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6 th <strong>International</strong> <strong>Workshop</strong> on Breast Densitometry and Breast Cancer Risk Assessment BREASTCARE: A PRIMARY CARE CLINIC-BASED RCT TO INCREASE BREAST CANCER KNOWLEDGE AND DISCUSSION OF RISK AND LIFESTYLE BEHAVIORS Celia P. Kaplan, DrPH, MA, Jennifer Livaudais-Toman, PhD, Steven Gregorich, PhD, Jeffrey Tice, MD, Karla Kerlikowske, MD, Rena Pasick, PhD, Alice Chen, MD, Eliseo J. Perez-Stable, MD, Leah S. Karliner, MD ABSTRACTS FOR SPEAKERS Background. Despite the availability of breast cancer risk assessment tools and interventions for risk reduction, these tools are not well integrated into clinical practice. As a result, many women do not engage in a discussion of their breast cancer risk with their physician, which may lead to underuse of effective risk reduction interventions. Methods. We conducted a randomized controlled trial that compared usual care to a tablet-personal computer (PC) based breast cancer risk assessment and education intervention (BreastCARE) delivered in a primary care setting. We enrolled women aged 40-74 years with no personal breast cancer history prior to their scheduled primary care visits at two clinics (one academic medical center, one safety-net) between June 2011 and August 2012, and randomized them to Intervention or Usual Care (UC) arms, stratified by race/ethnicity. The Intervention group completed the BreastCARE intervention at the clinic just prior to their clinic visit and women and physicians received a tailored risk report. The UC group completed a telephone-based risk assessment after their clinic visit. We categorized women as high or average risk based on family history using the Referral Screening Tool (RST) or breast cancer risk factors using the Gail/Breast Cancer Surveillance Consortium (BCSC) risk models. We contacted all women for a follow-up telephone survey one week after risk assessment. We used generalized estimating equations to account for clustering by physician, and to estimate differences at follow-up between Intervention and UC groups in above average knowledge of breast cancer risk factors (cut-point based on mean knowledge score from sample), and discussion of breast cancer risk and lifestyle behaviors (exercise and weight) with physician. Results. A total of 1,278 women completed risk assessments and signed consent forms (596 Intervention and 665 UC) and 1,235 (97%) completed follow-up interviews (580 Intervention and 655 UC). The mean sample age was 56 years (SD=9) with 35% non-Latina White, 23% Latina, 22% African American, 18% Asian/Pacific Islander and 2% Native American/other. Demographic characteristics and breast cancer risk distributions were well-balanced between Intervention and UC groups. Nine percent of women qualified for high-risk referral based on RST score and 16% qualified based on Gail/BCSC models. Compared to women in the UC group, those in the Intervention group reported greater knowledge of breast cancer risk factors (69% vs. 55%), and more discussion of breast cancer risk (41% vs. 14%), exercise (75% vs. 61%) and weight (67% vs. 57%) with physician. Discussion of risk was greatest among women at the highest risk for breast cancer who received the intervention (51% Intervention vs. 18% UC). Multivariable analysis results are presented in Table 1. Table 1. Multivariable analysis at follow-up* Above average knowledge of breast cancer risk factors 24 Discussed breast cancer risk with physician Discussed regular exercise with physician Discussed weight with physician OR (95% CI) OR (95% CI) OR (95% CI) OR (95% CI) (ref=UC) Intervention group 1.78 (1.37-2.31)° 3.94 (2.90-5.37)° 1.95 (1.51-2.51)° 1.60 (1.26-2.02)° *Analyses account for clustering of observations by physician and are adjusted for clinic site and objective breast cancer risk °p
6 th <strong>International</strong> <strong>Workshop</strong> on Breast Densitometry and Breast Cancer Risk Assessment IMPACT OF THE TRANSITION TO DIGITAL MAMMOGRAPHY ON THE BENEFITS, HARMS AND COSTS OF SCREENING FOR BREAST CANCER IN THE US Natasha K. Stout, PhD 1 ; Sandra J. Lee, DSc 2 ; Clyde B. Schechter, MD MA 3 ; Oguzhan Alagoz, PhD 4,5 ; Donald Berry, PhD 6 ; Diana S.M. Buist, PhD 7 ; Mucahit Cevik 4 ; Gary Chisholm 6 ; Harry J. de Koning, MD PhD 8 ; Hui Huang, MS 2 ; Rebecca Hubbard PhD 7 ; Karla Kerlikowske, MD 9 ; Mark Munsell, MS 6 ; Anna N. A. Tosteson, ScD 10 ; Amy Trentham-Dietz, PhD 5 ; Nicolien T. van Ravesteyn, MSc 8 ; Diana L. Miglioretti, PhD 11 ; Jeanne S. Mandelblatt, MD MPH 12 1 Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA; 2 Dana-Farber Cancer Institute, Boston, MA; 3 Departments of Family & Social Medicine and Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, New York; 4 Department of Industrial and Systems Engineering, University of Wisconsin, Madison, WI; 5 Department of Population Health Sciences and Carbone Cancer Center, University of Wisconsin, Madison, WI; 6 The University of Texas M.D. Anderson Cancer Center, Houston, TX; 7 Group Health Research Institute, Seattle, WA; 8 Department of Public Health, Erasmus MC, Rotterdam, The Netherlands; 9 Departments of Epidemiology and Biostatistics, and General Internal Medicine Section, Department of Veterans Affairs, University of California, San Francisco, CA; 10 The Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Lebanon, NH; 11 Department of Public Health Sciences, School of Medicine, University of California, Davis; 12 Department of Oncology, Georgetown University Medical Center and Cancer Prevention and Control Program, Lombardi Comprehensive Cancer Center Fueled in part by the 2005 Digital Mammographic Imaging Trial results showing improved sensitivity for selected subgroups of women, digital mammography has quickly replaced plain film mammography for routine breast cancer screening. Use in community settings supports the modest improvements in sensitivity for younger women and women with radiographically dense breasts seen in the trial, however, specificity is reduced. Further, digital has higher cost compared with plain film mammography. The impact of the switch in technology from film to digital mammography on women’s health and economic costs is unclear. Therefore, we will 1) assess the health effects and monetary costs of screening mammography using digital mammography instead of film according the 2009 US Preventive Services Task Force breast cancer screening guidelines, and 2) examine alternative screening schedules using digital mammography that extend screening to younger women or women with dense breast tissue, two subgroups where digital has been shown to perform better than film mammography. This analysis represents a collaboration between researchers from the National Cancer Institute’s Cancer Intervention and Surveillance Modeling Network (CISNET) and Breast Cancer Surveillance Consortium (BCSC). We will use a comparative modeling approach with five independent CISNET computer models of U.S. breast cancer epidemiology. The models account for differential risk breast cancer risk and mammography performance by breast density using inputs based on data from the BCSC. Model outcomes will include life years, quality-adjusted life years, costs, breast cancer mortality and false positives per screening scenario. We will compute incremental cost-effectiveness ratios for the digital screening strategies both within each model and across the five models to understand the value of alternative screening scenarios. The comparative modeling approach using five models will allow us to better account for uncertainty in breast cancer natural history on analysis conclusions about the benefits and harms of screening. ABSTRACTS FOR SPEAKERS 25
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