Outcomes of a digital health coaching program for individuals with acute myeloid and chronic lymphocytic leukemia.
Authors: Shelton Valerie , Brassil Kelly Jean , Fellman Bryan M. , Barr Austin , Chien Kelly Sharon , Hammond Danielle , Kantarjian Hagop M. , Wierda William G. , Ferrajoli Alessandra , Dinardo Courtney Denton 
Published: October 2023

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Background: Chronic lymphocytic leukemia (CLL) accounts for ~19,000 and acute myeloid leukemia (AML) accounts for ~20,000 new cases a year, according to SEER data. Individual management and overall survival rates vary by cancer type, each with unique and potentially long-term care needs. Digital interventions continue to expand, connecting with individuals beyond the clinical setting to support health self-efficacy and address overall wellness needs. However, data related to their application for hematologic malignancies is limited. Methods: The aim of this randomized, longitudinal cohort study was to evaluate the effect of a 3-month digital health coaching program on health self-efficacy, measured by the Cancer Behavior Inventory (CBI), and other patient reported outcomes (PROs) among individuals with AML or CLL. We aimed to enroll 500 participants, 250 each with CLL and AML, randomized to either the digital intervention or usual care. PROs were collected at baseline and up to once per month for 3 months via REDCAp. Clinical outcomes were tracked via electronic health record. The change in CBI scores from baseline to 3 months was calculated with 95% confidence intervals. A 2-sample t-test was used to compare change between intervention and control arms. PRO trends over time were analyzed using linear mixed models (LMMs). Results: The study enrolled 147 individuals from July 2020 through December 2022. Thirty-seven were enrolled in the AML group (19 control), and 110 in the CLL group (55 control). The mean change in CBI from baseline to 3 months in the AML control arm was -3.57 (95% CI: -17.30 – 10.15) and in the AML intervention arm was 7.03 (95% CI: -2.67 – 16.74), with higher scores indicating greater efficacy for coping. While not significant, mean change in CBI in the CLL control arm was 1.43 (95% CI: -3.45 – 6.31; p=0.556) and in the CLL intervention arm was 3.46 (95% CI: -1.44 – 8.37; p=0.219). In the CLL group, self-efficacy was associated with improved quality of life (p <0.001); For every unit increase in FACT-LEU-TOI, CBI increased on average by 0.81 units (95% CI: 0.62 – 1.00). Conclusions: Due to limited study enrollment during the COVID-19 pandemic, the study was not powered to detect a difference between groups. Data from the engaged cohort suggest a non-statistically significant trend over time in improvement in health self-efficacy for the participants engaged in digital health coaching. A recent meta-analysis suggests self-efficacy has a strong negative correlation with distress and positive correlation with quality of life and improved self-efficacy may mitigate negative effects of a cancer diagnosis and treatment. Data related to trends in PRO over time within and between AML and CLL cohorts provide further insights into physiologic and psychosocial outcomes for these populations. Clinical trial information: NCT04774744 .