Douglas F. Easton

Incorporating Continuous Mammographic Density Into the BOADICEA Breast Cancer Risk Prediction Model

PURPOSE Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA v7) predicts future breast cancer (BC) risk using data on cancer family history (FH), genetic markers, questionnaire-based risk factors, and mammographic density (MD) measured using the four-category Breast Imaging Reporting and Data System (BIRADS) classification. However, BIRADS requires manual reading, which is impractical on a large scale and may cause information loss. We extended BOADICEA to incorporate continuous MD measurements, calculated using the automated Volpara and STRATUS tools. METHODS We used data from the Karolinska Mammography Project for Risk Prediction of Breast Cancer cohort (60,276 participants; 1,167 incident BC). Associations between MD measurements and BC risk were estimated in a randomly selected training subset (two thirds of the data set). Percent MD residuals were calculated after regressing on age at mammography and BMI. Hazard ratios (HRs) were estimated using a Cox proportional hazards model, adjusting for FH and BOADICEA risk factors, and were incorporated into BOADICEA. The remaining one third of the cohort was used to assess the performance of the extended BOADICEA (v7.2) in predicting 5-year risks. RESULTS The BC HRs per standard deviation of residual STRATUS density were estimated to be 1.48 (95% CI, 1.33 to 1.64) and 1.41 (95% CI, 1.27 to 1.56) for pre- and postmenopausal women, respectively. The corresponding estimates for Volpara density were 1.27 (95% CI, 1.15 to 1.40) and 1.38 (95% CI, 1.25 to 1.54). The extended BOADICEA showed improved discrimination in the testing data set over using BIRADS, with a 1%-4% increase in AUC across different combinations of risk factors. On the basis of 5-year BC risk with MD as the sole input, approximately 11% of the women were reclassified into lower risk categories and 18% into higher risk categories using the extended model. CONCLUSION Incorporating continuous MD measurements into BOADICEA enhances BC risk stratification and facilitates the use of automated MD measures for risk prediction.

Evaluating the performance of the Breast and Ovarian Analysis of Disease Incidence Algorithm model in predicting 10-year breast cancer risks in UK Biobank

Abstract Background The Breast and Ovarian Analysis of Disease Incidence Algorithm (BOADICEA) model predicts breast cancer risk using cancer family history, epidemiological, and genetic data. We evaluated its validity in a large prospective cohort. Methods We assessed model calibration, discrimination and risk classification ability in 217 885 women (6838 incident breast cancers) aged 40-70 years of self-reported White ethnicity with no previous cancer from the UK Biobank. Age-specific risk classification was assessed using relative risk thresholds equivalent to the absolute lifetime risk categories of less than 17%, 17%-30%, and 30% or more, recommended by the National Institute for Health and Care Excellence guidelines. We predicted 10-year risks using BOADICEA v.6 considering cancer family history, questionnaire-based risk factors, a 313–single nucleotide polymorphisms polygenic score, and pathogenic variants. Mammographic density data were not available. Results The polygenic risk score was the most discriminative risk factor (area under the curve [AUC] = 0.65). Discrimination was highest when considering all risk factors (AUC = 0.66). The model was well calibrated overall (expected-to-observed ratio = 0.99, 95% confidence interval [CI] = 0.97 to 1.02; calibration slope = 0.99, 95% CI = 0.99 to 1.00), and in deciles of predicted risks. Discrimination was similar in women aged younger and older than 50 years. There was some underprediction in women aged younger than 50 years (expected-to-observed ratio = 0.89, 95% CI = 0.84 to 0.94; calibration slope = 0.96, 95% CI = 0.94 to 0.97), which was explained by the higher breast cancer incidence in UK Biobank than the UK population incidence in this age group. The model classified 87.2%, 11.4%, and 1.4% of women in relative risk categories less than 1.6, 1.6-3.1, and at least 3.1, identifying 25.6% of incident breast cancer patients in category relative risk of at least 1.6. Conclusion BOADICEA, implemented in CanRisk (www.canrisk.org), provides valid 10-year breast cancer risk, which can facilitate risk-stratified screening and personalized breast cancer risk management.

Breast Density Changes after Risk-Reducing Salpingo-oophorectomy in Women with a Pathogenic Germline Variant in BRCA1 or BRCA2

Abstract Background: We studied changes in mammographic density (MD) among premenopausal women with a pathogenic germline variant (PGV) in the BRCA1 or BRCA2 gene, comparing those who did and did not undergo risk-reducing salpingo-oophorectomy (RRSO) in the interval between mammograms, accounting for changes in exogenous oral contraceptive or hormone replacement therapy (HRT) use. Methods: From five studies of the International BRCA1/2 Carrier Cohort Study consortium, we included 691 participants who had two or more screening mammograms available, were less than 47 years at the time of RRSO (N = 208), or premenopausal at all mammograms without RRSO (N = 483). MD metrics [percent density (PD), dense area (DA), and non-DA] were quantified using STRATUS. Multivariable linear mixed models assessed changes in MD metrics between groups, adjusting for confounders. Results: The mean PD at first mammogram was 26.8% ± 15.3 (RRSO) and 31.3% ± 18.1 (no RRSO). In a median 1.1 years between mammograms, PD decreased on average by 0.9% [95% confidence interval (CI), −1.6 to −0.2] among women who did not undergo RRSO in the interval between mammograms compared with 5.9% (95% CI, −7.4 to −4.5) among women who underwent RRSO in the interval (adjusted difference, −5.9%; 95% CI, −9.5 to −2.2; P = 0.002). Results were driven primarily by MD changes among BRCA2 PGV carriers. The use of HRT after RRSO attenuated the decline in PD. Conclusions: On average, PD and DA decrease following RRSO in premenopausal carriers, particularly among BRCA2 PGV carriers. HRT formulation affects MD changes. Impact: A decrease in MD may inform the potential protective effect of RRSO against breast cancer.

Validation of the BOADICEA model for epithelial tubo-ovarian cancer risk prediction in UK Biobank

Abstract Background The clinical validity of the multifactorial BOADICEA model for epithelial tubo-ovarian cancer (EOC) risk prediction has not been assessed in a large sample size or over a longer term. Methods We evaluated the model discrimination and calibration in the UK Biobank cohort comprising 199,429 women (733 incident EOCs) of European ancestry without previous cancer history. We predicted 10-year EOC risk incorporating data on questionnaire-based risk factors (QRFs), family history, a 36-SNP polygenic risk score and pathogenic variants (PV) in six EOC susceptibility genes (BRCA1, BRCA2, RAD51C, RAD51D, BRIP1 and PALB2). Results Discriminative ability was maximised under the multifactorial model that included all risk factors (AUC = 0.68, 95% CI: 0.66–0.70). This model was well calibrated in deciles of predicted risk with calibration slope=0.99 (95% CI: 0.98–1.01). Discriminative ability was similar in women younger or older than 60 years. The AUC was higher when analyses were restricted to PV carriers (0.76, 95% CI: 0.69–0.82). Using relative risk (RR) thresholds, the full model classified 97.7%, 1.7%, 0.4% and 0.2% women in the RR < 2.0, 2.0 ≤ RR < 2.9, 2.9 ≤ RR < 6.0 and RR ≥ 6.0 categories, respectively, identifying 9.1 of incident EOC among those with RR ≥ 2.0. Discussion BOADICEA, implemented in CanRisk (www.canrisk.org), provides valid 10-year EOC risks and can facilitate clinical decision-making in EOC risk management.

Oral Contraceptive Use in BRCA1 and BRCA2 Mutation Carriers: Absolute Cancer Risks and Benefits

Abstract Background To help BRCA1 and 2 mutation carriers make informed decisions regarding use of combined-type oral contraceptive preparation (COCP), absolute risk-benefit estimates are needed for COCP-associated cancer. Methods For a hypothetical cohort of 10 000 women, we calculated the increased or decreased cumulative incidence of COCP-associated (breast, ovarian, endometrial) cancer, examining 18 scenarios with differences in duration and timing of COCP use, uptake of prophylactic surgeries, and menopausal hormone therapy. Results COCP use initially increased breast cancer risk and decreased ovarian and endometrial cancer risk long term. For 10 000 BRCA1 mutation carriers, 10 years of COCP use from age 20 to 30 years resulted in 66 additional COCP-associated cancer cases by the age of 35 years, in addition to 625 cases expected for never users. By the age of 70 years such COCP use resulted in 907 fewer cancer cases than the expected 9093 cases in never users. Triple-negative breast cancer estimates resulted in 196 additional COCP-associated cases by age 40 years, in addition to the 1454 expected. For 10 000 BRCA2 mutation carriers using COCP from age 20 to 30 years, 80 excess cancer cases were estimated by age 40 years in addition to 651 expected cases; by the age of 70 years, we calculated 382 fewer cases compared with the 6156 cases expected. The long-term benefit of COCP use diminished after risk-reducing bilateral salpingo-oophorectomy followed by menopausal hormone therapy use. Conclusion Although COCP use in BRCA1 and BRCA2 mutation carriers initially increases breast, ovarian, and endometrial cancer risk, it strongly decreases lifetime cancer risk. Risk-reducing bilateral salpingo-oophorectomy and menopausal hormone therapy use appear to counteract the long-term COCP-benefit.

Ovarian and Breast Cancer Risks Associated With Pathogenic Variants in RAD51C and RAD51D

Abstract Background The purpose of this study was to estimate precise age-specific tubo-ovarian carcinoma (TOC) and breast cancer (BC) risks for carriers of pathogenic variants in RAD51C and RAD51D. Methods We analyzed data from 6178 families, 125 with pathogenic variants in RAD51C, and 6690 families, 60 with pathogenic variants in RAD51D. TOC and BC relative and cumulative risks were estimated using complex segregation analysis to model the cancer inheritance patterns in families while adjusting for the mode of ascertainment of each family. All statistical tests were two-sided. Results Pathogenic variants in both RAD51C and RAD51D were associated with TOC (RAD51C: relative risk [RR] = 7.55, 95% confidence interval [CI] = 5.60 to 10.19; P = 5 × 10-40; RAD51D: RR = 7.60, 95% CI = 5.61 to 10.30; P = 5 × 10-39) and BC (RAD51C: RR = 1.99, 95% CI = 1.39 to 2.85; P = 1.55 × 10-4; RAD51D: RR = 1.83, 95% CI = 1.24 to 2.72; P = .002). For both RAD51C and RAD51D, there was a suggestion that the TOC relative risks increased with age until around age 60 years and decreased thereafter. The estimated cumulative risks of developing TOC to age 80 years were 11% (95% CI = 6% to 21%) for RAD51C and 13% (95% CI = 7% to 23%) for RAD51D pathogenic variant carriers. The estimated cumulative risks of developing BC to 80 years were 21% (95% CI = 15% to 29%) for RAD51C and 20% (95% CI = 14% to 28%) for RAD51D pathogenic variant carriers. Both TOC and BC risks for RAD51C and RAD51D pathogenic variant carriers varied by cancer family history and could be as high as 32–36% for TOC, for carriers with two first-degree relatives diagnosed with TOC, or 44–46% for BC, for carriers with two first-degree relatives diagnosed with BC. Conclusions These estimates will facilitate the genetic counseling of RAD51C and RAD51D pathogenic variant carriers and justify the incorporation of RAD51C and RAD51D into cancer risk prediction models.

Predicting the Likelihood of Carrying a BRCA1 or BRCA2 Mutation in Asian Patients With Breast Cancer

PURPOSE With the development of poly (ADP-ribose) polymerase inhibitors for treatment of patients with cancer with an altered BRCA1 or BRCA2 gene, there is an urgent need to ensure that there are appropriate strategies for identifying mutation carriers while balancing the increased demand for and cost of cancer genetics services. To date, the majority of mutation prediction tools have been developed in women of European descent where the age and cancer-subtype distributions are different from that in Asian women. METHODS In this study, we built a new model (Asian Risk Calculator) for estimating the likelihood of carrying a pathogenic variant in BRCA1 or BRCA2 gene, using germline BRCA genetic testing results in a cross-sectional population-based study of 8,162 Asian patients with breast cancer. We compared the model performance to existing mutation prediction models. The models were evaluated for discrimination and calibration. RESULTS Asian Risk Calculator included age of diagnosis, ethnicity, bilateral breast cancer, tumor biomarkers, and family history of breast cancer or ovarian cancer as predictors. The inclusion of tumor grade improved significantly the model performance. The full model was calibrated (Hosmer-Lemeshow P value = .614) and discriminated well between BRCA and non- BRCA pathogenic variant carriers (area under receiver operating curve, 0.80; 95% CI, 0.75 to 0.84). Addition of grade to the existing clinical genetic testing criteria targeting patients with breast cancer age younger than 45 years reduced the proportion of patients referred for genetic counseling and testing from 37% to 33% ( P value = .003), thereby improving the overall efficacy. CONCLUSION Population-specific customization of mutation prediction models and clinical genetic testing criteria improved the accuracy of BRCA mutation prediction in Asian patients.

Adapting the BOADICEA breast and ovarian cancer risk models for the ethnically diverse UK population

Abstract Background BOADICEA is a widely used algorithm for predicting breast and ovarian cancer risks, using a combination of genetic and lifestyle, hormonal and reproductive risk factors. However, it has largely been developed using data from White/European individuals, limiting its applicability to other ethnicities. Here, we updated BOADICEA to provide ethnicity-specific risk estimates. Methods We utilised data from multiple sources to derive estimates for the distributions and effect sizes of risk factors in major UK ethnic groups (White, Black, South Asian, East Asian, and Mixed), along with ethnicity-specific population cancer incidences. We also developed a method for deriving adjusted polygenic scores for individuals of mixed genetic ancestry. Results The predicted average absolute risks were smaller in all non-White ethnic groups than in Whites, and the risk distributions were narrower. The proportion of women classified as at moderate or high risk of breast or ovarian cancer, according to national guidelines, was considerably smaller in non-Whites. Discussion The updated BOADICEA, available in the CanRisk tool ( www.canrisk.org ), is based on more appropriate estimates for non-White women in the UK. Further validation of the model in prospective studies is required. Considering these findings, risk classification guidelines for non-White women may need to be revised.