Citations

10505 Background: Polygenic risk scores (PRS) have been shown to substantially improve breast cancer (BC) risk prediction when incorporated into traditional risk assessment models. However, PRS developed primarily in women of European ancestry have shown poor performance when applied to non-European populations. We previously described development and validation of a multiple-ancestry PRS (MA-PRS) that is based on individual ancestral genetic composition. MA-PRS has been incorporated into the Tyrer-Cuzick model for use in clinical practice and has been shown to provide independent value to the model. Here, we describe performance of the MA-PRS in a large cohort of women from diverse ancestral backgrounds. Methods: The study cohort included 203,586 patients who were referred for hereditary cancer testing and negative for pathogenic variants in genes associated with BC. MA-PRS was calculated as previously described based on 149 SNPs (93 BC and 56 ancestry-informative). Association of MA-PRS with invasive BC status (affected vs unaffected) was analyzed using logistic regression adjusted for personal and family cancer history, age, and ancestry. Calibration was assessed by examining the MA-PRS distribution within unaffected patients, and through goodness-of-fit tests. All analyses were conducted within the full cohort and within ancestral subpopulations. Odds ratios (ORs) are reported per standard deviation. Results: One-fifth (43,782/203,586, 21.5%) of patients were diagnosed with invasive BC, and 60,657 (29.8%) of patients reported BC in a first degree relative. The MA-PRS distribution was centered around zero among unaffected patients overall and within each subpopulation. MA-PRS significantly improved BC risk prediction over clinical factors in the full cohort (OR = 1.43, 95% CI:1.41-1.44) and within each ancestral subpopulation (Table). The strongest associations were observed in Ashkenazi Jewish (OR = 1.56, 95% CI:1.39-1.76) and South Asian (OR = 1.49,95% CI: 1.23-1.81) populations. The top decile of the MA-PRS consistently identified patients with two-fold increased risk of developing BC. Goodness-of-fit tests showed that the MA-PRS was well calibrated and predicted BC risk accurately in the tails of the distribution for both European and non-European women. Conclusions: The breast cancer MA-PRS based on genetic ancestral composition is well-calibrated and strongly associated with BC in all tested ancestral populations. Incorporation of PRS adds independent information to risk models and supports equitable access to personalized BC risk management. [Table: see text]

e18883 Background: Women comprise more than 40% of the American workforce, with many women working at the time of a breast cancer diagnosis. Pre-diagnosis psychological distress is a rarely studied factor that may affect cancer survivors’ workforce participation and mental health status post treatment. In this 2-site prospective cohort study, we evaluated return to work (RTW) in breast cancer patients (pts) with and without reported pre-diagnosis stress. Methods: We enrolled 198 female pts at Mayo Clinic in Minnesota and Florida with newly diagnosed stage 0-III breast cancer who worked 35-plus hours/week at time of diagnosis. Pts were screened for eligibility at the intake visit. Eligible pts were emailed a baseline survey at the time of diagnosis, then a follow-up survey at 3 months. Surveys assessed demographics, work factors, treatment, and psychological distress per the validated Kessler Psychological Distress Scale (K6). Primary aims were to assess 1) the impact of pre-diagnosis psychological distress on RTW in pts with a breast cancer diagnosis and 2) the incidence of severe psychological distress (K6 ≥13) in those with and without delay in RTW. Wilcoxon rank sum tests were used to compare pts with and without pre-diagnosis stress at baseline and 3 months. Results: 189 and 142 pts took part in the baseline and 3-month surveys, respectively. Here, 40.7% of enrolled pts reported experiencing one or more major life stressors in the 18 months before diagnosis. At 3 months, 6 of the 75 pts who responded (8.0%) endorsed a delay in RTW after breast cancer diagnosis. Half of these pts (3/75) had reported a pre-diagnosis stressor, revealing no significant difference in time to RTW between the stressed and not-stressed groups. Median K6 at diagnosis in those with delay in RTW was 14 (range, 10-17), significantly higher than the median K6 of 9 in those without delay in RTW (range, 6-23; p = 0.026). 5/6 pts who reported delay in RTW had baseline or 3-month K6 ≥13. There was no significant difference in the number of pts with K6 ≥13 at baseline vs. 3 months (31.2% vs. 21.8%, p = 0.85). Overall, the pt population was well educated and well salaried. Conclusions: Pre-diagnosis psychological distress is prevalent, but it does not seem to be associated with delayed RTW in breast cancer pts; indeed, few pts reported a delay in RTW. Pts with delayed RTW after a breast cancer diagnosis had significantly higher median K6, generally ≥13. Thus, delay in RTW in breast cancer pts may be a surrogate marker of more serious psychological illness. Additional study in a socioeconomically diverse pt population is needed.

Objective: The purpose of this feasibility pilot study was to evaluate safety and adherence of a wearable brain sensing wellness device designed to reduce stress among healthcare professionals (HCP). Methods: A total of 40 HCP were invited to participate in an open-label pilot study. Participants were asked to use a brain sensing wearable device (MUSE-S™) on a daily basis to reduce their stress, for a total of 90 days. Total study participation duration was 180 days. Study enrollment began in August 2021 and ended December 2021. The exploratory outcomes included stress, depression, sleep, burn-out, resilience, quality of life, and cognition. Results: Among the 40 HCP in study, the majority were female (85%), white (87.5%) and with an average age of 41.3 ± 11.0 years (SD). Participants used the wearable device an average of 23.8 times over a 30-day period with a mean duration of 5.8 min with each use. Study results demonstrate the positive impact of guided mindfulness using the wearable device MUSE-S™ and its accompanying application (APP). A statistically significant improvement was found for a reduction in stress ( P < .001) and improvement in resilience ( P = .02), quality of life ( P = .003), and cognition ( P < .001). The majority (91.9%) of the participants indicated they felt more relaxed after using the device, and 73% indicated they would continue to use this device at end-of-study. No adverse effects were reported. Conclusion: Study results show that 3 to 10 min of guided meditation during work hours through the use of a brain sensing wearable device is safe and acceptable, with associated health benefits for HCP.

Abstract Background: Personalized breast cancer (BC) risk assessment depends on known traditional risk factors, specific germline mutations, and genome-wide polygenic risk scores (PRS). PRS explains a substantial proportion of genetic BC susceptibility. Accuracy of BC risk prediction may be improved by combining a PRS with traditional risk factors. We recently developed and validated a 149-SNP PRS for women of diverse ancestries using ancestry-informative genetic markers and combined this with version 7 of the Tyrer-Cuzick (TC) model to generate a Combined Risk Score (CRS). Here, we describe a pre-specified prospective longitudinal clinical validation of CRS as a predictor of BC risk. Methods: Women in the U.S. who were referred for clinical genetic testing between January 2017 and February 2019 were matched to medical and hospital claims in an anonymized dataset. Women with a pathogenic mutation in a BC-related gene were excluded from analysis. Follow-up began 4 months after testing and extended to the earliest date of BC diagnosis, censoring at the time of BC preventive treatment, or November 1, 2019. Incident BC events were determined by an ICD10 code of C50.* and confirmed by relevant treatment codes. CRS calibration was evaluated by the ratio of observed (O) to expected (E) incident BCs for the full cohort, and for women split into event-based 5-year CRS risk deciles. Cox proportional hazards models were used to evaluate discriminatory accuracy in terms of hazard ratios (HR) with 95% confidence intervals (CI) and p-values from likelihood ratio chi-squared statistics. Kaplan-Meier analysis was used to examine risk for women split into high- or low-risk groups according to a 3% 5-year CRS risk threshold. Results: 130,058 women with 148,349 total patient years met study eligibility criteria and were matched to claims data. Over a median (range) follow-up of 12.1 (4.0-29.5) months, 340 incident BC events were observed. The CRS was well calibrated in the overall cohort with an O/E ratio of 1.11 (95% CI=0.99-1.23) and within deciles of predicted risk (Table). Importantly, in the highest risk decile, the O/E was 0.91 (95% CI=0.63-1.27) with CRS, but 0.67 (95% CI=0.46-0.94) with TC alone, illustrating the superior calibration of CRS. In a Cox model adjusted for age at testing, PRS had an HR per standard deviation (SD) of 1.48 (95% CI=1.33-1.64, p=2.55×10-13); the HR/SD was 1.43 (95% CI=1.29-1.59, p=1.61×10-11) after adjusting for family history. In a bivariate analysis using both CRS and TC to predict time to BC, CRS added significantly to the model after accounting for TC (HR/SD=2.89, 95% CI=2.12-3.94, p=1.20×10-11), whereas TC did not add significant information after accounting for CRS. 15,986 (12.3%) women were above the CRS high-risk threshold, including 123 with events. A total of 10,248 (7.9%) women were reclassified by the CRS model compared to the TC model. Among women who were classified as high-risk by TC, 32.6% were reclassified as low-risk by CRS; among those classified as low-risk by TC, 4.3% were reclassified as high-risk by CRS. The CRS high-risk group experienced events at over three times the rate of the low-risk group (HR=3.75, 95% CI=3.00-4.68, p=6.39×10-27). Conclusion: The CRS was well-calibrated in predicting BC and significantly improved upon a traditional risk factor model. Clinical use of the CRS may lead to improved BC prevention and screening strategies. Table: Absolute risk calibration by 5-year risk decile Incidence is reported per 1,000 women-years. 34 breast cancers were observed per decile. Citation Format: Brent Mabey, Elisha Hughes, Braden Probst, Holly J. Pederson, Timothy Simmons, Brian Morris, Brooke Hullinger, Susan Domchek, Charis Eng, Monique Gary, Jennifer Klemp, Semanti Mukherjee, Vijai Joseph, Kenneth Offit, Olufunmilayo I. Olopade, Sandhya Pruthi, Allison W. Kurian, Mark E. Robson, Pat Whitworth, Susanne Wagner, Jerry Lanchbury, Thomas Slavin, Alexander Gutin. PD14-05 Prospective longitudinal validation of a breast cancer risk prediction model in a cohort of 130,058 women [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 PD14-05.

Abstract Background: Despite evidence of substantial breast cancer risk reduction, few high-risk women adopt chemopreventive medications such as selective estrogen receptor modulators (SERMs) or aromatase inhibitors (AIs). Women with benign breast disease, such as atypical hyperplasia (AH) or lobular carcinoma in situ (LCIS), have an increased risk of developing breast cancer and derive a greater benefit from antiestrogens compared to other high-risk women. Reasons for low uptake of chemoprevention include insufficient patient and clinician knowledge about antiestrogens, time constraints during the clinical encounter, and concerns about side effects. To address these barriers, we have developed patient and provider web-based decision support tools to improve informed choice about breast cancer chemoprevention among women with AH or LCIS. Study design: We are conducting a cluster-randomized controlled trial of clinical decision support to improve chemoprevention informed choice among women with AH or LCIS and their treating providers. Twenty-six U.S. sites through the SWOG Cancer Research Network were randomly assigned 1:1 to standard educational materials alone or in combination with the patient-centered decision aid (RealRisks) and provider decision support tool (BNAV). A total of 415 patients and 200 healthcare providers will be recruited from these sites. RealRisks consists of interactive modules to calculate personalized breast cancer risk and elicit preferences on chemoprevention. The modules are available in English and Spanish. BNAV is comprised of self-directed case-based learning modules on breast cancer risk assessment and chemoprevention. Patients complete questionnaires at baseline, 6 and 12 months. Providers complete surveys at baseline and after their enrolled patient’s 6-month clinical encounter. The primary endpoint is chemoprevention informed choice at 6 months, using a measure combining knowledge, attitude, and intention scales. Secondary endpoints include perceived breast cancer risk/worry, chemoprevention knowledge/intention, decision conflict/regret, shared decision-making, and chemoprevention uptake. For patients who begin chemoprevention, adherence and reasons for discontinuation are assessed annually for up to 5 years. Barriers and facilitators to implementing RealRisks and BNAV into clinic workflow will be assessed by conducting patient and provider interviews at baseline and mid-implementation. Eligibility criteria: Eligible patients include women, age 35-74 years, with AH or LCIS, no history of breast cancer, no prior use of SERMs or AIs, no bilateral mastectomies, English or Spanish-speaking, and access to the internet. Eligible providers include breast surgeons, medical oncologists, primary care providers, and physician extenders who see patients with AH or LCIS. Statistical methods: We have 90% power to detect a 15% increase in the frequency of chemoprevention informed choice with a 1-sided 0.025 level test, assuming an intraclass correlation (ICC) of 0.02 to account for clustering, roughly equal accrual at each site, 10% loss to follow-up, and ≤10% event rate in the control arm. Current/target accrual: The trial was activated on 9/1/2020. As of 7/7/2022, all 26 sites have been randomized, 157/200 providers and 184/415 patients have been enrolled. Discussion: Our hybrid effectiveness/implementation study seeks to evaluate the effectiveness of a multi-level intervention in promoting informed decision-making about breast cancer chemoprevention. Study results will provide valuable insights on how the decision support tools are integrated in diverse clinical settings. Citation Format: Katherine D. Crew, Garnet Anderson, Kathryn Arnold, Andrew Stieb, Jacquelyn N. Amenta, Cynthia Law, Ana Sandoval-Leon, Sarah Colonna, Tari King, Debra Mangino, Sandhya Pruthi, Maria Grosse Perdekamp, Christa Braun-Inglis, Stacy Krisher, Lisa Yee, Danielle Bertoni, Samantha Seaward, Kari B. Wisinski, Justin Floyd, Corrine Zarwan, Tarah J. Ballinger, Lindi VanderWalde, Masey M. Ross, Preston Steen, Shelly Lo, Alison Conlin, Kathleen Yost, John Ellerton, Erin Lin, Holly J. Pederson, Sagar Sardesai, Cheryl Jernigan, Dawn Hershman, Marian L. Neuhouser, Banu K. Arun, Rita Kukafka. SWOG 1904: Cluster-randomized controlled trial of patient and provider decision support to increase chemoprevention informed choice among women with atypical hyperplasia or lobular carcinoma in situ (MiCHOICE) [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 OT1-15-01.

Introduction Mayo Clinic Connect is an online community of over 100,000 members who support each other through sharing lived experience when facing and managing new diagnoses. The community is moderated by Mayo Clinic staff and volunteer patient mentors. Methods Mayo Clinic breast clinic patients undergoing evaluation received a binder of support resources including a brochure about Mayo Clinic Connect at visits between January and May of 2019. Surveys were distributed at subsequent visits between May and December of 2019 to assess patient awareness about the online resource, participation frequency, purpose of use, and benefits for members, as well as reasons for not joining (non-members). The primary aim was to assess patient resilience, coping, and self-management after joining the online community. Results Nine hundred surveys were distributed, and 102 participants completed surveys between May and December 2019. Forty-five percent ( n = 46) had heard about Mayo Clinic Connect; 34% ( n = 15) through a brochure. The remainder heard about the community from a Mayo Clinic provider (43%; n = 19) or other resources (22%, n = 10; no response n = 2). Twenty percent ( n = 20) of survey participants registered as Breast Cancer group members, and most of this subgroup (55%; n = 11) reported understanding diagnosis, treatment plans, and finding peer support as reasons for joining. Seventy-five percent of Mayo Clinic Connect participants ( n = 15) reported the community met or exceeded expectations. Conclusion This pilot study reveals the potential positive impact of introducing an online peer support group into clinical care plans for patients coping with a new and anxiety-provoking cancer diagnosis.

Objective: The primary aim of this study was to evaluate the feasibility of collecting risk factor information and accessing digitized mammographic data in a medically marginalized population. A secondary aim was to examine the association between vitamin D status and mammographic density. Methods: Breast-screening examinations were provided for age-appropriate patients, and a referral for no-cost screening mammography was offered. Study participants were asked to undergo 25-hydroxyvitamin D testing at mammography and 1-year follow-up. Results: Of 62 women approached, 35 (56%) consented to participate. Of 32 participants who had baseline mammography, the median mammographic density measured by VolparaDensity (Volpara Solutions Limited) was 5.7%. After 1 year, 9 women obtained follow-up mammograms, with a median density of 5.7%. Vitamin D status was measured for 31 participants at baseline and 13 participants in the following year. Insufficient vitamin D status (<30 ng/mL) was noted in 77% at each time point. Mammographic density was not significantly correlated with vitamin D status ( P = .06). Conclusions: On the basis of this small pilot study, vitamin D insufficiency is common in this study population. Owing to the small sample size, an association between vitamin D insufficiency and breast density was not clear. Additional unexpected findings included substantial barriers in initial access to care and longitudinal follow-up in this population. Further study of these issues is needed.