Tanachat Nilanon1,2, Luciano P Nocera2, Alexander S Martin3, Anand Kolatkar4,5, Marcella May6, Zaki Hasnain7, Naoto T Ueno8, Sriram Yennu9, Angela Alexander10, Aaron E Mejia11, Roger Wilson Boles3, Ming Li3,11, Jerry S H Lee12, Sean E Hanlon12, Frankie A Cozzens Philips12, David I Quinn3,11,13, Paul K Newton7,11,14, Joan Broderick6, Cyrus Shahabi1,2, Peter Kuhn3,5,7,11,15, Jorge J Nieva3,11,13. 1. Department of Computer Science, University of Southern California, Los Angeles, CA. 2. Integrated Media Systems Center, University of Southern California, Los Angeles, CA. 3. Keck School of Medicine, University of Southern California, Los Angeles, CA. 4. Bridge Institute, University of Southern California, Los Angeles, CA. 5. Department of Biological Sciences, University of Southern California, Los Angeles, CA. 6. Dornsife Center for Self-Report Science, University of Southern California, Los Angeles, CA. 7. Department of Aerospace & Mechanical Engineering, University of Southern California, Los Angeles, CA. 8. Department of Breast Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX. 9. Department of Palliative, Rehabilitation, & Integrative Medicine, University of Texas MD Anderson Cancer Center, Houston, TX. 10. Department of Experimental Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, TX. 11. Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA. 12. Center for Strategic Scientific Initiatives, National Cancer Institute, Bethesda, MD. 13. Division of Medical Oncology, University of Southern California, Los Angeles, CA. 14. Department of Mathematics, University of Southern California, Los Angeles, CA. 15. Department of Biomedical Engineering, University of Southern California, Los Angeles, CA.
Abstract
PURPOSE: Unplanned health care encounters (UHEs) such as emergency room visits can occur commonly during cancer chemotherapy treatments. Patients at an increased risk of UHEs are typically identified by clinicians using performance status (PS) assessments based on a descriptive scale, such as the Eastern Cooperative Oncology Group (ECOG) scale. Such assessments can be bias prone, resulting in PS score disagreements between assessors. We therefore propose to evaluate PS using physical activity measurements (eg, energy expenditure) from wearable activity trackers. Specifically, we examined the feasibility of using a wristband (band) and a smartphone app for PS assessments. METHODS: We conducted an observational study on a cohort of patients with solid tumor receiving highly emetogenic chemotherapy. Patients were instructed to wear the band for a 60-day activity-tracking period. During clinic visits, we obtained ECOG scores assessed by physicians, coordinators, and patients themselves. UHEs occurring during the activity-tracking period plus a 90-day follow-up period were later compiled. We defined our primary outcome as the percentage of patients adherent to band-wear ≥ 80% of 10 am to 8 pm for ≥ 80% of the activity-tracking period. In an exploratory analysis, we computed hourly metabolic equivalent of task (MET) and counted 10 am to 8 pm hours with > 1.5 METs as nonsedentary physical activity hours. RESULTS: Forty-one patients completed the study (56.1% female; 61.0% age 40-60 years); 68% were adherent to band-wear. ECOG score disagreement between assessors ranged from 35.3% to 50.0%. In our exploratory analysis, lower average METs and nonsedentary hours, but not higher ECOG scores, were associated with higher 150-day UHEs. CONCLUSION: The use of a wearable activity tracker is generally feasible in a similar population of patients with cancer. A larger randomized controlled trial should be conducted to confirm the association between lower nonsedentary hours and higher UHEs.
PURPOSE: Unplanned health care encounters (UHEs) such as emergency room visits can occur commonly during cancer chemotherapy treatments. Patients at an increased risk of UHEs are typically identified by clinicians using performance status (PS) assessments based on a descriptive scale, such as the Eastern Cooperative Oncology Group (ECOG) scale. Such assessments can be bias prone, resulting in PS score disagreements between assessors. We therefore propose to evaluate PS using physical activity measurements (eg, energy expenditure) from wearable activity trackers. Specifically, we examined the feasibility of using a wristband (band) and a smartphone app for PS assessments. METHODS: We conducted an observational study on a cohort of patients with solid tumor receiving highly emetogenic chemotherapy. Patients were instructed to wear the band for a 60-day activity-tracking period. During clinic visits, we obtained ECOG scores assessed by physicians, coordinators, and patients themselves. UHEs occurring during the activity-tracking period plus a 90-day follow-up period were later compiled. We defined our primary outcome as the percentage of patients adherent to band-wear ≥ 80% of 10 am to 8 pm for ≥ 80% of the activity-tracking period. In an exploratory analysis, we computed hourly metabolic equivalent of task (MET) and counted 10 am to 8 pm hours with > 1.5 METs as nonsedentary physical activity hours. RESULTS: Forty-one patients completed the study (56.1% female; 61.0% age 40-60 years); 68% were adherent to band-wear. ECOG score disagreement between assessors ranged from 35.3% to 50.0%. In our exploratory analysis, lower average METs and nonsedentary hours, but not higher ECOG scores, were associated with higher 150-day UHEs. CONCLUSION: The use of a wearable activity tracker is generally feasible in a similar population of patients with cancer. A larger randomized controlled trial should be conducted to confirm the association between lower nonsedentary hours and higher UHEs.
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