which the age-specific incidence for genetically susceptible women increases to a high constant level by a predetermined age that varies among families.

The estimated breast and ovarian cancer risks were consistent with findings from retrospective family-based studies.2,3,6,10 The breast cancer SIRs decreased with increasing age for both BRCA1 and BRCA2 carriers, but the estimates were higher than those previously reported for younger age groups.2,21 From this prospective study, the estimated cumulative risks of ovarian cancer were low up to age 40 years for BRCA1 mutation carriers and up to age 50 years for BRCA2 mutation carriers.

This study was limited in the extent to which differences by birth cohort could be assessed because birth cohort was strongly associated with age. For age intervals with sufficient observations, there was no evidence of risk differences by birth cohort (eFigure 5 in the Supplement).

In line with retrospective studies of contralateral breast cancer risks,22,23 the present prospective analysis of BRCA1 and BRCA2 carriers combined demonstrated a higher risk when the first breast cancer was diagnosed before age 40 years vs after age 50 years (P = .03).

The contralateral breast cancer analysis also included women diagnosed as having breast cancer prior to study recruitment. The median interval between first breast cancer diagnosis and study recruitment was 4 years, and this did not vary by age at first breast cancer diagnosis or by gene. The inclusion of survivors could potentially bias the estimation of contralateral breast cancer risks if such risks were related to the outcome of the first cancer; however, there is no strong evidence of such a relationship in the general population. Furthermore, the results were similar after excluding women whose first breast cancer diagnosis occurred more than 5 years prior to study recruitment, suggesting that any bias is likely to be small. Contralateral breast cancer risks have been shown to be reduced by adjuvant treatment of the first cancer.24,25BRCA2 carriers are more likely to develop estrogen receptor–positive cancers, so their lower contralateral breast cancer risk estimates may in part be due to greater use of endocrine therapy. Hormone and chemotherapeutic treatments were not considered, so the present estimates represent risks averaged over different treatments.

There was increasing breast cancer risk for both BRCA1 and BRCA2 carriers with increasing number of relatives who had been diagnosed with breast cancer. Similar patterns were observed for the risk of ovarian cancer but the number of events for women with family history of ovarian cancer was small. The overall breast cancer risk estimates were somewhat higher than those estimated by kin cohort analyses, in which the risks are derived from cohorts of relatives of carriers identified among unselected cases.3,21 The present cohort of mutation carriers was primarily identified through clinical genetics centers and included women who, on average, are likely to have stronger family history of cancer compared with mutation carriers identified through population-based sampling of cases. Therefore, a likely explanation for the higher estimated risks in the present study is that cancer risks for mutation carriers are modified by genetic and nongenetic risk factors which aggregate in families, in line with evidence that other genetic factors modify cancer risks for mutation carriers.18,26-29 These results confirm that family history should be taken into account in determining cancer risks for carriers, as modeled explicitly in BOADICEA.3

This prospective analysis validates retrospective analyses demonstrating that cancer risk varies by mutation location within the BRCA1 or BRCA2 gene.16-18 Consistent with those findings, mutations that lie in exon 11 of either gene were associated with a lower breast cancer risk and possibly higher ovarian cancer risk. The number of women in this prospective cohort was too small to estimate risks for additional, recently identified breast or ovarian cancer cluster regions.18

This study has several limitations. Data on tumor phenotypes of cancers were not available. Therefore, the results represent average estimates over all phenotypes of breast and ovarian cancer. Although there was variation in the cancer risks for mutation carriers by cancer family history, the study sample was not identified through population screening of unaffected women. Therefore, the overall estimates may not be directly applicable to such women. The present results suggest that cancer risks for women with no family history are likely to be lower than those estimated here. The cancer risk estimates may be subject to some selection bias if the decision to participate in the study or opt for testing was related to factors that are associated with disease risk. It was not possible to contrast the unaffected study participants to all other unaffected family members who had negative test results or who did not opt for a genetic test or for study participation, as those data could not be collected. However, the analysis by family history addresses possible selection bias with respect to family history of cancer and the family history–specific estimates are expected to be unbiased. The number of events in some of the subgroups considered was small and therefore the estimates have wide confidence intervals. Family size was not taken into consideration because data on unaffected family members were not collected systematically. In addition, risk estimates are limited by the lack of information about the use of hormone therapies to prevent either first primary or contralateral breast cancers.

Conclusions

These findings provide information on cancer risk for BRCA1 and BRCA2 mutation carriers using prospective data and demonstrate the potential importance of family history and mutation location in risk assessment.

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Article Information

Corresponding Author: Antonis C. Antoniou, PhD, Strangeways Research Laboratory, Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Worts Causeway, Cambridge CB1 8RN, England (aca20@medschl.cam.ac.uk).

Accepted for Publication: May 18, 2017.

Authors/BRCA1 and BRCA2 Cohort Consortium members include the byline authors as well as the following individuals: Lesley McGuffog; D. Gareth Evans, MD, PhD; Daniel Barrowdale, MSc; Debra Frost; Julian Adlard, MD; Kai-ren Ong, MD; Louise Izatt, MD; Marc Tischkowitz, MD, PhD; Ros Eeles, MD, PhD; Rosemarie Davidson, MD; Shirley Hodgson, MD; Steve Ellis, MSc; Catherine Nogues, MD; Christine Lasset, MD; Dominique Stoppa-Lyonnet, MD, PhD; Jean-Pierre Fricker, MD; Laurence Faivre, MD, PhD; Pascaline Berthet, MD; Maartje J. Hooning, MD, PhD; Lizet E. van der Kolk, MD, PhD; Carolien M. Kets, MD, PhD; Muriel A. Adank, MD, PhD; Esther M. John, PhD; Wendy K. Chung, MD, PhD; Irene L. Andrulis, PhD; Melissa Southey, PhD; Mary B. Daly, MD, PhD; Saundra S. Buys, MD; Ana Osorio, PhD; Christoph Engel, MD; Karin Kast, MD; Rita K. Schmutzler, MD, PhD; Trinidad Caldes, MD; Anna Jakubowska, PhD; Jacques Simard, PhD; Michael L. Friedlander, MD, PhD; Sue-Anne McLachlan, MD; Eva Machackova, PhD; Lenka Foretova, MD, PhD; Yen Y. Tan, PhD; Christian F. Singer, PhD; Edith Olah, PhD; Anne-Marie Gerdes, MD, PhD; Brita Arver, MD, PhD; Håkan Olsson, MD, PhD.

Affiliations of Authors/BRCA1 and BRCA2 Cohort Consortium: Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, England (McGuffog, Barrowdale, Frost, Ellis); Division of Cancer Medicine, Peter MacCallum Cancer Centre, Melbourne, Australia (McLachlan); Genomic Medicine, Manchester Academic Health Sciences Centre, Institute of Human Development, Manchester University, Central Manchester University Hospitals NHS Foundation Trust, Manchester, England (Evans); Yorkshire Regional Genetics Service, Chapel Allerton Hospital, Leeds, England (Adlard); West Midlands Regional Genetics Service, Birmingham Women’s Hospital Healthcare NHS Trust, Birmingham, England (Ong); Clinical Genetics, Guy’s and St Thomas’ NHS Foundation Trust, London, England (Izatt); Department of Medical Genetics and National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, England (Tischkowitz); Oncogenetics Team, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Sutton, England (Eeles); Department of Clinical Genetics, South Glasgow University Hospitals, Glasgow, Scotland (Davidson); Department of Clinical Genetics, St George’s, University of London, London, England (Hodgson); Oncogénétique Clinique, Hôpital René Huguenin/Institut Curie, Saint-Cloud, France (Nogues); Unité de Prévention et d’Epidémiologie Génétique, Centre Léon Bérard, Lyon, France (Lasset); Institut Curie, Department of Tumour Biology, Paris, France (Stoppa-Lyonnet); Institut Curie, INSERM U830, Paris, France (Stoppa-Lyonnet); Université Paris Descartes, Sorbonne Paris Cité, Paris, France (Stoppa-Lyonnet); Unité d’Oncogénétique, Centre Paul Strauss, Strasbourg, France (Fricker); Centre de Lutte Contre le Cancer Georges François Leclerc, Dijon, France (Faivre); Centre de Génétique, Hôpital d’Enfants, CHU Dijon, Dijon, France (Faivre); Centre François Baclesse, Caen, France (Berthet); Department of Medical Oncology, Family Cancer Clinic, Erasmus MC Cancer Institute, Rotterdam, the Netherlands (Hooning); Family Cancer Clinic, Netherlands Cancer Institute, Amsterdam, the Netherlands (van der Kolk); Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands (Kets); Department of Clinical Genetics, VU University Medical Center, Amsterdam, the Netherlands (Adank); Department of Epidemiology, Cancer Prevention Institute of California, Fremont (John); Departments of Pedicatrics and Medicine, Columbia University, New York, New York (Chung); Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada (Andrulis); Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Ontario, Canada (Andrulis); Genetic Epidemiology Laboratory, Department of Pathology, University of Melbourne, Parkville, Australia (Southey); Department of Clinical Genetics, Fox Chase Cancer Center, Philadelphia, Pennsylvania (Daly); Department of Medicine, Huntsman Cancer Institute, Salt Lake City, Utah (Buys); Human Genetics Group, Spanish National Cancer Centre, Madrid, Spain (Osorio); Biomedical Network on Rare Diseases (CIBERER), Madrid, Spain (Osorio); Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany (Engel); LIFE–Leipzig Research Centre for Civilization Diseases, University of Leipzig, Leipzig, Germany (Engel); Department of Gynaecology and Obstetrics, University Hospital Carl Gustav Carus, Dresden, Germany (Kast); National Center for Tumor Diseases, Partner Site Dresden, Dresden, Germany (Kast); German Cancer Consortium, Dresden and German Cancer Research Center, Heidelberg, Germany (Kast); Center for Familial Breast and Ovarian Cancer, Center for Integrated Oncology, Medical Faculty, University of Cologne and University Hospital Cologne, Cologne, Germany (Schmutzler); Molecular Oncology Laboratory, Hospital Clinico San Carlos, Instituto de Investigación Sanitaria San Carlos, Madrid, Spain (Caldes); Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland (Jakubowska); Genomics Center, Centre Hospitalier Universitaire de Québec Research Center and Laval University, Québec City, Québec, Canada (Simard); Prince of Wales Clinical School, University of New South Wales, Sydney, Australia (Friedlander); Department of Medical Oncology, Prince of Wales Hospital, Randwick, Australia (Friedlander); Department of Medical Oncology, St Vincent’s Hospital, Fitzroy, Australia (McLachlan); Department of Cancer Epidemiology and Genetics, Masaryk Memorial Cancer Institute, Brno, Czech Republic (Machackova, Foretova); Department of Obstetrics and Gynecology and Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria (Tan, Singer); QIMR Berghofer Medical Research Institute, Herston, Australia (Tan); Department of Molecular Genetics, National Institute of Oncology, Budapest, Hungary (Olah); Department of Clinical Genetics, Copenhagen University Hospital Rigshospital, Copenhagen, Denmark (Gerdes); Department of Oncology and Pathology, Karolinska Institute, Stockholm, Sweden (Arver); Department of Oncology, Lund University Hospital, Lund, Sweden (Olsson).

Author Contributions: Dr Antoniou had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Drs Hopper, Kuchenbaecker, and Barnes are joint first authors. Drs Rookus, Easton, and Antoniou are joint senior authors.

Study concept and design: Hopper, Southey, Simard, Olsson, van Leeuwen, Andrieu, Goldgar, Rookus, Easton, Antoniou.

Acquisition, analysis, or interpretation of data: Kuchenbaecker, Hopper, Barnes, Phillips, Mooij, Roos-Blom, Jervis, McGuffog, Evans, Barrowdale, Frost, Adlard, Ong, Izatt, Tischkowitz, Eeles, Davidson, Hodgson, Ellis, Nogues, Lasset, Stoppa-Lyonnet, Fricker, Faivre, Berthet, Hooning, van der Kolk, Kets, Adank, John, Chung, Andrulis, Southey, Daly, Buys, Osorio, Engel, Kast, Schmutzler, Caldes, Jakubowska, Simard, Friedlander, McLachlan, Machackova, Foretova, Tan, Singer, Olah, Gerdes, Arver, Milne, Andrieu, Goldgar, Terry, Rookus, Antoniou.

Drafting of the manuscript: Kuchenbaecker, Hopper, Barnes, Jervis, Evans, Tischkowitz, Ellis, Lasset, Milne, Rookus, Antoniou.

Critical revision of the manuscript for important intellectual content: Kuchenbaecker, Hopper, Barnes, Phillips, Mooij, Roos-Blom, Jervis, McGuffog, Evans, Barrowdale, Frost, Adlard, Ong, Izatt, Tischkowitz, Eeles, Davidson, Hodgson, Nogues, Stoppa-Lyonnet, Fricker, Faivre, Berthet, Hooning, van der Kolk, Kets, Adank, John, Chung, Andrulis, Southey, Daly, Buys, Osorio, Engel, Kast, Schmutzler, Caldes, Jakubowska, Simard, Friedlander, McLachlan, Machackova, Foretova, Tan, Singer, Olah, Gerdes, Arver, Olsson, van Leeuwen, Andrieu, Goldgar, Terry, Rookus, Easton, Antoniou.

Statistical analysis: Kuchenbaecker, Barnes, Jervis, McGuffog, Rookus, Easton, Antoniou.

Obtained funding: Hopper, Phillips, Nogues, Hooning, John, Andrulis, Southey, Buys, Schmutzler, Jakubowska, Simard, Olsson, Milne, Andrieu, Goldgar, Rookus, Easton, Antoniou.

Administrative, technical, or material support: Hopper, Mooij, Roos-Blom, Jervis, McGuffog, Barrowdale, Frost, Adlard, Izatt, Eeles, Faivre, Hooning, van der Kolk, Chung, Southey, Engel, Kast, Schmutzler, Jakubowska, Simard, Foretova, Tan, Singer, Olah, Gerdes, Goldgar, Terry, Antoniou.

Study supervision: Hopper, Eeles, Berthet, Andrulis, Southey, Caldes, Rookus, Antoniou.

Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Dr Evans reports receipt of webinar fees from AstraZeneca. Dr Barrowdale reports holding shares in GlaxoSmithKline stock. Dr Stoppa-Lyonnet reports receipt of personal fees from AstraZeneca. Dr Simard reports holding BRCA1 and BRCA2 patents. Dr Friedlander reports receipt of fees for advisory board membership from AstraZeneca and Pfizer. Dr Goldgar reports holding patents and receipt of royalties from Myriad Genetics. No other disclosures were reported.

Funding/Support: This work was supported by Cancer Research–UK grants C12292/A20861 and C12292/A11174. Dr Antoniou is a Cancer Research–UK Senior Cancer Research Fellow. Dr Phillips is an Australian National Breast Cancer Foundation Practitioner Fellow. The BCFR was supported by grant UM1 CA164920 from the National Cancer Institute. This work was partially supported by Spanish Association Against Cancer grant AECC08, RTICC 06/0020/1060, FISPI08/1120, Mutua Madrileña Foundation grant SAF2010-20493, and the Spanish Ministry of Economy and Competitiveness grant SAF2014-57680-R. EMBRACE is supported by Cancer Research–UK grants C1287/A10118, C1287/A1190, C1287/A16563, C1287/A17523, and C1287/A23382. Dr Evans is supported by a National Institute for Health Research (NIHR) grant to the Biomedical Research Centre, Manchester. The investigators at the Institute of Cancer Research and the Royal Marsden NHS Foundation Trust are supported by an NIHR grant to the Biomedical Research Centre at the Institute of Cancer Research and the Royal Marsden NHS Foundation Trust. Dr Eeles is supported by Cancer Research–UK grant C5047/A8385 and by NIHR support to the Biomedical Research Centre at the Institute of Cancer Research and the Royal Marsden NHS Foundation Trust. Dr Tischkowitz is supported by the European Research Council (grant 310018). The German Consortium of Hereditary Breast and Ovarian Cancer is supported by the German Cancer Aid (grant 110837 to Dr Schmutzler). This work was supported by LIFE (Leipzig Research Center for Civilization Diseases), Universität Leipzig. LIFE is funded by means of the European Union, by the European Regional Development Fund, and by means of the Free State of Saxony within the framework of the excellence initiative. The French national cohort, GENEPSO, was supported by a grant from the Fondation de France and the Ligue Nationale Contre le Cancer and is supported by a grant from INCa as part of the European program ERA-NET on Translational Cancer Research (TRANSCAN-JTC2012; grant 2014-008). Dr Caldes is supported by grants RD12/0036/0006 and CB161200301 from ISCIII (Spain), partially supported by European Regional Development FEDER funds. This work was supported by the Canadian Institute for Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer program (grant CRN-87521) and the Ministry of Economic Development, Innovation and Export Trade (grant PSR-SIIRI-701). We acknowledge the PERSPECTIVE project, which was supported by the government of Canada through Genome Canada and the CIHR, the Ministère de l’Économie, Innovation et Exportation du Québec through Genome Québec, and the Quebec Breast Cancer Foundation. The Hungarian Breast and Ovarian Cancer Study group at the Hungarian National Institute of Oncology was supported by Hungarian research grant NKFIH-OTKA K-112228 to Dr Olah. The Hereditary Breast and Ovarian Cancer Research Group Netherlands (HEBON) study is supported by Dutch Cancer Society grants NKI1998-1854, NKI2004-3088, and NKI2007-3756, Netherlands Organisation of Scientific Research grant NWO 91109024, Pink Ribbon grants 110005 and 2014-187.WO76, Biobanking and BioMolecular Resources Research Infrastructure grant NWO 184.021.007/CP46, and Transcan grant JTC 2012 Cancer 12-054. The International Hereditary Cancer Centre study was supported by grant PBZ_KBN_122/P05/2004. kConFab and the kConFab Follow-Up Study were supported by grants from the Australian National Breast Cancer Foundation (IF17), the Australian National Health and Medical Research Council (454508, 288704, 145684), Cancer Australia (809195), the US National Institutes of Health (1RO1CA159868), the Queensland Cancer Fund, the Cancer Councils of New South Wales, Victoria, Tasmania, and South Australia, and the Cancer Foundation of Western Australia. The Masaryk Memorial Cancer Institute study is supported by MH CZ-DRO (Masaryk Memorial Cancer Institute 00209805), by the MEYS-NPS I-LO1413 project, and by Charles University in Prague project UNCE204024 (MZ). SWE-BRCA collaborators were supported by the Swedish Cancer Society. Dr Olsson is supported by European Research Council Advanced Grant ERC-2011-294576.

Role of the Funders/Sponsors: The funding organizations had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication.

Disclaimer: The content of this article does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the BCFR, nor does mention of trade names, commercial products, or organizations imply endorsement by the US government or the BCFR.

Additional Contributions: The authors thank all of the study participants. HEBON thanks the registration teams of the Netherlands Comprehensive Cancer Organisation (IKNL) and the Nationwide Network and Registry of Histopathology and Cytopathology in the Netherlands (PALGA) for part of the data collection. In HEBON, the following centers collaborate, so these persons at least contributed to the data collection: Netherlands Cancer Institute (coordinating center): M. A. Rookus, PhD, F. B. L. Hogervorst, PhD, F. E. van Leeuwen, PhD, L. E. van der Kolk, PhD, MD, M. K. Schmidt, PhD, N. S. Russell, PhD, MD, J. L. de Lange, MSc, R. Wijnands, MSc, T. M. Mooij, MSc; Erasmus Medical Center: J. M. Collée, MD, A. M. W. van den Ouweland, PhD, M. J. Hooning, PhD, MD, C. Seynaeve, PhD, MD, C. H. M. van Deurzen, PhD, MD, I. M. Obdeijn, PhD, MD; Leiden University Medical Center: C. J. van Asperen, PhD, MD, J. T. Wijnen, PhD, R. A. E. M. Tollenaar, PhD, MD, P. Devilee, PhD, T. C. T. E. F. van Cronenburg, MSc; Radboud University Nijmegen Medical Center: C. M. Kets, PhD, MD, A. R. Mensenkamp, PhD; University Medical Center Utrecht: M. G. E. M. Ausems, PhD, MD, R. B. van der Luijt, PhD, C. C. van der Pol, PhD, MD; Amsterdam Medical Center: C. M. Aalfs, PhD, MD, T. A. M. van Os, MD; VU University Medical Center: J. J. P. Gille, PhD, Q. Waisfisz, PhD, M. Adank, PhD, MD, H. E. J. Meijers-Heijboer, PhD, MD; Maastricht University Medical Center: E. B. Gómez-Garcia, PhD, MD, M. J. Blok, PhD; University of Groningen: J. C. Oosterwijk, PhD, MD, A. H. van der Hout, PhD, M. J. Mourits, PhD, MD, G. H. de Bock, PhD; IKNL: S. Siesling, PhD, J. Verloop, PhD; PALGA: L. I. H. Overbeek, PhD. No compensation was received by any of these persons except for Drs Siesling, Verloop, and Overbeek, who were compensated for their linkages with IKNL and PALGA. We thank members and participants in the Breast Cancer Family Registry from the New York, Northern California, Ontario, Philadelphia, and Utah sites for their contributions to the study. BCFR Australia acknowledges the contributions of Maggie Angelakos, BSc (Centre for Epidemiology and Biostatistics, University of Melbourne; data management), Judith Maskiell, BHealthScN (Centre for Epidemiology and Biostatistics, University of Melbourne; study coordinator), Gillian Dite, PhD, Centre for Epidemiology and Biostatistics, University of Melbourne; study design and data management), and Helen Tsimiklis, BSc (Genetic Epidemiology Laboratory, Department of Pathology, University of Melbourne; biorepository manager, preparation and shipment of ABCFS samples included in project). We thank Alicia Barroso (Human Genetics Group, Spanish National Cancer Centre [CNIO]; BRCA1/2 genetic testing in CNIO samples), Rosario Alonso (Genotyping Unit, CNIO; sample preparation), and Guillermo Pita, BEng (Genotyping Unit, CNIO; database management) for their assistance. We acknowledge the GENEPSO centers: the coordinating center, Hôpital René Huguenin/Institut Curie, Saint Cloud: Catherine Noguès, MD, Emmanuelle Fourme-Mouret, MD, Sandrine Caputo, PhD, Akila Hamimi, MSc, and Valerie Gallot, who centralized and managed the data and organized carrier follow-up, and the collaborating centers, which contributed to carriers recruitment and follow-up: Dominique Stoppa-Lyonnet, PhD, MD, Institut Curie, Paris; Marion Gauthier-Villars, MD, Institut Curie, Paris; Bruno Buecher,MD, Institut Curie, Paris; Olivier Caron, MD, Institut Gustave Roussy, Villejuif; Catherine Noguès, MD, Hôpital René Huguenin/Institut Curie, Saint Cloud; Emmanuelle Fourme-Mouret, MD, Hôpital René Huguenin/Institut Curie, Saint Cloud; Jean-Pierre Fricker, MD, Centre Paul Strauss, Strasbourg; Christine Lasset, MD, Centre Léon Bérard, Lyon; Valérie Bonadona, PhD, MD, Centre Léon Bérard, Lyon; Pascaline Berthet, MD, Centre François Baclesse, Caen; Laurence Faivre, MD, Hôpital d’Enfants CHU and Centre Georges François Leclerc, Dijon; Elisabeth Luporsi, PhD, MD, Centre Alexis Vautrin, Vandoeuvre-les-Nancy; Véronique Mari, MD, Centre Antoine Lacassagne, Nice; Laurence Gladieff, MD, Institut Claudius Regaud, Toulouse; Paul Gesta, MD, Réseau Oncogénétique Poitou Charente, Niort; Hagay Sobol, PhD, MD, Institut Paoli-Calmettes, Marseille; François Eisinger, MD, Institut Paoli-Calmettes, Marseille; Michel Longy, PhD, MD Institut Bergonié, Bordeaux; Catherine Dugast, MD (deceased), Centre Eugène Marquis, Rennes; Chrystelle Colas, MD, G. H. Pitié Salpétrière, Paris; Isabelle Coupier, MD, CHU Arnaud de Villeneuve, Montpellier; Pascal Pujol, MD, CHU Arnaud de Villeneuve, Montpellier; Carole Corsini, MD, CHU Arnaud de Villeneuve, Montpellier; Alain Lortholary, MD, Centres Paul Papin and Catherine de Sienne, Angers, Nantes; Philippe Vennin, MD (deceased), Centre Oscar Lambret, Lille; Claude Adenis, MD, Centre Oscar Lambret, Lille; Tan Dat Nguyen, MD, Institut Jean Godinot, Reims; Capucine Delnatte, MD, Centre René Gauducheau, Nantes; Julie Tinat, MD, Centre Henri Becquerel, Rouen; Isabelle Tennevet, MD, Centre Henri Becquerel, Rouen; Jean-Marc Limacher, MD, Hôpital Civil, Strasbourg; Christine Maugard, PhD, Hôpital Civil, Strasbourg; Yves-Jean Bignon, MD, Centre Jean Perrin, Clermont-Ferrand; Liliane Demange (deceased), MD, Polyclinique Courlancy, Reims; Clotilde Penet, MD, Polyclinique Courlancy, Reims; Hélène Dreyfus, MD, Clinique Sainte Catherine, Avignon; Odile Cohen-Haguenauer, MD, Hôpital Saint-Louis, Paris; Laurence Venat-Bouvet, MD, CHRU Dupuytren, Limoges; Dominique Leroux, MD, Couple-Enfant-CHU de Grenoble; Hélène Dreyfus, MD, Couple-Enfant-CHU de Grenoble; Hélène Zattara-Cannoni, MD, Hôpital de la Timone, Marseille; Sandra Fert-Ferrer, MD, Hôtel Dieu–Centre Hospitalier, Chambery; and Odile Bera, MD, CHU Fort de France, Fort de France. We acknowledge Alicia Tosar, PhD (Molecular Oncology Laboratory, Hospital Clinico San Carlos, Instituto de Investigación Sanitaria San Carlos) and Pedro Perez-Segura, MD, PhD (Medical Oncology Branch, Hospital Clinico San Carlos, Instituto de Investigación Sanitaria San Carlos), both of whom contributed to the follow-up of members of their families. We thank the national manager of kConFab, Heather Thorne, BSci, and the kConFab data manager, Eveline Niedermayr, from the Peter MacCallum Cancer Centre. We also thank all of the kConFab research nurses and staff, the heads and staff of the Family Cancer Clinics, and the many families who contributed to kConFab. None of the named individuals received compensation for their role in the study.

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