Using mHealth Technology to Evaluate Daily Symptom Burden among Adult Survivors of Childhood Cancer: A Feasibility Study

Abstract

Background: Cancer therapies predispose survivors to a high symptom burden. This study utilized mobile health (mHealth) technology to assess the feasibility of collecting daily symptoms from adult survivors of childhood cancer to evaluate symptom fluctuation and associations with future health-related quality-of-life (HRQOL). Methods: This prospective study used an mHealth platform to distribute a 20-item cancer-related symptom survey (5 consecutive days each month) and an HRQOL survey (the day after the symptom survey) over 3 consecutive months to participants from the Childhood Cancer Survivor Study. These surveys comprised a PROMIS-29 Profile and Neuro-QOL assessed HRQOL. Daily symptom burden was calculated by summing the severity (mild, moderate, or severe) of 20 symptoms. Univariate linear mixed-effects models were used to analyze total, person-to-person, day-to-day, and month-to-month variability for the burden of 20 individual symptoms. Multivariable linear regression was used to analyze the association between daily symptom burden in the first month and HRQOL in the third month, adjusted for covariates. Results: Out of the 60 survivors invited, 41 participated in this study (68% enrollment rate); 83% reported their symptoms ≥3 times and 95% reported HRQOL in each study week across 3 months. Variability of daily symptom burden differed from person-to-person (74%), day-to-day (18%), and month-to-month (8%). Higher first-month symptom burden was associated with poorer HRQOL related to anxiety (regression coefficient: 6.56; 95% CI: 4.10–9.02), depression (6.32; 95% CI: 3.18–9.47), fatigue (7.93; 95% CI: 5.11–10.80), sleep (6.07; 95% CI: 3.43–8.70), pain (5.16; 95% CI: 2.11–8.22), and cognitive function (–6.89; 95% CI: –10.00 to –3.79) in the third month. Conclusions: Daily assessment revealed fluctuations in symptomology, and higher symptom burden was associated with poorer HRQOL in the future. Utilizing mHealth technology for daily symptom assessment improves our understanding of symptom dynamics and sources of variability.