Evaluating heart-hate variability, salivary cortisol and physical activity as predictors of cancer-related fatigue recovery in breast-cancer survivors over a 12 week period by use of a smartphone application

Introduction Cancer-related fatigue (CRF) is one of the most prevalent and debilitating problems in breast cancer survivors (BCS) that can persist many years beyond successful cancer treatment. Parasympathetic nervous system activity (measured via heart-rate variability; HRV), cortisol dysregulation and decreased physical activity are plausible, but understudied contributors to CRF. Repeated daily measurements of CRF and tracking daily physical activity over a 12-week period should give more information regarding temporal patterns of CRF among BCS. Objective The purpose of this study is 1) to investigate patterns of CRF in fatigued BCS over time; 2) to assess HRV, salivary cortisol and level of physical activity as predictors of cancer-related fatigue (CRF) in BCS over a 12-week period; and 3) to explore whether a smartphone application intervention results in increased daily physical activity, as well as improved HRV, salivary cortisol and CRF in BCS relative to healthy female controls over a 12 week period. Methods A total of 30 fatigued breast cancer survivors (FACIT-F score ≤ 34) and 30 aged-matched female controls will be randomly assigned to either an intervention or control group. Both groups will receive a smartphone application tracking daily physical activity. While the intervention group will receive this application with feedback regarding their daily physical activity, the control groups will receive the application without feedback. Behavioral data will be collected by means of GPS and Wi-Fi for localization, and accelerometer, barometer, magnetometer and gyroscope for activity recognition. HRV and salivary cortisol will be collected at rest, as well as during and after a significant stressor (Trier Social Stress Test). Fatigue will be measured by the FACIT-F Scale, which will be completed at baseline (T1), 4 weeks (T2) and 12 weeks (T3). Group differences will be tested by one-way analysis of variance (ANOVA) and intervention effects will be analyzed using mixed models with repeated measurements. Hypotheses We hypothesize that HRV, cortisol dysregulation and level of physical activity at baseline can predict CRF-recovery over a 12-week period. The smartphone application will be associated with improved physical activity in the BCS intervention group and that changes of physiological correlates of CRF can be observed (i.e., HRV and salivary cortisol). Conclusion This study will examine associations between HRV, salivary cortisol, physical activity and CRF in BCS over time. The results of this study may provide insight into factors that contribute to the development, persistence and/or consequences of CRF by use of an innovative mobile application.