Incorporating Biomarkers of Prognosis and Cardiovascular Disease Risk in the Fit2Thrive Physical Activity Promotion Intervention for Breast Cancer Survivors

PROJECT SUMMARY/ABSTRACT Higher physical activity (PA) is associated with reduced risk of breast cancer (BC) recurrence and progression and increased survival. Increased PA is also associated with reductions in cardiovascular disease (CVD) mortality, the leading cause of non-cancer mortality among BC survivors (BCS). PA may prevent BC progression and CVD via its effects on inflammation and also decrease CVD risk via effects on cardiometabolic biomarkers. However, the exact biologic mechanisms are poorly understood as few PA interventions include biomarkers of BC progression or CVD risk. Additionally, most PA interventions are costly, intense, on-site multicomponent interventions that provide little insight into what components (i.e. phone calls, Fitbits, etc.) are, or are not, effective, and traditional venous blood sample collection is often costly and requires lab visits limiting the potential public health impact of this research. In order to increase public health relevance, it is critical to develop a better understanding of not only how PA influences BC progression and CVD risk, but how different PA interventions and PA dose impact outcomes using more scalable methods. The purpose of the present study is to examine the extent to which each of five completely remotely-delivered social cognitive theory (SCT)-guided PA intervention components ameliorate a pro-inflammatory phenotype of BC progression and CVD risk [i.e. interleukin-6, tumor necrosis factor-alpha interleukin-10, c-reactive protein (CRP)] and cardiometabolic biomarkers [i.e. glucose, triglycerides, total cholesterol and high-density lipoproteins] in a nationwide sample of BCS (n=256) at 12 weeks and 24 week follow-up using Multiphase Optimization Strategy (MOST) methodology. We will also explore potential mediators (i.e. SCT constructs, adherence, PA) and/or moderators (i.e. demographics, disease characteristics) of these effects. MOST is an innovative, multi-phase framework adapted from engineering that uses highly efficient factorial experiments to evaluate individual, and combined, effects of intervention components to determine which ones can be reduced, eliminated or replaced to improve efficiency. We will use self-collection of dried blood spots (DBS) via a simple finger stick to collect blood samples as they require no lab visits and represent a novel, low cost, alternative to venous blood sample collection. The proposed study represents the first systematic effort to use MOST to examine BC progression and cardiometabolic biomarkers in a remotely-delivered PA intervention using scalable biomarker collection methods. Data from this study will provide preliminary effect sizes to be used to assemble an intervention to be evaluated in a larger R01 that is optimized to yield the maximum changes in biomarker outcomes for the minimum cost. These data will contribute to the development of more tailored outcome-specific PA interventions and PA prescriptions for BCS to improve health and disease outcomes.