Yvonne H Sada1,2, Olia Poursina3, He Zhou3, Biruh T Workeneh4, Sandhya V Maddali3, Bijan Najafi3. 1. Department of Medicine, Section of Hematology and Oncology, Dan L Duncan Cancer Center, Baylor College of Medicine, Houston, Texas, United States of America. 2. Houston VA Center for Innovations in Quality, Effectiveness, and Safety, Michael E. DeBakey VA Medical Center, Houston, Texas, United States of America. 3. Michael E. DeBakey Department of Surgery, Interdisciplinary Consortium on Advanced Motion Performance (iCAMP), Baylor College of Medicine, Houston, Texas, United States of America. 4. Department of Nephrology, Division of Internal Medicine, MD Anderson Cancer Center, Houston, Texas, United States of America.
Abstract
OBJECTIVE: Cancer-related fatigue (CRF) is highly prevalent among cancer survivors, which may have long-term effects on physical activity and quality of life. CRF is assessed by self-report or clinical observation, which may limit timely diagnosis and management. In this study, we examined the effect of CRF on mobility performance measured by a wearable pendant sensor. METHODS: This is a secondary analysis of a clinical trial evaluating the benefit of exercise in cancer survivors with chemotherapy-induced peripheral neuropathy (CIPN). CRF status was classified based on a Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F) score ≤ 33. Among 28 patients (age = 65.7±9.8 years old, BMI = 26.9±4.1kg/m2, sex = 32.9%female) with database variables of interest, twenty-one subjects (75.9%) were classified as non-CRF. Mobility performance, including behavior (sedentary, light, and moderate to vigorous activity (MtV)), postures (sitting, standing, lying, and walking), and locomotion (e.g., steps, postural transitions) were measured using a validated pendant-sensor over 24-hours. Baseline psychosocial, Functional Assessment of Cancer Therapy-General (FACT-G), Falls Efficacy Scale-International (FES-I), and motor-capacity assessments including gait (habitual speed, fast speed, and dual-task speed) and static balance were also performed. RESULTS: Both groups had similar baseline clinical and psychosocial characteristics, except for body-mass index (BMI), FACT-G, FACIT-F, and FES-I (p<0.050). The groups did not differ on motor-capacity. However, the majority of mobility performance parameters were different between groups with large to very large effect size, Cohen's d ranging from 0.91 to 1.59. Among assessed mobility performance, the largest effect sizes were observed for sedentary-behavior (d = 1.59, p = 0.006), light-activity (d = 1.48, p = 0.009), and duration of sitting+lying (d = 1.46, p = 0.016). The largest correlations between mobility performance and FACIT-F were observed for sitting+lying (rho = -0.67, p<0.001) and the number of steps per day (rho = 0.60, p = 0.001). CONCLUSION: The results of this study suggest that sensor-based mobility performance monitoring could be considered as a potential digital biomarker for CRF assessment. Future studies warrant evaluating utilization of mobility performance to track changes in CRF over time, response to CRF-related interventions, and earlier detection of CRF.
OBJECTIVE:Cancer-related fatigue (CRF) is highly prevalent among cancer survivors, which may have long-term effects on physical activity and quality of life. CRF is assessed by self-report or clinical observation, which may limit timely diagnosis and management. In this study, we examined the effect of CRF on mobility performance measured by a wearable pendant sensor. METHODS: This is a secondary analysis of a clinical trial evaluating the benefit of exercise in cancer survivors with chemotherapy-induced peripheral neuropathy (CIPN). CRF status was classified based on a Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F) score ≤ 33. Among 28 patients (age = 65.7±9.8 years old, BMI = 26.9±4.1kg/m2, sex = 32.9%female) with database variables of interest, twenty-one subjects (75.9%) were classified as non-CRF. Mobility performance, including behavior (sedentary, light, and moderate to vigorous activity (MtV)), postures (sitting, standing, lying, and walking), and locomotion (e.g., steps, postural transitions) were measured using a validated pendant-sensor over 24-hours. Baseline psychosocial, Functional Assessment of Cancer Therapy-General (FACT-G), Falls Efficacy Scale-International (FES-I), and motor-capacity assessments including gait (habitual speed, fast speed, and dual-task speed) and static balance were also performed. RESULTS: Both groups had similar baseline clinical and psychosocial characteristics, except for body-mass index (BMI), FACT-G, FACIT-F, and FES-I (p<0.050). The groups did not differ on motor-capacity. However, the majority of mobility performance parameters were different between groups with large to very large effect size, Cohen's d ranging from 0.91 to 1.59. Among assessed mobility performance, the largest effect sizes were observed for sedentary-behavior (d = 1.59, p = 0.006), light-activity (d = 1.48, p = 0.009), and duration of sitting+lying (d = 1.46, p = 0.016). The largest correlations between mobility performance and FACIT-F were observed for sitting+lying (rho = -0.67, p<0.001) and the number of steps per day (rho = 0.60, p = 0.001). CONCLUSION: The results of this study suggest that sensor-based mobility performance monitoring could be considered as a potential digital biomarker for CRF assessment. Future studies warrant evaluating utilization of mobility performance to track changes in CRF over time, response to CRF-related interventions, and earlier detection of CRF.
Authors: Zeeshan Butt; Jin-Shei Lai; Deepa Rao; Allen W Heinemann; Alex Bill; David Cella Journal: J Psychosom Res Date: 2012-11-15 Impact factor: 3.006
Authors: Christopher T V Swain; Nga H Nguyen; Tobyn Eagles; Jeff K Vallance; Terry Boyle; Ian M Lahart; Brigid M Lynch Journal: Cancer Date: 2019-11-12 Impact factor: 6.860
Authors: Laura Q Rogers; Stephen J Markwell; Kerry S Courneya; Edward McAuley; Steven Verhulst Journal: J Cancer Surviv Date: 2010-11-26 Impact factor: 4.442
Authors: Lynne I Wagner; Julian Schink; Michael Bass; Shalini Patel; Maria Varela Diaz; Nan Rothrock; Timothy Pearman; Richard Gershon; Frank J Penedo; Steven Rosen; David Cella Journal: Cancer Date: 2014-11-06 Impact factor: 6.860
Authors: Gertrudis I J M Kempen; Lucy Yardley; Jolanda C M van Haastregt; G A Rixt Zijlstra; Nina Beyer; Klaus Hauer; Chris Todd Journal: Age Ageing Date: 2007-11-20 Impact factor: 10.668
Authors: Gurtej Grewal; Rashad Sayeed; Steve Yeschek; Robert Alexander Menzies; Talal K Talal; Lawrence A Lavery; David G Armstrong; Bijan Najafi Journal: Gerontology Date: 2012-05-10 Impact factor: 5.140
Authors: Roger Hilfiker; Andre Meichtry; Manuela Eicher; Lina Nilsson Balfe; Ruud H Knols; Martin L Verra; Jan Taeymans Journal: Br J Sports Med Date: 2017-05-13 Impact factor: 13.800
Authors: Steven Piantadosi; Arvind M Shinde; Gillian Gresham; Andrew E Hendifar; Brennan Spiegel; Elad Neeman; Richard Tuli; B J Rimel; Robert A Figlin; Curtis L Meinert Journal: NPJ Digit Med Date: 2018-07-05