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BACKGROUND: Artificial intelligence (AI) may improve cancer detection and risk prediction during mammography screening, but radiologists' preferences regarding its characteristics and implementation are unknown. PURPOSE: To quantify how different attributes of AI-based cancer detection and risk prediction tools affect radiologists' intentions to use AI during screening mammography interpretation. MATERIALS AND METHODS: Through qualitative interviews with radiologists, we identified five primary attributes for AI-based breast cancer detection and four for breast cancer risk prediction. We developed a discrete choice experiment based on these attributes and invited 150 US-based radiologists to participate. Each respondent made eight choices for each tool between three alternatives: two hypothetical AI-based tools versus screening without AI. We analyzed samplewide preferences using random parameters logit models and identified subgroups with latent class models. RESULTS: Respondents (n = 66; 44% response rate) were from six diverse practice settings across eight states. Radiologists were more interested in AI for cancer detection when sensitivity and specificity were balanced (94% sensitivity with

Background COVID-19 restrictions and fear dramatically changed the use of medical care. Understanding the magnitude of cancelled and postponed appointments and associated factors can help identify approaches to mitigate unmet need. Objective To determine the proportion of medical visits cancelled or postponed and for whom. We hypothesized that adults with serious medical conditions and those with higher anxiety, depressive symptoms, and avoidance-oriented coping would have more cancellations/postponements. Design Four nationally representative cross-sectional surveys conducted online in May, July, October, and December 2020. Participants 59,747 US adults who completed 15-min online surveys. 69% cooperation rate. Measures Physical and mental health visits and cancer screening cancelled or postponed over prior 2 months. Plan to cancel or postpone visits over the next 2 months. Relationship with demographics, medical conditions, local COVID-19 death rate, anxiety, depressive symptoms, coping, intolerance of uncertainty, and perceived COVID-19 risk. Key Results Of the 58% (N = 34,868) with a medical appointment during the 2 months before the survey, 64% had an appointment cancelled or postponed in May, decreasing to 37% in December. Of the 41% of respondents with scheduled cancer screening, 20% cancelled/postponed, which was stable May to December. People with more medical conditions were more likely to cancel or postpone medical visits (OR 1.19 per condition, 95% CI 1.16, 1.22) and cancer screening (OR 1.20, 95% CI 1.15, 1.24). Race, ethnicity, and income had weak associations with cancelled/postponed visits, local death rate was unrelated, but anxiety and depressive symptoms were strongly related to cancellations, and this grew between May and December. Conclusions Cancelled medical care and cancer screening were more common among persons with medical conditions, anxiety and depression, even after accounting for COVID-19 deaths. Outreach and support to ensure that patients are not avoiding needed care due to anxiety, depression and inaccurate perceptions of risk will be important.

Background Breast cancer risk models guide screening and chemoprevention decisions, but the extent and effect of variability among models, particularly at the individual level, is uncertain. Objective To quantify the accuracy and disagreement between commonly used risk models in categorizing individual women as average vs. high risk for developing invasive breast cancer. Design Comparison of three risk prediction models: Breast Cancer Risk Assessment Tool (BCRAT), Breast Cancer Surveillance Consortium (BCSC) model, and International Breast Intervention Study (IBIS) model. Subjects Women 40 to 74 years of age presenting for screening mammography at a multisite health system between 2011 and 2015, with 5-year follow-up for cancer outcome. Main Measures Comparison of model discrimination and calibration at the population level and inter-model agreement for 5-year breast cancer risk at the individual level using two cutoffs (≥ 1.67% and ≥ 3.0%). Key Results A total of 31,115 women were included. When using the ≥ 1.67% threshold, more than 21% of women were classified as high risk for developing breast cancer in the next 5 years by one model, but average risk by another model. When using the ≥ 3.0% threshold, more than 5% of women had disagreements in risk severity between models. Almost half of the women (46.6%) were classified as high risk by at least one of the three models (e.g., if all three models were applied) for the threshold of ≥ 1.67%, and 11.1% were classified as high risk for ≥ 3.0%. All three models had similar accuracy at the population level. Conclusions Breast cancer risk estimates for individual women vary substantially, depending on which risk assessment model is used. The choice of cutoff used to define high risk can lead to adverse effects for screening, preventive care, and quality of life for misidentified individuals. Clinicians need to be aware of the high false-positive and false-negative rates and variation between models when talking with patients.

Background The efficacy of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) convalescent plasma (CCP) for preventing infection in exposed, uninfected individuals is unknown. CCP might prevent infection when administered before symptoms or laboratory evidence of infection. Methods This double-blinded, phase 2 randomized, controlled trial (RCT) compared the efficacy and safety of prophylactic high titer (≥1:320 by Euroimmun ELISA) CCP with standard plasma. Asymptomatic participants aged ≥18 years with close contact exposure to a person with confirmed coronavirus disease 2019 (COVID-19) in the previous 120 hours and negative SARS-CoV-2 test within 24 hours before transfusion were eligible. The primary outcome was new SARS-CoV-2 infection. Results In total, 180 participants were enrolled; 87 were assigned to CCP and 93 to control plasma, and 170 transfused at 19 sites across the United States from June 2020 to March 2021. Two were excluded for screening SARS-CoV-2 reverse transcription polymerase chain reaction (RT-PCR) positivity. Of the remaining 168 participants, 12/81 (14.8%) CCP and 13/87 (14.9%) control recipients developed SARS-CoV-2 infection; 6 (7.4%) CCP and 7 (8%) control recipients developed COVID-19 (infection with symptoms). There were no COVID-19-related hospitalizations in CCP and 2 in control recipients. Efficacy by restricted mean infection free time (RMIFT) by 28 days for all SARS-CoV-2 infections (25.3 vs 25.2 days; P = .49) and COVID-19 (26.3 vs 25.9 days; P = .35) was similar for both groups. Conclusions Administration of high-titer CCP as post-exposure prophylaxis, although appearing safe, did not prevent SARS-CoV-2 infection. Clinical Trials Registration NCT04323800.

We examined parents' COVID-19 vaccination intentions for their children, reasons for not vaccinating, and the potential impact of a school/daycare vaccination requirement or pediatrician's recommendation on vaccination intentions. Two online surveys were conducted in June-July and September-October 2021, before pediatric COVID-19 vaccines were authorized for emergency use in children age&nbsp

ImportanceWith a shortfall in fellowship-trained breast radiologists, mammography screening programs are looking toward artificial intelligence (AI) to increase efficiency and diagnostic accuracy. External validation studies provide an initial assessment of how promising AI algorithms perform in different practice settings.ObjectiveTo externally validate an ensemble deep-learning model using data from a high-volume, distributed screening program of an academic health system with a diverse patient population.Design, Setting, and ParticipantsIn this diagnostic study, an ensemble learning method, which reweights outputs of the 11 highest-performing individual AI models from the Digital Mammography Dialogue on Reverse Engineering Assessment and Methods (DREAM) Mammography Challenge, was used to predict the cancer status of an individual using a standard set of screening mammography images. This study was conducted using retrospective patient data collected between 2010 and 2020 from women aged 40 years and older who underwent a routine breast screening examination and participated in the Athena Breast Health Network at the University of California, Los Angeles (UCLA).Main Outcomes and MeasuresPerformance of the challenge ensemble method (CEM) and the CEM combined with radiologist assessment (CEM+R) were compared with diagnosed ductal carcinoma in situ and invasive cancers within a year of the screening examination using performance metrics, such as sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC).ResultsEvaluated on 37 317 examinations from 26 817 women (mean [SD] age, 58.4 [11.5] years), individual model AUROC estimates ranged from 0.77 (95% CI, 0.75-0.79) to 0.83 (95% CI, 0.81-0.85). The CEM model achieved an AUROC of 0.85 (95% CI, 0.84-0.87) in the UCLA cohort, lower than the performance achieved in the Kaiser Permanente Washington (AUROC, 0.90) and Karolinska Institute (AUROC, 0.92) cohorts. The CEM+R model achieved a sensitivity (0.813 [95% CI, 0.781-0.843] vs 0.826 [95% CI, 0.795-0.856]; P = .20) and specificity (0.925 [95% CI, 0.916-0.934] vs 0.930 [95% CI, 0.929-0.932]; P = .18) similar to the radiologist performance. The CEM+R model had significantly lower sensitivity (0.596 [95% CI, 0.466-0.717] vs 0.850 [95% CI, 0.766-0.923]; P P P = .004).Conclusions and RelevanceThis study found that the high performance of an ensemble deep-learning model for automated screening mammography interpretation did not generalize to a more diverse screening cohort, suggesting that the model experienced underspecification. This study suggests the need for model transparency and fine-tuning of AI models for specific target populations prior to their clinical adoption.

We examined COVID-19 vaccination status, intention, and hesitancy and the effects of five strategies to increase the willingness of unvaccinated adults (≥18 years) to get a COVID vaccine.Online surveys were conducted between October 1-17, 2020 (N = 14,946), December 4-16, 2020 (N = 15,229), April 8-22, 2021 (N = 14,557), June 17-July 6, 2021 (N = 30,857), and September 3-October 4, 2021 (N = 33,088) with an internet-based, non-probability opt-in sample of U.S. adults matching demographic quotas. Respondents were asked about current COVID-19 vaccination status, intention and hesitancy to get vaccinated, and reasons for vaccine hesitancy. Unvaccinated respondents were assigned to treatment groups to test the effect of five strategies (endorsements, changing social restrictions, financial incentives, vaccine requirements for certain activities, and vaccine requirements for work). Chi-square tests of independence were performed to detect differences in the response distributions.Willingness to be vaccinated (defined as being vaccinated or planning to be) increased over time from 47.6 % in October 2020 to 81.1 % in October 2021. By October 2021, across most demographic groups, over 75 % of survey respondents had been or planned to be vaccinated. In terms of strategies: (1) endorsements had no positive effect, (2) relaxing the need for masks and social distancing increased Intention to Get Vaccinated (IGV) by 6.4 % (p 0.01), (3) offering financial incentives increased the IGV between 12.3 and 18.9 % (p .001), (4) vaccine requirements for attending sporting events or traveling increased IGV by 7.8 % and 9.1 %, respectively (p = 0.02), and vaccine requirement for work increased IGV by 35.4 %. The leading causes (not mutually exclusive) for hesitancy were concerns regarding vaccine safety (52.5 %) or side effects (51.6 %), trust in the government's motives (41.0 %), and concerns about vaccine effectiveness (37.6 %).These findings suggest that multiple strategies may be effective and needed to increase COVID-19 vaccination among hesitant adults during the pandemic.

Does local partisan context influence the adoption of prosocial behavior? Using a nationwide survey of 60,000 adults and geographic data on over 180 million registered voters, we investigate whether neighborhood partisan composition affects a publicly observable and politicized behavior: wearing a mask. We find that Republicans are less likely to wear masks in public as the share of Republicans in their zip codes increases. Democratic mask wearing, however, is unaffected by local partisan context. Consequently, the partisan gap in mask wearing is largest in Republican neighborhoods, and less apparent in Democratic areas. These effects are distinct from other contextual effects such as variations in neighborhood race, income, or education. In contrast, partisan context has significantly reduced influence on unobservable public health recommendations like COVID-19 vaccination and no influence on nonpoliticized behaviors like flu vaccination, suggesting that differences in mask wearing reflect the publicly observable and politicized nature of the behavior instead of underlying differences in dispositions toward medical care.

The authors tested the use of tablets to collect breast cancer risk data and compared the approach against paper-based scantrons. The goal was to examine the usability of digital technology for data collection in underserved populations. A total of 340 individuals were randomized to answer a breast health survey via either tablets (170) or paper forms (170). Post questionnaire surveys were conducted to evaluate the usability of tablets. Outcomes included completion time, satisfaction, and the numbers and types of questions raised by patients during the survey. There was no significant difference in questionnaire completion time between two groups (12.5 vs. 12.1 minutes, p = 0.07). The tablet group was more satisfied with the experience (p < 0.001). Low health literacy women spent more time on the questionnaire (p < 0.05). Electronic devices can be utilized to collect breast cancer risk data in underserved, ethnically diverse populations. Future healthcare questionnaire applications should focus on accessibility improvements for these populations.

The authors tested the use of tablets to collect breast cancer risk data and compared the approach against paper-based scantrons. The goal was to examine the usability of digital technology for data collection in underserved populations. A total of 340 individuals were randomized to answer a breast health survey via either tablets (170) or paper forms (170). Post questionnaire surveys were conducted to evaluate the usability of tablets. Outcomes included completion time, satisfaction, and the numbers and types of questions raised by patients during the survey. There was no significant difference in questionnaire completion time between two groups (12.5 vs. 12.1 minutes, p = 0.07). The tablet group was more satisfied with the experience (p < 0.001). Low health literacy women spent more time on the questionnaire (p < 0.05). Electronic devices can be utilized to collect breast cancer risk data in underserved, ethnically diverse populations. Future healthcare questionnaire applications should focus on accessibility improvements for these populations.

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 >1.66% were significantly more likely to be using chemoprevention p< 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 < 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.

Introduction:Scientific quality and feasibility are part of ethics review by Institutional Review Boards (IRBs). Scientific Review Committees (SRCs) were proposed to facilitate this assessment by the Clinical and Translational Science Award (CTSA) SRC Consensus Group. This study assessed SRC feasibility and impact at CTSA-affiliated academic health centers (AHCs).Methods:SRC implementation at 10 AHCs was assessed pre/post-intervention using quantitative and qualitative methods. Pre-intervention, four AHCs had no SRC, and six had at least one SRC needing modifications to better align with Consensus Group recommendations.Results:Facilitators of successful SRC implementation included broad-based communication, an external motivator, senior-level support, and committed SRC reviewers. Barriers included limited resources and staffing, variable local mandates, limited SRC authority, lack of anticipated benefit, and operational challenges. Research protocol quality did not differ significantly between study periods, but respondents suggested positive effects. During intervention, median total review duration did not lengthen for the 40% of protocols approved within 3 weeks. For the 60% under review after 3 weeks, review was lengthened primarily due to longer IRB review for SRC-reviewed protocols. Site interviews recommended designing locally effective SRC processes, building buy-in by communication or by mandate, allowing time for planning and sharing best practices, and connecting SRC and IRB procedures.Conclusions:The CTSA SRC Consensus Group recommendations appear feasible. Although not conclusive in this relatively short initial implementation, sites perceived positive impact by SRCs on study quality. Optimal benefit will require local or federal mandate for implementation, adapting processes to local contexts, and employing SRC stipulations.

Background Leronlimab, a monoclonal antibody blocker of C-C chemokine receptor type 5 originally developed to treat human immunodeficiency virus infection, was administered as an open-label compassionate-use therapeutic for coronavirus disease 2019 (COVID-19). Methods Twenty-three hospitalized severe/critical COVID-19 patients received 700 mg leronlimab subcutaneously, repeated after 7 days in 17 of 23 patients still hospitalized. Eighteen of 23 received other experimental treatments, including convalescent plasma, hydroxychloroquine, steroids, and/or tocilizumab. Five of 23 received leronlimab after blinded, placebo-controlled trials of remdesivir, sarilumab, selinexor, or tocilizumab. Outcomes and results were extracted from medical records. Results Mean age was 69.5 ± 14.9 years; 20 had significant comorbidities. At baseline, 22 were receiving supplemental oxygen (3 high flow, 7 mechanical ventilation). Blood showed markedly elevated inflammatory markers (ferritin, D-dimer, C-reactive protein) and an elevated neutrophil-to-lymphocyte ratio. By day 30 after initial dosing, 17 were recovered, 2 were still hospitalized, and 4 had died. Of the 7 intubated at baseline, 4 were fully recovered off oxygen, 2 were still hospitalized, and 1 had died. Conclusions Leronlimab appeared safe and well tolerated. The high recovery rate suggested benefit, and those with lower inflammatory markers had better outcomes. Some, but not all, patients appeared to have dramatic clinical responses, indicating that unknown factors may determine responsiveness to leronlimab. Routine inflammatory and cell prognostic markers did not markedly change immediately after treatment, although interleukin-6 tended to fall. In some persons, C-reactive protein clearly dropped only after the second leronlimab dose, suggesting that a higher loading dose might be more effective. Future controlled trials will be informative.

UNSTRUCTURED Developing innovative, efficient, and institutionally scalable biospecimen consent for remnant tissue that meets the National Institutes of Health consent guidelines for genomic and molecular analysis is essential for precision medicine efforts in cancer. This study aims to pilot-test an electronic video consent that individuals could complete largely on their own. The University of California, Los Angeles developed a video consenting approach designed to be comprehensive yet fast (around 5 minutes) for providing universal consent for remnant biospecimen collection for research. The approach was piloted in 175 patients who were coming in for routine services in laboratory medicine, radiology, oncology, and hospital admissions. The pilot yielded 164 completed postconsent surveys. The pilot assessed the usefulness, ease, and trustworthiness of the video consent. In addition, we explored drivers for opting in or opting out. The pilot demonstrated that the electronic video consent was well received by patients, with high scores for usefulness, ease, and trustworthiness even among patients that opted out of participation. The revised more animated video pilot test in phase 2 was better received in terms of ease of use (P=.005) and the ability to understand the information (P

BACKGROUND The COVID-19 pandemic has influenced the mental health of millions across the globe. Understanding factors associated with depressive symptoms and anxiety across 12 months of the pandemic can help identify groups at higher risk and psychological processes that can be targeted to mitigate the long-term mental health impact of the pandemic. OBJECTIVE This study aims to determine sociodemographic features, COVID-19-specific factors, and general psychological variables associated with depressive symptoms and anxiety over 12 months of the pandemic. METHODS Nationwide, cross-sectional electronic surveys were implemented in May (n=14,636), July (n=14,936), October (n=14,946), and December (n=15,265) 2020 and March/April 2021 (n=14,557) in the United States. Survey results were weighted to be representative of the US population. The samples were drawn from a market research platform, with a 69% cooperation rate. Surveys assessed depressive symptoms in the past 2 weeks and anxiety in the past week, as well as sociodemographic features; COVID-19 restriction stress, worry, perceived risk, coping strategies, and exposure; intolerance of uncertainty; and loneliness. RESULTS Across 12 months, an average of 24% of respondents reported moderate-to-severe depressive symptoms and 32% reported moderate-to-severe anxiety. Of the sociodemographic variables, age was most consistently associated with depressive symptoms and anxiety, with younger adults more likely to report higher levels of those outcomes. Intolerance of uncertainty and loneliness were consistently and strongly associated with the outcomes. Of the COVID-19-specific variables, stress from COVID-19 restrictions, worry about COVID-19, coping behaviors, and having COVID-19 were associated with a higher likelihood of depressive symptoms and anxiety. CONCLUSIONS Depressive symptoms and anxiety were high in younger adults, adults who reported restriction stress or worry about COVID-19 or who had had COVID-19, and those with intolerance of uncertainty and loneliness. Symptom monitoring as well as early and accessible intervention are recommended.

Background The COVID-19 pandemic has influenced the mental health of millions across the globe. Understanding factors associated with depressive symptoms and anxiety across 12 months of the pandemic can help identify groups at higher risk and psychological processes that can be targeted to mitigate the long-term mental health impact of the pandemic. Objective This study aims to determine sociodemographic features, COVID-19-specific factors, and general psychological variables associated with depressive symptoms and anxiety over 12 months of the pandemic. Methods Nationwide, cross-sectional electronic surveys were implemented in May (n=14,636), July (n=14,936), October (n=14,946), and December (n=15,265) 2020 and March/April 2021 (n=14,557) in the United States. Survey results were weighted to be representative of the US population. The samples were drawn from a market research platform, with a 69% cooperation rate. Surveys assessed depressive symptoms in the past 2 weeks and anxiety in the past week, as well as sociodemographic features; COVID-19 restriction stress, worry, perceived risk, coping strategies, and exposure; intolerance of uncertainty; and loneliness. Results Across 12 months, an average of 24% of respondents reported moderate-to-severe depressive symptoms and 32% reported moderate-to-severe anxiety. Of the sociodemographic variables, age was most consistently associated with depressive symptoms and anxiety, with younger adults more likely to report higher levels of those outcomes. Intolerance of uncertainty and loneliness were consistently and strongly associated with the outcomes. Of the COVID-19-specific variables, stress from COVID-19 restrictions, worry about COVID-19, coping behaviors, and having COVID-19 were associated with a higher likelihood of depressive symptoms and anxiety. Conclusions Depressive symptoms and anxiety were high in younger adults, adults who reported restriction stress or worry about COVID-19 or who had had COVID-19, and those with intolerance of uncertainty and loneliness. Symptom monitoring as well as early and accessible intervention are recommended.

Background: WISDOM is a large (target enrollment>40,000) healthy women preference-tolerant, pragmatic study comparing traditional annual screening to personalized risk-based breast screening. Cancer screening, routine health care, and elective procedures were disrupted due to attempts to manage resources during the COVID-19 pandemic. Understanding of the impact on COVID-19 on trial participants is important to gain a broader understanding of the effect of the pandemic on healthcare activities. Methods: Women aged 40-74 years with no history of breast cancer or DCIS, and no previous double mastectomy can join the WISDOM (NCT02620852) study online at wisdomstudy.org. A total of 28,600 women have consented to participate. As part of the trial, each patient completes a baseline and interval surveys through a Salesforce platform. In May, the study IRB was amended to add a COVID specific survey with questions related to participants COVID risk perceptions, coexisting conditions, and receipt of healthcare services in the 2 months prior to the survey. An initial survey was sent May 2020, with follow-up surveys planned every 2 months. In addition, national surveys on a population-based cross section of individuals across the nation will be performed in parallel. Data was collected, de-identified, and then analyzed using basic descriptive analysis, chi-2 analysis, and logit regression. Results: A total of 7,523 individuals in WISDOM responded to the survey (response rate 27%). Of those that responded, the average age at the time of the survey was 59 (range 40-79). The population was 87% Caucasian, 6% Hispanic, and 4% African-American. Only 3.6% of the sample felt they had COVID-19 either by symptoms or through testing. However, 10.0% felt they were at higher risk compared to similar individuals their age to get COVID-19. Of the sample, 29% had some form of high-risk coexisting condition that put them at higher risk for COVID-19. In terms of healthcare utilization in the prior 2 months, 43% had a routine medical visit cancelled by their primary care provider or health system, whereas 26% cancelled an appointment themselves. In terms of breast cancer screening, 16% had their screening visit either cancelled or delayed. Individuals who believed they were at higher risk (and more likely to have shorter interval screening recommendations on this trial) had a higher Odds Ratio (1.66) for a screening cancellation (p Citation Format: Arash Naeim, Neil Wenger, Karen Sepucha, Annette Stanton, Ryan Baxter-King, Leah Sabacan, Antonia Petruse, Patricia Choy, Susie Brain, Laura Esserman, Wisdom Study and Athena Breast Health Network Investigators and Advocate Partners, Lynn Vavreck. Health maintenance and breast cancer screening during the COVID-19 pandemic [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 SS2-04.

BACKGROUND Febrile neutropenia is one of the most common oncologic emergencies and is associated with significant, preventable morbidity and mortality. Most patients who experience a febrile neutropenia episode are hospitalized, resulting in significant economic cost. OBJECTIVE This exploratory study implemented a remote monitoring system comprising a digital infrared thermometer and a pulse oximeter with the capability to notify providers in real time of abnormalities in vital signs that could suggest early clinical deterioration and thereby improve clinical outcomes. METHODS The remote monitoring system was implemented and compared to standard-of-care vital signs monitoring in hospitalized patients with underlying hematologic malignancies complicated by a febrile neutropenia episode in order to assess the feasibility and validity of the system. Statistical analysis was performed using the intraclass correlation coefficient (ICC) to assess the consistency between the measurements taken using traditional methods and those taken with the remote monitoring system for each of the vital sign parameters (temperature, heart rate, and oxygen saturation). A linear mixed-effects model with a random subject effect was used to estimate the variance components. Bland-Altman plots were created for the parameters to further delineate the direction of any occurring bias. RESULTS A total of 23 patients were enrolled in the study (mean age 56, SD 23-75 years; male patients: n=11, 47.8%). ICC analysis confirmed the high repeatability and accuracy of the heart rate assessment (ICC=0.856), acting as a supplement to remote temperature assessment. While the sensitivity and specificity for capturing tachycardia above a rate of 100 bpm were excellent (88% and 97%, respectively), the sensitivity of the remote monitoring system in capturing temperatures >37.8 °C and oxygen saturation CONCLUSIONS Overall, this novel approach using temperature, heart rate, and oxygen saturation assessments successfully provided real-time, clinically valuable feedback to providers. While temperature and oxygen saturation assessments lagged in terms of sensitivity compared to a standard in-hospital system, the heart rate assessment provided highly accurate complementary data. As a whole, the system provided additional information that can be applied to a clinically vulnerable population. By transitioning its application to high-risk patients in the outpatient setting, this system can help prevent additional use of health care services through early provider intervention and potentially improve outcomes.

BACKGROUND Obtaining explicit consent from patients to use their remnant biological samples and deidentified clinical data for research is essential for advancing precision medicine. OBJECTIVE We aimed to describe the operational implementation and scalability of an electronic universal consent process that was used to power an institutional precision health biobank across a large academic health system. METHODS The University of California, Los Angeles, implemented the use of innovative electronic consent videos as the primary recruitment tool for precision health research. The consent videos targeted patients aged ≥18 years across ambulatory clinical laboratories, perioperative settings, and hospital settings. Each of these major areas had slightly different workflows and patient populations. Sociodemographic information, comorbidity data, health utilization data (ambulatory visits, emergency room visits, and hospital admissions), and consent decision data were collected. RESULTS The consenting approach proved scalable across 22 clinical sites (hospital and ambulatory settings). Over 40,000 participants completed the consent process at a rate of 800 to 1000 patients per week over a 2-year time period. Participants were representative of the adult University of California, Los Angeles, Health population. The opt-in rates in the perioperative (16,500/22,519, 73.3%) and ambulatory clinics (2308/3390, 68.1%) were higher than those in clinical laboratories (7506/14,235, 52.7%; PPPP CONCLUSIONS This is one of the few large-scale, electronic video–based consent implementation programs that reports a 65.5% (26,314/40,144) average overall opt-in rate across a large academic health system. This rate is higher than those previously reported for email (3.6%) and electronic biobank (50%) informed consent rates. This study demonstrates a scalable recruitment approach for population health research.

Purpose To analyze women with suspicious findings (assessed as Breast Imaging Reporting and Data System [BI-RADS] 4), examining the value of clinical and imaging predictors in predicting cancer diagnosis. Patients and Methods A set of 2138 examinations (1978 women) given a BI-RADS 4 with matching pathology results were analyzed. Predictors such as patient demographics, clinical risk factors, and imaging-derived features such as BI-RADS assessment and qualitative breast density were considered. Independent predictors of breast cancer were determined by univariate analysis and multivariate logistic regression. Results In univariate analysis, age, race, body mass index, age at first live birth, BI-RADS assessment, qualitative breast density, and risk triggers were found to be independent predictors. In multivariate analysis, age, BI-RADS score, breast density, race, presence of a lump, and number of risk triggers were the most predictive. An integrative logistic regression model achieved a performance of 0.84 cross-validated area under the curve. No variable was a constant independent predictor when stratifying the population on the basis of the BI-RADS score. Conclusion While BI-RADS assessment remains the strongest predictor of breast cancer, the inclusion of clinical risk factors such as age, breast density, presence of a lump, and number of risk triggers derived from guidelines improves the specificity of identifying individuals with imaging descriptors associated with BI-RADS 4A and 4B that are more likely to be diagnosed with breast cancer.

BACKGROUND Developing innovative, efficient, and institutionally scalable biospecimen consent for remnant tissue that meets the National Institutes of Health consent guidelines for genomic and molecular analysis is essential for precision medicine efforts in cancer. OBJECTIVE This study aims to pilot-test an electronic video consent that individuals could complete largely on their own. METHODS The University of California, Los Angeles developed a video consenting approach designed to be comprehensive yet fast (around 5 minutes) for providing universal consent for remnant biospecimen collection for research. The approach was piloted in 175 patients who were coming in for routine services in laboratory medicine, radiology, oncology, and hospital admissions. The pilot yielded 164 completed postconsent surveys. The pilot assessed the usefulness, ease, and trustworthiness of the video consent. In addition, we explored drivers for opting in or opting out. RESULTS The pilot demonstrated that the electronic video consent was well received by patients, with high scores for usefulness, ease, and trustworthiness even among patients that opted out of participation. The revised more animated video pilot test in phase 2 was better received in terms of ease of use (P=.005) and the ability to understand the information (PP CONCLUSIONS Efforts to better educate the community may be needed to help overcome some of the barriers in engaging individuals to participate in precision health initiatives.

The COVID-19 pandemic changed the clinical research landscape in America. The most urgent challenge has been to rapidly review protocols submitted by investigators that were designed to learn more about or intervene in COVID-19. International Review Board (IRB) offices developed plans to rapidly review protocols related to the COVID-19 pandemic. An online survey was conducted with the IRB Directors at Clinical and Translational Science Awards (CTSA) institutions as well as two focus groups. Across the CTSA institutions, 66% reviewed COVID-19 protocols across all their IRB committees, 22% assigned protocols to just one committee, and 10% created a new committee for COVID-19 protocols. Fifty-two percent reported COVID-19 protocols were reviewed much faster, 41% somewhat faster, and 7% at the same speed as other protocols. Three percent reported that the COVID-19 protocols were reviewed with much better quality, 32% reported slightly better quality, and 65% reported the reviews were of the same quality as similar protocols before the COVID-19 pandemic. IRBs were able to respond to the emergent demand for reviewing COVID-19 protocols. Most of the increased review capacity was due to extra effort by IRB staff and members and not changes that will be easily implemented across all research going forward.

BACKGROUND On-body wearable sensors have been used to predict adverse outcomes such as hospitalizations or fall, thereby enabling clinicians to develop better intervention guidelines and personalized models of care to prevent harmful outcomes. In our previous work, we introduced a generic remote patient monitoring framework (Sensing At-Risk Population) that draws on the classification of human movements using a 3-axial accelerometer and the extraction of indoor localization using Bluetooth low energy beacons, in concert. Using the same framework, this paper addresses the longitudinal analyses of a group of patients in a skilled nursing facility. We try to investigate if the metrics derived from a remote patient monitoring system comprised of physical activity and indoor localization sensors, as well as their association with therapist assessments, provide additional insight into the recovery process of patients receiving rehabilitation. OBJECTIVE The aim of this paper is twofold: (1) to observe longitudinal changes of sensor-based physical activity and indoor localization features of patients receiving rehabilitation at a skilled nursing facility and (2) to investigate if the sensor-based longitudinal changes can complement patients’ changes captured by therapist assessments over the course of rehabilitation in the skilled nursing facility. METHODS From June 2016 to November 2017, patients were recruited after admission to a subacute rehabilitation center in Los Angeles, CA. Longitudinal cohort study of patients at a skilled nursing facility was followed over the course of 21 days. At the time of discharge from the skilled nursing facility, the patients were either readmitted to the hospital for continued care or discharged to a community setting. A longitudinal study of the physical therapy, occupational therapy, and sensor-based data assessments was performed. A generalized linear mixed model was used to find associations between functional measures with sensor-based features. Occupational therapy and physical therapy assessments were performed at the time of admission and once a week during the skilled nursing facility admission. RESULTS Of the 110 individuals in the analytic sample with mean age of 79.4 (SD 5.9) years, 79 (72%) were female and 31 (28%) were male participants. The energy intensity of an individual while in the therapy area was positively associated with transfer activities (β=.22; SE 0.08; P=.02). Sitting energy intensity showed positive association with transfer activities (β=.16; SE 0.07; P=.02). Lying down energy intensity was negatively associated with hygiene activities (β=–.27; SE 0.14; P=.04). The interaction of sitting energy intensity with time (β=–.13; SE 0.06; P=.04) was associated with toileting activities. CONCLUSIONS This study demonstrates that a combination of indoor localization and physical activity tracking produces a series of features, a subset of which can provide crucial information to the story line of daily and longitudinal activity patterns of patients receiving rehabilitation at a skilled nursing facility. The findings suggest that detecting physical activity changes within locations may offer some insight into better characterizing patients’ progress or decline.

Background On-body wearable sensors have been used to predict adverse outcomes such as hospitalizations or fall, thereby enabling clinicians to develop better intervention guidelines and personalized models of care to prevent harmful outcomes. In our previous work, we introduced a generic remote patient monitoring framework (Sensing At-Risk Population) that draws on the classification of human movements using a 3-axial accelerometer and the extraction of indoor localization using Bluetooth low energy beacons, in concert. Using the same framework, this paper addresses the longitudinal analyses of a group of patients in a skilled nursing facility. We try to investigate if the metrics derived from a remote patient monitoring system comprised of physical activity and indoor localization sensors, as well as their association with therapist assessments, provide additional insight into the recovery process of patients receiving rehabilitation. Objective The aim of this paper is twofold: (1) to observe longitudinal changes of sensor-based physical activity and indoor localization features of patients receiving rehabilitation at a skilled nursing facility and (2) to investigate if the sensor-based longitudinal changes can complement patients’ changes captured by therapist assessments over the course of rehabilitation in the skilled nursing facility. Methods From June 2016 to November 2017, patients were recruited after admission to a subacute rehabilitation center in Los Angeles, CA. Longitudinal cohort study of patients at a skilled nursing facility was followed over the course of 21 days. At the time of discharge from the skilled nursing facility, the patients were either readmitted to the hospital for continued care or discharged to a community setting. A longitudinal study of the physical therapy, occupational therapy, and sensor-based data assessments was performed. A generalized linear mixed model was used to find associations between functional measures with sensor-based features. Occupational therapy and physical therapy assessments were performed at the time of admission and once a week during the skilled nursing facility admission. Results Of the 110 individuals in the analytic sample with mean age of 79.4 (SD 5.9) years, 79 (72%) were female and 31 (28%) were male participants. The energy intensity of an individual while in the therapy area was positively associated with transfer activities (β=.22; SE 0.08; P=.02). Sitting energy intensity showed positive association with transfer activities (β=.16; SE 0.07; P=.02). Lying down energy intensity was negatively associated with hygiene activities (β=–.27; SE 0.14; P=.04). The interaction of sitting energy intensity with time (β=–.13; SE 0.06; P=.04) was associated with toileting activities. Conclusions This study demonstrates that a combination of indoor localization and physical activity tracking produces a series of features, a subset of which can provide crucial information to the story line of daily and longitudinal activity patterns of patients receiving rehabilitation at a skilled nursing facility. The findings suggest that detecting physical activity changes within locations may offer some insight into better characterizing patients’ progress or decline.

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 ( 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 ( 5-year risk classification according to the BCRAT, BCSC and BCSC-PRS models 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.