Patterns in remote symptom monitoring compliance among patients with cancer.

496 Background: Remote symptom monitoring (RSM) enables patients with cancer to report treatment-related symptoms in real time. This analysis examines how patient sociodemographic characteristics may influence RSM compliance rates. Methods: Patients initiating first-time cancer treatment (chemotherapy, immunotherapy, targeted therapy) at University of South Alabama Health Mitchell Cancer Institute between May 2024 and April 2025 were approached for RSM enrollment. Enrolled patients received weekly symptom surveys, with results routed to their nurse via the electronic health record. Compliance was defined as completion of at least one RSM survey per month for six months tracked using the electronic patient-reported outcomes (ePROs) platform, Carevive PROmpt. Compliance was calculated by comparing complete versus incomplete surveys, which were abstracted from the ePROs platform. Likelihood of compliance was compared using unadjusted relative risk (RR) and 95% confidence intervals stratified by age, race, sex, rurality, and cancer type. Results: Of 252 RSM-enrolled patients, median age was 61 (range 22–89), 75% were female, 34% were Black, 22% lived in a rural area, and 37% were diagnosed with a gynecological cancer. Of 6,018 submitted surveys, 75% were compliant. Compliance rates differed by age with increasing compliance for each decade. Patients in the 30-39 age group were 36% less likely to be compliant than those aged 80-89 (RR=0.64, 95% CI = [0.28, 1.44]). Rural patients were 21% more likely to be compliant than urban patients though not significantly different (RR=1.2, 95% CI: [0.88, 1.67]). Compliance was essentially equivalent when stratified by race and sex (RR=0.99 and 1.04, 95% CI = [0.85, 1.15] and [0.93, 1.16] respectively). Compliance differed by cancer type with the greatest difference noted in GU cancer patients compared to gynecologic cancer patients (RR=0.52, 95% CI: [0.27, 1.02]). In adjusted models, compliance was similar by patient sociodemographic characteristics. Although not statistically significant, younger patients, those aged 30–39, showed a trend toward lower compliance compared to older age groups. Conclusions: No substantial differences in RSM compliance were seen by race, sex, or rurality. However, a potential age-related disparity may warrant further investigation in a larger cohort. These findings demonstrate similar compliance across demographic groups that historically experience poor access. RSM may level the playing field to improve supportive oncology care and decrease hospitalization across populations. Targeted strategies may be needed to improve ePRO compliance, especially among younger patients and those disease teams with lower adherence.