Larson, Nicole L.

Abstract Polygenic risk scores (PRSs), which quantify inherited susceptibility to complex traits and diseases, have emerged as valuable tools for risk stratification and precision medicine. Despite their promise, PRS developed on European cohorts often demonstrate substantially reduced predictive accuracy in non-European populations, due to differences in genetic architecture. The disproportionate representation of European ancestry cohorts in genome-wide association studies (GWAS) leads to inequitable deployment of PRS technologies across diverse populations. Here, we introduce PRANA (Polygenic Risk Adaptation via Neural-network Architecture), a deep learning framework that adapts an existing PRS developed on one population to other ancestries. Unlike methods that require large-scale GWAS in the target population, PRANA leverages pre-trained PRS models derived from European cohorts and adapts them using modestly sized cohorts from the target population. We evaluated PRANA on seven complex traits in South Asian, East Asian and Ashkenazi Jewish populations, as well as in selected smaller East Asian subpopulations where the scarcity of training data poses a particular challenge. PRANA mostly improved predictive performance of the baseline PRS models by 5%-20% in terms of effect size (β) and Nagelkerke’s R², and, in most cases, outperformed existing cross-ancestry multi-PRS approaches. These results highlight PRANA as a scalable and practical strategy to reduce disparities in genomic risk prediction and advance the equitable application of PRS in diverse populations.

ABSTRACT Background Alcohol intake is a modifiable risk factor for breast cancer, yet patterns of alcohol intake in women with breast cancer remain underexplored. This study evaluates demographic and clinical predictors of alcohol intake in patients with breast cancer. Methods Patients at Mayo Clinic Rochester diagnosed with breast cancer (Stage 0–3) between July 2014 to March 2022 were surveyed about their average alcohol intake over the 10 years prior to their diagnosis. Alcohol intake was categorized as < 1, 1–4, 5–14, and ≥ 15 drinks per week. Demographic, behavioral, and clinical data were analyzed using univariate Fisher exact tests and multivariate multinomial logistic regression. Results Of 2030 participants (mean age at diagnosis: 59 years; 99.3% female; 95.9% White), 29% consumed < 1 drink/week, 48% reported 1–4 drinks/week, 20% consumed 5–14 drinks/week, and 3% reported ≥ 15 drinks/week. Older age at diagnosis (≥ 60 years), non‐White race, financial difficulty, and never smoking were associated with less alcohol intake. Patients who reported higher levels of mild–moderate intensity exercise reported more alcohol intake. Tumor stage, tumor receptors, and BRCA mutation status were not associated with alcohol intake. PROMIS‐10 physical health scores correlated with alcohol intake in univariate but not multivariate models. Conclusion Alcohol intake is more common prior to a breast cancer diagnosis for patients who are younger, White, financially secure, exercising, and smoking. These findings may inform alcohol intake‐related breast cancer prevention efforts and highlight patient subgroups who could benefit from targeted counseling at the time of diagnosis.

e12697 Background: Postpartum-associated breast cancer (PABC) has been defined clinically as breast cancer (BC) diagnosed within the first 5 years of the most recent birth. Though generally rare, incidence rates are increasing in conjunction with delayed childbearing and older maternal age at first birth. Currently, there are limited data regarding serial patient-reported outcomes in this patient population compared to non-PABC patients. Methods: Patients with PABC from the Mayo Clinic Breast Disease Registry who completed baseline, 2, and 4-year surveys were matched 1:1 to BC patients whose cancers occurred more than 5 years after their most recent birth (or in the setting of nulliparity) based on age, clinical stage, treatment received, and tumor subtype. Survey results from the Patient Health Questionnaire-2 (PHQ-2), Patient-Reported Outcomes Measurement Information System-10 (PROMIS-10), and Impact of Event Scale-Revised (IES-R) collected at approximately two and four years after diagnosis were compared between PABC and non-PABC patients. Univariable analyses used Wilcoxon rank sum tests, whereas multivariable analyses employed linear regression models adjusting for potential confounding effects. Results: A total of 222 individuals were included (111 with PABC). A higher proportion of individuals in the PABC cohort were married compared to the non-PABC cohort (80% vs. 42%, p < 0.001); otherwise, the groups were well-balanced across multiple categories, including age, gender, race/ethnicity, menopausal status, and germline mutation status. In univariable analyses, the Year 2 composite PHQ-2 score was significantly worse among individuals with non-PABC (p = 0.04), and the non-PABC cohort reported greater difficulty with sleep (p = 0.03) as measured by IES-R at Year 4. Both associations attenuated in a multivariable analysis controlling for marital status. In marital status-adjusted analyses of Year 4 survey results, PABC participants reported greater difficulty in carrying out social activities but were less likely to report emotional distress as evaluated by PROMIS-10 (compared with non-PABC participants). No other variables were significant univariably or multivariably (p > 0.05). Conclusions: In general, quality of life is similar among survivors of PABC compared to those diagnosed with breast cancer outside the postpartum period (or when nulliparous). However, our findings reveal that individuals with PABC are less likely to experience emotional distress 2 and 4 years after the BC diagnosis, which is unexpected, given that postpartum patients typically report higher levels of distress compared to their non-postpartum counterparts. Further investigation into these findings is warranted.

11025 Background: Adjuvant endocrine therapy (AET) improves outcomes in HR+ breast cancer. Nonadherence to AET is common, but manual screening for nonadherence is fraught. High-specificity structured cancer electronic health record (EHR) data, particularly if it includes key variables like stage, could streamline these steps for both clinical care and research purposes. We conducted an analysis of approaches to identifying patients as eligible for a multi-site AET adherence study to understand how variation in structured data informatics-supported screening impacts coordinator time. Methods: Mayo Clinic implemented a two-step identification: (1) EHR structured data (diagnosis date, stage, ER/PR/HER2 positivity, medication script) to prescreen for eligibility; (2) SureScripts fills to flag nonadherence using proportion of days covered < 80% across early fills. Medical College of Wisconsin (MCW) implemented a more manual screening process for Step 1 using only medication scripts. Coordinators at both sites then conducted a medical record review to assess if the resulting list of patients had a plan to continue AET for at least two additional years. Opt-out clinician permission preceded patient contact; pharmacists delivered a patient reported outcome (PRO)-guided intervention and documented encounters. Results: At Mayo, 829 patients were prescreened for study eligibility through informatics workflow; 120 (14.5%) met eligibility criteria. At MCW, 1,763 patients were prescreened; 168 (9.5%) were eligible. EHR filters included non–breast cancer encounters (50% at MCW) and ineligible based on time since cancer (36% at Mayo; 26% at MCW). At Mayo, screening required 5.6 minutes/patient for experienced coordinators. At MCW, experienced coordinators averaged 6.67 minutes/patient and inexperienced coordinators averaged 9.33 minutes/patient. Conclusions: Structured EHR data, pharmacy-fill information, and standardized workflows allowed consistent prescreening, intervention and recruitment processes across sites. Higher-specificity informatics-supported screening reduced the percentage of patients requiring manual review and reduced coordinator screening time. It also supported timely provider-permission steps and patient outreach. These workflows were feasible to implement at both institutions, and study enrollment is ongoing. Clinical trial information: NCT06765707 .

Abstract Purpose To evaluate alcohol intake trends and identify demographic, clinical, lifestyle and socioeconomic factors associated with alcohol consumption in late survivorship among breast cancer survivors. Methods Individuals diagnosed with stage 0–3 breast cancer enrolled in the Mayo Clinic Breast Disease registry between 2014 to 2022 reported their average weekly alcohol intake at baseline (time of diagnosis) and at approximately four years post-diagnosis. Alcohol intake was divided into four categories and cross-sectional associations with demographic, clinical, and lifestyle factors were examined using Monte Carlo-based Fisher exact tests and multivariable multinomial logistic regression. Changes in alcohol consumption from baseline to Year 4 were evaluated using Bowker’s test of symmetry and multinomial models. Results Among 719 participants, alcohol intake 4 years post diagnosis closely resembled baseline patterns, with 30.2% of patients reporting no alcohol use and 48.8% of patients consuming 1–4 drinks per week. Younger age and current smoking status were strongly associated with higher intake at Year 4. Exercise and better physical health were associated with higher alcohol intake in univariable models, however not in adjusted models. From time of diagnosis to Year 4, 15.6% of patients decreased their alcohol intake, 10.2% increased alcohol intake, and 74.3% reported no change. Higher levels of mild intensity exercise were associated with an elevation in alcohol intake over time. Conclusion Alcohol consumption remained stable in late survivorship, in contrast to the initial decline in alcohol use during early survivorship seen in this cohort. Younger age and smoking were key associations with higher alcohol intake.

Abstract Background Breast cancer (BC) survivors frequently experience sleep disturbances, which may persist for many years after treatment. This study aimed to describe trends in sleep-related symptoms over time and identify factors that may be associated with sleep disturbances in BC survivors. Patients and Methods Adult patients from the Mayo Clinic Breast Disease Registry were surveyed annually for up to 7 years post-diagnosis. Sleep disturbance severity was assessed using numeric rating scales for difficulty falling and staying asleep. Data from 3354 unique patients were analyzed, excluding those with metastatic disease or recurrence. Univariable and multivariable analyses were performed at the 1-year survey timepoint to evaluate disease and patient-related factors that were associated with increased sleep-related symptoms, and these factors were also assessed in relationship to sleep-related symptoms over time. Results In multivariable analyses, more trouble falling asleep was associated with financial insecurity, higher clinical stage, more cigarettes smoked per day, and less weekly exercise. More trouble staying asleep was associated with older age, race, advanced education, financial insecurity, and higher clinical stage. Over time, there was a nonsignificant trend toward increased trouble falling asleep and fluctuations in trouble staying asleep. Higher clinical stage and receipt of radiotherapy were associated with decreased severity in trouble falling asleep over time, while more cigarettes smoked per day was linked to increased severity in trouble staying asleep. Conclusions These findings highlight the complex interplay of clinical, lifestyle, and demographic factors in sleep disturbances among BC survivors, underscoring the need for tailored sleep management strategies.

Background/Objectives: This study aims to evaluate the quality of life (QoL) and oncological outcomes in premenopausal women diagnosed with hormone receptor-positive breast cancer who are receiving either bilateral oophorectomy (BO) or gonadotropin-releasing hormone agonist (GnRH) therapy. Both methods serve to inhibit ovarian function, which is essential for the management of estrogen-dependent tumors; however, their effects on QoL have yet to be fully clarified. Methods: Data were analyzed from the Mayo Clinic Breast Disease Registry, focusing on women under 55 diagnosed with estrogen receptor-positive breast cancer who received either BO or GnRH within one year of diagnosis. QoL was assessed using the Patient-Reported Outcomes Measurement Information System Global-10 (PROMIS-10) at baseline and annually for five years. Results: A total of 181 patients were enrolled in the study; 40 into the BO group and 141 to the GnRH group. Both groups exhibited similar levels of sexual dysfunction after a one-year period; however, the BO group stated a higher frequency of hot flashes. PROMIS-10 scores improved in both mental and physical health over time, with no significant differences between the groups. Within the BO group, one recurrence was observed, in contrast to the GnRH group, which had six events. Nonetheless, the difference in recurrence rates did not reach statistical significance. Conclusions: The long-term QoL and oncologic outcomes for premenopausal women with hormone receptor-positive breast cancer were similar for BO and GnRH therapy. These findings emphasize the need for individualized treatment decisions, considering patient preferences and side effects.

Context.— A clinic was created for patients to review their explanted organs with a pathologist. Objective.— To prospectively investigate the benefits of this type of clinic as perceived by both transplant patients and their pathologists. Design.— In this prospective study, patients participated in a videotaped viewing of heart and/or lung explants by the patient and their guest(s) and pathologist (December 2017–August 2022). Patients received a 3D-printed replica of their explant. After viewing the explanted organ, patients and their guests participated in an interview to assess their experiences. Video-reflexive ethnography was used by pathologists for data collection and practice improvement. Results.— Of 143 patients who viewed their explanted organ, 21 patients consented to having the organ-viewing session taped and to participate in a postviewing interview. The study group was comprised of 12 men; the median age was 57.5 years (range, 29–67 years). Five pathologists took part in reflexive sessions. The clinics were viewed positively by patients, providing an opportunity to better understand their disease. Pathologists had a similarly positive experience and gained important insights to patient journeys. Proposals for improvement were brought forward from both patients and pathologists. Conclusions.— Video-reflexive ethnography provided the opportunity for patients and pathologists to reflect on patient-pathology clinic appointments. This work serves as a template to build out pathology-based clinics.

11114 Background: Advances in early detection and treatment of breast cancer (BC) have significantly improved survival outcomes. In this growing survivor population, addressing modifiable lifestyle factors such as alcohol intake (AI), a known risk factor for BC and BC recurrence, is critical to improving prognosis and health-related quality of life (HRQoL). This study examines AI patterns and their associations with mental and physical HRQoL in early BC survivorship. Methods: Adult patients newly diagnosed (≤1 year) with stage I–III BC at Mayo Clinic Rochester were invited to enroll in the Mayo Clinic Breast Disease Registry. Of the 3252 patients who consented, 1997 completed surveys approximately one-year post-diagnosis, capturing weekly AI, demographic factors, and PROMIS-10 scores. PROMIS-10 (a 10-item measure of health, well-being, and distress) physical and mental health T-scores (mean = 50, SD = 10) are standardized to the U.S. population. Weekly AI was categorized as minimal/none (<1 drink), mild (1–4 drinks), moderate (5–14 drinks), or high (≥15 drinks). Univariate analyses were performed with Monte Carlo-based Fisher exact tests. Multivariate multinomial logistic regression models using a glogit link function assessed AI as the outcome and PROMIS-10 scores as independent variables, adjusting for financial status, smoking, chemotherapy, and moderate exercise because those were associated with AI at year 1 in prior analyses. Results: Univariate analyses revealed statistically significant associations between AI and PROMIS-10 scores (Table 1). Adjusted multivariate analyses identified that patients with better physical health were more likely to drink 1–4 or 5–14 drinks/week and less likely to abstain (<1 drink/week) than those with poorer physical health (p=0.027). There was no statistically significant association between AI and mental health QoL after adjustment for covariates. Conclusions: Better physical HRQoL during early survivorship was associated with higher AI, suggesting that patients who are feeling physically unwell may be less likely to drink alcohol. Additional public health messaging about the relationship between AI and breast cancer risk and recurrence may be needed, especially for those who are feeling well enough to consume alcohol. Univariate analyses of year 1 PROMIS-10 scores with year 1 alcohol consumption using Monte Carlo-based Fisher exact test. Alcoholic drinks per week at year 1 < 1(N=1204) 1-4(N=600) 5-14(N=175) 15+(N=18) Total(N=1997) P-value PROMIS global mental health T score, Year 1, n (%) 0.008 < 50 466 (63.8%) 200 (27.4%) 54 (7.4%) 10 (1.4%) 730 (37.1%) 50+ 718 (57.9%) 394 (31.8%) 120 (9.7%) 7 (0.6%) 1239 (62.9%) Missing 20 6 1 1 28 PROMIS global physical health T score, Year 1, n (%) <0.001 < 50 440 (66.5%) 165 (24.9%) 50 (7.6%) 7 (1.1%) 662 (33.6%) 50+ 740 (56.7%) 432 (33.1%) 124 (9.5%) 10 (0.8%) 1306 (66.4%) Missing 24 3 1 1 29

12083 Background: Fatigue and sleep disturbance are prevalent during and after cancer treatment; sleep-related symptoms affect 30-50% of patients with cancer, and sleep-wake disruptions persist beyond the immediate post-surgical period in breast cancer (BC) survivors. Identifying demographic- and treatment-related factors associated with sleep-related symptoms during survivorship is critical to inform interventions for those at highest risk of sleep disturbance. Methods: Patients who were seen at least once at Mayo Clinic Rochester following an initial diagnosis of BC at age 18 or older and provided informed consent were prospectively enrolled in the Mayo Clinic Breast Disease Registry. Surveys mailed to this cohort included two 11-point numeric rating scale questions regarding difficulty falling asleep and staying asleep in the past week, with values for each ranging from 0 (no problem) to 10 (as severe as you can imagine). Participants who provided sleep-related information on the Year 1 survey (answered approximately one year after cancer diagnosis) were included. Participants were excluded if they had clinical or pathologic metastatic disease and/or recurrence prior to the Year 1 survey. Associations of sleep-related symptoms with demographic and clinical characteristics were assessed using multivariate linear regression models, fitting the sleep difficulty rating scale as the outcome and clinical and demographic factors as exposures. Results: In total, 3,354 participants met inclusion criteria. The average age at BC diagnosis was 59, and most participants were female (99.3%), White (95.4%), non-Hispanic (96.2%), married (78.1%), had at least some college education (80.4%), did not report financial insecurity (76.2%), did not consume alcohol (60.6%) or smoke tobacco (93.2%), and reported at least some weekly exercise (76,6%). Sixty-two percent of participants had clinical stage 0 or I disease; 50.3% underwent lumpectomy (not mastectomy), 59.2% received radiotherapy, 34.1% received chemotherapy, and 67.2% received endocrine therapy. Overall, sleep-related symptoms were relatively low (mean rating for falling asleep = 2.1, mean rating for staying asleep = 3.1). In multivariate analyses, more difficulty falling asleep was associated with higher clinical stage (p < 0.001), more cigarettes smoked per day (p = 0.012), less moderate and/or strenuous exercise (p = 0.001), and more financial hardship (p < 0.001). More difficulty staying asleep was associated with higher clinical stage (0.003), older age (p < 0.001), more education (p = 0.011), and more financial hardship (p < 0.001). Conclusions: In our cohort of BC survivors, factors associated with both increased difficulty with falling and staying asleep at one year after diagnosis are higher clinical stage and more financial hardship. Future research should explore the course of these symptoms over time and across varied treatment trajectories.