Patterns and predictors of electronically measured oral anticancer medication (OAM) adherence among patients with multiple myeloma (MM).
Authors: Sarah M. Belcher, Susan M. Sereika, Jacqueline Dunbar-Jacob, Katherine Yeager, Margaret Q. Rosenzweig, Mounzer E. Agha, Benyam Muluneh, Lindsay M Sabik, Valire Copeland, Sarah McGregor, Catherine Bender
Journal: Journal of Clinical Oncology (2024)

7547 Background: Adherence to costly, long-term OAM is a mainstay of life-extending therapy for patients with MM and can dramatically affect cancer outcomes, but little is known about adherence in patients with MM. The purpose was to describe temporal patterns and predictors of OAM adherence among patients with MM via electronic event monitoring (EEM) adherence data. Methods: This was a six-month prospective study of OAM adherence, symptoms, and quality of life among n=70 patients prescribed OAM maintenance therapy for MM who used EEM. Patient reported measures of symptoms (Edmonton Symptom Assessment Scale; Patient Health Questionnaire-9; PROMIS Fatigue; Brief Pain Inventory; Comprehensive Score for financial Toxicity), sociodemographic data, and medical record clinical data were collected at enrollment and 3 and 6 months. Group-based trajectory modeling (GBTM) was applied to EEM data based on AARDEX MEMS smart pill bottles, aggregated monthly (i.e., 30-day intervals) over 6 months of monitoring. Adherence indices were % of prescribed dosestaken and % of days with correct intake. Predictors of adherence trajectory group membership were explored and summarized as bivariate correlations as effect sizes. Results: Participants were on average 63.9 y/o (SD=10.6) and predominantly male (55.9%) and non-Hispanic white (86.8%) or Black (10.3%). At enrollment, participants had been prescribed lenalidomide (68.6%) or pomalidomide (31.4%) for a median 11.5 (IQR: 22, range: 0-100) months. For mean dose adherence, GBTM revealed 3 distinct trajectories: 62.9% were in the high (~97% adherence) and slightly linear decreasing adherence group (π 3 =.627); 27.1% were in the high/moderate and curvilinear decreasing group (π 2 =.272), representing 85% adherence at start, dropping to &lt;70% by 6 months; and 10% had a low and curvilinear (π 1 =.100) pattern, representing only ~40% adherence over time. For mean days adherence, 2 distinct trajectories were identified: high and linear decreasing (81.4%, π 2 =.801), representing adherence starting at 90%, dropping to 85%; and low and stable (18.6%, π 1 =.199), representing ~40% adherence over time. Effect sizes for baseline predictors of the low trajectory group ranged from .02 to .37 (median r = .20, small), In particular, participants who self-identified as non-Hispanic Black or Hispanic “other” race being more likely to be in the low trajectory groups for both dose (p=.009) and days (p=.010) adherence. Conclusions: OAM adherence measured with EEM data was dynamic and suggests potential mechanisms of health inequities by race and ethnicity and a need for interventions to monitor for and address disparate adherence. Larger studies with longer observation and more frequent assessments with in-depth social determinants of health are needed to better understand OAM adherence patterns and correlates over time.