BRCAPRO is a widely used breast cancer risk prediction model based on family history. A major limitation of this model is that it does not consider non-genetic risk factors. We expand BRCAPRO by combining it with another popular model, BCRAT, that uses mostly non-genetic risk factors, and show that the expanded model can achieve improvements in prediction accuracy over both BRCAPRO and BCRAT.Accurate risk stratification is key to reducing cancer morbidity through targeted screening and preventative interventions. Multiple breast cancer risk prediction models are used in clinical practice, and often provide a range of different predictions for the same patient. Integrating information from different models may improve the accuracy of predictions, which would be valuable for both clinicians and patients. BRCAPRO is a widely used model that predicts breast cancer risk based on detailed family history information. A major limitation of this model is that it does not consider non-genetic risk factors. To address this limitation, we expand BRCAPRO by combining it with another popular existing model, BCRAT , which uses a largely complementary set of risk factors, most of them non-genetic. We consider two approaches for combining BRCAPRO and BCRAT: (1) modifying the penetrance (age-specific probability of developing cancer given genotype) functions in BRCAPRO using relative hazard estimates from BCRAT, and (2) training an ensemble model that takes BRCAPRO and BCRAT predictions as input. Using both simulated data and data from Newton-Wellesley Hospital and the Cancer Genetics Network, we show that the combination models are able to achieve performance gains over both BRCAPRO and BCRAT. In the Cancer Genetics Network cohort, we show that the proposed BRCAPRO + BCRAT penetrance modification model performs comparably to IBIS, an existing model that combines detailed family history with non-genetic risk factors. Breast cancer is the second most common cancer and the second leading cause of cancer death in women in the U.S. ,2. IdentBRCAPRO is a family history-based model that provides carrier probabilities for breast cancer susceptibility genes BRCA1 and BRCA2 as well as future risk estimates for invasive breast and ovarian cancer. It translates family history data into risk estimates using Mendelian laws of inheritance, Bayes’ rule, and literature-based estimates of mutation prevalence and penetrance (age-specific probability of developing cancer given genotype). In contrast, BCRAT estimates an individual’s future risk of invasive breast cancer based on a relative hazard model that includes age, hormonal and reproductive risk factors, history of benign disease, and first-degree family history of breast cancer. The relative hazard model was originally trained using case-control data from Caucasian women participating in a U.S. mammography screening program. It was later updated for African-American , Asian-AThere already exist models that incorporate both detailed family history information and non-genetic risk factors, namely, IBIS   and BOADWe consider two combination approaches: (1) penetrance modification and (2) ensemble learning. While we focus on BRCAPRO and BCRAT in this paper, these approaches can be applied in general to expand any Mendelian model to include additional risk factors. The first approach modifies the penetrance functions in BRCAPRO to account for the effects of the BCRAT risk factors. We develop a penetrance modification model, BRCAPRO + BCRAT (M), using a relative hazard approach that has similarities to the one used in IBIS.Ensemble learning consists of training multiple base models and combining their predictions. A wide variety of ensemble methods have been developed, including stacking , which iWe compare the performance of the combination models to the individual BRCAPRO and BCRAT models in simulations and a data application, where we use training data from the Newton-Wellesley Hospital (NWH) and validation data from the Cancer Genetics Network (CGN). In the data application, we use IBIS as a reference for comparison in order to evaluate the strategy of developing a hybrid model from the ground up versus the strategy of combining existing models.Given a female individual without a previous diagnosis of breast cancer who presents for risk assessment (the counselee), the goal is to predict her risk of developing invasive breast cancer within BRCAPRO  estimateBRCAPRO calculates the counselee’s probability of having a given genotype using Bayes’ rule and Mendelian laws of inheritance. This calculation depends on mutation prevalence and penetrance estimates obtained from published studies , version 2.1.We ran BCRAT using the BCRA R package . We used the command line program for version 8, selecting the competing mortality option.Software for running IBIS is available at The penetrance modification approach combines BRCAPRO and BCRAT by using the BCRAT relative hazard to modify the calculation of the non-carrier future risk in BRCAPRO. Specifically, the baseline non-carrier hazard in the BRCAPRO future risk calculation is scaled by the BCRAT relative hazard based on a discrete proportional hazards model , because the modification of the hazard function induces a modification of the corresponding penetrance function. This combination approach is similar to replacing the non-carrier future risk from BRCAPRO with the future risk from BCRAT. However, it is not identical because BRCAPRO and BCRAT use slightly different baseline hazards  incorporates the BCRAT risk factors before averaging the genotype-specific risks. The advantage of the latter approach is that it allows the effects of the BCRAT risk factors to differ by genotype. Genotype-specific effects have been observed for certain BCRAT risk factors, such as age at menarche  , for a fAlternatively, we can use BRCAPRO and BCRAT predictions and their product as covariates in a time-to-event model. We consider a Fine-Gray proportional subdistribution hazards model for breast cancer, accounting for death as a competing risk , we used In the simulations and data application, we considered the binary outcome of being diagnosed with breast cancer within We used five performance measures : (1) theIn the data application, certain individuals in the validation dataset were censored before s (IPCW) ,50 to caFor the time-to-event outcome, O/E was calculated by comparing the numbers of observed and expected cases across the entire study period; for the expected number of cases E, we predicted risk up to the end of the individual follow-up time for each counselee, meaning that tatistic  is the png risks . In the ng risks ,54. We hng risks .We calculated 95% bootstrap confidence intervals (CIs) for all of the performance measures except for the time-to-event C-statistic, for which a 95% CI was obtained using perturbation resampling . For eacWe performed simulations to compare the 5-year performance of the combination models to that of the individual BRCAPRO and BCRAT models in a setting where the assumptions of the penetrance modification model hold.First, we generated each counselee’s baseline family history, consisting of (1) the family structure , (2) dates of birth, (3) genotypes, (4) cancer ages, and (5) death ages.We simulated pedigrees in order to mimic the family structures observed in real families from the CGN dataset  using the default Ashkenazi Jewish allele frequencies for BRCA1 and BRCA2 in BRCAPRO, which reflect a higher-risk population . For individuals in subsequent generations, we generated genotypes according to Mendelian inheritance.For each individual, we generated baseline breast and ovarian cancer phenotypes conditional on genotype. Age of onset was sampled from {1, 2, …, baseline age}, with probabilities provided by the genotype-specific penetrance functions from BRCAPRO. The probability of being unaffected at baseline was provided by one minus the cumulative penetrance up to the baseline age. Counselees were assumed to be alive at baseline, while for each non-counselee we generated a death age from a distribution with mean of 80 and standard deviation of 15. If an individual had an age of onset greater than their age at death, then the individual’s cancer status was changed to unaffected. Counselees with breast cancer at baseline were excluded from the analyses.We then generated baseline BCRAT covariates  by sampling values from the distribution in the CGN. Values for different covariates were sampled independently of each other. The BCRAT covariates were used to modify the BRCAPRO non-carrier penetrance to obtain the BRCAPRO + BCRAT (M) non-carrier penetrance (Equation ).For counselees who did not have breast cancer at baseline, future ages of onset were generated from the BRCAPRO + BCRAT (M) penetrances  penetrances are the same as in BRCAPRO), which were rescaled to be conditional on not having developed cancer by the baseline age. Cases were defined as counselees who developed breast cancer within five years of their baseline age. The 5-year outcomes were not subject to censoring.We simulated 100,000 families in total. After excluding 4443 counselees with breast cancer at baseline, we used the first randomly generated 50,000 counselees to train the ensemble model , we trained ensemble models for the binary outcome at 5 (Model ) and for5 (Model ). We valIn the analyses, we excluded women with any of the following conditions prior to baseline: invasive breast cancer, ductal carcinoma in situ, lobular carcinoma in situ, bilateral mastectomy or bilateral oophorectomy. In addition, we excluded women who tested positive for BRCA1/2 prior to baseline (BCRAT requirement), women The characteristics of the training and validation datasets are described below and summarized in After applying the exclusion criteria, the training cohort consisted of 37,881 women who visited the breast imaging department of NWH in Newton, Massachusetts for screening or diagnostic imaging from February 2007 through December 2009. During the initial (baseline) visit, information was collected on personal and family history of cancer, reproductive history, sociodemographic factors, and lifestyle factors. Family history was limited to relatives with cancer. Breast cancer diagnoses through 2015 were determined from the Massachusetts State Cancer Registry, Partners Hospital Cancer Registries, and patient self-reporting. The median age of the counselees was 49, with an interquartile range (IQR) of 43–58; 30,758 (81.2%) of the counselees were White, while 5684 (15.0%) had at least one affected first- or second-degree relative. The median follow-up time was 6.7 years (IQR 6.3–7.2). All counselees were followed for at least six years. There were 495 counselees (1.3%) who developed breast cancer within five years of baseline and 714 counselees (1.9%) who developed breast cancer over the course of follow-up.https://cran.r-project.org/web/packages/densratio/index.html (accessed on 20 April 2018)).Because the NWH cohort represents a general screening population and the CGN validation cohort (described below) represents a higher-risk population enriched for family history of cancer, we applied importance weights to the training data based on the distributions of the BCRAT covariates, 5-year BCRAT predictions, and 5-year BRCAPRO predictions when we fit the ensemble models. The weights were estimated using least squares importance fitting via the densratio R package  phone interview and annual follow-up updates. From 2009 onward, information was collected on reproductive history, cancer treatments, cancer screening results, and genetic testing results.The median age of the counselees was 47 (IQR 38–57); 6104 (83.5%) of the counselees were White, while 3143 (42.9%) had at least one female first-degree relative with breast cancer. The median follow-up time was 7.3 years (IQR 6.0–8.3) and 934 (12.8%) counselees were censored within five years of baseline without being diagnosed with breast cancer. Of the counselees, 159 (2.2%) developed breast cancer during follow-up, with 112 of the diagnoses occurring within five years of baseline. Demographic characteristics stratified by center are provided in Information on certain risk factors was missing or incomplete. We did not have information on atypical hyperplasia (used in BCRAT and IBIS), breast density (used in IBIS), polygenic risk scores (used in IBIS), or hormone replacement therapy (used in IBIS). Participants were asked whether they had ever had a benign breast biopsy, but were not asked about the number of biopsies   and IBIS  were well-calibrated, while BCRAT , BRCAPRO + BCRAT (E) , BRCAPRO + BCRAT (E2) , and BRCAPRO  underestimated risk. When calibration was considered by decile , 8 out oThe AUCs were 0.68 (95% CI 0.63–0.72) for the combination models, 0.67 for IBIS (95% CI 0.62–0.71), 0.66 for BCRAT (95% CI 0.61–0.71), and 0.65 (95% CI 0.60–0.69) for BRCAPRO. IBIS had the highest SNB , followed by BRCAPRO + BCRAT (M)  and the ensemble models , SNB = 0.23 and SNP = 0.23, 95% CI 0.10–0.33 for (E)). All models performed similarly with respect to the Brier score and logarithmic score. Across 1000 bootstrap replicates, BRCAPRO + BCRAT (M) outperformed BRCAPRO and BCRAT with respect to all performance measures except the Brier score in the majority of the replicates. Each ensemble model outperformed BRCAPRO and BCRAT with respect to all metrics except O/E in the majority of the replicates. Furthermore, each of the three combination models outperformed IBIS with respect to AUC, Brier score, and logarithmic score in the majority of the replicates, although IBIS had better calibration and SNB in most replicates.Among counselees who met the NCCN criteria for further genetic risk evaluation , the comThe performance measures based on the time-to-event outcome are shown in Overall, the relative performance of the models for the time-to-event outcome was similar to the relative performance for the five-year outcome; however, among counselees meeting the NCCN criteria BCRAT had worse discriminatory accuracy for the time-to-event outcome than the other models. O/E and discriminatory accuracy did not change substantially compared to Model combination is a way to systematically integrate information from different models to achieve more comprehensive and accurate risk assessment. By leveraging existing models instead of building new ones from the ground up, it is possible to save considerable time and effort, remove barriers to adoption if the ingredient models are well-accepted, and, in the case of ensemble approaches such as stacking, permit reuse of proprietary models as long as predictions can be obtained even when the full model is not available.We used model combination to expand a widely used Mendelian model, BRCAPRO, to include non-genetic risk factors from a widely used non-Mendelian model. We considered two approaches, namely, penetrance modification and ensemble learning. The penetrance modification model BRCAPRO + BCRAT (M) and the ensemble models BRCAPRO + BCRAT (E) for binary outcomes and BRCAPRO + BCRAT (E2) for time-to-event outcomes all achieved accuracy gains over BRCAPRO and BCRAT in simulations and data from the CGN, showing the value of model combination. Augmenting the family history input to BRCAPRO with non-genetic risk factors and augmenting the BCRAT risk factors with more detailed family history information both led to improvements, and could provide a better tool to users of either BRCAPRO or BCRAT as well as to clinicians who use both and then qualitatively integrate the two estimates for their patients.In data simulated under the penetrance modification model, all combination models outperformed BRCAPRO and BCRAT with respect to calibration, discrimination, net benefit, and prediction accuracy based on the Brier score and logarithmic score. In the CGN cohort, we additionally validated IBIS, an existing model that combines detailed family history with non-genetic risk factors. The penetrance modification model achieved comparable performance to IBIS overall, outperforming BRCAPRO with respect to each performance measure and outperforming BCRAT with respect to each measure except the Brier score in a large majority of bootstrap replicates. The ensemble models outperformed BRCAPRO with respect to each measure and BCRAT with respect each measure other than calibration, showing worse overall calibration than the penetrance modification model. In the subset of women with a strong family history of breast/ovarian cancer based on NCCN criteria, all combination models showed notable improvements in discrimination and net benefit over BRCAPRO and BCRAT.While the AUC gains of 2–3% achieved by the combination models over BRCAPRO and BCRAT in the entire CGN cohort may not change the clinical implications for most individuals, the net benefit measure, which aims to quantify the expected benefits versus harms of treatment and has been used to assess the clinical utility of numerous models in cancer research and other fields ,46, provBCRAT performed well in the entire CGN cohort, although it had less discrimination and net benefit than the combination models and IBIS among women with a strong family history, highlighting the importance of collecting detailed family history information for higher-risk subgroups . FurtherThe additional inputs in the combination models compared to BRCAPRO or BCRAT alone require additional data collection effort; however, models integrating detailed family history and non-genetic risk factors are already used in clinical practice (IBIS and BOADICEA), and these models use similar inputs compared to our combination models. Furthermore, missing values are allowed in our combination models, which can help to reduce the burden of data collection in clinical practice.A limitation of our study arises from missing information on BCRAT and IBIS risk factors in the CGN dataset . This could potentially have affected the discrimination of BCRAT, IBIS, and the combination models as well as their relative ranking. To mitigate this concern, we observe that the models retain relatively good discrimination that is comparable to previous studies ,16. FurtAnother limitation is that the CGN and NWH cohorts are predominantly non-Hispanic white (>80%), with <5% Black and <10% Hispanic. The combination models evaluated here do not overcome the potential limitations of BRCAPRO and BCRAT in predicting risk among racial/ethnic minorities, at least as evaluated in the current datasets. While one recent study evaluated BRCAPRO, BCRAT, IBIS, and BRCAPRO + BCRAT (M) in a diverse US cohort and found no significant difference in model performance between Black and White women , BCRAT hA further challenge is that the NWH and CGN cohorts are not representative of the same clinical population. The NWH cohort is a lower-risk cohort; as seen in The two combination approaches considered here each have their strengths and limitations. Ensembling via logistic regression calibrates the model to the training data. The penetrance modification model, on the other hand, relies on previously published estimates of prevalence, penetrance, and relative hazards. These features can be a strength or a limitation depending on how well the training dataset represents the target population. While ensembling can sometimes be successful without training weights , in our approach we used stacking to train weights on individual-level data. This opens opportunities for recalibration to improve suitability for a population different from the training population.A disadvantage of estimating ensemble weights via logistic regression is the need to estimate the censoring distribution when there are counselees in the training dataset who are censored before the last time point of interest. An advantage of ensembling is its greater flexibility compared to the penetrance modification approach. Ensembling can easily handle any number of models that can be of any form. Including additional risk factors is straightforward. The penetrance modification model requires more assumptions, as it specifically combines a model based on Mendelian inheritance with a relative hazard model. Additional risk modifiers can be incorporated as new relative hazard estimates become available; however, it is important to properly scale the relative hazards to be compatible with the hazard functions they are meant to modify and to consider whether the effects of the risk modifiers differ by carrier status. BRCAPRO + BCRAT (M) currently modifies only the non-carrier hazard function, for which it uses the BCRAT relative hazard. Future work is needed to evaluate the inclusion of modifiers of the carrier hazard functions. One more advantage of ensembling is that after the model is trained it only requires the predictions from the models being combined , and does not require the raw inputs, which are potentially less accessible than the predictions.BRCAPRO + BCRAT (M) has been externally validated in two average-risk cohorts: a large US mammography screening cohort of over 120,000 women  and an AWhile at least two breast cancer risk prediction models integrating detailed family history and non-genetic risk factors, namely, IBIS and BOADICEA, are well-validated and widely available, our work contributes to the improvement of clinical risk prediction in the following ways: (1) we have developed an expanded version of BRCAPRO that can easily be integrated in clinical and research settings where BRCAPRO is currently used, and (2) the model combination methodology proposed in this paper is applicable to a wide range of prediction problems. BRCAPRO is currently part of seven widely used and commercially available clinical tools. These have thousands of users, not all of whom have access to IBIS and BOADICEA. The proposed BRCAPRO + BCRAT (M) model has been added to the software implementation of BRCAPRO, which can facilitate its integration in clinical and research settings where BRCAPRO is used. Two useful features of BRCAPRO are the free availability of its software and code (through the BayesMendel R package) for research purposes and the option for users to specify their own values for the model parameters (through the brcaparams function in the BayesMendel R package), including modifications to the allele frequencies and penetrance instead of using the default published estimates. This provides researchers with the flexibility to tailor the model to different populations as well as an easy way to check the sensitivity of risk predictions to differing sets of parameter values. While risk calculation tools for IBIS and BOADICEA are freely available, to the best of our knowledge the code is not easily accessible and there is no option to customize and implement user-specified parameters. Furthermore, the model combination approaches we propose can be applied to many other prediction problems. Ensemble learning can be used to combine an arbitrary number of models of any type. Penetrance modification is a way to incorporate risk factors beyond family history into complex Mendelian models, including the recently developed multi-gene and multi-syndrome model PanelPro ,62, whicIn summary, we have demonstrated the feasibility of two complementary and methodologically different approaches to integrating the popular breast cancer risk assessment models BRCAPRO and BCRAT. Both combination models show accuracy improvements over the existing models, and can potentially prove effective in clinical application. In the CGN validation, BRCAPRO + BCRAT (M) achieved comparable performance to the IBIS model by leveraging the strengths of BRCAPRO and BCRAT. Additional validation of BRCAPRO + BCRAT (M) in independent prospective studies, ideally with larger and more diverse cohorts and more complete covariate information, would provide further support for clinical adoption.


The German Consortium Hereditary Breast and Ovarian Cancer (GC-HBOC) consists of 23 academic centers striving to provide high-quality regional care for affected individuals and healthy at-risk family members. According to the standard operating procedures defined by the GC-HBOC, a Familial Breast and Ovarian Cancer Center was implemented at the University Medicine Greifswald over a four-year period from 2018 to 2021, despite the COVID-19 pandemic. Genetic analyses were performed in a total of 658 individuals, including 41 males, which paved the way to local annual risk-adapted breast cancer surveillance for 91 women and prophylactic surgery for 34 women in 2021. Our experience in the North Eastern part of Germany demonstrates that it is possible to establish a high-risk breast and ovarian cancer service even in a sparsely populated region. Major facilitators are the interdisciplinary collaboration of dedicated local experts, the support of the GC-HBOC, fruitful clinical and scientific cooperations and the use of technical improvements. As a blueprint, our project report may help to further expand the network of specialized and knowledge-generating care for HBOC families. BRCA1, BRAC2, PALB2 and TP53. Therefore, these genes are referred to as high-risk genes. Other genes, such as CHEK2 or ATM, are classified as moderate–penetrance due to a lower lifetime cancer risk associated with them (The identification of a germline variant in one of the core disease genes defined by the German Consortium Hereditary Breast and Ovarian Cancer (GC-HBOC) increases significantly the lifetime risk to develop breast and ovarian cancer . It alsoith them .Until 2018, there was no Familial Breast and Ovarian Cancer Center in the North Eastern part of Germany. To establish regional integrated care with the best possible quality for affected individuals and their healthy at-risk family members, a specialized center was established at the University Medicine Greifswald according to the standard operating procedures defined by the GC-HBOC. The organization of interdisciplinary expert-level human genetics, gynecological and radiological care in sparsely populated areas is challenging though. Only five hospitals currently meet the criteria to run certified breast cancer centers (BCC) within the entire German federal state Mecklenburg-Western Pomerania , which includes whole-body magnetic resonance imaging (MRI)  and a GeFor Mecklenburg-Western Pomerania, the joint cancer registry documented an average of 1303 new female and 17 new male breast cancer cases per year c. In addIn 2018, major health insurance companies concluded contracts with the University Medicine Greifswald to cover the costs for the identification and surveillance of individuals with hereditary breast and ovarian cancer, including their at-risk relatives. Two years later, cooperations were started with the certified breast cancer center and the certified gynecological tumor center in MV’s capital city Schwerin and the certified breast cancer center at the Dietrich-Bonhoeffer Medical Center Neubrandenburg b. This pBRCA1/BRCA2 testing were excluded.We here conducted a retrospective analysis of 658 patients with fulfilled inclusion criteria of the GC-HBOC, who were either screened for pathogenic germline variants in HBOC disease genes with the TruRisk gene panel or tested for a familial mutation at the Familial Breast and Ovarian Cancer Center Greifswald between January 2018 and December 2021. Additionally, 26 TNBC cases analyzed at the University Medicine Greifswald MVZ GmbH in accordance with the AGO guidelines  were revThe standard operating procedures of the GC-HBOC were adjusted to the local conditions, and quality assurance measures were established, including accreditation of the molecular genetics laboratory according to DIN EN ISO 15189:2014 in 2018, certification of the Familial Breast and Ovarian Cancer Center according to ISO 9001:2015 in 2021, annual audits by an external company, interdisciplinary quality circles, training of the participating staff and integration of all documents into the quality management software roXtra.ATM , BARD1 , BRCA1 , BRCA2 , BRIP1 , CDH1 , CHEK2 , PALB2 , RAD51C , RAD51D , and TP53 . BRIP1 and BARD1 were included as HBOC core genes in 2018 and 2019. PTEN , and STK11  were analyzed for patients with additional signs of PTEN hamartoma tumor syndrome (PHTS) or Peutz-Jeghers syndrome (PJS), respectively. For patients with OC or with a positive family history of hereditary nonpolyposis colorectal cancer (HNPCC)-related tumors, the target region was extended to MLH1 , MSH2 , MSH6 , PMS2  and EPCAM . The Agilent SureSelectQXT enrichment kit was used for target enrichment and library preparation . The indexed library was sequenced with 2  ×  150  bp paired-read runs on a MiSeq instrument . FASTQ files were generated with the MiSeq Reporter Software (Illumina). The SeqNext module of the Sequence Pilot software  was used for read mapping, alignment, variant calling and copy number variation (CNV) analyses. Pathogenic or likely pathogenic variants were confirmed on a second DNA sample using Sanger sequencing or MLPA . For all OC patients, the exons 11 to 15 of the PMS2 gene were analyzed by Sanger sequencing after long-range PCR amplification  which was classified as pathogenic. In the following years, the BRCA2 variant was also detected in one of his sisters, who developed breast cancer at age 44, and in one of his healthy daughters. In his oldest daughter and a maternal cousin, on the other hand, the variant could be excluded by predictive analyses.The male index case III/15, who was diagnosed with multifocal, hormone receptor-positive, HER2-negative breast cancer at the age of 49 years, was tested by our laboratory in 2015 prior to our integration into the GC-HBOC. Sequence analysis for BRCA2 variant. Since the niece herself fulfilled the GC-HBOC inclusion criteria, a complete gene panel analysis was performed as a second step. NGS-based copy number variation (CNV) analysis identified a heterozygous deletion in RAD51D which was verified by multiplex ligation-dependent probe amplification (MLPA). Re-evaluation of the NGS raw data confirmed that the breakpoints were located in exon 9 and the 3’ UTR (untranslated region) of RAD51D (c.896_*505delinsT). The deletion was listed in the HerediCaRe database and was classified as pathogenic by the VUS Task Force based on cDNA analysis in the GC-HBOC. Notably, a recently published study of the Breast Cancer Association Consortium (BCAC) with more than 60,000 female BC patients and more than 53,000 controls has demonstrated that protein truncation RAD51D variants are associated with a moderately increased BC risk [Recently, the niece (IV/2) of the index patient developed TNBC at the age of 39 and presented at our Familial Breast and Ovarian Cancer Center. A targeted genetic analysis did not detect the known familial  BC risk . Thus, iRAD51D deletion was designed to save the costs of the MLPA analyses, and the variant was also found in the male index case III/15. Supplementary predictive analyses can now be offered to his daughters and further relatives.Finally, a specific PCR assay for the familial Over the last decades, we have learned much about the genetics of familial breast and ovarian cancer, gene-specific cancer risk profiles and the benefits of intensified surveillance with MRI for high-risk patients ,37. HoweOur data demonstrate that almost 35 to 40% of BC and OC patients in Mecklenburg-Western Pomerania who are expected to fulfill the GC-HBOC inclusion criteria are currently using the services offered by the new center in Greifswald . The steThe special care offered at the GC-HBOC Center Greifswald is a benefit for the patients, the participating experts and the local institutions. The interdisciplinary exchange in the newly established local genetic board, in which complex test results and risk calculations are discussed, is perceived as very positive by the participating experts from gynecology, human genetics, radiology and oncology. Furthermore, the opportunity to discuss variants of uncertain significance with the VUS Task Force, the exchange of ideas in the GC-HBOC working groups and the collaboration with colleagues from the other centers on internal quality assessments and scientific projects have also contributed to the successful establishing phase of our center and to the implementation of the latest research results into our diagnostics. An example is the establishment of the NGS-based CNV detection which has contributed to a significant reduction in the diagnostic turnaround time. As illustrated by our selected family report, this pipeline now also allows a robust CNV detection in moderate-penetrance risk genes without additional MLPA analyses.With support of the GC-HBOC, high-quality integrated care for affected individuals and their healthy at-risk relatives is now offered to patients who previously had long travel distances to the next GC-HBOC centers and, therefore, often did not take advantage of specialized care. Technical improvements, extended inclusion criteria, dedicated employees with broad experience and interpersonal collaborations were key factors to the successful implementation of a Familial Breast and Ovarian Cancer Center in the North Eastern part of Germany. For the future success of the center, it will be crucial to recruit additional qualified staff, sign contracts with more health insurance companies, complete the certification process and find new ways to provide care in a sparsely populated region in order to reach more patients.


Human leukocyte antigen (HLA) genes play critical roles in immune surveillance, an important defence against tumors. Imputing HLA genotypes from existing single-nucleotide polymorphism datasets is low-cost and efficient. We investigate the relevance of the major histocompatibility complex region in breast cancer susceptibility, using imputed class I and II HLA alleles, in 25,484 women of Asian ancestry.n = 175) with info scores greater than 0.8 and frequencies greater than 0.01 were included . We studied the associations between HLA alleles and breast cancer risk using logistic regression, adjusting for population structure and age. Associations between HLA alleles and the risk of subtypes of breast cancer  were examined.A total of 12,901 breast cancer cases and 12,583 controls from 12 case–control studies were included in our pooled analysis. HLA imputation was performed using SNP2HLA on 10,886 quality-controlled variants within the 15–55 Mb region on chromosome 6. HLA alleles . Ninety-five percent of the effect sizes (OR) observed were between 0.90 and 1.23. Similar results were observed when different subtypes of breast cancer were studied (95% of ORs were between 0.85 and 1.18).We did not observe associations between any HLA allele and breast cancer risk at No imputed HLA allele was associated with breast cancer risk in our large Asian study. Direct measurement of HLA gene expressions may be required to further explore the associations between HLA genes and breast cancer risk.The online version contains supplementary material available at 10.1007/s12282-022-01366-w. The major histocompatibility complex (MHC) region in the human genome is gene dense, highly polymorphic, and known as a hotspot for disease associations (mainly autoimmune and infectious). Mapping to the short arm of chromosome 6, the MHC region includes human leukocyte antigen (HLA) genes and plays various critical roles in regulating immune response. One such function is immune surveillance, which is an important defense against tumors .Many studies have examined HLA genotypes in the MHC region in relation to breast cancer susceptibility –4. HowevTraditional GWAS analyses do not go beyond the interrogation of individual single-nucleotide polymorphisms (SNPs). The MHC region is unique in that beyond SNPs, there is an additional layer of functional polymorphisms in the form of HLA genotypes . TransfoProbe-based genotyping commonly used in GWAS is suboptimal for querying variation in the MHC region due to its extensive polymorphic nature . HoweverWe studied 25,484 women from 12 case–control studies participating in the Breast Cancer Association Consortium (BCAC). These women were genetically Asian with known breast cancer status. Our study includes a total of 12,901 breast cancer patients and 12,583 controls . This study was approved by the ethics board of the Agency for Science, Technology and Research (ASTAR IRB Ref: 2020-154). Informed consent was obtained by the individual studies which contributed to BCAC.DNA was genotyped using OncoArray (Illumina Infinium array) , 10. A dn = 175) with info scores greater than 0.8 and frequency greater than 0.01 were selected for association analysis : 45–60) and the median age at enrollment for controls  was 51 years (IQR: 44–58) . The majority of cases (68%) and controls (81%) had at least one child. Forty-three percent of cases were post-menopausal at the time of diagnosis, a similar proportion of post-menopausal controls (45%) were recruited. Older age at menarche was observed in some studies  (Supplementary Table 4). The majority of breast cancer cases were ER-positive , HER2-negative , and stage II  (Supplementary Table 1).The median age at breast cancer diagnosis for cases n = 2,901 wasP < 5e−8) . Effect sizes  observed ranged from 0.77 to 1.25, where 95% of the effect sizes observed were between 0.92 and 1.07. Similar non-significant results were observed when subgroups of breast cancer were studied, with the smallest p-value observed for rs9784889 and HER2-negative breast cancer   and breast cancer risk reached genome-wide significance (−8) Fig. A. The sm5) Figs. .Fig. 2MaOf the 273 imputed HLA alleles, 175 had info scores greater than 0.8 and frequencies greater than 0.01; seventy-one were classic 2-digits HLA alleles and 104 were classic 4-digits HLA alleles (Supplementary Table 5). Heatmap of the 71 classic 2-digits HLA alleles by study participants did not show obvious clustering of cases and controls .P = 1.08e-3)  (Table P = 0.324) and between HLA-A*26 and late-stage breast cancer  were not significant. HLA-A*36 alleles were not imputed.Three of 14 articles identified in the literature reported associations between classic HLA class I or class II alleles and breast cancer risk (Supplementary Methods). All studies used a case–control design and HLA ascertained from blood samples. Only Leong et al. reported significant associations between HLA-A*31 and breast cancer risk (Fisher’s exact test P = 0.040) (Supplementary Table 6).Similar results were observed when different subtypes of breast cancer were studied   between variants in the MHC region  and breast cancer risk in our Asian study of 12,901 breast cancer cases and 12,583 controls  [It was suggested that the MHC region is associated with breast cancer susceptibility studies of European populations , 13. In Gourley et al.  reportedP = 0.020) as a risk allele for breast cancer in 59 invasive ductal carcinoma breast cancer patients and 77 controls without breast cancer in Malaysia. In a subset of Malaysian women in our study, HLA-A*31 was not associated with breast cancer risk . It should be noted that the Malaysia study determined HLA-A expression using the Biotest HLA-A Sequence-Specific primers (SSP), while only imputed HLA alleles were interrogated in our study [Our systematic review identified one Asian study examining the relationship between HLA class I alleles and breast cancer risk . Leong eur study .While it is conceivable that HLA genes play critical roles in immune surveillance against breast cancers, there are many other studies that show no consistent link between HLA and breast cancer . ResultsThis is the largest study to date to examine the associations between the MHC region and breast cancer risk in Asians . However, there are several limitations worth noting. Validation of the imputed HLA loci was not performed by the direct typing of HLA loci. An average error rate of between three to six percent has been reported for the prediction of high-resolution (four-digit) HLA alleles using imputation software . Due to In conclusion, imputed class I and II HLA alleles were not associated with breast cancer risk in our Asian sample. Direct measurement of HLA gene expressions may be required to further explore the associations between HLA genes and breast cancer risk.Supplementary file1 (XLSX 3996 kb)Supplementary file2 (DOCX 15 kb)Below is the link to the electronic supplementary material.


Linkage disequilibrium (LD)-based clumping was performed to identify independent candidate variants. None of the 9.7 million genetic variants tested for interactions with MHT use reached genome-wide significance. Only 213 variants, representing 18 independent loci, had p-values < 1 × 105. The strongest evidence was found for rs4674019 , which showed genome-wide significant interaction  with current MHT use when analysis was restricted to population-based studies only. Limiting the analyses to combined estrogen–progesterone MHT use only or to estrogen receptor (ER) positive cases did not identify any genome-wide significant evidence of interactions. In this large genome-wide SNP-MHT interaction study of breast cancer, we found no strong support for common genetic variants modifying the effect of MHT on breast cancer risk. These results suggest that common genetic variation has limited impact on the observed MHT–breast cancer risk association.Use of menopausal hormone therapy (MHT) is associated with increased risk for breast cancer. However, the relevant mechanisms and its interaction with genetic variants are not fully understood. We conducted a genome-wide interaction analysis between MHT use and genetic variants for breast cancer risk in 27,585 cases and 34,785 controls from 26 observational studies. All women were post-menopausal and of European ancestry. Multivariable logistic regression models were used to test for multiplicative interactions between genetic variants and current MHT use. We considered interaction p-values < 5 × 10 The use of menopausal hormone therapy (MHT) is associated with up to 23% increased risk of breast cancer. MHT use has been reduced among postmenopausal women since the report by the Women’s Health Initiative (WHI) clinical trial and observational study3 which has been subsequently confirmed by other studies and meta-analyses5. Breast cancer risk increases with longer duration of use6, and is higher for combined estrogen–progesterone MHT (EPT) use as compared with estrogen-only (ET) regimens5. Additionally, the association between MHT use and breast cancer may also differ by tumor molecular subtype. A prospective cohort study in UK found that current MHT use was associated with increased risk for estrogen receptor positive (ER+) breast cancers, but not with ER- breast cancers7. Several other observational studies also found that MHT use was associated with elevated risk of ER+ breast cancer12.Breast cancer is one of the most common cancers in women. There were 268,600 new cases and 41,760 deaths due to breast cancer estimated in the U.S. in 201914, and therefore induces mutagenesis16. Genome-wide association studies (GWAS) have identified over 200 single nucleotide polymorphisms (SNPs) that are associated with invasive breast cancer risk19. Further analyses based on these GWAS findings have identified several genes that might interact with MHT use on breast cancer risk, including SNPs regulating the fibroblast growth factor receptor two (FGFR2) gene20, as well as SNPs close to the Kruppel like factor 4 (KLF4) gene and the insulin like growth-factor-binding protein 5 (IGFBP5) gene23. A meta-analysis of four genome-wide case-only interaction studies found suggestive evidence of interactions between MHT use and SNPs in genes related to transmembrane signaling and immune cell activation24. However, none of the findings reached genome-wide significance.The biological mechanisms underlying the effect of MHT use on breast cancer risk is not fully understood. One proposed mechanism is that higher estrogen and progesterone levels increase the proliferation of breast epithelial cells, which results in accumulation of genetic mutations and insufficient DNA repairIn the present study, we performed a comprehensive genome-wide interaction analysis of current MHT use by pooling individual-level data from 26 epidemiological studies. We also performed genome-wide interaction analysis of MHT use on ER+ breast cancer specifically.23. Breast cancer cases were defined as incident invasive or in-situ breast tumors, confirmed by medical records, pathological reports or death certificates. Cases of benign breast disease or cases diagnosed more than five years before study enrollment were excluded.Individual level data were pooled from 26 epidemiological studies, including eight population-based case–control studies, 13 nested studies from prospective cohort studies and five studies with mixed design from the Breast Cancer Association Consortium (BCAC) Table . Data coParticipants were excluded if they were male, pre-menopausal, of non-European ancestry, with unknown age at reference date, or missing information on MHT use. Reference date was defined as date of diagnosis for cases, and date of interview for controls. Menopausal status was reported at time of interview. For women with missing menopausal status, we assumed postmenopausal status for those who were > 54 years old. Only studies with information on MHT use in at least 150 breast cancer cases and 150 controls were included in the data analysis.All participating studies were approved by the relevant ethics committees and informed consent was obtained from study participants.MHT use was defined as use for at least three months of any type of MHT, including EPT and ET. Current MHT use was defined as use at, or within the six months prior to the reference date. Former MHT use was defined as women who had a history of using MHT but had quit more than 6 months prior to the reference date.26 or the Illumina OncoArray 500K (OncoArray)27. Details on genotyping, imputation and quality-control checks have been published previously26. For these analyses, 9680 cases and 10,598 controls were genotyped using iCOGs, and 17,905 cases and 24,187 controls were genotyped using OncoArray. Both datasets were imputed to the 1000 Genomes Phase 3 release28. For samples that were genotyped on both iCOGs and OncoArray, OncoArray data was used. SNPs were excluded if imputation r2 < 0.5 for iCOGs, and r2 < 0.8 for OncoArray. A total of 9,661,037 genetic variants (SNPs and indels) were included for analysis in both datasets.Samples were genotyped by the Illumina custom iSelect genotyping array (iCOGs)29, thus fitting a model of the form:We used multivariable logistic regression models to test for interaction between each genetic variant and current MHT use (compared to never users) on breast cancer risk, adjusting for age at reference date, study, former MHT use, an indicator for study design , an interaction term of study design indicator and current MHT use to account for different main effect of current MHT use by study design, and principal components to account for potential population stratification30. OncoArray and iCOGs datasets were analyzed separately, and platform-specific interaction parameter estimates  was used–5), we performed linkage disequilibrium (LD)-based clumping to identify independent loci that might interact with MHT use on breast cancer risk (SWISS version 1.0.05b). SNPs in LD (r2 > 0.1 based on the build-in 1000G_2014-11_EUR) within 1 Mb from the most significantly associated SNP were removed so that independent SNPs remained in each region.For variants reaching suggestive evidence of interaction , were included in the analyses Table . Cases w–8, Fig. –5). After LD-based clumping, 18 independent SNPs remained, none of which were in LD with currently known breast cancer risk GWAS loci (Table –7). When restricting the analyses to population-based studies only , this same SNP rs4674019 showed statistically significantly interaction with current MHT use on breast cancer risk . Sensitivity analysis using population-based studies only did not find statistically significant interactions.Similarly, we did not observe any genome-wide significant interactions between SNPs and combined EPT use on breast cancer risk Fig. B. There Restricting our cases to those with ER+ breast cancer did not result in any genome-wide significant findings Figs.  and S3. In this large genome-wide analysis of postmenopausal women of European ancestry, we did not identify any genetic variants that were strong modifiers of the association between current MHT use on breast cancer risk. Although the interaction between SNP rs4674019 and current MHT use was statistically significant among population-based studies only, the variate allele frequency is relatively rare (EAF = 5%) and needs further validation.33, we found that current use of MHT, and in particular current EPT use, was associated with an increased risk of breast cancer for postmenopausal women. The mechanisms underlying this association are not fully understood. It has been hypothesized that estrogen stimulates cell proliferation through ERα-mediated hormone activity and increases mutation rates through a cytochrome P450-mediated metabolic activation that results in DNA damage34. In addition, the risk associated with ER+ breast cancer is substantially higher than for ER- breast cancer, particularly for EPT use, suggesting an ER-dependent pathway5. In vitro and in vivo studies found that estradiol and 4-OH-estradiol, metabolites of estrogen, may induce mutations and damage DNA by forming DNA adducts to bind to adenine and guanine on the DNA backbone36. The role of progestogens in human breast carcinogenesis is less clear, although it has been suggested that synthetic progestogens are pro-proliferative and may thus promote cancer cell growth38.Consistent with previous literature40. In a previous two-stage GWAS interaction analysis among ~ 2700 cases and ~ 2700 controls, five SNPs had suggestive evidence of interaction with current MHT use; but none of them reached genome-wide significance41. A meta-analysis of genome-wide case-only studies in 2920 cases also found no statistically significant interactions between SNPs and MHT use on breast cancer overall or by subtype24. Although our study had a larger sample size and increased statistical power than previous genome-wide analyses, we similarly did not find any genome-wide statistically significant interactions between genetic variants and MHT use in this study, and we further did not replicate previously suggested SNPs (data not shown).Although MHT use has been found to be associated with increased breast cancer risk in both epidemiologic and experimental studies, no published studies to date have identified genome-wide significant interactions for breast cancer risk between candidate single variants and MHT use among postmenopausal women–6). The rs4674019 SNP is an intronic variant in the coding region for the long intergenic non-protein coding RNA 607 (LINC00607). Although the functionality of long non-coding RNAs is still not clear, it has been recently recognized that abnormal expression of long non-coding RNAs may play an important role in cell cycle control and cell differentiation, which is related to cancer and neurodegenerative disease44. Expression levels of LINC00607 were found to be significantly downregulated among lung adenocarcinoma tissues, compared to adjacent tissues45. Other GWAS have shown genetic variants in the LINC00607 gene to be associated with height in people of European ancestry46. Previous evidence for long noncoding RNAs in relation to breast cancer risk is limited; but it is possible that changes in exogenous hormone levels due to MHT use result in differential expression that eventually leads to tumorigenesis.The region for which the strongest evidence of interaction with current MHT use on breast cancer risk was observed (lead SNP rs4674019), was also implicated in the analysis restricted to combined EPT use only  gene on chromosome 3. PRICKLE2 encodes a non-canonical Wnt signaling protein that mediates feedback amplification to generate asymmetric planar cell polarity (PCP) signaling47. The Wnt pathway has been found to be activated in more than half of breast tumors, and is associated with lower overall survival for breast cancer patients48. In particular, the upregulation of the Wnt/PCP pathway has been suggested to be associated with more malignant phenotypes, such as abnormal tissue polarity, invasion and metastasis49. Exposure to estrogen has been associated with accelerated tumor formation in ER-knockout/Wnt-1 mice36. It is plausible that MHT acts partially through the alternative Wnt pathway rather than ER-dependent pathways to promote breast tumor development.We also observed suggestive evidence of interaction between current use of both MHT and EPT and rs146251672. SNP rs146251672 is located in the intronic region for the prickle planar cell polarity protein 2  was also not available among the study participants, although the statistical power might be further limited since the main association of ET and breast cancer risk is much smaller than EPT useIt is important to note that the lack of statistical interaction, on the log-scale, does not necessarily imply a lack of biological interaction. The results are consistent with a model in which the effects of genetic variants and MHT use combine multiplicatively on risk, which could still indicate important interactions at a functional level. Overall, our results suggest that it is not necessary to include interaction variables for G × MHT use in development of breast cancer risk prediction models. Although our results suggested that potential interaction effect between SNP rs4674019 and current MHT, further validation is needed. Several suggestive interactions also warrant further investigations in independent studies.In this large genome-wide SNP-MHT interaction study of breast cancer, we found no strong support for common genetic variants modifying the effect of MHT on breast cancer risk. These results suggest that common genetic variation has limited impact on the observed MHT–breast cancer risk association.Supplementary Information.


BRCA1 and/or BRCA2 genes. Women with BRCA mutations are at a significantly increased lifetime risk of developing OC, often presenting with a high-grade serous pathology, which is associated with higher mortality due to its aggressive characteristic. Therefore, a targeted, cost-effective approach to prevention is paramount to improve clinical outcomes and mortality. Current guidelines offer multiple preventive strategies for individuals with hereditary OC (HOC), including genetic counselling to identify the high-risk women and risk-reducing interventions (RRI), such as surgical management or chemoprophylaxis through contraceptive medications. Evidence for sporadic OC is abundant as compared to the existing dearth in the hereditary subgroup. Hence, our review article narrates an overview of HOC and explores the RRI developed over the years. It attempts to compare the cost effectiveness of these strategies with women of the general population in order to answer the crucial question: what is the most prudent clinically and economically effective strategy for prevention amongst high-risk women?Ovarian cancer (OC) is the most lethal gynaecological malignancy. The search for a widely affordable and accessible screening strategy to reduce mortality from OC is still ongoing. This coupled with the late-stage presentation and poor prognosis harbours significant health-economic implications. OC is also the most heritable of all cancers, with an estimated 25% of cases having a hereditary predisposition. Advancements in technology have detected multiple mutations, with the majority affecting the  Globally, ovarian cancer (OC) is the eighth most common cancer among women and the eighteenth most common cancer overall . With arTP53 mutations, whereas type I have specific mutations targeting cell signalling pathways, which in turn unsettle BRCA expression, namely KRAS, BRAF, ERBB2, CTNNB1, PTEN, PIK3CA, ARID1A, and PPP2R1A [Primary OC can be categorised into non-epithelial and epithelial, germ cell, and sex cord-stromal cancer, with epithelial being the most common. Non-epithelial accounts for approximately 10% of all OC and includes mainly germ cell tumours, sex cord-stromal tumours, and some extremely rare tumours ,5. Germ  PPP2R1A ,10. Sero PPP2R1A . The rec PPP2R1A . As the  PPP2R1A .BRCA1 mutation carriers and 20–30% in BRCA2 mutation carriers, which is significantly higher than the general population [OC aetiology can be categorised into sporadic and hereditary. Approximately 23% of OC has a hereditary element, with the majority of those caused by defects within the BRCA DNA repair genes . It is epulation . Severalpulation ,16. Thespulation . Genomicpulation ,19,20.Given the lack of evidence to support screening in high-risk individuals, a preventative approach, usually in the form of surgery or chemoprevention, is the first line of management in these women ,27,28,29This review paper aims to explore the aetiology and risk factors of HOC. Current preventative strategies were analysed for their clinical and economic impact to determine the most clinically and economically effective strategy for OC prevention amongst high-risk women.HOC constitutes almost a quarter of all epithelial OC cases . Family HOC is also comprised of hereditary cancer syndromes (HCS), with mutations inherited in an autosomal dominant (AD) fashion leading to multiple primaries presenting at a young age. The two principal syndromes accounting for at least 20% of all epithelial OC are hereditary breast and ovarian cancer syndrome (HBOC) and Lynch syndrome (LS), also known as hereditary non-polyposis colorectal cancer syndrome (HNPCC) ,37.BRCA1 and BRCA2 tumour-suppressor genes [BRCA1 is thought to be 0.07–0.09% and for BRCA2 0.14–0.22% [BRCA1 and BRCA2 is 40% and 20% and 49 to 53 years and 55 to 58 years, respectively [BARD1, BRIP1, CHEK2, MRE11A, MSH6, NBN, PALB2, RAD50, RAD51C, or TP53 -based multigene panels [BARD1 gene showed one novel and three previously known genomic alterations in Ratajska et al.’s cohort of 255 unselected OC cases. These were almost nil in their control group, thus highlighting their pathogenic potential [BRIP1 mutation increases OC risk by 8-fold and decreases lifespan by almost four years [PALB2 gene mutation is prevalent in up to 4% of BRCA-negative HBOC cases. Yang et al. found a significant association between PALB2 pathogenic variants and OC  [RAD51C gene is prevalent in up to 2.9% of HBOC families negative for BRCA1 and/or BRCA2 mutations. Meindl et al. found six pathogenic variants in RAD51C among 1100 German families, yielding a relative risk of six for developing OC [RAD50 and MRE11A are constituents of the MRE11 complex. Heikkinen et al. identified germline mutations in RAD50 and MRE11A among 151 HBOC families [NBN gene was very low (0.2%), hence not contributing significantly to OC risk [MSH6, MLH1, and PMS2 were associated with a prolonged overall survival in OC. That supports the potential positive prognostic value of MMR genes in OC patients treated with platinum-based chemotherapy.HBOC constitutes approximately 80% of HOC and 15% of epithelial OC cases . Within or genes . These e14–0.22% . The lifectively ,40. More or TP53 . BARD1, e panels . The BARotential . The BRIur years . The PALt three) . The RADoping OC . RAD50 afamilies . Meanwhi OC risk . In epit OC risk . FurtherMSH2 (38% cases), MLH1 (32%), PMS2 (15%), and MSH6 (15%) [BRCA mutation survival [LS is the second commonest cause of HOC responsible for approximately 15% cases and 4% of epithelial OC cases . It primH6 (15%) . Grindedsurvival .TP53, PTEN, STK11, CDH1, and NF1 genes, respectively [Other rarer syndromes concerning HOC include Li–Fraumeni syndrome, Cowden syndrome, Peutz–Jeghers syndrome, diffuse gastric cancer syndrome, and neurofibromatosis type 1 syndrome. These arise primarily due to mutations in the ectively . Figure BRCA gene. Although genetic testing is widely recommended to determine the probability of inheriting a malignant condition, only ~30% of women undergo it. The concept of cascade testing involves testing an affected individual for a pathogenic hereditary variant. This, in turn, is extended to unaffected blood relatives once the specific variant is identified [As mentioned above, the most commonly identified genetic mutation leading to HOC is in the entified .Genetic counselling is a multi-stage process by which individuals at risk of hereditary cancers are identified and educated regarding probability of acquisition and passing it on to the future generation. Genetic counselling is of paramount importance in HOC, as early identification of mutations can have both preventive as well as therapeutic implications, i.e., screening and/or risk-reducing interventions (RRI) ranging from chemoprevention to risk-reducing surgery (RRS) .The concept of multimodality screening for OC in postmenopausal women among the general population gained popularity after two landmark trials—the US-based Prostate, Lung, Colon, and Ovary (PLCO) Cancer Screening Trial (1993–2001) and then the UK-based Collaborative Trial of OC Screening (UKCTOCS) (2001–2005) ,54,55,56Multimodality screening incorporates a blood test, i.e., serum biomarker cancer antigen 125 (CA125), and imaging test, i.e., transvaginal ultrasound (TVS). In the PLCO, these tools were used individually . HoweverOC screening has relatively poor outcomes for early detection or prevention as evident from PLCO and UKCTOCS ,54,55,56Both the UKCTOCS and PLCO have demonstrated a lack of evidence for support of screening methods to significantly affect mortality ,54,55,56BRCA mutations at a younger age [Hormonal chemoprevention is primarily aimed at patients who have been diagnosed with a nger age .COCP usage inhibits ovulation. This reduces the number of ovulation cycles in a woman’s lifetime, thereby decreasing the overall exposure to female hormones. This in turn theoretically decreases the risk of OC, and hence, COCP have been used as a prophylactic option for OC. Narod et al. showed that patients who take COCP for any length of time carried reduced risk of OC by approximately 50%. This figure increased to 60% after 6 years of continuous COCP use [BRCA1 and/or BRCA2 mutation carriers. They showed a 36% risk reduction in OC for every 10 years of COCP use. Importantly, this cohort did not show any association with breast cancer—this link was shown only in COCP formulations that were used prior to 1975, and more recent formulations have not shown a significant association [A meta-analysis of 18 case-control and retrospective cohort studies (1503 OC cases) showed that the risk of OC was significantly reduced in COCP users vs. non-COCP users in ociation .The largest pooled data on COCP users demonstrated a prevention of approximately 200,000 diagnoses of OC worldwide, leading to a prevention of 100,000 deaths. Large meta-analyses and systemic reviews have shown a strong benefit of COCP use, demonstrating an odds ratio (OR) of 0.73  0.66–0.81) and a lifetime reduction risk of 0.54%. These pooled datasets, however, have not differentiated between BRCA-positive and non-BRCA patients .BRCA mutation carriers [The clear benefit of COCP needs to be weighed up against theoretical risk of breast cancer, as they have shown to mildly elevate the risk of breast cancer in the general population. However, studies have proven inconclusive on this link for carriers ,64. BaseP53 and has been shown to possess anti-proliferative, anti-metastatic properties against OC cells in vitro. These findings have not been translated to clinical trials yet. A prospective nationwide cohort study indicated that the use of progestogen only products did not significantly reduce the risk of OC. No large studies have been conducted on the effects of POP in high-risk BRCA positive individuals thus far; therefore, it remains to be seen whether this intervention may be used in the future to protect BRCA carriers from ovarian cancer [Progestin-only pills (POP), etonogestrel subdermal implants, and injectable depot medroxyprogesterone acetate (DMPA) may have a protective role against OC. Progesterone increases the expression of the tumour suppressor gene n cancer .BTL for sterilisation has been shown to reduce risk of OC. However, there are limited studies on applying BTL to BRCA carriers. In the BRCA1 population with previous BTL, Narod et al. in 2001 demonstrated a 39% overall risk reduction in developing OC. This decreased to a 28% risk reduction with concomitant COCP usage. These risk-reducing effects of BTL were not reproducible for BRCA2 carriers . A 2011 The aforementioned protective effect can be due to a mechanical barrier blocking the retrograde flow of carcinogens from the vagina or perineum. More specifically, epithelial cells embryologically derived from the Mullerian ductal system including FT and endometrium can predispose to endometrioid or serous variants of OC. Prevention of their ascent courtesy BTL are in sync with Cibula et al.’s results .In their meta-analysis, Rice et al. showed the relative risk amongst BRCA patients with vs. without BTL was not statistically different amongst the general population (risk ratio (RR) 0.64 vs. 0.7). Although results show promise, long-term implications of the procedure have not been well-documented, especially in BRCA-positive patients .RRBSO is considered the gold-standard treatment in BRCA positive patients for prevention of OC. This is based on the traditional hypothesis that the ovarian surface epithelium inclusions occurring during ovulation are subject to cellular metaplasia, leading to various subtypes of OC. OC once initiated would then continue disseminating via the FT to the other gynaecological organs and peritoneal cavities. A prospective study by Kauff et al. have shown 70–85% reduction in OC and overall significant reduction in mortality . RebbeckThe optimal age for RRBSO of 35 to 40 years is primarily based on the positive outcomes of the aforementioned studies as well as the relatively increased risk of developing BRCA1-related OC after 40 years. Interestingly, RRBSO can be delayed in BRCA2-related OC cases, as their relative risk of malignancy does not start until aged 50. The rate of OC is low under 40 but reaches approximately 10% by age 50 in BRCA 1 carriers. In BRCA 2 carriers, this remains low until aged 50 ,70.Despite RRBSO being the standard RRS, it is not without its risks. The procedure induces a surgical menopause and oestrogen lack on average 10 years earlier than those who have their ovaries intact . Long-teOne of the more popular theories of epithelial OC tumour precursors originating in the 1990s has an extra-ovarian origin, namely from the fimbrial end of the fallopian tube epithelium, which constitutes the tubo-ovarian complex. These are primarily serous tubal intraepithelial carcinomas (STIC). Labidi-Galy et al. performed whole-genome sequencing and copy number analysis of laser capture micro dissected fallopian tube lesions in BRCA-related OC patients post RRBSO. The majority of tumour-specific alterations were prevalent in STIC, and a window of 7 years between development of STIC to epithelial OC was noted .Based on this theory, Faulkner et al. showed a 50% risk reduction for OC in favour of RRBS alone . RRBS isHysterectomy is slowly emerging as a RRS to prevent OC. According to Rice et al., the protective effect can be due to prevention of retrograde flow as mentioned prior. Another theory can be the “screening effect”, i.e., surgeons removing possible pre-malignant lesions on direct visualization. Cutting off blood supply to the ovary would decrease the oestrogen production and hence reduce overall hormone exposure, implying another protective mechanism .A Canadian population-based retrospective cohort compared outcomes of 43,931 low-risk women from 2008–2011 that underwent hysterectomy with and without RRBSO/RRBS/BTL. With regards to surgical outcomes, these hysterectomy-based approaches proved to be feasible, safe, efficacious, and had minimal complications . HoweverA wide range of practice guidelines, protocols, and recommendations regarding genetic testing have been formulated by various professional organisations for the high-risk OC population who would benefit from genetic counselling and preventive strategies. Select guidelines are covered in this section and are depicted in BRCA mutation [The SGO primarily looked at HBOC and LS. They recommended genetic testing and thereafter genetic counselling for all women at increased predisposition for OC due to personal or family history. These included cases with high-grade epithelial OC/tubal/peritoneal cancer; breast cancer ≤ 45 years/≤ 50 years with a limited family history; breast cancer with one first-degree relative having breast cancer ≤5; 0 years or with epithelial OC/tubal/peritoneal cancer at any age; breast cancer with ≥2 first-degree relatives having breast cancer at any age or pancreatic/aggressive prostate cancer; triple-negative breast cancer ≤ 60 years; breast cancer and Ashkenazi Jewish (AJ) ancestry; and two breast primaries with first one diagnosed before 50 years. Also included in this cohort are women unaffected with cancer but with first-degree relative diagnosed with any of the aforesaid factors or with male breast cancer or with known mutation .The SGO also recommends genetic assessment for women with a high likelihood for LS. They include ones with endometrial or colorectal cancer with evidence of microsatellite instability or loss of dMMR protein ; first-degree relative affected with endometrial or colorectal cancer either diagnosed before 60 years or at risk for LS; first- or second-degree relative with a known MMR gene mutation . TechnicThe SGO did not yield any evidence to support screening. They advocated usage of COCP in HBOC. RRBSO was recommended between 35 and 40 years as a standard of care. RRBS was to be considered if RRBSO was declined although it would not act as a substitute due to offering only OC and nil breast cancer risk reduction .BRCA1 and/or BRCA2 variants. If positive, then genetic counselling with regard to screening and RRI options was deemed mandatory. In the event of individuals declining testing or counselling, the same screening recommendations as for BRCA mutant carriers are to be followed. All BRCA carriers should be encouraged to attend high-risk follow up clinics. The aforesaid were level evidence V and grade recommendations B (V B) [The main area of interest for ESMO was HBOC. They recommended genetic testing for all women above 25 years of age hailing from families harbouring pathogenic  B (V B) .The ESMO considered COCP to be a risk-reducing measure (II C). They advocated 6-monthly multimodality screening from the age of 30 years as a screening measure (V C). Similar to SGO recommendations, the ESMO also advocated RRBSO from age 35 to 40 years (II B), as it was the most effective RRI for OC (IA). They did not recommend RRBS alone outside the clinical trial setting (V C) .BRCA mutation and multigene panel testing (level C). According to the ACOG, RRBSO is the sole intervention to reduce OC-specific mortality and should be implemented in BRCA1 carriers aged 35 to 40 years and BRCA2 carriers aged 40 to 45 years. They used TVS or serum CA125 as tools more for short-term surveillance rather than screening at 30 to 35 years of age before they could have RRBSO (level C) [The ACOG published guidelines on both HBOC and LS. On the basis of consistent scientific evidence, they recommended genetic counselling for all women with epithelial OC and those with personal or family history of breast cancer or OC (level B). On the basis of consensus, they recommended genetic testing in women where detailed risk assessment revealed a high probability of an inherited cancer syndrome. The recommended testing modalities of HBOC were level C) .With regard to LS, they recommended genetic testing in all women with endometrial or colorectal cancer irrespective of age of diagnosis and also those with a positive family history (level B). For unaffected females having a first-degree relative with endometrial or colorectal cancer diagnosed before 60 years or those with positive personal/family history, genetic risk assessment was advised (level B). They also advocated RRBSO and total hysterectomy as a potent risk-reducing modality for the aforesaid women in their 40s (level B) .BRCA and LS genes (level B/C). In the event of suspicious LS with no proven LS-associated pathogenic variant on NGS, the MICG recommended searching for association with other somatic or germline variants (level B) [Meanwhile, the MICG concentrated on LS. They recommended screening for LS in OC patients who were diagnosed ≤50 years or at any age if having non-serous and non-mucinous histology (level C). Regarding methodology of screening, they strongly recommended NGS, which would include level B) .Akin to the guidance mentioned aforesaid, the MICG strongly recommended that RRBSO and risk-reducing hysterectomy (RRH) should be offered in MMR pathogenic variants at 35 to 40 years of age following completion of family/childbearing (level B). Additionally, women undergoing the above are to be offered oestrogen-only hormone replacement therapy (HRT) until natural menopause (level B) .With regard to chemoprevention, they passed a level B recommendation for COCP usage to reduce risk of OC and endometrial cancer and a level A recommendation for aspirin to reduce risk of colorectal cancer in all MMR variants .BRCA mutations (level B). The Ontario Family History Assessment Tool, the Manchester Scoring System, the Referral Screening Tool, and the Pedigree Assessment Tool are some examples of risk assessment tools used. They recommended against risk assessment/counselling/testing in women without personal or family history of the aforesaid (level D) [HBOC was the focus for the USPSTF. They recommended familial risk assessment and,, accordingly genetic counselling and/or testing for women with a personal or family history of breast/ovarian/tubal/peritoneal cancer or pedigree with level D) .BRCA1 and/or BRCA2 and other susceptibility testing for all patients diagnosed with epithelial OC irrespective of personal or family history. If found negative on germline testing, then somatic BRCA1 and/or BRCA2 or likely pathogenic variant testing is advocated. First- or second-degree relatives of aforesaid women with positive germline mutation are to be offered risk assessment, genetic counselling, and testing. Strength of the two aforesaid recommendations were strong. They also recommend offering somatic testing for MMR to women diagnosed with any histologic variant of epithelial OC, with strength being moderate [The ASCO also focused on HBOC. They recommended germline moderate .BRCA1, BRCA2, CDH1, PALB2, PTEN, and TP53 was recommended. In terms of HBOC, testing criteria included individuals with positive personal history of cancer, i.e., epithelial OC/exocrine pancreatic cancer at any age or breast cancer with the following clauses. They include breast cancer diagnosed at any age with a AJ ancestry/≥1 first-/second-degree relative with breast cancer < 50 years or OC; pancreatic or prostate cancer at any age/≥3 cases of breast cancer, including individual and close relatives; breast cancer diagnosed at age ≤ 45 years or ≤60 with triple-negative breast cancer; breast cancer diagnosed at age 46 to 50 years with unknown family history; second breast cancer diagnosed at any age or ≥1 close relative with breast/OC/pancreatic/prostate cancer at any age. With regard to Li–Fraumeni syndrome, testing was recommended for individuals with pathogenic TP53 variant or who met classic Li–Fraumeni syndrome or Chompret criteria [The primary interest of the NCCN was HBOC and Li–Fraumeni syndrome. Testing for criteria .BRCA1 variants and 40–45 years in BRCA2 counterparts upon family completion. In the event of RRBSO being declined, multimodality screening commencing at 30 to 35 years of age warranted consideration [If criteria for HBOC were met, and testing was positive for pathogenic variants, genetic counselling for RRI primarily RRSO was mandatory. The NCCN recommended RRBSO at 35–40 years in deration .They recognised the OC risk reduction due to COCP usage but noted conflicting breast cancer risk data. Hence, they expressed the need for large prospective trials to identify the conflicting relationship before passing a strong recommendation .The cost of treatment per patient with OC remains the highest among all cancer types. As an example, the average initial cost in the first year can amount to around USD 80,000, whereas the final year cost may increase to USD 100,000 . Over thBased on data from the PLCO Trial, Drescher et al. found that annual screening using rising CA125 to predict candidates for TVS yields a mortality reduction of 13% and incremental cost-effectiveness ratio (ICER) of USD 89,000 per year of life saved (YLS). This was a better proposal than semi-annual screening with a higher mortality reduction (20%) but with lower cost effectiveness, i.e., ICER of USD 117,000/YLS .Kearns et al. analysed the cost effectiveness of sequential ROCA based multimodal screening in the UK setting, based on the UKCTOCS Trial. Compared to TVS alone, multimodal screening was more effective and less expensive. Compared to no screening, multimodal screening was of course more effective and expensive, generating an ICER of almost GBP 9000 per quality-adjusted life years (QALY) .Menon et al. performed a within-trial (UKCTOCS) economic evaluation of multimodal screening vs. no screening. Keeping the CA125-ROCA unit cost of GBP 20 per patient, multimodal screening had an ICER of around GBP 90,000 per life years gained (LYG) compared to no screening. This figure down trended to GBP 78,000 when the unit cost was lowered to GBP 15 per patient . Moss etThe aforesaid health economic analyses therefore yielded similar results ,82,83. CAs discussed previously, most of the high-grade serous OC are noted to originate from the fallopian tube ,85. ThisWomen with HOC risk comprise of BRCA mutation carriers, LS carriers, those with a strong family history or high individual familial risk, and those belonging to certain Jewish populations.BRCA1 and/or BRCA2 . It thus proved a considerable alternative to avoid the adverse effects of RRBSO [As discussed above, BRCA mutation carriers have a significant lifetime risk of OC and breast cancer. Therefore, RRS as a preventive strategy has been deemed beneficial. Grann et al. offered RRS including risk-reducing bilateral oophorectomy (RRBO)/risk-reducing bilateral mastectomy (RRBM) to their cohort of 30-year-old BRCA carriers, whom they followed-up for 50 years. Compared to surveillance, RRBO improved survival by 0.4 and 2.6 years in the low-risk and high-risk models, respectively. The high-risk model also yielded QALY of 0.5 in favour of RRBO . Andersoof RRBSO . A Germaof RRBSO .As discussed previously, women with LS/HNPCC are at a lifetime risk of OC and endometrial cancer. Taking this into consideration, screening and RRS, i.e., RRH + RRBSO, have been recommended as prevention strategies. Kwon et al. compared five RRI in their cohort of LS carriers, namely combined strategy , screening only from 30 years, RRH + RRBSO at 40 years, and 30 years and no RRI. The combined strategy was found to be the most cost-effective with an ICER of USD 195,000 per QALY . In anotBRCA1 and/or BRCA2 mutation. Knowledge of this paves the way for planning preventive strategies and estimate absolute risk reduction [We earlier discussed about family history of cancer being the strongest predisposing factor and raised the importance of genetic testing and genetic counselling concerning eduction ,97. Hoskeduction . A similBRCA mutational burden of 2.5%. Akin to the Muller et al. strategy, Grann et al.’s screen and RRBM + RRBSO group turned out to be the most cost-effective among the other RRS. The ICER and average survival when compared to no screen was around USD 21,000 per LYG and 38 days, respectively [BRCA mutational burden of ≥10%, thus amounting to 0.11 million. They were offered RRS in terms of RRBSO or RRBM. Population-based genetic screening was compared to family-history-based screening. It reduced OC incidence by 0.34% or 276 cases. Average survival was prolonged by 33 days (0.1 QALY or 0.09 LYG). The ICER was GBP 2079 per QALY [The AJ population has an extremely significant ectively . Rubenstectively . A similper QALY . Interesper QALY .BRCA prevalence of 0.7% and presence of founder mutations from the AJ population, cannot be ignored [BRCA testing in Jews irrespective of Ashkenazi/Sephardi descent [The SJ population, with an overall  ignored . Referen ignored , Patel e descent .OC remains a deadly cancer with poor prognosis. Public health strategies for OC prevention and early treatment are paramount to improve disease outcomes. There are still no effective tools for general population screening. This is also reflected economically, with mixed results from several studies analysing the cost effectiveness of screening programmes. Improvements in genetic testing have aided the identification of women at higher risk of developing OC. There is a lack of clear consensus in guidelines on the optimum time and age for prophylactic surgery or genetic counselling services. Nevertheless, it is clear that prophylaxis is effective at reducing OC incidence and mortality. Furthermore, the literature suggests a clear economic benefit in prophylactic measures within high-risk groups. Surgical prophylaxis, namely BSO, constitutes the main management option, boasting the most favourable outcomes and superior cost effectiveness. However, this comes with the risks and long-term complications of the procedure, which is an important consideration given that the literature suggests increased clinical benefit and cost effectiveness when carried out earlier in life. Whilst chemoprevention may be an alternative to young women who wish to preserve their fertility, there is currently limited evidence on its economic impact. Given the complexity and uniqueness of each patient, including associated risks for surgical complications, a personalised management is mandated through multidisciplinary team discussion that takes into consideration the fertility, mental wellbeing, endocrine health, and gynaecologic health of each patient.


The World Health Organisation (WHO) launched the Global Breast Cancer Initiative (GBCI) in 2020 intending to reduce global breast cancer mortality by 2.5% per year until 2040, thereby averting an estimated 2.5 million deaths. In this study, we aimed to determine the coverage and socio-economic inequalities in the screening for breast cancer over one decade before the establishment of the GBCI.For each country, using STATA 16 software and sampling weights, we analyzed the datasets of Demographic and Health Surveys (DHS) that included questions on breast cancer screening and were conducted between 2010 and 2019 in low- and middle-income countries. We included women aged 15-49 years and considered screening using breast self-examination (BSE), clinical breast examination (CBE), and mammography. Absolute and relative inequalities were determined using the Slope Index of Inequality (SII) and Concentration Index (CIX) respectively.P value .015). For the CIX and SII for screening using mammography, the inequalities were pro-rich in all the countries.A total of 18 surveys from 13 countries were included in this study. Only six surveys from five countries measured the rates of screening by mammography which ranged from 5.58% to 12.96%. Considering screening using any method, the proportion that had ever screened for breast cancer ranged from 2.53% to 60.21%. Higher rates of screening were seen in upper-middle-income countries compared to low-income countries. For the CIX for screening using any method, the inequalities were pro-rich in all the countries except the Philippines where it was pro-poor with a CIX of –2.84 (There exist socio-economic disparities in the coverage of breast cancer using mammography, clinical breast examination, and breast self-exam. There is a need to address these disparities to achieve the targets of breast cancer control by the GBCI.


However, Chinese American participants’ understanding of BRCA testing was significantly lower than that of NHW participants (p = 0.030). Our findings suggest that a disparity exists in BRCA testing knowledge between Chinese American and NHW breast cancer patients. Genetic education and counseling are needed to improve BRCA testing knowledge and uptake among Chinese American breast cancer patients.Breast cancer is the most commonly diagnosed cancer among Chinese American women. Knowing the BRCA1 and BRCA2 (BRCA1/2) gene mutation status can improve breast cancer patients’ health outcomes by guiding targeted treatment towards preventing breast cancer recurrence and other BRCA-related cancers. Nevertheless, it is unclear if there is a disparity in knowledge and use of BRCA testing among Chinese American breast cancer patients. This cross-sectional study investigated the possible presence of differences in the knowledge and the use of BRCA testing between Chinese American and Non-Hispanic White (NHW) breast cancer patients. We surveyed 45 Chinese American and 48 NHW adult breast cancer patients who had been diagnosed with breast cancer within the previous two years through telephone interviews. The results showed that race was not statistically related to the use of BRCA testing. BRCA testing utilization was associated with family history ( The incidence of breast cancer, the most common cancer among women in the United States (U.S.), has continued to increase in recent years . ApproxiCurrently, leading agencies suggest that BRCA testing could be offered (after genetic counseling) to adults who have blood-related family members with harmful BRCA1/2 gene mutations, have a family history of BRCA-related cancers, or have a personal history that suggests an elevated risk of carrying pathogenic BRCA mutations  ,9,10.For many breast cancer patients, genetic testing can be beneficial for identifying BRCA gene mutations, guiding targeted treatments, informing patients and healthcare providers to take effective action in preventing the recurrence of breast and other BRCA-related cancers, and sharing BRCA testing results with family members ,11. HoweAsian Americans are the fastest-growing racial or ethnic group in the US , and canAlthough the above studies report a disparity in BRCA testing utilization and knowledge between Black, Hispanic and NHW breast cancer patients, it was unclear if such a disparity also exists between Asian American and NHW breast cancer patients. The prevalence of the BRCA1 and BRCA2 mutations among Asian Americans with strong personal and/or family history of breast cancer was about 11.5% and 13%, respectively . DespiteThis study used survey data from a mixed-method research project that was designed to explore treatment decision-making among Chinese American and Non-Hispanic White breast cancer patients in Southern California . The resPotential participants were identified through the Surveillance, Epidemiology, and End Results (SEER) cancer registry in Southern California and from community clinics. The inclusion criteria of participants were women who: (1) had been diagnosed with breast cancer within two years from the time of enrollment (from 2013 to 2015), (2) were 18 years of age or older, and (3) self-identified as Chinese or NHW. The exclusion criterion was for individuals who had a history of other cancers. Trained bilingual (Mandarin/Cantonese and English) research team members recruited participants through phone calls and in-person invitations in the community clinics.Survey data were collected through two telephone interviews. The interviews were conducted over two weeks to decrease the burden placed upon participants and the time required to respond to survey questions. These interviews were conducted in the participant’s preferred language . Of 181 eligible patients, 98 (48 Chinese Americans and 50 NHWs) consented to participate, with 93 (45 Chinese Americans and 48 NHWs) completing both interviews.The measures for the outcome variables (use of BRCA testing and BRCA knowledge) and covariates (family history of breast cancer and participant characteristics) are shown as follows:Use of BRCA testing. A brief introduction to BRCA testing was first provided to the participants in the survey. Next, we included a question asking whether participants had ever utilized BRCA testing in the past BRCA knowledge. A seven-item BRCA knowledge questionnaire, developed by Peters et al. (2005) with three answer options , was used to test participant knowledge about BRCA testing . An examFamily history of breast cancer. Participants were asked if they had any family members  who had been diagnosed with breast cancer. Participant characteristics. Patient-reported demographic information was collected, describing their age, place of birth, educational level, marriage status, annual household income, and health insurance coverage. Additionally, the acculturation level of Chinese American participants was measured from a valid language acculturation scale using four questions that asked them to characterize their English speaking, writing, reading, and listening proficiency into five levels from 1 = “not good at all” to 5 = “very good” . A mean t-test and Chi-square tests were used to compare the differences between Chinese and NHW participants’ characteristics. Then, we applied bivariate analysis  to explore the associations between dependent variables (use of BRCA testing and BRCA knowledge), and independent variables . A binary backward logistic regression analysis was performed based on the results of the bivariate analysis to include statistically significant independent variables with the dependent variable (use of BRCA testing (p < 0.05) [p-value ≤ 0.2 were included in the final model following the recommendations [p-value > 0.2) to investigate possible associations between the use of BRCA testing and the statistically significant independent variables based on the bivariate analysis results. Linearity, normality, and homoscedasticity assumptions for the linear regression were also examined. The annual household income was not included in the final logistic and linear regression models due to multicollinearity with the employment status. For multiple regression analysis with five and six independent variables, a sample size of 90 and 98 is required to detect a medium effect with a power of 0.8, respectively [SPSS  was used to conduct the data analysis. Descriptive statistical tests were used to analyze each participant’s use of BRCA testing, BRCA knowledge, family history of breast cancer, and demographic data.  < 0.05) . The Hosndations . Additioectively .p = 0.009). There were significant differences between NHW and Chinese American participants regarding education levels (p = 0.001). While 91.7% of NHW participants had more than a high school education, only 57.8% of Chinese American participants received higher education. Additionally, the income levels between the two race groups were also significantly different (p = 0.002). A higher proportion of Chinese American participants (59.0%) had a lower income level  compared to NHW participants (21.7%).About 68.9% and 62.5% of Chinese and NHW participants were married, respectively. All participants reported being covered by health insurance, with 60.0% of Chinese American participants and 72.9% of NHW participants being covered by private health insurance. The employment rates of Chinese and NHW participants were 44.4% and 43.8%, respectively. Approximately one-third of Chinese participants (34.1%), and half of NHW participants (50.0%) reported that they had a family history of breast cancer. Only 4 (9.3%) Chinese and 8 (17.0%) NHW participants responded that they had family members who had used BRCA testing before. A total of 53.5% of Chinese American participants were found to have a low level of language acculturation, and almost all the Chinese American participants (93.3%) were born outside the U.S. The mean English language acculturation score of Chinese American participants was 2.70 .About one-third of our participants (33.3% of Chinese Americans and 35.4% of NHWs) reported that they had utilized BRCA testing. The use of BRCA testing was not found to be significantly different between Chinese American and NHW breast cancer patients. The bivariate analyses showed that participants’ utilization of BRCA testing was significantly associated with age, annual household income level, employment status, private insurance coverage, family history of breast cancer, or family member(s) who had undergone BRCA testing (Ps < 0.05). Therefore, all these variables were included in the multivariate logistic regression model as independent variables. p = 0.019). Moreover, older participants were less likely to undergo BRCA testing than younger participants .As illustrated in The average BRCA genetic testing knowledge score of participants was 1.90 , which suggests that participants had a low level of BRCA-related knowledge. For example, none of the participants answered the following three questions correctly “all people with altered BRCA gene will get breast cancer”, “the BRCA genes cause about one-half of all breast cancers.”, and “about 1 in 10 women have an altered BRCA gene” .p = 0.040). Bivariate analyses showed that BRCA knowledge scores were significantly correlated with race, age, annual household income level, education level, employment status, private health insurance coverage, prior use of BRCA testing, and prior use of BRCA testing among family members (Ps < 0.05). Therefore, these variables were included in the multiple linear regression model as independent variables. The mean BRCA knowledge score for Chinese American participants was 1.58 (SD = 1.44), which was significantly lower than the mean score of NHW participants scores  (p > 0.2). Only participant race  and age (≥65 years old)  were found to be significantly associated with BRCA knowledge score.In the present study, we conducted a preliminary exploration of this topic to determine if there were differences between Chinese American and NHW breast cancer patients. We did not find a significant difference in BRCA genetic testing utilization between these two groups in our sample. However, the Chinese participants had less knowledge of BRCA testing than NHW participants. Our results are similar to those reported in two other studies that found that race and ethnicity were not significant factors in BRCA genetic testing utilization rates among breast cancer patients ,27, but Notably, our findings also show that, overall, both the Chinese American and NHW breast cancer patients in our sample had very limited knowledge about BRCA genetic testing. These results are different from those reported in a previous study among 206 women  with early-onset breast cancer that found that approximately 46% of their participants  had total BRCA genetic testing knowledge scores of ≥6 out of 7 . The lowOverall, our findings suggest that genetic counseling and education about BRCA genetic testing may have been inadequate for our participants. A study found that only about 62% of tested high-risk breast cancer patients had received genetic counseling . A lack It is worth noting that Chinese American breast cancer patients had even lower levels of knowledge than NHW breast cancer patients after analyzing participants’ age, education level, employment, insurance, and whether family member(s) had undergone BRCA testing. Previous studies also found that African Americans and Hispanics had lower levels of knowledge about breast cancer genetics and testing than NHWs ,34,35,36It should be made clear that this study is subject to one main limitation. Due to the challenges that are faced by researchers in recruiting Chinese breast cancer patients in a specific research timeframe and area, our sample size was small, the average age of our participants was relatively high, and all were from Southern California, which limits the scope of our findings. Despite the limitation, this study serves as a pioneer pilot study that sheds light on BRCA testing in an understudied but growing Chinese American breast cancer population. It also contributes to the limited literature in the field of precision medicine and public health. The implications of the study results may help reduce health disparities in future clinical practice. Future studies with larger and more diverse samples are needed to further determine if there are disparities in BRCA testing utilization and BRCA knowledge among Chinese breast cancer patients.To conclude, this study investigated and reported the differences in BRCA genetic testing utilization and knowledge between Chinese American and NHW breast cancer patients. Our study demonstrates that there is no significant difference between the BRCA testing uptake rates of Chinese American and NHW breast cancer patients. Nevertheless, all participants were found to have low levels of BRCA testing knowledge. Chinese American participants also exhibited lower levels of BRCA knowledge than NHW participants. It is critically important that effective genetic education and counseling are created and disseminated to improve BRCA genetic testing knowledge among all breast cancer patients.