Anderson, Garnet L.

Background: Several breast cancer (BC) risk prediction models have been developed to provide personal risk assessments. Though individually validated, their performance has not been systematically evaluated across a wide range of populations or ages. Methods: We harmonized individual-level baseline questionnaire data and incident BC diagnoses from 21 cohorts from North America, Europe, and Australia participating in the Breast Cancer Risk Prediction Project. Five-year absolute risk of invasive BC was estimated for five established risk prediction models using classical risk factors only. Discrimination was evaluated by area under the curve (AUC). Calibration was assessed using average and risk-decile specific expected to observed (E/O) ratios. Performance metrics were meta-analyzed across cohorts and models. Metaregression tested associations between cohort characteristics and performance metrics. Results: This analysis included 1,595,977 women aged 20-75 years, enrolled in studies between 1976-2015, with 19,062 (1.2%) invasive BC cases ascertained within 5 years from exposure assessment. Age-adjusted AUCs were similar across models and cohorts (pooled AUCs by model: 0.57-0.58), while E/O ratios varied substantially (pooled E/O ratios by model: 0.83-1.25). Overestimation was common among predicted high-risk individuals (>3%). No appreciable differences in model performance by cohort age, birth year, race, and variable missingness emerged. Calibration improved after assigning race-specific incidence rates. Conclusion: Existing BC risk prediction models provided similar risk discrimination across multiple cohorts, although there was overestimation of risk for high-risk individuals. Performance variation across cohorts was not driven by specific characteristics, which supports development of a unified risk model for diverse populations that leverages appropriate incidence rates.

Abstract Background Breast cancer chemoprevention is underutilized among high-risk women. We examined whether decision support could increase informed decision making. Methods We conducted a cluster randomized controlled trial to evaluate the effect of a patient-facing decision aid (RealRisks) and provider tool (BNAV) compared with standard education on the number of women with high-risk breast lesions making informed choices. Questionnaires were administered at baseline and 6 and 12 months. The primary outcome was chemoprevention informed choice (defined as adequate knowledge and attitudes congruent with decision) at 6 months. Secondary endpoints included breast cancer risk perceptions, worry, chemoprevention knowledge, decision conflict, and chemoprevention decision. Results Across 31 randomized sites, we enrolled 210 providers, who were primarily breast health specialists. Of these, 24 sites (14 intervention, 10 control) enrolled 412 patients. Among 287 patients evaluable for the primary outcome, there were no statistically significant differences in informed choice between the intervention and control arms at 6 months (35% vs 27%, respectively; P = .20) and 12 months (37% vs 25%, respectively; P = .05). At 6 months, women in the intervention compared with control arm were more likely to have accurate breast cancer risk perceptions (31% vs 21%, respectively; P = .03) and adequate chemoprevention knowledge (33% vs 23%, respectively; P = .04). At 12 months, 52% of women in the control and 50% in the intervention arm self-reported initiating chemoprevention. Conclusion Decision support led to modest improvements in accurate risk perceptions and chemoprevention knowledge but not informed choice. Relatively high chemoprevention uptake was achieved among women with high-risk breast lesions managed mainly by breast health specialists. Trial Registration NCT04496739, https://clinicaltrials.gov/study/NCT04496739?cond=NCT04496739&viewType=Card&rank=1

Abstract Breast cancer risk assessment tools are widely used in clinical practice to guide decisions regarding screening timing and modality, lifestyle interventions, genetic testing, preventive therapy, and risk-reducing surgery. Although a number of tools designed for the general population are used in practice, they face a series of challenges including: (i) modest discriminatory ability due to lack of a unified model that flexibly incorporates a comprehensive set of risk factors; (ii) inability to produce subtype-specific risk estimates, relevant for tailoring screening and/or preventive strategies (e.g. prophylactic endocrine therapy that is effective only for hormone receptor positive tumors); (iii) lack of data from diverse populations to build models that work well for all women; and, (iv) scarcity of opportunities for comparative validation of different models. The Breast Cancer Risk Prediction Project (BCRPP), a collaboration currently including 20 prospective cohorts from the National Cancer Institute’s Cohort Consortium, is addressing these challenges by harmonizing, sharing, and analyzing data on over 1.8 million women, over 115, 000 of whom have developed breast cancer. The BCRPP is developing a comprehensive tool that will predict breast cancer risk, overall and by subtypes, across major racial and ethnic groups in the United States. This tool incorporates known and emerging risk factors (e.g. reproductive history, anthropometry, smoking, alcohol intake, medication use, mammography, family history, and measured genotypes). In parallel to model building and validation efforts, BCRPP investigators are developing privacy-preserving web and mobile interfaces to deliver the risk tools to patients and clinicians. Here we present descriptive data on participating cohorts (e.g. dates of enrollment, ages at enrollment, length of follow up, numbers of cases by subtype), summarize missing data patterns and our approach to model development and validation that accounts for heterogeneity in missingness patterns across cohorts, and describe data governance procedures and data sharing infrastructure (including pooled and federated analyses, to account for policy limitations on sharing individual data). Descriptive information and procedures for requesting and accessing data are available via the BCRPP data platform (https://epidataplatforms.cancer.gov/bcrpp/). Although originally assembled for risk model development, these data on a large and diverse sample of women with extensive harmonized risk factors and covariates can be a resource to address other outstanding questions in breast cancer epidemiology across time, the lifecourse, and diverse populations. Citation Format: Peter Kraft, Laura Beane-Freeman, Julie Palmer, Ellen O'Meara, Jeanine Genkinger, James Lacey, Thomas Rohan, Lauren Teras, Marian L. Neuhouser, Kala Visvanathan, Celine Vachon, Roger Milne, Christopher Haiman, Yu Chen, Heather Eliassen, Cari Kitahara, Katie O'Brien, Emily White, Garnet Anderson, I-Min Lee, Archie Campbell, Renee Fortner, Ylva Lagerros, Sven Sandin, Mia Gaudet, Montserrat Garcia-Closas, Nilanjan Chatterjee. The Breast Cancer Risk Prediction Project: a resource of 1.8 million women with diverse backgrounds from 20 prospective cohorts to improve breast cancer risk prediction and advance breast cancer epidemiology [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3583.

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.

Background The association of social isolation or lack of social network ties in older adults is unknown. This knowledge gap is important since the risk of heart failure (HF) and social isolation increase with age. The study examines whether social isolation is associated with incident HF in older women, and examines depressive symptoms as a potential mediator and age and race and ethnicity as effect modifiers. Methods and Results This study included 44 174 postmenopausal women of diverse race and ethnicity from the WHI (Women's Health Initiative) study who underwent annual assessment for HF adjudication from baseline enrollment (1993–1998) through 2018. We conducted a mediation analysis to examine depressive symptoms as a potential mediator and further examined effect modification by age and race and ethnicity. Incident HF requiring hospitalization was the main outcome. Social isolation was a composite variable based on marital/partner status, religious ties, and community ties. Depressive symptoms were assessed using CES‐D (Center for Epidemiology Studies‐Depression). Over a median follow‐up of 15.0 years, we analyzed data from 36 457 women, and 2364 (6.5%) incident HF cases occurred; 2510 (6.9%) participants were socially isolated. In multivariable analyses adjusted for sociodemographic, behavioral, clinical, and general health/functioning; socially isolated women had a higher risk of incident HF than nonisolated women (HR, 1.23; 95% CI, 1.08–1.41). Adding depressive symptoms in the model did not change this association (HR, 1.22; 95% CI, 1.07–1.40). Neither race and ethnicity nor age moderated the association between social isolation and incident HF. Conclusions Socially isolated older women are at increased risk for developing HF, independent of traditional HF risk factors. Registration URL: http://www.clinicaltrials.gov ; Unique identifier: NCT00000611.

Background: Prospective, randomized trials are needed to determine optimal treatment approaches for palliative care problems such as malignant bowel obstruction (MBO). Randomization poses unique issues for such studies, especially with divergent treatment approaches and varying levels of equipoise. We report our experience accruing randomized patients to the Prospective Comparative Effectiveness Trial for Malignant Bowel Obstruction (SWOG S1316) study, comparing surgical and nonsurgical management of MBO. Methods: Patients with MBO who were surgical candidates and had treatment equipoise were accrued and offered randomization to surgical or nonsurgical management. Patients choosing nonrandomization were offered prospective observation. Trial details are listed on www.clinicaltrials.gov (NCT #02270450). An accrual algorithm was developed to enhance enrollment. Results: Accrual is ongoing with 176 patients enrolled. Most (89%) patients chose nonrandomization, opting for nonsurgical management. Of 25 sites that have accrued to this study, 6 enrolled patients on the randomization arm. Approximately 59% (20/34) of the randomization accrual goal has been achieved. Patient-related factors and clinician bias have been the most prevalent reasons for lack of randomization. An algorithm was developed from clinician experience to aid randomization. Using principles in this tool, repeated physician conversations discussing treatment options and goals of care, and a supportive team–approach has helped increase accrual. Conclusions: Experience gained from the S1316 study can aid future palliative care trials. Although difficult, it is possible to randomize patients to palliative studies by giving clinicians clear recommendations utilizing an algorithm of conversation, allotment of necessary time to discuss the trial, and encouragement to overcome internal bias.