Validation of the BOADICEA model in a prospective cohort of BRCA1/2 pathogenic variant carriers.

BACKGROUND: No validation has been conducted for the BOADICEA multifactorial breast cancer risk prediction model specifically in BRCA1/2 pathogenic variant (PV) carriers to date. Here, we evaluated the performance of BOADICEA in predicting 5-year breast cancer risks in a prospective cohort of BRCA1/2 PV carriers ascertained through clinical genetic centres. METHODS: We evaluated the model calibration and discriminatory ability in the prospective TRANsIBCCS cohort study comprising 1614 BRCA1 and 1365 BRCA2 PV carriers (209 incident cases). Study participants had lifestyle, reproductive, hormonal, anthropometric risk factor information, a polygenic risk score based on 313 SNPs and family history information. RESULTS: The full multifactorial model considering family history together with all other risk factors was well calibrated overall (E/O=1.07, 95% CI: 0.92 to 1.24) and in quintiles of predicted risk. Discrimination was maximised when all risk factors were considered (Harrell's C-index=0.70, 95% CI: 0.67 to 0.74; area under the curve=0.79, 95% CI: 0.76 to 0.82). The model performance was similar when evaluated separately in BRCA1 or BRCA2 PV carriers. The full model identified 5.8%, 12.9% and 24.0% of BRCA1/2 PV carriers with 5-year breast cancer risks of <1.65%, <3% and <5%, respectively, risk thresholds commonly used for different management and risk-reduction options. CONCLUSION: BOADICEA may be used to aid personalised cancer risk management and decision-making for BRCA1 and BRCA2 PV carriers. It is implemented in the free-access CanRisk tool (https://www.canrisk.org/).

Long-term outcomes of young, node-negative, chemotherapy-naïve, triple-negative breast cancer patients according to BRCA1 status.

BACKGROUND: Due to the abundant usage of chemotherapy in young triple-negative breast cancer (TNBC) patients, the unbiased prognostic value of BRCA1-related biomarkers in this population remains unclear. In addition, whether BRCA1-related biomarkers modify the well-established prognostic value of stromal tumor-infiltrating lymphocytes (sTILs) is unknown. This study aimed to compare the outcomes of young, node-negative, chemotherapy-naïve TNBC patients according to BRCA1 status, taking sTILs into account. METHODS: We included 485 Dutch women diagnosed with node-negative TNBC under age 40 between 1989 and 2000. During this period, these women were considered low-risk and did not receive chemotherapy. BRCA1 status, including pathogenic germline BRCA1 mutation (gBRCA1m), somatic BRCA1 mutation (sBRCA1m), and tumor BRCA1 promoter methylation (BRCA1-PM), was assessed using DNA from formalin-fixed paraffin-embedded tissue. sTILs were assessed according to the international guideline. Patients' outcomes were compared using Cox regression and competing risk models. RESULTS: Among the 399 patients with BRCA1 status, 26.3% had a gBRCA1m, 5.3% had a sBRCA1m, 36.6% had tumor BRCA1-PM, and 31.8% had BRCA1-non-altered tumors. Compared to BRCA1-non-alteration, gBRCA1m was associated with worse overall survival (OS) from the fourth year after diagnosis (adjusted HR, 2.11; 95% CI, 1.18-3.75), and this association attenuated after adjustment for second primary tumors. Every 10% sTIL increment was associated with 16% higher OS (adjusted HR, 0.84; 95% CI, 0.78-0.90) in gBRCA1m, sBRCA1m, or BRCA1-non-altered patients and 31% higher OS in tumor BRCA1-PM patients. Among the 66 patients with tumor BRCA1-PM and ≥ 50% sTILs, we observed excellent 15-year OS (97.0%; 95% CI, 92.9-100%). Conversely, among the 61 patients with gBRCA1m and < 50% sTILs, we observed poor 15-year OS (50.8%; 95% CI, 39.7-65.0%). Furthermore, gBRCA1m was associated with higher (adjusted subdistribution HR, 4.04; 95% CI, 2.29-7.13) and tumor BRCA1-PM with lower (adjusted subdistribution HR, 0.42; 95% CI, 0.19-0.95) incidence of second primary tumors, compared to BRCA1-non-alteration. CONCLUSIONS: Although both gBRCA1m and tumor BRCA1-PM alter BRCA1 gene transcription, they are associated with different outcomes in young, node-negative, chemotherapy-naïve TNBC patients. By combining sTILs and BRCA1 status for risk classification, we were able to identify potential subgroups in this population to intensify and optimize adjuvant treatment.

Cancer risks for other sites in addition to breast in CHEK2 c.1100delC families.

PURPOSE: Female CHEK2 c.1100delC heterozygotes are eligible for additional breast surveillance due to an increased breast cancer risk. Increased risks for other cancers have been reported. We studied whether CHEK2 c.1100delC is associated with an increased risk for other cancers within these families. METHODS: Including 10,780 individuals from 609 families, we calculated standardized incidence rates (SIRs) and absolute excess risk (AER, per 10.000 person years) by comparing first-reported cancer derived from the pedigrees with general Dutch population rates from 1970 onwards. Attained-age analyses were performed for sites in which significant increased risks were found. Considering study design, we primarily focused on cancer risk in women. RESULTS: We found significant increased risks of colorectal cancer (CRC; SIR=1.43, 95%CI=1.14-1.76; AER=1.43) and hematological cancers (SIR=1.32; 95%CI=1.02-1.67; AER=0.87). CRC was significantly more frequent from age 45 onwards. CONCLUSION: A significantly increased risk of CRC, and hematological cancers in women was found, starting at a younger age than expected. Currently, colorectal surveillance starts at age 45 in high-risk individuals. Our results suggest that some CHEK2 c.1100delC families might benefit from this surveillance as well, however, further research is needed to determine who may profit from this additional colorectal surveillance.

Long-term outcome of high-grade serous carcinoma established in risk-reducing salpingo-oophorectomy specimens in asymptomatic BRCA1/2 germline pathogenic variant carriers.

OBJECTIVE: The aim of this study was to describe the long-term outcome of asymptomatic BRCA1/2 germline pathogenic variant (GPV) carriers with high-grade serous carcinoma (HGSC) in their risk-reducing salpingo-oophorectomy (RRSO) specimen. METHODS: In a previously described cohort of asymptomatic BRCA1/2 GPV carriers derived from the Hereditary Breast and Ovarian cancer in the Netherlands (HEBON) study, women with HGSC at RRSO were identified. Main outcome was ten-year disease-free survival (DFS). Secondary outcomes were time to recurrence, ten-year disease-specific survival (DSS), ten-year overall survival (OS). Patient, disease and treatment characteristics associated with recurrence were described. RESULTS: The 28 included women with HGSC at RRSO were diagnosed at a median age of 55.3 years (range: 33.5-74.3). After staging, eighteen women had (FIGO) stage I, three stage II and five had stage III disease. Two women did not undergo surgical staging and were classified as unknown stage. After a median follow-up of 13.5 years (range: 9.1-24.7), six women with stage I (33%), one woman with stage II (33%), two women with stage III (40%) and none of the women with unknown stage developed a recurrence. Median time to recurrence was 6.9 years (range: 0.8-9.2 years). Ten-year DFS was 68%, ten-year DSS was 88% and ten-year OS was 82%. CONCLUSION: Most asymptomatic BRCA1/2 GPV carriers with HGSC at RRSO were diagnosed at an early stage. Nevertheless, after a median follow-up of 13.5 years, nine of the 28 women with HGSC at RRSO developed a recurrence after a median of 6.9 years.

Clinical applicability of the Polygenic Risk Score for breast cancer risk prediction in familial cases.

BACKGROUND: Common low-risk variants are presently not used to guide clinical management of familial breast cancer (BC). We explored the additive impact of a 313-variant-based Polygenic Risk Score (PRS313) relative to standard gene testing in non-BRCA1/2 Dutch BC families. METHODS: We included 3918 BC cases from 3492 Dutch non-BRCA1/2 BC families and 3474 Dutch population controls. The association of the standardised PRS313 with BC was estimated using a logistic regression model, adjusted for pedigree-based family history. Family history of the controls was imputed for this analysis. SEs were corrected to account for relatedness of individuals. Using the BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm) V.5 model, lifetime risks were retrospectively calculated with and without individual PRS313. For 2586 cases and 2584 controls, the carrier status of pathogenic variants (PVs) in ATM, CHEK2 and PALB2 was known. RESULTS: The family history-adjusted PRS313 was significantly associated with BC (per SD OR=1.97, 95% CI 1.84 to 2.11). Including the PRS313 in BOADICEA family-based risk prediction would have changed screening recommendations in up to 27%, 36% and 34% of cases according to BC screening guidelines from the USA, UK and the Netherlands (National Comprehensive Cancer Network, National Institute for Health and Care Excellence, and Netherlands Comprehensive Cancer Organisation), respectively. For the population controls, without information on family history, this was up to 39%, 44% and 58%, respectively. Among carriers of PVs in known moderate BC susceptibility genes, the PRS313 had the largest impact for CHEK2 and ATM. CONCLUSIONS: Our results support the application of the PRS313 in risk prediction for genetically uninformative BC families and families with a PV in moderate BC risk genes.

Breast cancer genomes from CHEK2 c.1100delC mutation carriers lack somatic TP53 mutations and display a unique structural variant size distribution profile.

BACKGROUND: CHEK2 c.1100delC was the first moderate-risk breast cancer (BC) susceptibility allele discovered. Despite several genomic, transcriptomic and functional studies, however, it is still unclear how exactly CHEK2 c.1100delC promotes tumorigenesis. Since the mutational landscape of a tumor reflects the processes that have operated on its development, the aim of this study was to uncover the somatic genomic landscape of CHEK2-associated BC. METHODS: We sequenced primary BC (pBC) and normal genomes of 20 CHEK2 c.1100delC mutation carriers as well as their pBC transcriptomes. Including pre-existing cohorts, we exhaustively compared CHEK2 pBC genomes to those from BRCA1/2 mutation carriers, those that displayed homologous recombination deficiency (HRD) and ER- and ER+ pBCs, totaling to 574 pBC genomes. Findings were validated in 517 metastatic BC genomes subdivided into the same subgroups. Transcriptome data from 168 ER+ pBCs were used to derive a TP53-mutant gene expression signature and perform cluster analysis with CHEK2 BC transcriptomes. Finally, clinical outcome of CHEK2 c.1100delC carriers was compared with BC patients displaying somatic TP53 mutations in two well-described retrospective cohorts totaling to 942 independent pBC cases. RESULTS: BC genomes from CHEK2 mutation carriers were most similar to ER+ BC genomes and least similar to those of BRCA1/2 mutation carriers in terms of tumor mutational burden as well as mutational signatures. Moreover, CHEK2 BC genomes did not show any evidence of HRD. Somatic TP53 mutation frequency and the size distribution of structural variants (SVs), however, were different compared to ER+ BC. Interestingly, BC genomes with bi-allelic CHEK2 inactivation lacked somatic TP53 mutations and transcriptomic analysis indicated a shared biology with TP53 mutant BC. Moreover, CHEK2 BC genomes had an increased frequency of > 1 Mb deletions, inversions and tandem duplications with peaks at specific sizes. The high chromothripsis frequency among CHEK2 BC genomes appeared, however, not associated with this unique SV size distribution profile. CONCLUSIONS: CHEK2 BC genomes are most similar to ER+ BC genomes, but display unique features that may further unravel CHEK2-driven tumorigenesis. Increased insight into this mechanism could explain the shorter survival of CHEK2 mutation carriers that is likely driven by intrinsic tumor aggressiveness rather than endocrine resistance.

Associations of height, body mass index, and weight gain with breast cancer risk in carriers of a pathogenic variant in BRCA1 or BRCA2: the BRCA1 and BRCA2 Cohort Consortium.

INTRODUCTION: Height, body mass index (BMI), and weight gain are associated with breast cancer risk in the general population. It is unclear whether these associations also exist for carriers of pathogenic variants in the BRCA1 or BRCA2 genes. PATIENTS AND METHODS: An international pooled cohort of 8091 BRCA1/2 variant carriers was used for retrospective and prospective analyses separately for premenopausal and postmenopausal women. Cox regression was used to estimate breast cancer risk associations with height, BMI, and weight change. RESULTS: In the retrospective analysis, taller height was associated with risk of premenopausal breast cancer for BRCA2 variant carriers (HR 1.20 per 10 cm increase, 95% CI 1.04-1.38). Higher young-adult BMI was associated with lower premenopausal breast cancer risk for both BRCA1 (HR 0.75 per 5 kg/m2, 95% CI 0.66-0.84) and BRCA2 (HR 0.76, 95% CI 0.65-0.89) variant carriers in the retrospective analysis, with consistent, though not statistically significant, findings from the prospective analysis. In the prospective analysis, higher BMI and adult weight gain were associated with higher postmenopausal breast cancer risk for BRCA1 carriers (HR 1.20 per 5 kg/m2, 95% CI 1.02-1.42; and HR 1.10 per 5 kg weight gain, 95% CI 1.01-1.19, respectively). CONCLUSION: Anthropometric measures are associated with breast cancer risk for BRCA1 and BRCA2 variant carriers, with relative risk estimates that are generally consistent with those for women from the general population.

Prospective validation of the BOADICEA multifactorial breast cancer risk prediction model in a large prospective cohort study.

BACKGROUND: The multifactorial Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) breast cancer risk prediction model has been recently extended to consider all established breast cancer risk factors. We assessed the clinical validity of the model in a large independent prospective cohort. METHODS: We validated BOADICEA (V.6) in the Swedish KARolinska Mammography Project for Risk Prediction of Breast Cancer (KARMA) cohort including 66 415 women of European ancestry (median age 54 years, IQR 45-63; 816 incident breast cancers) without previous cancer diagnosis. We calculated 5-year risks on the basis of questionnaire-based risk factors, pedigree-structured first-degree family history, mammographic density (BI-RADS), a validated breast cancer polygenic risk score (PRS) based on 313-SNPs, and pathogenic variant status in 8 breast cancer susceptibility genes: BRCA1, BRCA2, PALB2, CHEK2, ATM, RAD51C, RAD51D and BARD1. Calibration was assessed by comparing observed and expected risks in deciles of predicted risk and the calibration slope. The discriminatory ability was assessed using the area under the curve (AUC). RESULTS: Among the individual model components, the PRS contributed most to breast cancer risk stratification. BOADICEA was well calibrated in predicting the risks for low-risk and high-risk women when all, or subsets of risk factors are included in the risk prediction. Discrimination was maximised when all risk factors are considered (AUC=0.70, 95% CI: 0.66 to 0.73; expected-to-observed ratio=0.88, 95% CI: 0.75 to 1.04; calibration slope=0.97, 95% CI: 0.95 to 0.99). The full multifactorial model classified 3.6% women as high risk (5-year risk ≥3%) and 11.1% as very low risk (5-year risk <0.33%). CONCLUSION: The multifactorial BOADICEA model provides valid breast cancer risk predictions and a basis for personalised decision-making on disease prevention and screening.

Enhancing the BOADICEA cancer risk prediction model to incorporate new data on RAD51C, RAD51D, BARD1 updates to tumour pathology and cancer incidence.

BACKGROUND: BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm) for breast cancer and the epithelial tubo-ovarian cancer (EOC) models included in the CanRisk tool (www.canrisk.org) provide future cancer risks based on pathogenic variants in cancer-susceptibility genes, polygenic risk scores, breast density, questionnaire-based risk factors and family history. Here, we extend the models to include the effects of pathogenic variants in recently established breast cancer and EOC susceptibility genes, up-to-date age-specific pathology distributions and continuous risk factors. METHODS: BOADICEA was extended to further incorporate the associations of pathogenic variants in BARD1, RAD51C and RAD51D with breast cancer risk. The EOC model was extended to include the association of PALB2 pathogenic variants with EOC risk. Age-specific distributions of oestrogen-receptor-negative and triple-negative breast cancer status for pathogenic variant carriers in these genes and CHEK2 and ATM were also incorporated. A novel method to include continuous risk factors was developed, exemplified by including adult height as continuous. RESULTS: BARD1, RAD51C and RAD51D explain 0.31% of the breast cancer polygenic variance. When incorporated into the multifactorial model, 34%-44% of these carriers would be reclassified to the near-population and 15%-22% to the high-risk categories based on the UK National Institute for Health and Care Excellence guidelines. Under the EOC multifactorial model, 62%, 35% and 3% of PALB2 carriers have lifetime EOC risks of <5%, 5%-10% and >10%, respectively. Including height as continuous, increased the breast cancer relative risk variance from 0.002 to 0.010. CONCLUSIONS: These extensions will allow for better personalised risks for BARD1, RAD51C, RAD51D and PALB2 pathogenic variant carriers and more informed choices on screening, prevention, risk factor modification or other risk-reducing options.

PredictCBC-2.0: a contralateral breast cancer risk prediction model developed and validated in ~ 200,000 patients.

BACKGROUND: Prediction of contralateral breast cancer (CBC) risk is challenging due to moderate performances of the known risk factors. We aimed to improve our previous risk prediction model (PredictCBC) by updated follow-up and including additional risk factors. METHODS: We included data from 207,510 invasive breast cancer patients participating in 23 studies. In total, 8225 CBC events occurred over a median follow-up of 10.2 years. In addition to the previously included risk factors, PredictCBC-2.0 included CHEK2 c.1100delC, a 313 variant polygenic risk score (PRS-313), body mass index (BMI), and parity. Fine and Gray regression was used to fit the model. Calibration and a time-dependent area under the curve (AUC) at 5 and 10 years were assessed to determine the performance of the models. Decision curve analysis was performed to evaluate the net benefit of PredictCBC-2.0 and previous PredictCBC models. RESULTS: The discrimination of PredictCBC-2.0 at 10 years was higher than PredictCBC with an AUC of 0.65 (95% prediction intervals (PI) 0.56-0.74) versus 0.63 (95%PI 0.54-0.71). PredictCBC-2.0 was well calibrated with an observed/expected ratio at 10 years of 0.92 (95%PI 0.34-2.54). Decision curve analysis for contralateral preventive mastectomy (CPM) showed the potential clinical utility of PredictCBC-2.0 between thresholds of 4 and 12% 10-year CBC risk for BRCA1/2 mutation carriers and non-carriers. CONCLUSIONS: Additional genetic information beyond BRCA1/2 germline mutations improved CBC risk prediction and might help tailor clinical decision-making toward CPM or alternative preventive strategies. Identifying patients who benefit from CPM, especially in the general breast cancer population, remains challenging.

Breast cancer and cardiovascular outcomes after breast cancer in survivors of Hodgkin lymphoma.

BACKGROUND: Hodgkin lymphoma (HL) survivors treated with chest radiotherapy have an increased risk of breast cancer (BC). Prior HL treatment and associated cardiovascular disease (CVD) risk may limit BC treatment options. It is unknown how treatment adaptations affect BC and CVD outcomes. METHODS: The authors compared 195 BC patients treated with chest/axillary radiotherapy for HL (BC-HL) with 5988 age- and calendar year-matched patients with first primary BC (BC-1). Analyses included cumulative incidence functions and Cox regression models, accounting for tumor characteristics and BC treatment. RESULTS: Compared to BC-1 patients, BC-HL patients received anthracycline-containing chemotherapy (23.7% vs. 43.8%, p < .001) and breast-conserving surgery followed by radiotherapy (7.1% vs. 57.7%, p < .001) less often. BC treatment considerations were reported for 71% of BC-HL patients. BC-HL patients had a significantly higher risk of 15-year overall mortality than BC-1 patients (61% vs. 23%). Furthermore, risks of BC-specific mortality and nonfatal BC events were significantly increased among BC-HL patients, also when accounting for tumor and treatment characteristics (2.2- to 4.5-fold). BC-HL patients with a screen-detected BC had a significantly reduced (61%) BC-specific mortality. One-third of BC-HL patients had CVD at BC-diagnosis, compared to <0.1% of BC-1 patients. Fifteen-year CVD-specific mortality and CVD incidence were significantly higher in BC-HL patients than in BC-1 patients (15.2% vs. 0.4% and 40.4% vs. 6.8%, respectively), which was due to HL treatment rather than BC treatment. CONCLUSIONS: BC-HL patients experience a higher burden of CVD and worse BC outcomes than BC-1 patients. Clinicians should be aware of increased CVD risk when selecting BC treatment for HL survivors. LAY SUMMARY: Patients with breast cancer after Hodgkin lymphoma (BC-HL) may have limited options for BC treatment, due to earlier HL treatment and an associated increased risk of cardiovascular disease (CVD). BC treatment considerations were reported for 71% of BC-HL patients. We examined whether BC-HL patients have a higher risk of CVD or BC events (recurrences/metastases) compared to patients with breast cancer that had no earlier tumors (BC-1). We observed a higher burden of CVD and worse BC outcomes in HL patients compared to BC-1 patients. Clinicians should be aware of increased CVD risk when selecting BC treatment for HL survivors.

Survival of BRCA1/BRCA2-associated pT1 breast cancer patients, a cohort study.

PURPOSE: Intensive screening in BRCA1/2 mutation carriers aims to improve breast cancer (BC) prognosis. Our aim is to clarify the prognostic impact of tumor size in BRCA mutation carriers with a pT1 BC, which is currently unclear. We are especially interested in differences between pT1a, pT1b, and pT1c regarding the prognosis of node-negative breast cancer, the effect of chemotherapy, and the prevalence of lymph node involvement. METHODS: For this study, BRCA1/2-associated BC patients were selected from a nationwide cohort. Primary outcomes were 10-year overall survival (OS) per pT1a-b-c group and the effect of chemotherapy on prognosis of node-negative BC, using Kaplan-Meier and Cox models. Finally, we evaluated lymph node involvement per pT1a-b-c group. RESULTS: 963 women with pT1 BRCA1/2-associated BC diagnosed between 1990 and 2017 were included, of which 679 had pN0 BC. After a median follow-up of 10.5 years, 10-year OS in patients without chemotherapy was 77.1% in pT1cN0 and lower than for pT1aN0 (91.4%, p = 0.119) and pT1bN0 (90.8%, p = 0.024). OS was better with than without chemotherapy for pT1cN0 (91.6% vs. 77.1%, p = 0.001; hazard ratio (HR) 0.56, 95% confidence interval (CI): 0.21-1.48). Lymph node involvement was 24.9% in pT1c, 18.8% in pT1b, and 8.6% in pT1a. CONCLUSION: Smaller tumor size is associated with better OS and less lymph node involvement in pT1 BRCA1/2-associated BC patients. The results suggest that early detection in BRCA1/2 mutation carriers of pT1a/b BC may reduce mortality and the need for systemic therapy.

Towards implementation of comprehensive breast cancer risk prediction tools in health care for personalised prevention.

Advances in knowledge about breast cancer risk factors have led to the development of more comprehensive risk models. These integrate information on a variety of risk factors such as lifestyle, genetics, family history, and breast density. These risk models have the potential to deliver more personalised breast cancer prevention. This is through improving accuracy of risk estimates, enabling more effective targeting of preventive options and creating novel prevention pathways through enabling risk estimation in a wider variety of populations than currently possible. The systematic use of risk tools as part of population screening programmes is one such example. A clear understanding of how such tools can contribute to the goal of personalised prevention can aid in understanding and addressing barriers to implementation. In this paper we describe how emerging models, and their associated tools can contribute to the goal of personalised healthcare for breast cancer through health promotion, early disease detection (screening) and improved management of women at higher risk of disease. We outline how addressing specific challenges on the level of communication, evidence, evaluation, regulation, and acceptance, can facilitate implementation and uptake.

Comprehensive trends in incidence, treatment, survival and mortality of first primary invasive breast cancer stratified by age, stage and receptor subtype in the Netherlands between 1989 and 2017.

Our study aimed to provide a comprehensive overview of trends in incidence, survival, mortality and treatment of first primary invasive breast cancer (BC), according to age, stage and receptor subtype in the Netherlands between 1989 and 2017. Data from all women diagnosed with first primary stage I to IV BC (N = 320 249) were obtained from the Netherlands Cancer Registry. BC mortality and general population data were retrieved from Statistics Netherlands. Age-standardised incidence and mortality rates were calculated with annual percentage change (APC) and average annual percentage change (AAPC) statistics. The relative survival (RS) was used as estimator for disease-specific survival. The BC incidence for all BC patients combined significantly increased until 2013 from 126 to 158 per 100 000 person-years, after which a declining trend was observed. Surgery became less extensive, but (neo-)adjuvant systemic treatments and their combinations were given more frequently. The RS improved for all age groups and for most stages and receptor subtypes, but remained stable for all subtypes since 2012 to 2013 and since 2000 to 2009 for Stage IV BC at 15 years of follow-up. Overall, the 5- and 10-year RS increased from 76.8% (95% confidence interval [CI]: 76.1, 77.4) and 55.9% (95% CI: 54.7, 57.1) in 1989 to 1999 to 91.0% (95% CI: 90.5, 91.5) and 82.9% (95% CI: 82.2, 83.5), respectively, in 2010 to 2016. BC mortality improved regardless of age and overall decreased from 57 to 35 per 100 000 person-years between 1989 and 2017. In conclusion, the BC incidence in the Netherlands has steadily increased since 1989, but the latest trends show promising declines. Survival improved markedly for most patients and the mortality decreased regardless of age.

Long-term risk of subsequent ipsilateral lesions after surgery with or without radiotherapy for ductal carcinoma in situ of the breast.

BACKGROUND: Radiotherapy (RT) following breast-conserving surgery (BCS) for ductal carcinoma in situ (DCIS) reduces ipsilateral breast event rates in clinical trials. This study assessed the impact of DCIS treatment on a 20-year risk of ipsilateral DCIS (iDCIS) and ipsilateral invasive breast cancer (iIBC) in a population-based cohort. METHODS: The cohort comprised all women diagnosed with DCIS in the Netherlands during 1989-2004 with follow-up until 2017. Cumulative incidence of iDCIS and iIBC following BCS and BCS + RT were assessed. Associations of DCIS treatment with iDCIS and iIBC risk were estimated in multivariable Cox models. RESULTS: The 20-year cumulative incidence of any ipsilateral breast event was 30.6% (95% confidence interval (CI): 28.9-32.6) after BCS compared to 18.2% (95% CI 16.3-20.3) following BCS + RT. Women treated with BCS compared to BCS + RT had higher risk of developing iDCIS and iIBC within 5 years after DCIS diagnosis (for iDCIS: hazard ratio (HR)age < 50 3.2 (95% CI 1.6-6.6); HRage ≥ 50 3.6 (95% CI 2.6-4.8) and for iIBC: HRage<50 2.1 (95% CI 1.4-3.2); HRage ≥ 50 4.3 (95% CI 3.0-6.0)). After 10 years, the risk of iDCIS and iIBC no longer differed for BCS versus BCS + RT (for iDCIS: HRage < 50 0.7 (95% CI 0.3-1.5); HRage ≥ 50 0.7 (95% CI 0.4-1.3) and for iIBC: HRage < 50 0.6 (95% CI 0.4-0.9); HRage ≥ 50 1.2 (95% CI 0.9-1.6)). CONCLUSION: RT is associated with lower iDCIS and iIBC risk up to 10 years after BCS, but this effect wanes thereafter.

Improved risk estimation of locoregional recurrence, secondary contralateral tumors and distant metastases in early breast cancer: the INFLUENCE 2.0 model.

PURPOSE: To extend the functionality of the existing INFLUENCE nomogram for locoregional recurrence (LRR) of breast cancer toward the prediction of secondary primary tumors (SP) and distant metastases (DM) using updated follow-up data and the best suitable statistical approaches. METHODS: Data on women diagnosed with non-metastatic invasive breast cancer were derived from the Netherlands Cancer Registry (n = 13,494). To provide flexible time-dependent individual risk predictions for LRR, SP, and DM, three statistical approaches were assessed; a Cox proportional hazard approach (COX), a parametric spline approach (PAR), and a random survival forest (RSF). These approaches were evaluated on their discrimination using the Area Under the Curve (AUC) statistic and on calibration using the Integrated Calibration Index (ICI). To correct for optimism, the performance measures were assessed by drawing 200 bootstrap samples. RESULTS: Age, tumor grade, pT, pN, multifocality, type of surgery, hormonal receptor status, HER2-status, and adjuvant therapy were included as predictors. While all three approaches showed adequate calibration, the RSF approach offers the best optimism-corrected 5-year AUC for LRR (0.75, 95%CI: 0.74-0.76) and SP (0.67, 95%CI: 0.65-0.68). For the prediction of DM, all three approaches showed equivalent discrimination (5-year AUC: 0.77-0.78), while COX seems to have an advantage concerning calibration (ICI < 0.01). Finally, an online calculator of INFLUENCE 2.0 was created. CONCLUSIONS: INFLUENCE 2.0 is a flexible model to predict time-dependent individual risks of LRR, SP and DM at a 5-year scale; it can support clinical decision-making regarding personalized follow-up strategies for curatively treated non-metastatic breast cancer patients.

Genetic susceptibility to radiation-induced breast cancer after Hodgkin lymphoma.

Female Hodgkin lymphoma (HL) patients treated with chest radiotherapy (RT) have a very high risk of breast cancer. The contribution of genetic factors to this risk is unclear. We therefore examined 211 155 germline single-nucleotide polymorphisms (SNPs) for gene-radiation interaction on breast cancer risk in a case-only analysis including 327 breast cancer patients after chest RT for HL and 4671 first primary breast cancer patients. Nine SNPs showed statistically significant interaction with RT on breast cancer risk (false discovery rate, <20%), of which 1 SNP in the PVT1 oncogene attained the Bonferroni threshold for statistical significance. A polygenic risk score (PRS) composed of these SNPs (RT-interaction-PRS) and a previously published breast cancer PRS (BC-PRS) derived in the general population were evaluated in a case-control analysis comprising the 327 chest-irradiated HL patients with breast cancer and 491 chest-irradiated HL patients without breast cancer. Patients in the highest tertile of the RT-interaction-PRS had a 1.6-fold higher breast cancer risk than those in the lowest tertile. Remarkably, we observed a fourfold increased RT-induced breast cancer risk in the highest compared with the lowest decile of the BC-PRS. On a continuous scale, breast cancer risk increased 1.4-fold per standard deviation of the BC-PRS, similar to the effect size found in the general population. This study demonstrates that genetic factors influence breast cancer risk after chest RT for HL. Given the high absolute breast cancer risk in radiation-exposed women, these results can have important implications for the management of current HL survivors and future patients.

The prognostic value of the tumor-stroma ratio is most discriminative in patients with grade III or triple-negative breast cancer.

The tumor-stroma ratio (TSR) was evaluated as a promising parameter for breast cancer prognostication in clinically relevant subgroups of patients. The TSR was assessed on hematoxylin and eosin-stained tissue slides of 1,794 breast cancer patients from the Nottingham City Hospital. An independent second cohort of 737 patients from the Netherlands Cancer Institute to Antoni van Leeuwenhoek was used for evaluation. In the Nottingham Breast Cancer series, the TSR was an independent prognostic parameter for recurrence-free survival (RFS; HR 1.35, 95% CI 1.10-1.66, p = 0.004). The interaction term was statistically significant for grade and triple-negative status. Multivariate Cox regression analysis showed a more pronounced effect of the TSR for RFS in grade III tumors (HR 1.89, 95% CI 1.43-2.51, p < 0.001) and triple-negative tumors (HR 1.86, 95% CI 1.10-3.14, p = 0.020). Comparable hazard ratios and confidence intervals were observed for grade and triple-negative status in the ONCOPOOL study. The prognostic value of TSR was not modified by age, tumor size, histology, estrogen receptor status, progesterone receptor status, human epidermal growth factor receptor 2 status or lymph node status. In conclusion, patients with a stroma-high tumor had a worse prognosis compared to patients with a stroma-low tumor. The prognostic value of the TSR is most discriminative in grade III tumors and triple-negative tumors. The TSR was not modified by other clinically relevant parameters making it a potential factor to be included for improved risk stratification.

Breast cancer risk factors and their effects on survival: a Mendelian randomisation study.

BACKGROUND: Observational studies have investigated the association of risk factors with breast cancer prognosis. However, the results have been conflicting and it has been challenging to establish causality due to potential residual confounding. Using a Mendelian randomisation (MR) approach, we aimed to examine the potential causal association between breast cancer-specific survival and nine established risk factors for breast cancer: alcohol consumption, body mass index, height, physical activity, mammographic density, age at menarche or menopause, smoking, and type 2 diabetes mellitus (T2DM). METHODS: We conducted a two-sample MR analysis on data from the Breast Cancer Association Consortium (BCAC) and risk factor summary estimates from the GWAS Catalog. The BCAC data included 86,627 female patients of European ancestry with 7054 breast cancer-specific deaths during 15 years of follow-up. Of these, 59,378 were estrogen receptor (ER)-positive and 13,692 were ER-negative breast cancer patients. For the significant association, we used sensitivity analyses and a multivariable MR model. All risk factor associations were also examined in a model adjusted by other prognostic factors. RESULTS: Increased genetic liability to T2DM was significantly associated with worse breast cancer-specific survival (hazard ratio [HR] = 1.10, 95% confidence interval [CI] = 1.03-1.17, P value [P] = 0.003). There were no significant associations after multiple testing correction for any of the risk factors in the ER-status subtypes. For the reported significant association with T2DM, the sensitivity analyses did not show evidence for violation of the MR assumptions nor that the association was due to increased BMI. The association remained significant when adjusting by other prognostic factors. CONCLUSIONS: This extensive MR analysis suggests that T2DM may be causally associated with worse breast cancer-specific survival and therefore that treating T2DM may improve prognosis.

Validation of the BOADICEA model and a 313-variant polygenic risk score for breast cancer risk prediction in a Dutch prospective cohort.

PURPOSE: We evaluated the performance of the recently extended Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA version 5) in a Dutch prospective cohort, using a polygenic risk score (PRS) based on 313 breast cancer (BC)-associated variants (PRS313) and other, nongenetic risk factors. METHODS: Since 1989, 6522 women without BC aged 45 or older of European descent have been included in the Rotterdam Study. The PRS313 was calculated per 1 SD in controls from the Breast Cancer Association Consortium (BCAC). Cox regression analysis was performed to estimate the association between the PRS313 and incident BC risk. Cumulative 10-year risks were calculated with BOADICEA including different sets of variables (age, risk factors and PRS313). C-statistics were used to evaluate discriminative ability. RESULTS: In total, 320 women developed BC. The PRS313 was significantly associated with BC (hazard ratio [HR] per SD of 1.56, 95% confidence interval [CI] [1.40-1.73]). Using 10-year risk estimates including age and the PRS313, other risk factors improved the discriminatory ability of the BOADICEA model marginally, from a C-statistic of 0.636 to 0.653. CONCLUSIONS: The effect size of the PRS313 is highly reproducible in the Dutch population. Our results validate the BOADICEA v5 model for BC risk assessment in the Dutch general population.