Public cervical cancer screening recommendations from US cancer centers: Assessing adherence to national guidelines

Though widespread adoption of cervical cancer screening (CCS) in the US has been associated with a reduction in cervical cancer incidence and mortality, screening also carries with it potential risks. Newer national guidelines recommend decreased screening frequency to optimize the benefit/risk balance and to prevent over-screening. Here, we examined the alignment of US cancer center websites' public recommendations on CCS with national guidelines. We reviewed the websites of 1024 cancer centers accredited by the US Commission on Cancer during January-August 2022. We recorded the recommended frequency and type of CCS and any screening risks mentioned, comparing against national US Preventive Service Task Force (USPSTF) and American Cancer Society (ACS) guidelines. Of 1024 US cancer centers, 60% (610) provided CCS recommendations. Most centers are in alignment with the screening starting age (96%, 544/565) and stopping age (94%, 440/470) recommended by national guidelines. Of 508 centers specifying the frequency of standalone cervical cytology, 83% (419) recommended a screening interval of three years; however, 14% (73) recommended cervical cytology more frequently than the three-year interval recommended by the ACS/USPSTF. Screening risks were mentioned by 20% (124/610) of centers. Our findings highlight the importance of education on screening benefits and risks for physicians and patients to enable shared decision making based on evidence-based guidelines.

Development and testing of a polygenic risk score for breast cancer aggressiveness

Aggressive breast cancers portend a poor prognosis, but current polygenic risk scores (PRSs) for breast cancer do not reliably predict aggressive cancers. Aggressiveness can be effectively recapitulated using tumor gene expression profiling. Thus, we sought to develop a PRS for the risk of recurrence score weighted on proliferation (ROR-P), an established prognostic signature. Using 2363 breast cancers with tumor gene expression data and single nucleotide polymorphism (SNP) genotypes, we examined the associations between ROR-P and known breast cancer susceptibility SNPs using linear regression models. We constructed PRSs based on varying p-value thresholds and selected the optimal PRS based on model r2 in 5-fold cross-validation. We then used Cox proportional hazards regression to test the ROR-P PRS's association with breast cancer-specific survival in two independent cohorts totaling 10,196 breast cancers and 785 events. In meta-analysis of these cohorts, higher ROR-P PRS was associated with worse survival, HR per SD = 1.13 (95% CI 1.06-1.21, p = 4.0 × 10-4). The ROR-P PRS had a similar magnitude of effect on survival as a comparator PRS for estrogen receptor (ER)-negative versus positive cancer risk (PRSER-/ER+). Furthermore, its effect was minimally attenuated when adjusted for PRSER-/ER+, suggesting that the ROR-P PRS provides additional prognostic information beyond ER status. In summary, we used integrated analysis of germline SNP and tumor gene expression data to construct a PRS associated with aggressive tumor biology and worse survival. These findings could potentially enhance risk stratification for breast cancer screening and prevention.

Validation Study on Risk-Reduction Activities after Exposure to a Personalized Breast Cancer Risk-Assessment Education Tool in High-Risk Women in the WISDOM Study

We performed a 318-participant validation study of an individualized risk assessment tool in women identified as having high- or highest-risk of breast cancer in the personalized arm of the Women Informed to Screen Depending on Measures of risk (WISDOM) trial. Per protocol, these women were educated about their risk and risk reducing options using the Breast Health Decisions (BHD) tool, which uses patient-friendly visuals and 8th grade reading level language to convey risk and prevention options. Prior to exposure to the educational tool, 4.7% of women were already taking endocrine risk reduction, 38.7% were reducing alcohol intake, and 62.6% were exercising. Three months after initial use of BHD, 8.4% of women who considered endocrine risk reduction, 33% of women who considered alcohol reduction, and 46% of women who considered exercise pursued the risk-reducing activities. Unlike lifestyle interventions which are under the control of the patient, additional barriers at the level of the healthcare provider may be impeding the targeted use of endocrine risk reduction medications in women with elevated breast cancer risk.

Abstract P5-04-08: Breast cancer screening using ultrasound increases recall, biopsy, and cancer detection rates

Background: Ultrasound is often used as an adjunct to mammography for breast cancer (BC) screening. Usage of screening ultrasound (US) varies by state, likely due to differences in state-specific breast density notification laws and mandates requiring insurance coverage of supplemental screening for women at elevated risk of breast cancer. Screening US can increase cancer detection rates among women with dense breasts, but may increase recalls and benign biopsies. As more states adopt policies mandating insurance coverage for “medically necessary” breast cancer imaging, it is important to understand the impact to screening US utilization and subsequent service utilization. This analysis examines use of screening US by state as well as associated rates of recall, biopsy, and cancer detection.

Methods: We analyzed deidentified administrative claims. We included women aged 18-74 years with ≥1 claim for screening mammography in 2018. First claim was index date. Continuous enrollment was required in a commercial (COM) or Medicare Advantage (MA) plan from 1/2016 to index date (baseline period) and from index date to 6 months after (follow-up period). Recall, biopsy, and cancer detection rates were calculated for the follow-up period. Recall was defined as ≥1 claim for mammography, diagnostic ultrasound, or MRI in the follow-up period. We used CPT/HCPCS codes to identify procedures. Screening US was identified by CPT 76641 (complete) with modifier 50 (bilateral) or LT/RT (left/right). Using ICD codes, cancer detection was defined as ≥1 claim for DCIS or invasive BC. We examined screening US rates by insurance type, state, and age. Proportions were compared with chi-squared tests.

Results: 939,410 women met study criteria (70% COM, 30% MA; Tables 1-2). In the COM population, recall, biopsy, and cancer detection rates with screening US were approximately two-fold higher than without (recall: 26.1% vs. 11.8%; biopsy: 5.0% vs 1.6%; cancer detection: 1.0% vs. 0.4%). In the MA population, recall, biopsy, and cancer detection rates with screening US were roughly three-fold higher than without (recall: 23.6% vs 9.0%; biopsy: 5.2% vs 1.6%; cancer detection: 1.9% vs 0.7%). In NY, NJ, and CT, the rate of screening US usage was > 14 times higher than in all other states (29.1% vs 1.9%). These three states had higher recall and biopsy rates, but similar cancer detection rates compared to all other states (recall: 14.4% vs. 11.4%; biopsy: 2.5% vs 1.7%; cancer detection: 0.6% vs. 0.5%). All proportion differences reached statistical significance (p < 0.001).

Conclusion: Screening US was associated with increases in recall and biopsy, but modest increases in absolute cancer detection rates. Observed state by state variation of screening US is likely driven by laws requiring zero patient payment insurance coverage of “medically necessary” imaging which, as is the case with NY, NJ, and CT, is interpreted to include screening US. Our results demonstrate that screening US may lead to a large increase in recall rates and biopsies without consequentially improving the cancer detection rate.

Table 1: Recall, biopsy, and cancer detection rates by age with and without use of adjunctive breast screening ultrasound in a commercially insured U.S. population * values are suppressed to comply with requirements for data release

Table 2: Recall, biopsy, and cancer detection rates by age with and without use of adjunctive breast screening ultrasound in a Medicare Advantage (MA) U.S. population * values are suppressed to comply with requirements for data release

Citation Format: James Staib, Rashna Soonavala, Stacey Dacosta Byfield, Kimberly Badal, Kierstin Catlett, Liz Maffey, Mi-Ok Kim, Kenneth Wimmer, Yiwey Shieh, Laura J. Esserman. Breast cancer screening using ultrasound increases recall, biopsy, and cancer detection rates [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P5-04-08.

Abstract PD14-07: PD14-07 Associations of Breast Cancer Risk Level and Prediction of Tumor Aggressiveness in the Athena Breast Health Network

Background: The Athena Breast Health Network (Athena) is a University of California (UC) initiative integrating clinical care and research to drive improvements in breast cancer screening. Through standardized, self-reported clinical intake forms, a patient’s breast health status and information regarding their breast cancer risk is captured before each mammography appointment. Breast cancer risk models provide a level of risk to develop breast cancer but do not take into account aggressiveness of breast cancer. Here, we evaluated outcome data of a large screening cohort for association between risk level and aggressiveness at diagnosis. Methods: We calculated Breast Cancer Surveillance Consortium (BCSC) risk scores for a cohort of 8,923 consented UCSF Athena participants from the years 2012-2018 with a median follow-up of 5-years. To identify those who developed invasive breast cancer on or after completing an Athena intake form, we performed a cancer linkage with the San Francisco Mammography Registry (SFMR), a local registry that regularly collects cancer data from the California Cancer Registry. We classified tumors as aggressive if they met one or more of the following criteria: hormone receptor (HR)-negative, HER2-positive, grade 3. All other tumors were classified as non-aggressive. We used student’s t-tests to examine associations between BCSC 5-year risk score, the development of invasive breast cancer, and tumor aggressiveness among cases. To account for the association between older age and higher BCSC risk score (as well as HR-positive subtypes), we stratified by percentiles of BCSC risk by age (top 2.5% vs. bottom 97.5%). The top 2.5% by age threshold consistently identifies women with lifetime risk of 23–28% and was chosen as high-risk threshold to trigger annual screening in the WISDOM study (Dreher: PMID34843026). Results: Of 8,923 participants, 170 (2%) developed breast cancer during the follow-up period. The average 5-year BCSC risk score for women with breast cancer was 1.81% and 1.47% for those without (p< 0.001). Among women with breast cancer, 123 (72%) developed non-aggressive cancers and 47 (28%) developed aggressive cancers. The average 5-year BCSC risk score for women with non-aggressive and aggressive cancers was 1.89% and 1.60%, respectively (p=0.13). In analyses stratified by percentile of BCSC risk by age, 521 (6%) participants had a BCSC 5-year risk score in the top 2.5% by age and 8,402 (94%) participants had a BCSC 5-year risk score in the bottom 97.5%. A higher percentage of women with non-aggressive cancers vs healthy women (controls) were in the top 2.5% by age (p = 0.001), but the percentage of aggressive cancers vs healthy women in the top 2.5% by age was similar (p = 0.61). Conclusion: Through this study we confirmed that higher 5-year BCSC risk scores are associated with higher overall breast cancer development. Interestingly, participants with the highest 5-year BCSC risk scores (top 2.5% by age), are more likely to develop cancers with non-aggressive features (low grade, hormone positive). This suggests that the BCSC model may preferentially predict less aggressive tumors, and those with the highest 5-year BCSC risk may be more likely to benefit from endocrine risk reduction therapy. There remains a gap in our ability to identity those at risk for aggressive cancers. Our findings highlight the need for screening programs to better understand who is at risk for what type of breast cancer. Current work is focused on developing models tailored to risk prediction of aggressive cancers.

Citation Format: Katherine Leggat-Barr, Tomiyuri Lewis, Rosalyn Sayaman, Paige Warner, Kathy Malvin, Leah Sabacan, Elene Tsopurashvili, WISDOM Study and Athena Breast Health Network Investigators and Advocate Partners, Allison Stover Fiscalini, Jeffrey Tice, Karla Kerlikowske, Yiwey Shieh, Laura J. Esserman, Laura Van ’t Veer. PD14-07 Associations of Breast Cancer Risk Level and Prediction of Tumor Aggressiveness in the Athena Breast Health Network [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD14-07.

Whole exome sequencing and replication for breast cancer among Hispanic/Latino women identifies FANCM as a susceptibility gene for estrogen-receptor-negative breast cancer

Introduction

Breast cancer (BC) is one of the most common cancers globally. Genetic testing can facilitate screening and risk-reducing recommendations, and inform use of targeted treatments. However, genes included in testing panels are from studies of European-ancestry participants. We sequenced Hispanic/Latina (H/L) women to identify BC susceptibility genes.

Methods

We conducted a pooled BC case-control analysis in H/L women from the San Francisco Bay area, Los Angeles County, and Mexico (4,178 cases and 4,344 controls). Whole exome sequencing was conducted on 1,043 cases and 1,188 controls and a targeted 857-gene panel on the remaining samples. Using ancestry-adjusted SKAT-O analyses, we tested the association of loss of function (LoF) variants with overall, estrogen receptor (ER)-positive, and ER-negative BC risk. We calculated odds ratios (OR) for BC using ancestry-adjusted logistic regression models. We also tested the association of single variants with BC risk.

Results

We saw a strong association of LoF variants in FANCM with ER-negative BC (p=4.1×10-7, OR [CI]: 6.7 [2.9-15.6]) and a nominal association with overall BC risk. Among known susceptibility genes, BRCA1 (p=2.3×10-10, OR [CI]: 24.9 [6.1-102.5]), BRCA2 (p=8.4×10-10, OR [CI]: 7.0 [3.5-14.0]), and PALB2 (p=1.8×10-8, OR [CI]: 6.5 [3.2-13.1]) were strongly associated with BC. There were nominally significant associations with CHEK2, RAD51D, and TP53.

Conclusion

In H/L women, LoF variants in FANCM were strongly associated with ER-negative breast cancer risk. It previously was proposed as a possible susceptibility gene for ER-negative BC, but is not routinely tested in clinical practice. Our results demonstrate that FANCM should be added to BC gene panels.

Abstract PR008: Development and testing of a polygenic risk score for breast cancer. Aggressiveness

Background: Aggressive breast cancers have increased proliferation or metastatic potential and portend a poor prognosis. The ability to identify women at elevated risk of aggressive cancers could have major implications for screening and prevention, yet there are no available tools for predicting aggressive cancer risk. We sought to construct a polygenic risk score (PRS) for aggressive breast cancers by leveraging the associations of single nucleotide polymorphisms (SNPs) with tumor gene expression. We used as our measure of aggressiveness the risk of recurrence score weighted on proliferation (ROR-P), a validated tumor prognostic signature. We hypothesized that known breast cancer susceptibility SNPs would have differential associations with ROR-P, which could then be used to construct a PRS for ROR-P. Methods: We developed our PRS in a case-only analysis of 3 studies containing SNP genotypes and tumor gene expression: The Cancer Genome Atlas, METABRIC, and the I-SPY 2 TRIAL (total n=2,363). We used linear regression models to evaluate individual SNP associations with ROR-P, adjusted for genetic ancestry and study. We then constructed PRS using varying p-value thresholds and used cross-validation to identify the PRS with highest model r2. To assess whether the ROR-P PRS was associated with poor prognosis, we performed survival analysis in two longitudinal cohorts of breast cancer patients: the UK Biobank (women with incident invasive cancers only) and the Pathways Study. These studies included 10,196 total cases with 785 deaths. We built Cox proportional hazards models to evaluate the association between the ROR-P PRS (adjusted for genetic ancestry) and breast cancer-specific survival (BCSS) in both studies. We then performed meta-analysis of the Cox model results. We also constructed joint models containing the ROR-P PRS and a PRS representing the case-case risk of ER-negative vs. ER-positive cancer, PRSER-/ER+. Results: We tested the associations between 226 breast cancer susceptibility SNPs and ROR-P. The best-performing PRS contained 76 SNPs and had a cross-validated r2 of 0.051. In the UK Biobank and Pathways Study, higher ROR-P PRS was associated with worse BCSS, with nearly identical effects observed in each study, HR per standard deviation of 1.13 (95% CI 1.05-1.21, p=9.0x10-4) in meta-analysis. The ROR-P PRS’s effect was minimally attenuated when adjusted for PRSER-/ER+, suggesting that the ROR-P PRS was providing additional prognostic information beyond ER status. Conclusions: We used breast cancer susceptibility SNPs to construct a PRS for ROR-P, a prognostic signature recapitulating aggressiveness, and found the ROR-P PRS to be associated with worse BCSS. Our findings represent an improvement on current PRS for overall breast cancer risk, which preferentially predict cancers with favorable prognosis. Given that aggressive cancers are more likely to present as advanced cancers even among women undergoing routine screening, our findings could potentially identify women who may benefit from more intensive screening.

Citation Format: Yiwey Shieh, Jacquelyn Roger, Christina Yau, Denise Wolf, Gillian Hirst, Lamorna Swigart, Scott Huntsman, Donglei Hu, Jovia Nierenberg, Pooja Middha, Rachel Heise, Linda Kachuri, Qianqian Zhu, Song Yao, Christine Ambrosone, Marilyn Kwan, Bette Caan, John Witte, Lawrence Kushi, Laura van ’T. Veer, Laura Esserman, Elad Ziv. Development and testing of a polygenic risk score for breast cancer. Aggressiveness. [abstract]. In: Proceedings of the AACR Special Conference: Precision Prevention, Early Detection, and Interception of Cancer; 2022 Nov 17-19; Austin, TX. Philadelphia (PA): AACR; Can Prev Res 2023;16(1 Suppl): Abstract nr PR008.

Abstract 5883: Development and testing of a polygenic risk score for proliferative breast cancers

Background: Identification of women at elevated risk for highly proliferative, poor prognosis breast cancers could have important implications for screening and prevention. Genome-wide association studies (GWAS) have found >200 single nucleotide polymorphisms (SNPs) associated with breast cancer risk, with many SNPs differentially associated with ER status or intrinsic subtype. We hypothesized that some of these SNPs are preferentially associated with more proliferative tumors, while others are preferentially associated with less proliferative tumors. In this study, we aimed to build a polygenic risk score (PRS) predictive of proliferative tumors, using the GWAS-identified SNPs.

Methods: We used data from 3 studies that included array-based SNP genotyping and tumor transcriptomic data: The Cancer Genome Atlas, METABRIC, and the I-SPY 2 Trial (total n=2,467). Our outcome was the risk of recurrence score weighted on proliferation (ROR-P), a validated tumor prognostic signature. Using the breast cancer risk SNPs, we built respective linear regression models to predict ROR-P, with genetic ancestry, study, and ER status as covariates. We performed 5-fold cross-validation and used the model r2 to identify the optimal p-value threshold for including SNPs in the PRS. To decrease uncertainty of our estimates, we performed 100 repeats across the pooled datasets. To test whether this model predicted poor prognosis breast cancers, we first used it to impute ROR-P among genotyped breast cancer cases in UK Biobank (UKB). We then examined the association between “genetically predicted” ROR-P and breast cancer-specific survival using Cox proportional hazards models adjusted for genetic ancestry and age at diagnosis.

Results: Associations between 224 breast cancer SNPs and ROR-P were tested. The best-performing model in cross-validation contained 96 SNPs, each associated with ROR-P at p < 0.45, with model r2 0.054. The SNPs with the strongest positive correlations with ROR-P included those discovered in GWAS for HER2-positive and ER-negative cancers, both of which tend to be highly proliferative. Among 7,247 incident cancers in UKB, higher genetically predicted ROR-P was associated with shorter survival, with a per-standard deviation hazard ratio of 1.14 (95% CI 1.05-1.24, p = 0.002).

Conclusions: We used breast cancer susceptibility SNPs to construct a PRS fitted to ROR-P, a prognostic signature recapitulating tumor proliferation. This PRS was associated with worse clinical outcomes in breast cancer cases from UKB. Our results suggest that correlations between SNPs and tumor gene expression can be used to “tune” PRS to tumor phenotype, e.g. proliferation. Highly proliferative tumors are more likely to present as advanced cancers even among women getting routine screening. If replicated in other datasets, our findings could be used to identify women who may especially benefit from tailored screening and prevention.

Citation Format: Yiwey Shieh, Jacquelyn Roger, Scott Huntsman, Donglei Hu, Jovia L. Nierenberg, Pooja Middha Kapoor, Christina Yau, Gillian Hirst, Laura van 't Veer, Laura Esserman. Development and testing of a polygenic risk score for proliferative breast cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5883.

Abstract P5-19-04: The WISDOM study: Reducing sequential steps and implementing parallel workflows in pragmatic trials

Background:The WISDOM Study is a preference-tolerant pragmatic study, comparing annual mammograms to a risk-based screening. Eligibility includes women ages 40-74 years with no history of breast cancer or DCIS. Participants are enrolled to one study arm: annual screening or risk-based screening (includes genetic testing). Pragmatic trials often involve gathering real-time data over multiple time points. Collecting real-time data sequentially can limit enrollment, delay study assignments, and reduce participant engagement. The WISDOM Study has identified such bottlenecks and has implemented parallel workflows, reducing the overall wait time for participants to complete required study steps. These data highlight how moving participants through the study more efficiently can improve enrollment and retention and inform other pragmatic trials. Methods: WISDOM participants have the option to either choose their study arm or be randomized into one as part of the preference tolerant randomized trial design. Participants then complete breast health questionnaires and genetic testing (if in the risk-based arm). This information is analyzed by the WISDOM breast cancer risk assessment algorithm, the result of which is then communicated to the participant through a screening assignment letter (SAL). Specific data elements, such as breast density found participants’ mammogram reports and genetic testing results are required for study randomization process and risk assessment calculations, respectively. The WISDOM randomization algorithm is stratified by several factors, including breast cancer risk estimated using the Breast Cancer Surveillance Consortium (BCSC) model, which uses mammographic density as a key input variable. The study team changed the workflow to allow participants to proceed to randomization without specific information by imputing both density and risk. Additionally, a parallel workflow improvement process was implemented to obtain mammogram reports while genetic testing was being completed. Results: Before the weighted BCSC and imputed density algorithms were introduced, it took an average of 47 days to randomize participants after completion of the baseline enrollment questionnaires. Now, participants are randomized immediately which has reduced delays by 100%. Prior to implementing the parallel workflow for genetic testing and mammogram ascertainment, genetic testing kits were sent only after mammogram reports were collected and validated. The expected turnaround time for genetic testing results was 30-60 days and on average, results were returned to participants in 42 days. Streamlining the study design to obtain mammogram reports while participants complete their genetic testing has shortened the time for participants to receive their screening assignment letters (SALs) from an average of 160 days to 78 days, a reduction by 49%. In comparison, participants in the annual arm of the study who do not complete genetic testing, receive their SALs after an average of 38 days from enrollment. This is due to long wait times to obtain mammographic densities from outside medical facilities. Conclusions: Creating parallel data ascertainment workflows and reducing sequential steps in the study process has increased completion of individual enrollment activities. Participants now are randomized immediately upon joining the study and have access to their SALs and genetic results more rapidly. This approach eliminated randomization wait times and improved efficiency of the early in the enrollment process. We are evaluating the impact on participant retention going forward. Workflow efficiency is critical to improve the patient experience, and our learnings can inform future trial design, particularly for studies requiring data from outside sources.

Citation Format: Tomiyuri Lewis, Stephanie Flores, Leah Sabacan, Patricia Choy, Halle Thannickal, Yiwey Shieh, Jeffrey Tice, Elad Ziv, Lisa Madlensky, Martin Eklund, Christina Yau, Amie Blanco, Barry Tong, Deborah Goodman, Nancy Anderson, Heather Harvey, Steele Fors, Hannah L Park, Samrrah Raouf, Skye Stewart, Janet Wernisch, Barbara Koenig, Celia Kaplan, Robert Hiatt, Neil Wenger, Vivian Lee, Diane Heditsian, Susie Brain, Dolores Moorehead, Barbara A Parker, Alexander Borowsky, Hoda Anton-Culver, Arash Naeim, Andrea Kaster, Laura van ‘t Veer, Andrea Z LaCroix, Olufunmilayo I Olopade, Deepa Sheth, Agustin Garcia, Rachel Lancaster, Michael Plaza, Wisdom Study, Athena Breast Health Network Investigators, Advocate Partners, Allison S Fiscalini, Laura Esserman. The WISDOM study: Reducing sequential steps and implementing parallel workflows in pragmatic trials [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P5-19-04.

Abstract P5-19-01: The impact of streamlined processes and patient-directed messaging to improve enrollment in a remote, pragmatic clinical trial

Background Recent advances in technology have made it possible to conduct remote clinical trials that allow individuals to participate from home with comfort, privacy, and ease. Despite these advances, challenges persist in running remote trials, such as survey question redundancies, lack of patient-initiated data-sharing tools, and unclear patient communication around critical enrollment steps. The Women Informed to Screen Depending on Measures of risk (WISDOM) Study is a pragmatic, preference-tolerant randomized control breast cancer screening trial comparing personalized risk-based screening to traditional, annual screening. The study population includes women ages 40-74 without a history of breast cancer or DCIS. Since 2016, study enrollment has been available to all women in the U.S. who meet study eligibility criteria. Since October 2020, WISDOM has implemented multiple strategies to improve participant experience: participant-initiated data-sharing tools and clear participant messaging. This abstract presents the efficacy of these interventions as they relate to increasing patient enrollment in remote, pragmatic clinical trials. Methods The WISDOM Study online enrollment process includes registration, participant study arm selection or randomization, online consent, and enrollment (submission of multiple study surveys over a secure, online platform). Barriers to online enrollment were uncovered through an internally-conducted needs assessment of participants who enrolled between 2019-2020, and participant feedback obtained through phone interviews conducted by WISDOM’s embedded ethics study. Improvements to our online enrollment procedures were executed in October 2020 and included: improving the clarity of study arm selection options, streamlining data collection surveys, and enacting a secure, patient-initiated online data-sharing tool and an online portal feature with auto-launch of critical information. Study metrics were obtained through Google Analytics and Salesforce. Results Prior to the end of 2020, only 62% of the 30,046 participants who registered for the WISDOM Study completed study enrollment. After improving the enrollment process, of the 5,334 participants registered for the study between Jan-June 2021, 69% completed the enrollment process finishing both the online consent and survey forms. Conversion from consent to enrollment went from 78% in January 2020 to 93% in June 2021. Currently, 56% participants complete enrollment in one day. Streamlining online patient questionnaires led to an increase in completion rates, with 75% of participants completing their yearly surveys, compared to 59% prior to April 2021. A secure patient upload feature for data sharing led to 1,054 participants successfully sharing their mammogram reports with WISDOM between March - June 2021. Previously, mammogram reports were missing for 20% of enrolled participants. This feature has enabled WISDOM to process 300 additional mammogram reports per month. Integration of an auto-launch feature in the participant’s portal in Feb 2021 has led to a 17% increase in participants viewing their screening recommendations in Yr 1. Prior to auto-launch, only 59% (n=6328) of Yr 1 screening recommendations and 61% (n=3681) of genetic testing reports were viewed by participants. Since implementation, the numbers increased to 78% (n=8406) and 85% (n=5160), respectively. Conclusions. Streamlining data to the most essential elements, and minimizing the steps required to share clinical documents, complete questionnaires and open key study notification is essential to improving enrollment rates in virtual, pragmatic trials. Patient-initiated data-sharing tools such as the ability for participants to share documents through secure, online portals is one example of success.

Citation Format: Patricia Choy, Tomiyuri Lewis, Stephanie Flores, Leah Sabacan, Halle Thannickal, Steffanie Goodman, Yiwey Shieh, Lisa Madlensky, Jeffrey A. Tice, Elad Ziv, Martin Eklund, Amie Blanco, Barry Tong, Deborah Goodman, Nancy Anderson, Heather Harvey, Steele Fors, Hannah Lui Park, Antonia Petruse, Skye Stewart, Samrrah Raouf, Janet Wernisch, Barbara Koenig, Celia Kaplan, Robert Hiatt, Neil Wenger, Vivian Lee, Diane Heditsian, Susie Brain, Dolores Moorehead, Barbara A Parker, Alexander Borowsky, Hoda Anton-Culver, Arash Naeim, Andrea Kaster, Laura van 't Veer, Andrea Z LaCroix, Olufunmilayo I. Olopade, Deepa Sheth, Agustin Garcia, Rachel Lancaster, Jennifer James, Galen Joseph, Wisdom Study, Athena Breast Health Network Investigators and Advocates, Allison Stover Fiscallini, Laura Esserman. The impact of streamlined processes and patient-directed messaging to improve enrollment in a remote, pragmatic clinical trial [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P5-19-01.

Abstract PO-164: Pathogenic variants in breast cancer risk genes in Latinas

Introduction: Pathogenic variants (PVs) in high- and intermediate-penetrance breast cancer susceptibility genes have large effects on disease risk. While individual PVs are rare, in aggregate, they markedly contribute to breast cancer risk in women of European ancestry in the general population. We examined the association with risk of developing breast cancer in Latinas. Methods: We conducted a pooled case-control analysis of breast cancer in Latinas from the San Francisco Bay Area, Los Angeles, and Mexico (4,172 cases and 3,692 controls). Case ascertainment included 2,095 participants from high-risk breast cancer studies (age below 50 years at breast cancer diagnosis, family history, or bilateral breast cancer) and 5,769 from general population studies. We determined presence of a rare PV in nine known breast cancer risk genes (ATM, BARD1, BRCA1, BRCA2, CHEK2, PALB2, PTEN, RAD51C, and TP53). We examined associations between PVs in each gene and breast cancer using multivariable logistic regression models, adjusted for age and ancestry. Secondary analyses were stratified by age, family history, or Indigenous American (IA) ancestry. Results: PVs in known risk genes were detected in 7.0% of cases and 1.7% of controls in participants from general population studies. Odds ratios (OR) for breast cancer in those with PVs in BRCA1, BRCA2, CHEK2, PALB2, and TP53 were 15.7 (95% CI: 5.7-64.8), 7.0 (95% CI: 3.7-14.4), 1.9 (95% CI: 1.0-4.0), 6.1 (95% CI: 3.1-13.9), and 3.7 (95% CI: 1.1-16.2) respectively. PVs in ATM (OR: 1.2, 95% CI: 0.7-2.1), BARD1 (OR: 1.5, 95% CI: 0.3-10.4), PTEN (PVs in 4 cases and 0 controls), and RAD51C (OR: 1.5, 95% CI: 0.2-11.5) were not significantly associated with breast cancer. Among cases, those with age<50 at diagnosis or with family history of breast cancer had increased odds of having a PV, with ORs of 1.4 (95% CI: 1.0-1.9) and 2.3 (95% CI: 1.4-4.0), respectively. IA above the median was associated with increased odds of having a PV among cases (OR: 1.8; 95% CI: 1.4-2.5) but not among controls. Discussion: Among Latina participants, having a PV in any of the nine genes was associated with increased risk of breast cancer. As expected, cases who were younger or had a family history of breast cancer were more likely to have a PV. In addition, cases but not controls with high IA were more likely to have a PV. The higher prevalence of PVs among high IA cases but not controls may be due to the younger age of these women and/or lower prevalence of other environmental risk factors. Our PV prevalence estimates among Latinas were similar to those previously found among European ancestry participants. Our results suggest that there may be clinical utility in testing for rare PVs in breast cancer risk genes among those in the general population.

Citation Format: Jovia L Nierenberg, Aaron Adamson, Yuan C. Ding, Yiwey Shieh, Donglei Hu, Scott Huntsman, Esther M. John, Gabriela Torres-Mejia, Christopher A. Haiman, Lawrence H. Kushi, Charite N. Ricker, Linda Steele, Robin Lee, Jeffrey N. Weitzel, Laura Fejerman, Elad Ziv, Susan L. Neuhausen. Pathogenic variants in breast cancer risk genes in Latinas [abstract]. In: Proceedings of the AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2021 Oct 6-8. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr PO-164.

Elevated risk thresholds predict endocrine risk-reducing medication use in the Athena screening registry

Risk-reducing endocrine therapy use, though the benefit is validated, is extremely low. The FDA has approved tamoxifen and raloxifene for a 5-year Breast Cancer Risk Assessment Tool (BCRAT) risk ≥ 1.67%. We examined the threshold at which high-risk women are likely to be using endocrine risk-reducing therapies among Athena Breast Health Network participants from 2011-2018. We identified high-risk women by a 5-year BCRAT risk ≥ 1.67% and those in the top 10% and 2.5% risk thresholds by age. We estimated the odds ratio (OR) of current medication use based on these thresholds using logistic regression. One thousand two hundred and one (1.2%) of 104,223 total participants used medication. Of the 33,082 participants with 5-year BCRAT risk ≥ 1.67%, 772 (2.3%) used medication. Of 2445 in the top 2.5% threshold, 209 (8.6%) used medication. Participants whose 5-year risk exceeded 1.67% were more likely to use medication than those whose risk was below this threshold, OR 3.94 (95% CI = 3.50-4.43). The top 2.5% was most strongly associated with medication usage, OR 9.50 (8.13-11.09) compared to the bottom 97.5%. Women exceeding a 5-year BCRAT ≥ 1.67% had modest medication use. We demonstrate that women in the top 2.5% have higher odds of medication use than those in the bottom 97.5% and compared to a risk of 1.67%. The top 2.5% threshold would more effectively target medication use and is being tested prospectively in a randomized control clinical trial.

Development and pilot of an online, personalized risk assessment tool for a breast cancer precision medicine trial

Breast cancer risk reduction has been validated by large-scale clinical trials, but uptake remains low. A risk communication tool could provide personalized risk-reduction information for high-risk women. A low-literacy-friendly, visual, and personalized tool was designed as part of the Women Informed to Screen Depending On Measures of risk (WISDOM) study. The tool integrates genetic, polygenic, and lifestyle factors, and quantifies the risk-reduction from undertaking medication and lifestyle interventions. The development and design process utilized feedback from clinicians, decision-making scientists, software engineers, and patient advocates. We piloted the tool with 17 study participants, collecting quantitative and qualitative feedback. Overall, participants felt they better understood their personalized breast cancer risk, were motivated to reduce their risk, and considered lifestyle interventions. The tool will be used to evaluate whether risk-based screening leads to more informed decisions and higher uptake of risk-reduction interventions among those most likely to benefit.

Abstract OT-21-01: Personalized breast cancer screening in a population-based study: Women informed to screen depending on measures of risk (WISDOM)

Background: WISDOM is a 100,000 healthy women preference-tolerant, pragmatic study comparing traditional annual screening to personalized risk-based breast screening. The novelty of WISDOM personalized screening is the integration of previously validated genetic and clinical risk factors (age, family history, breast biopsy results, ethnicity, mammographic density) into a single risk assessment model that directs the starting age, timing, and frequency of screening. The goal of WISDOM is to determine if personalized screening, compared to annual screening, is as safe, less morbid, enables prevention, and is more accepted by women. The study is registered on ClinicalTrials.gov, NCT02620852. Methods: Women aged 40-74 years with no history of breast cancer, DCIS or previous double mastectomy can join the study online at wisdomstudy.org. Participants can either elect randomization or self-select a study arm. Then, they provide electronic consent and sign the Release for Medical Information via DocuSign. For all participants, 5-year risk of developing breast cancer is calculated according to the Breast Cancer Surveillance Consortium (BCSC) model. Participants in the personalized arm undergo panel-based mutation testing (BRCA1, BRCA2, TP53, PTEN, STK11, CDH1, ATM, PALB2, and CHEK2), and their 5-year risk is calculated using the BCSC score combined with a Polygenic Risk Score (BCSC-PRS) that includes 229 single nucleotide polymorphisms (SNPs) known to increase breast cancer risk. The SNPs and mutations are assessed by saliva-based testing through Color Genomics. Five-year risk level thresholds are used to stratify participants as low-, moderate- and high risk. Risk stratification determines age to start, stop, and frequency of screening in the personalized arm. Accrual: As of July 2020 the WISDOM Study is open to all eligible women in the United States. To date, 38,762 eligible women have registered, and 28,706 women have consented to participate in the trial. The median age is 56 years. Seventy-seven percent of participants are Caucasian, 2% African-American, 5% Asian, and 8% of self-reported Hispanic ethnicity. WISDOM is partnering with Blue Cross Blue Shield Association for regional plan opt-in coverage, self-insured companies (Salesforce, Genentech, Qualcomm, CalPERS) and Medi-Cal (Inland Empire Health Plan) using a coverage with evidence progression approach. Accrual expansion and diversity: To ensure that resulting data are meaningful and potentially practice-changing for all populations of women, the WISDOM Study is enhancing the diversity of our participant population by establishing WISDOM sites in diverse areas with large African-American (Alabama, Louisiana, Illinois) and Latina (Florida) populations. These new recruitment sites, intentionally selected for the diverse communities they serve, have established partnerships with community organizations and outreach navigators. Additionally, we have translated the WISDOM Study to Spanish to facilitate access by Latina communities. With the engagement of patient advocates and community partnerships, expanding diversity in the study population will strengthen our scientific knowledge of breast cancer risk and improve access to personalized breast cancer screening recommendations for all women. Enrollment will continue through 2022. Conclusions: Results of 5 years follow-up will enable us to demonstrate whether personalized screening improves outcomes for future patients and it improves healthcare value by reducing screen volumes and costs without jeopardizing outcomes.

Citation Format: Irene Acerbi, Allison Stover Fiscalini, Mandy Che, Yiwey Shieh, Lisa Madlensky, Jeffrey Tice, Elad Ziv, Martin Eklund, Amie Blanco, Barry Tong, Deborah Goodman, Lamees Nassereddine, Nancy Anderson, Heather Harvey, Steele Fors, Hannah L Park, Antonia Petruse, Skye Stewart, Janet Wernisch, Larissa Risty, Ian Hurley, Barbara Koenig, Celia Kaplan, Robert Hiatt, Neil Wenger, Vivian Lee, Diane Heditsian, Susie Brain, Leah Sabacan, Tianyi Wang, Barbara A Parker, Alexander Borowsky, Hoda Anton-Culver, Arash Naeim, Andrea Kaster, Melinda Talley, Laura van 't Veer, Andrea Z LaCroix, Olufunmilayo I Olopade, Deepa Sheth, Augustin Garcia, Rachel Lancaster, Wisdom Study and Athena Breast Health Network Investigators and Advocate Partners, Laura Esserman. Personalized breast cancer screening in a population-based study: Women informed to screen depending on measures of risk (WISDOM) [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr OT-21-01.

A Polygenic Risk Score for Breast Cancer in US Latinas and Latin American Women

Background

More than 180 single nucleotide polymorphisms (SNPs) associated with breast cancer susceptibility have been identified; these SNPs can be combined into polygenic risk scores (PRS) to predict breast cancer risk. Because most SNPs were identified in predominantly European populations, little is known about the performance of PRS in non-Europeans. We tested the performance of a 180-SNP PRS in Latinas, a large ethnic group with variable levels of Indigenous American, European, and African ancestry.

Methods

We conducted a pooled case-control analysis of US Latinas and Latin American women (4658 cases and 7622 controls). We constructed a 180-SNP PRS consisting of SNPs associated with breast cancer risk (P < 5 × 10^–8). We evaluated the association between the PRS and breast cancer risk using multivariable logistic regression, and assessed discrimination using an area under the receiver operating characteristic curve. We also assessed PRS performance across quartiles of Indigenous American genetic ancestry. All statistical tests were two-sided.

Results

Of 180 SNPs tested, 142 showed directionally consistent associations compared with European populations, and 39 were nominally statistically significant (P < .05). The PRS was associated with breast cancer risk, with an odds ratio per SD increment of 1.58 (95% confidence interval [CI = 1.52 to 1.64) and an area under the receiver operating characteristic curve of 0.63 (95% CI = 0.62 to 0.64). The discrimination of the PRS was similar between the top and bottom quartiles of Indigenous American ancestry.

Conclusions

The 180-SNP PRS predicts breast cancer risk in Latinas, with similar performance as reported for Europeans. The performance of the PRS did not vary substantially according to Indigenous American ancestry.

Abstract P5-08-01: Breast cancer risk thresholds as a predictor of chemoprevention uptake in the Athena Breast Health Network

Background: Large-scale chemoprevention trials validated endocrine risk reduction strategies to lower breast cancer risk. We sought to understand the risk at which women are likely to adopt chemoprevention. A 5-year Gail risk of 1.67% or above is considered elevated risk, and the FDA indication for prescribing chemoprevention. We examined chemoprevention use in the Athena Breast Health Network (Athena), which includes approximately 100,000 women who are screened by mammography at Sanford Health, UC Davis, UC Irvine, UC Los Angeles, UC San Diego, and UC San Francisco.

Methods: We calculated the Gail risk score for women who had completed an Athena online intake survey distributed before being seen at screening centers; this survey included questions about chemoprevention usage. First, we analyzed 16,518 surveys of 9,318 unique women without breast cancer or DCIS who received breast cancer screening at UCSF from 2011- 2018 and who consented to research. These women also self-reported use of chemoprevention. We stratified Gail risk scores by a threshold of 1.67%, and by percentiles to identify those women in the top 2.5% by age. We compared current chemoprevention use in these different breast cancer risk strata, and factors associated with its use. An analysis including all 100,000 women in the Athena Network will be presented at SABCS.

Results: Overall, at UCSF, 48 of 9,318 women (0.51%) reported current chemoprevention use. The 5-year Gail risk was greater than 1.66% in 3,675 of 9,318 women (39%), of whom 205 (2.2%) were in the top 2.5% of risk by age. Chemoprevention use was reported by 13 of 205 (6.3%) women in the top 2.5% of risk by age (mean Gail risk 5.6%), as compared to 41 of 3,675 (1.1%) who were at Gail above 1.66% (mean Gail = 3.9%). Women in the top 2.5% and those with Gail risk &gt;1.66% were significantly more likely to be using chemoprevention p&lt; 0.01 for each respectively). Chemoprevention uptake was correlated with the joint effect of the top 2.5% of risk by age and increasing Gail score (OR = 10.25; P = 0.009). Preliminary results were consistent among the 100,000 women in the Athena registry (analysis ongoing). In addition, chemoprevention use was more likely in older women (OR = 1.10; P &lt; 0.01, for every year of age) and in those women with Ashkenazi ancestry on both sides of the family compared to none (OR = 2.32; P = 0.02). Race and education were not associated with use of chemoprevention.

Discussion: Women with higher Gail scores in the top 2.5% of risk by age are positively associated with current chemoprevention use (6.34%). Importantly, this analysis presents a risk-stratified, population-level risk reduction strategy, using the top 2.5% risk threshold by age. It provides an opportunity to specifically target chemoprevention to women at highest need to reduce their breast cancer risk. In the WISDOM Study (NCT02620852), we are prospectively testing active outreach based on breast cancer risk in the top 2.5% of risk by age, and have developed a breast health decisions aid to standardize communication of risk-reducing options.

Citation Format: Yash S Huilgol, Holly Keane, Yiwey Shieh, Jeffrey Tice, Elad Ziv, Lisa Madlensky, Leah Sabacan, Irene Acerbi, Mandy Che, Allison Stover Fiscalini, Hoda Anton-Culver, Alexander D Borowsky, Sharon Hunt, Arash Naeim, Barbara Parker, Laura J van 't Veer, Athena Breast Health Network Investigators and Advocate Partners and Laura J Esserman. Breast cancer risk thresholds as a predictor of chemoprevention uptake in the Athena Breast Health Network [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P5-08-01.

Abstract P2-10-05: A breast cancer multi-racial/ethnic polygenic risk score for improved personalized breast cancer screening

Background: Polygenic risk scores (PRS) integrate risk information from breast cancer associated SNPs (single nucleotide polymorphism). The risk scores have mostly been developed in populations of European ancestry, and have been shown to improve risk prediction over standard breast cancer risk models in these populations. The ability of the PRS to personalize screening is currently being studied. We included PRS as a component of breast cancer risk assessment in the WISDOM Study, a trial of personalized vs. annual breast cancer screening. In order to account for race/ethnicity in PRS risk assessment, we developed a race/ethnicity calibrated and inclusive PRS risk score that we incorporated here into the Gail model to determine impact on risk stratification.

Methods: We constructed two different PRS for each race/ethnicity: For Caucasian populations, we constructed two PRS based on SNPs discovered in European-ancestry populations. One PRS was based on 167 SNPs (PRS-167) and the other based on 313 SNPs (PRS-313) from the Breast Cancer Association Consortium studies as previously published. For each of the Asian-, Hispanic- and African-ancestry populations we added additional ancestry specific SNPs to the PRS-167 or the PRS-313, that were literature curated or our own identified race/ethnicity SNPs that we validated to provide independent risk prediction for their ancestry group: Asian added 10 or 4 additional SNPs, Hispanic 2 SNPs, and African 8 and 12 SNPs, respectively to each model. We tested this approach using datasets from several case-control studies of multiple racial/ethnic populations and compared discrimination of the models using area under the receiver operating characteristic curve (AUROC). Furthermore, we applied our multi-racial/ethnic PRS-313 in a sample of ~3000 multi-racial/ethnic women from the Athena Breast Screening Registry, case-control sampled by Gail score to be at elevated (Gail &gt;1.67) or average (Gail≤1.67) risk, to evaluate the impact of our multi-ethnic adjustment on risk stratification.

Results: A multi-race/ethnicity adjusted PRS-313 and PRS-167 plus ethnicity specific SNPs has moderate-high discriminatory power with AUROCs of 0.65 and 0.64, respectively. The specificity of our PRS-167 in the different race/ethnicity ancestries performs relatively well in Asian (AUROC 0.59) and Hispanic (AUROC 0.63) populations, but less so in African-ancestry (AUROC 0.56). Incorporating multi-race/ethnicity PRS into Gail model selected women, resulted in 20% of average-risk women transitioning to risk above 1.67%, and conversely, 38% of elevated risk patients were reclassified to average risk.

Conclusion: We constructed a PRS risk score that can be applied to multi-ethnic populations and found moderate-high discrimination. Additional work is needed for the African-ancestry population. The addition of a multi-race/ethnicity SNP model to risk classification based on the Gail model significantly changes risk stratification and clinical care recommendations due to down- or up-reclassification of women at average versus elevated risk.

Citation Format: Sarah Theiner, Donglei Hu, Scott Huntsman, Yiwey Shieh, Laura Fejerman, Irene Acerbi, Sarah D Sawyer, Paige Kendall, Wei Zheng, Dezheng Huo, Olufunmilayo I Olopade, Christopher Haiman, Karla Kerlikowske, Steven Cummings, Ester John, Gabriela Torres-Mejia, Lawrence H Kushi, Denise Wolf, Jeffery A Tice, David A Pearce, Laura Esserman, Athena Breast Health Network Investigators and Advocate Partners, Laura J van ‘t Veer, Elad Ziv. A breast cancer multi-racial/ethnic polygenic risk score for improved personalized breast cancer screening [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P2-10-05.

Abstract 3361: A prescription for new trial designs for drug development focused on the neoadjuvant setting: Save lives, resources, and time

Background: Traditionally, new drug combinations are first tested for safety and efficacy in the stage 4 setting. The I-SPY 2 TRIAL has focused on bringing promising new combinations into the phase 2/3 high-risk setting once safety is established. I-SPY 2 is an adaptive neoadjuvant platform trial for women with stage 2/3 breast cancer at high risk for early recurrence. In this setting, complete pathologic response (pCR) is the primary endpoint. We and others have demonstrated that pCR is highly predictive of distant recurrence free survival at 3 years. In I-SPY 2 the hazard rate is 0.2 (Confidence Interval 0.11-0.37), regardless of subtypes or agent. Agents that extend progression free survival in the metastatic setting, can be lifesaving when given at an earlier stage setting.

Methods: The health economic benefits of achieving pCR were investigated using a Markov model describing the risk of recurrence, progression and death. The risk of recurrence was informed by I-SPY 2 and the risk of cancer progression and the associated treatment costs were based on literature values. We assumed constant recurrence rate without accounting for subtype specific rates in this first version of the model.

Results: For each additional patient with pathologic complete response a net monetary benefit of $170,000 (Credible Interval 95% 100,000—250,000) and a gain of 4 life-years (CrI 95% 2—6) was predicted. The ICER for pCR is -$45,000. This represents the aggregate benefit across all I-SPY cancers. Modeling accounting for cancer subtype is in process and will be presented also.

Conclusion: A short term endpoint, response to chemotherapy in the neoadjuvant setting, which is highly correlated with long term outcome, provides the opportunity to focus drug development on improving that endpoint. Enabling more patients to achieve a pCR would provide enormous benefit in terms of lives and resources saved. The economic modeling, along with the findings from I-SPY 2 suggests that we should shift drug development to the high risk early setting and evolve drug designs to improve every patient’s outcome. In I-SPY 2, we are shifting our platform trial design to increase every patient’s chance to achieve pCR. Platform adaptive trials in the early stage neoadjuvant setting are ideal for advancing the field and maximizing benefit for patients.

Citation Format: Andreas Karlsson, Yiwey Shieh, Andre Dempsey, Christina Yau, Angela Dmichele, Doug Yes, Laura van't Veer, Nola Hylton, Martin Eklund, Laura Esserman. A prescription for new trial designs for drug development focused on the neoadjuvant setting: Save lives, resources, and time [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3361.

Abstract 2419: A polygenic risk score predicts breast cancer risk in Latinas

Background: Genome-wide association studies (GWAS) have identified over 180 single nucleotide polymorphisms (SNPs) associated with breast cancer risk. Polygenic risk scores (PRS) represent the combined effects of multiple SNPs and have been consistently shown to improve the performance of existing risk models. Most SNPs were discovered in women of European ancestry. Thus, there are limited data on how PRS perform in Latinas, whose ancestry is a mixture of European and Indigenous American. We therefore sought to validate the performance of a 184-SNP PRS in Latinas.

Methods: We conducted a pooled analysis of U.S. Latina and Mexican participants from 6 existing studies. Our analysis included 3,441 women with breast cancer and 7,773 women without breast cancer. We constructed a PRS containing 184 SNPs associated with breast cancer in prior GWAS, p &lt; 5 x 10-8. We used multivariable logistic regression to evaluate the associations between the PRS and breast cancer, adjusting for genetic ancestry and study of origin. To assess discrimination, we calculated the area under the receiver operating characteristic curve (AUROC). To test the performance of the PRS by genetic ancestry, we stratified our analysis by quartiles of Indigenous American genetic ancestry.

Results: The PRS was associated with breast cancer, with an odds ratio (OR) per standard deviation increment of 1.51 (95% CI 1.44-1.59). The PRS showed intermediate discrimination for cases vs. controls, with an AUROC of 0.62 (95% CI 0.60-0.63). When we stratified the analysis by genetic ancestry, the PRS performed worse in women with higher Indigenous American/lower European ancestry. Specifically, the discrimination of the PRS was least in the top quartile of Indigenous American ancestry and greatest in the bottom quartile, with AUROC of 0.60 (95% CI 0.57-0.62) vs. 0.65 (95% CI 0.62-0.67), respectively (p = 0.01). The corresponding ORs per standard deviation of the PRS were 1.40 (95% CI 1.29-1.53) for the top quartile and 1.70 (95% CI 1.52-1.89) for the bottom quartile of Indigenous American ancestry (p = 0.006).

Conclusions: A 184-SNP PRS predicts breast cancer in Latinas, with the AUROC of 0.62 in our study being comparable to previous estimates in Europeans. However, the performance of the PRS varied according to genetic ancestry. While our results suggest the PRS may be used as-is in Latinas with higher European ancestry, future efforts should focus on refining the PRS in Latinas of higher Indigenous American ancestry through discovery and replication of novel predictive SNPs in this subgroup.

Citation Format: Yiwey Shieh, Laura Fejerman, Sarah D. Sawyer, Donglei Hu, Scott Huntsman, Esther M. John, Lawrence H. Kushi, Gabriela Torres-Mejia, Jeffrey N. Weitzel, Christopher A. Haiman, Elad Ziv, Susan L. Neuhausen. A polygenic risk score predicts breast cancer risk in Latinas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2419.

Body mass index, mammographic density, and breast cancer risk by estrogen receptor subtype

Background

Obesity and elevated breast density are common risk factors for breast cancer, and their effects may vary by estrogen receptor (ER) subtype. However, their joint effects on ER subtype-specific risk are unknown. Understanding this relationship could enhance risk stratification for screening and prevention. Thus, we assessed the association between breast density and ER subtype according to body mass index (BMI) and menopausal status.

Methods

We conducted a case-control study nested within two mammography screening cohorts, the Mayo Mammography Health Study and the San Francisco Bay Area Breast Cancer SPORE/San Francisco Mammography Registry. Our pooled analysis contained 1538 ER-positive and 285 ER-negative invasive breast cancer cases and 4720 controls matched on age, menopausal status at time of mammogram, and year of mammogram. Percent density was measured on digitized film mammograms using computer-assisted techniques. We used polytomous logistic regression to evaluate the association between percent density and ER subtype by BMI subgroup (normal/underweight, < 25 kg/m² versus overweight/obese, ≥ 25 kg/m²). We used Wald chi-squared tests to assess for interactions between percent density and BMI. Our analysis was stratified by menopausal status and hormone therapy usage at the time of index mammogram.

Results

Percent density was associated with increased risk of overall breast cancer regardless of menopausal status or BMI. However, when analyzing breast cancer across ER subtype, we found a statistically significant (p = 0.008) interaction between percent density and BMI in premenopausal women only. Specifically, elevated percent density was associated with a higher risk of ER-negative than ER-positive cancer in overweight/obese premenopausal women [OR per standard deviation increment 2.17 (95% CI 1.50–3.16) vs 1.33 (95% CI 1.11–1.61) respectively, P_{heterogeneity} = 0.01]. In postmenopausal women, elevated percent density was associated with similar risk of ER-positive and ER-negative cancers, and no substantive differences were seen after accounting for BMI or hormone therapy usage.

Conclusions

The combination of overweight/obesity and elevated breast density in premenopausal women is associated with a higher risk of ER-negative compared with ER-positive cancer. Eighteen percent of premenopausal women in the USA have elevated BMI and breast density and may benefit from lifestyle modifications involving weight loss and exercise.

Electronic supplementary material

The online version of this article (10.1186/s13058-019-1129-9) contains supplementary material, which is available to authorized users.

Abstract P4-09-03: Simulated outcomes of personalized versus guideline-based breast cancer screening

Introduction: Personalized screening, or screening tailored to individual breast cancer risk, is being studied as an improvement on the current practice of guideline-based screening. WISDOM (Women Informed to Screen Depending on Measures of Risk) is an ongoing randomized trial comparing personalized to annual screening. To project the efficacy, safety, and cost of personalized screening on a population level, we constructed a simulation model comparing personalized to guideline-based strategies across the outcomes of advanced (Stage IIB+) cancers, false positives, biopsies, and cost.

Methods: Our simulated cohort consisted of 100,000 women aged 40-74 with demographic and risk factor distributions based on the U.S. screening population. We modeled the WISDOM approach to personalized screening where recommendations are based on the results of panel-based mutation testing and 5-year risk estimates from a clinical risk model modified by a polygenic risk score containing 76 genetic variants (SNPs). Simulated women were randomly assigned a clinical and genetic risk profile, which were integrated to generate a 5-year risk estimate. This was then used to assign a starting and stopping age, frequency, and modality (MRI vs. mammogram) of screening. We compared the aggregate outcomes over a 1-year time window between personalized screening and 3 strategies based on U.S. professional society guidelines (Table).

Results: There was no statistically significant difference in advanced cancers between screening strategies (Table). However, the biennial, hybrid, and personalized strategies resulted in fewer false positives and biopsies compared to annual screening, and at lower cost. Though aggregate outcomes between the hybrid and personalized strategies were similar, the average 5-year risk of women assigned to annual screening under the personalized strategy was higher than that of the hybrid strategy, 1.7% vs. 1.2%. Similarly, the average 5-year risk of women assigned to biennial screening was lower under the personalized strategy, 1.1% vs. 1.9%.

Conclusion: Our simulations show that personalized screening results in a similar incidence of advanced cancers as annual screening while reducing false positives, biopsies, and cost. Compared to other guideline-based strategies, personalized screening better allocates screening resources by identifying higher-risk women for more intensive screening, and lower-risk women for less intensive screening.

Descriptions and simulated outcomes of four screening strategiesStrategyStarting age, yearsStopping age, yearsFrequencyStage IIB+ cancers, RR1 (95% CI)2False positives, RR1 (95% CI)2Biopsies, RR1 (95% CI)2Cost, millions USD per 100,000 womenAnnual (American College of Obstetricians and Gynecologists)4074Annualrefrefref$22.1Biennial (U.S. Preventive Services Task Force)5074Biennial1.13 (0.98-1.28)0.44 (0.33-0.56)0.46 (0.35-0.58)$8.4Hybrid (American Cancer Society)45Per life expectancy45-55: Annual 55+: Biennial1.09 (0.95-1.25)0.58 (0.49-0.67)0.64 (0.56-0.73)$14.7Personalized (WISDOM)40-503Per life expectancyAnnual or Biennial41.01 (0.89-1.12)0.55 (0.46-0.65)0.56 (0.47-0.65)$14.11relative risk; 295% confidence interval; 3start when 5-year risk &gt; 1.3%; 4annual if age 40-49 + dense breasts or top 2.5th percentile of 5-year risk

Citation Format: Shieh Y, Esserman L, Eklund M. Simulated outcomes of personalized versus guideline-based breast cancer screening [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P4-09-03.

Abstract OT2-08-01: Personalized breast cancer screening in a population based study: Women Informed to Screen Depending On Measures of risk (WISDOM)

Background: WISDOM is a 100,000 healthy women preference-tolerant, pragmatic study comparing annual to personalized risk-based breast screening. The novelty of WISDOM personalized screening is the integration of previously validated genetic and clinical risk factors (age, family history, breast biopsy results, ethnicity, mammographic density) into a single risk assessment model that directs the starting age, timing, and frequency of screening. The goal of WISDOM is to determine if personalized screening, compared to annual screening, is as safe, less morbid, enables prevention, and is preferred by women. The study is registered on ClinicalTrials.gov, NCT02620852.

Methods: Women aged 40-74 years with no history of breast cancer or DCIS, and no previous double mastectomy can join the study online at wisdomstudy.org. Participants can elect randomization or self-select a study arm, and provide electronic consent and Release for Medical Information using DocuSign. For all participants, 5-year risk of developing breast cancer is calculated according to the Breast Cancer Screening Consortium (BCSC) model. Participants in the personalized arm undergo panel-based mutation testing, and their 5-year risk is calculated using the BCSC score combined with a Polygenic Risk Score (BCSC-PRS) that includes 75 single nucleotide polymorphisms (SNPs, increase to 229) known to increase breast cancer risk. SNPs and mutations (BRCA1, BRCA2, TP53, PTEN, STK11, CDH1, ATM, PALB2, and CHEK2) are assessed by saliva-based testing through Color Genomics. 5-year risk level thresholds are used to stratify for low-, moderate- and high risk. Risk stratification determines age to start, stop, and frequency of screening.

Enrollment: As of July 2018, the WISDOM study is open to all eligible women in California, North Dakota, South Dakota, Minnesota and Iowa. To date, 23,329 eligible women have registered and 14,393 women have consented to participate in the trial. We analyzed 3,255 participants who have completed risk assessment in the personalized arm. The median age was 56 years. 82% were Caucasian, 1% African-American, and 6% Asian. 9% self-reported as Hispanic. We are partnering with health insurers and self-insured companies using coverage with evidence progression. To strengthen generalizability, we are expanding to other states. WISDOM enrollment will continue past 2019.

Feasibility: To evaluate the addition of PRS, we used paired statistical tests (McNemar) to compare the distributions of BCSC, and BCSC-PRS risk estimates around low-risk (&lt;1.3%), and very-high risk (&gt;6%) thresholds, the latter corresponding to 5-year risk of a BRCA mutation carrier. The median 5-year risk was 1.5% (IQR 1.0-2.1%) using the BCSC model, and 1.4% (IQR 0.8-2.5%) using the BCSC-PRS model. The BCSC-PRS model classified more women into the low (&lt;1%) and very high (≥6%) risk categories compared to the BCSC model (p &lt; 0.001).

Conclusions: Our findings demonstrate that incorporating genetic variants into a validated clinical model is feasible and impacts risk classification compared to a model without genetic risk factors. Results at 5 years will reveal if this classification improves healthcare value by reducing screen volumes and costs without jeopardizing outcomes.

Citation Format: Acerbi I, Shieh Y, Madlensky L, Tice J, Ziv E, Eklund M, Blanco A, DeRosa D, Tong B, Goodman D, Nassereddine L, Anderson N, Harvey H, Layton T, Park HL, Petruse A, Stewart S, Wernisch J, Risty L, Koenig B, Sarrafan S, Firouzian R, Kaplan C, Hiatt R, Parker BA, Wenger N, Lee V, Heditsian D, Brain S, Stover Fiscalini A, Borowsky AD, Anton-Culver H, Naeim A, Kaster A, Talley M, van 't Veer LJ, LaCroix A, Wisdom Study and Athena Breast Health Network Investigators and Advocate Partners, Esserman LJ. Personalized breast cancer screening in a population based study: Women Informed to Screen Depending On Measures of risk (WISDOM) [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr OT2-08-01.

Abstract OT3-03-01: Preference-Tolerant randomized trial of risk-based vs. annual breast cancer screening: WISDOM study in progress

Purpose: Women Informed to Screen Depending on Measures of risk (WISDOM) trial is a pragmatic study comparing two real world approaches to clinical care for breast screening: annual screening versus personalized screening. The novelty of the personalized arm of the study is that we are combining known risk factors (age, family history, history of breast disease, ethnicity, BIRADS breast density, and genetics) into a single risk assessment model. All components of the model have been tested and established, but have never been used jointly.

The goal of the WISDOM study is to examine the effectiveness of personalized breast cancer screening and to bring objective recommendations to the current mammography screening debate.

Methods: The WISDOM trial will enroll 100,000 women with a preference-tolerant design that will determine if risk-based screening vs. annual screening, is as safe, less morbid, enables prevention, and is preferred by women. Women 40 - 74 years of age with no history of breast cancer or DCIS, and no previous double mastectomy can join the study from the WISDOM Study website (wisdomstudy.org). All participants sign up, elect randomization or self-select the study arm, provide electronic consent using DocuSign (eConsent), and sign a Medical Release Form. For all participants, 5-year risk of developing breast cancer is calculated according to the Breast Cancer Screening Consortium (BCSC) model. For participants in the personalized arm, the overall 5-year risk BCSC score is combined with a Polygenic Risk Score, based on a genetic test including mutations in 9 genes (BRCA1, BRCA2, TP53, PTEN, STK11, CDH1, ATM, PALB2, and CHEK2) and a panel of 75 common single nucleotide polymorphisms known to increase breast cancer risk. Risk stratification will determine frequency of screening. The study is registered on ClinicalTrials.gov as NCT02620852.

Results: As of June 12th 2017, the WISDOM study is live at all UC medical centers and recruitment is open to all eligible women in California. Up to date 4,769 eligible women registered at all sites. 2,823 women have consented in the trial. 64% were randomized and 36% chose their screening arm. A pilot was conducted to test the logistics of online participation and examine the acceptance of the study design and approach. We are partnering with health insurance companies and self-insured companies to reach our recruitment goal.

Conclusions: Enrollment will be completed by end of 2018.

Acknowledgment: support by the Patient-Centered Outcomes Research Institute (PCORI), PCS-1402-10749 to L.J.E.

(*) Authors equally contributed to this work.

Citation Format: Acerbi I, Abihider K, Ling J, Layton T, DeRosa D, Madlensky L, Tice J, Shieh Y, Ziv E, Sarrafan S, Firouzian R, Tong B, Blanco A, Lee V, Heditsian D, Brain S, Kaplan C, Borowsky A, Anton-Culver H, Naeim A, Cink T, Stover Fiscalini A, Parker B, van 't Veer L, Wisdom Study and Athena Breast Health Network Investigators and Advocate Partners, LaCroix A, Esserman L. Preference-Tolerant randomized trial of risk-based vs. annual breast cancer screening: WISDOM study in progress [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr OT3-03-01.

Abstract P3-09-02: Risk stratification using clinical risk factors and genetic variants in a personalized screening trial

Introduction: Tailoring breast cancer screening according to individual risk may represent an improvement over the current practice of age-based screening. WISDOM (Women Informed to Screen Depending on Measures of Risk) is an ongoing randomized trial comparing the safety, efficacy, cost, and patient acceptability of personalized versus annual screening. Women in the personalized arm receive screening recommendations based on sequencing of 9 genes associated with hereditary breast cancer and a 5-year risk estimate from the Breast Cancer Surveillance Consortium (BCSC) risk model modified by a polygenic risk score (PRS) comprised of 75 single nucleotide polymorphisms. WISDOM represents the first-ever use of a PRS to prospectively modify risk estimates and allows comparison of risk model performance in a population-based setting. Thus, we evaluated the risk estimates generated by: 1) the Breast Cancer Risk Assessment Tool (BCRAT) based on the Gail model, 2) the BCSC model, and 3) the BCSC model modified by the PRS (BCSC-PRS).

Methods: We analyzed participants in the personalized screening arm of the WISDOM Study (NCT02620852). The trial opened in October 2016 and is enrolling participants aged 40-74 years. Participants' self-reported demographic and risk factor information were collected through an online portal. Genotyping of participants in the personalized arm was done using a custom panel from Color Genomics. 5-year risk estimates were generated using the BCRAT (2011 version), BCSC, and BCSC-PRS models. In the latter, the PRS was used as a Bayesian likelihood ratio to modify the BCSC 5-year risk estimate. We compared the distributions of BCRAT, BCSC, and BCSC-PRS risk estimates around a low-risk (&lt;1%) and moderately high-risk (≥3%) threshold using a paired statistical test (McNemar).

Results: To date, WISDOM has enrolled 2,065 participants, of whom 1,157 are in the personalized arm and 830 have completed risk assessment. The median age was 57 years (interquartile range, IQR 49-64). 83% were Caucasian, 2% African-American, and 7% Asian. 8% self-reported as Hispanic. The median 5-year risk was 1.7% (IQR 1.1-2.3%) using the BCRAT, 1.6% (IQR 1.1-2.3%) using the BCSC model, and 1.5% (IQR 0.9-2.7%) using the BCSC-PRS model. The BCSC-PRS model classified more women into the low (&lt;1%) and moderately high (≥3%) risk categories compared with the BCRAT (p &lt; 0.001) and BCSC model (p &lt; 0.001), Table.

5-year risk classification according to the BCRAT, BCSC and BCSC-PRS models &lt;1%1-3%≥3% n (%)n (%)n (%)Gail161 (19)556 (67)113 (14)BCSC159 (19)568 (68)103 (12)BCSC-PRS275 (33)379 (46)176 (21)

Discussion: Adding a PRS to the BCSC model categorized significantly more women below the low-risk threshold and above the moderately high-risk threshold compared with the BCSC model and BCRAT. Furthermore, the BCSC and BCRAT generated similar distributions of risk estimates. Follow-up with incident breast cancer data is needed to determine whether the reclassification provided by the PRS improves risk stratification and clinical outcomes. However, our preliminary findings suggest that incorporating genetic variants into a validated clinical model is feasible and could enhance risk prediction.

Citation Format: Shieh Y, Ziv E, Eklund M, Sabacan L, Firouzian R, Madlensky L, Anton-Culver H, Borowsky A, LaCroix A, Naeim A, Parker B, van't Veer L, Esserman L, Tice J, WISDOM Study and Athena Network Investigators WS. Risk stratification using clinical risk factors and genetic variants in a personalized screening trial [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P3-09-02.

Joint relative risks for estrogen receptor-positive breast cancer from a clinical model, polygenic risk score, and sex hormones

BACKGROUND

Models that predict the risk of estrogen receptor (ER)-positive breast cancers may improve our ability to target chemoprevention. We investigated the contributions of sex hormones to the discrimination of the Breast Cancer Surveillance Consortium (BCSC) risk model and a polygenic risk score comprised of 83 single nucleotide polymorphisms.

METHODS

We conducted a nested case-control study of 110 women with ER-positive breast cancers and 214 matched controls within a mammography screening cohort. Participants were postmenopausal and not on hormonal therapy. The associations of estradiol, estrone, testosterone, and sex hormone binding globulin with ER-positive breast cancer were evaluated using conditional logistic regression. We assessed the individual and combined discrimination of estradiol, the BCSC risk score, and polygenic risk score using the area under the receiver operating characteristic curve (AUROC).

RESULTS

Of the sex hormones assessed, estradiol (OR 3.64, 95% CI 1.64-8.06 for top vs bottom quartile), and to a lesser degree estrone, was most strongly associated with ER-positive breast cancer in unadjusted analysis. The BCSC risk score (OR 1.32, 95% CI 1.00-1.75 per 1% increase) and polygenic risk score (OR 1.58, 95% CI 1.06-2.36 per standard deviation) were also associated with ER-positive cancers. A model containing the BCSC risk score, polygenic risk score, and estradiol levels showed good discrimination for ER-positive cancers (AUROC 0.72, 95% CI 0.65-0.79), representing a significant improvement over the BCSC risk score (AUROC 0.58, 95% CI 0.50-0.65).

CONCLUSION

Adding estradiol and a polygenic risk score to a clinical risk model improves discrimination for postmenopausal ER-positive breast cancers.

Abstract P5-09-05: A model with polygenic risk score and mammographic density predicts interval cancers

Introduction:

Interval breast cancers present with clinical symptoms following a normal screening mammogram. They are associated with unfavorable biological features and with dense breasts. Models predictive of aggressive phenotypes may facilitate tailored screening for women at elevated risk of interval cancers. Polygenic risk scores (PRS) represent the cumulative effects of multiple single nucleotide polymorphisms (SNPs) and can be used to risk-stratify women. In prior reports, PRS is preferentially associated with screen-detected rather than interval cancers. We investigated methods to refine the PRS to preferentially predict interval cancers, and tested the performance of the PRS in joint models with mammographic breast density (MBD).

Methods:

We used data from 1058 breast cancer cases from The Cancer Genome Atlas (TCGA) as the discovery set for our PRS. We selected 107 SNPs from genomewide association studies of breast cancer risk for testing against tumor status at last follow-up in TCGA. Presence of tumor indicated recurrence, progression, or positive margins after resection. Women with tumor present at &lt;100 days of follow-up were excluded. Suggestive associations (p&lt;0.2) were used to construct a PRS, calculated as the sum across all SNPs of the per-allele log-odds ratio multiplied by the number of risk alleles for each SNP. We tested the performance of the PRS in a nested case-control dataset with 471 cases (102 interval cancers, 369 screen detected) and 496 controls from the California Pacific Medical Center Research Institute cohort. Logistic regression was used to evaluate the association between PRS, MBD and interval cancers. Area under the receiver operating characteristic (AUROC) curve was used to measure discrimination.

Results:

Of 107 SNPs, 23 had suggestive associations with presence of tumor at last follow-up in TCGA. The 23-SNP PRS discriminated between women with interval cancers and controls, with AUROC 0.57 (95% CI 0.51-0.63). With the inclusion of MBD in the model, the AUROC was 0.68 (95% CI 0.62-0.74). Women in the highest PRS quintile had an unadjusted 2.07-fold odds (95% CI 1.05-4.07) of developing interval cancers compared with women in the lowest quintile; adjustment for MBD did not change the point estimate. The PRS also discriminated between women with interval and screen-detected cancers, although the findings did not reach statistical significance (AUROC 0.55, 95% CI 0.48-0.61). With the inclusion of MBD in the model, the AUROC was 0.63 (95% CI 0.57-0.69).

Discussion:

A PRS associated with presence of tumor at last follow-up was independently predictive of interval cancers relative to controls. Models with PRS and MBD discriminated between interval and screen-detected cancers, although MBD provided most of the predictive power. Our findings are limited by the size and low number of recurrences in TCGA. It is possible that tumor status largely reflects treatment received, and may only partially represent the biological pathways of interval cancers. Our results suggest that SNPs may potentially identify women at risk for developing interval breast cancer, although further validation is required.

Citation Format: Shieh Y, Hu D, Huntsman S, Ma L, Gard CC, Leung JWT, Tice JA, Cummings SR, Kerlikowske K, Ziv E. A model with polygenic risk score and mammographic density predicts interval cancers [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P5-09-05.

Breast Cancer Screening in the Precision Medicine Era: Risk-Based Screening in a Population-Based Trial

Ongoing controversy over the optimal approach to breast cancer screening has led to discordant professional society recommendations, particularly in women age 40 to 49 years. One potential solution is risk-based screening, where decisions around the starting age, stopping age, frequency, and modality of screening are based on individual risk to maximize the early detection of aggressive cancers and minimize the harms of screening through optimal resource utilization. We present a novel approach to risk-based screening that integrates clinical risk factors, breast density, a polygenic risk score representing the cumulative effects of genetic variants, and sequencing for moderate- and high-penetrance germline mutations. We demonstrate how thresholds of absolute risk estimates generated by our prediction tools can be used to stratify women into different screening strategies (biennial mammography, annual mammography, annual mammography with adjunctive magnetic resonance imaging, defer screening at this time) while informing the starting age of screening for women age 40 to 49 years. Our risk thresholds and corresponding screening strategies are based on current evidence but need to be tested in clinical trials. The Women Informed to Screen Depending On Measures of risk (WISDOM) Study, a pragmatic, preference-tolerant randomized controlled trial of annual vs personalized screening, will study our proposed approach. WISDOM will evaluate the efficacy, safety, and acceptability of risk-based screening beginning in the fall of 2016. The adaptive design of this trial allows continued refinement of our risk thresholds as the trial progresses, and we discuss areas where we anticipate emerging evidence will impact our approach.

Population-based screening for cancer: hope and hype

Several important lessons have been learnt from our experiences in screening for various cancers. Screening programmes for cervical and colorectal cancers have had the greatest success, probably because these cancers are relatively homogenous, slow-growing, and have identifiable precursors that can be detected and removed; however, identifying the true obligate precursors of invasive disease remains a challenge. With regard to screening for breast cancer and for prostate cancer, which focus on early detection of invasive cancer, preferential detection of slower-growing, localized cancers has occurred, which has led to concerns about overdiagnosis and overtreatment; programmes for early detection of invasive lung cancers are emerging, and have faced similar challenges. A crucial consideration in screening for breast, prostate, and lung cancers is their remarkable phenotypic heterogeneity, ranging from indolent to highly aggressive. Efforts have been made to address the limitations of cancer-screening programmes, providing an opportunity for cross-disciplinary learning and further advancement of the science. Current innovations are aimed at identifying the individuals who are most likely to benefit from screening, increasing the yield of consequential cancers on screening and biopsy, and using molecular tests to improve our understanding of disease biology and to tailor treatment. We discuss each of these concepts and outline a dynamic framework for continuous improvements in the field of cancer screening.

Impact of mammographic screening on the detection of good and poor prognosis breast cancers

We sought to compare the molecular signature of node negative cancers from two cohorts 15 years apart, to determine if there is molecular evidence of increase in low and ultralow risk cancers over time. We studied the impact of age, time period of diagnosis, and mammographic screening on biology of tumors where The Netherlands Cancer Institute 70-gene prognosis signature was generated as part of 2 validation series, one retrospective (1984-1992), Cohort 1, and one prospective (2004-2006), Cohort 2. A total of 866 patients were analyzed. Regardless of time period of diagnosis, the proportion of T1, grade 1, hormone receptor positive (HR) tumors, and good prognosis by 70-gene signature significantly increases as age increases (P < 0.01). In women aged 49-60, the time period of diagnosis significantly affects the proportion of cancers that were NKI 70-gene low risk: 40.6% (67/165) compared with 58% (119/205) for Cohorts 1 and 2, respectively. This is in contrast to the absence of a significant change for women under age 40, where 25% (17/68) and 30% (17/56) were low risk in Cohorts 1 and 2, respectively. In women aged 49-60, using an ultralow risk threshold of the 70-gene signature, 10% of tumors in Cohort 1 were ultralow risk compared with 30% for women with screen-detected cancers in Cohort 2. Older age and method of detection (screening) are associated with a higher likelihood of a biologically low risk tumor. In women over age 50, biologically low risk tumors are frequent and tools that classify risk may minimize overtreatment.

Characterizing the impact of 25 years of DCIS treatment

The significant increase in the detection and treatment of ductal carcinoma in situ (DCIS) since the introduction of screening mammography has not been accompanied by the anticipated reduction in invasive breast cancer (IBC) incidence. The prevalence of DCIS requires a reexamination of the population level effects of detecting and treating DCIS. To further our understanding of the possible impact of DCIS diagnosis and treatment on IBC incidence in the U.S., we simulated breast cancer incidence over 25 years under various assumptions regarding the baseline incidence of IBC and the progression of DCIS to IBC. The simulations demonstrate a tradeoff between the expected increased incidence of IBC absent any DCIS detection and treatment and the rate of progression of DCIS to IBC. Our analyses indicate that a high progression of DCIS to IBC implies a significant increase in incidence of IBC over what is observed had we not detected and treated DCIS. Conversely, if we assume that there would not have been a significant increase over and above the observed incidence evident in SEER, then our model indicates that the rate of DCIS progression to clinically significant IBC is low. Given the tradeoff illustrated by our model, we must reevaluate the assumption that DCIS is a short-term obligate precursor of invasive cancer and instead focus on further exploration of the true natural history of DCIS.

Rethinking screening for breast cancer and prostate cancer

After 20 years of screening for breast and prostate cancer, several observations can be made. First, the incidence of these cancers increased after the introduction of screening but has never returned to prescreening levels. Second, the increase in the relative fraction of early stage cancers has increased. Third, the incidence of regional cancers has not decreased at a commensurate rate. One possible explanation is that screening may be increasing the burden of low-risk cancers without significantly reducing the burden of more aggressively growing cancers and therefore not resulting in the anticipated reduction in cancer mortality. To reduce morbidity and mortality from prostate cancer and breast cancer, new approaches for screening, early detection, and prevention for both diseases should be considered.

A role for biomarkers in the screening and diagnosis of breast cancer in younger women

The widespread usage of screening mammography has resulted in an increase in the detection of early-stage disease, particularly in situ (stage 0) and early-stage (stage 1) cancers. However, incidence of stage 2 and 3 disease has not fallen commensurately, suggesting a bias in the detection of indolent cancers rather than aggressive cancers. Improved screening and diagnosis of a broader range of cancers is therefore an important need. Although MRI is a very sensitive breast cancer detection tool that has become standard for women at very high risk, it lacks sufficient specificity and cost-effectiveness for use as a general screen. The greatest opportunity for molecular tools to improve breast cancer outcomes is to better discern biologically aggressive cancers, especially in women under the age of 50 years. In this age group, presentation in stage 2 or 3 is more common and mammographic screening is less efficacious. We propose a multi-tiered triage strategy that uses emerging markers of susceptibility to segment the population for more focused screening with imaging. In particular, it would be helpful to identify a subset of at-risk, younger women who would benefit from intensive surveillance or preventive interventions. It is likely that tests for susceptibility, unless they are highly specific, will need to be combined with indicators of short-term risk. Although the combined sensitivity and specificity of screening must be high, each individual test does not require high specificity. It is important, however, for the susceptibility tests and short-term risk markers to be highly sensitive. If the majority of women under 50 years of age who develop breast cancer are captured with this strategy, then mammography screening for the general population can start at age 50 years. Finally, and perhaps most importantly, biomarkers of susceptibility and short-term risk are likely to provide insight into the biology of tumors that develop, leading to new interventions to support prevention. The most effective preventive strategies will be those where a marker predicts risk for the disease, as well as the benefit from preventive interventions.

Detection of norwalk-like virus in shellfish implicated in illness

In the 1990s, Norwalk-like viruses (NLVs) were identified in patient specimens as the primary pathogen associated with shellfish-borne gastroenteritis in the United States. Identification of these viruses from implicated shellfish has been difficult due to inefficient recovery of viruses, natural polymerase chain reaction (PCR) inhibitors in shellfish, and low virus contamination. Recent improvements to the method of detecting NLVs in shellfish include enhanced processing of virus and shellfish samples, application of nested PCR and nucleotide sequencing, and increased knowledge of NLV genetic diversity. Using a newly developed and sensitive method, an NLV G2 strain was identified in 2 oyster samples implicated in a 1998 California outbreak involving 171 cases. NLV capsid primers demonstrated a greater specificity of PCR detection than did polymerase primers. The 175-base viral capsid nucleotide sequences derived from oysters were 100% identical to those derived from a patient stool sample. This finding supports the epidemiologic associations indicating that contaminated shellfish serve as the vehicle for NLV transmission.