Association of iterative cannabis care plans with rates of symptom relief and side effect burden in oncology patients.

12070 Background: Cannabis is increasingly used to manage cancer-related symptoms including pain, sleep disturbance, anxiety, and appetite or gastrointestinal complaints. However, patient responses are highly variable, clinicians report limited confidence in guiding use, and optimal dosing is difficult to predict from baseline characteristics. We evaluated whether an iterative, guided cannabis care model incorporating ongoing patient feedback and care-plan adjustments is associated with improved symptom relief and lower side-effect burden in a real-world oncology population. Methods: We conducted a retrospective observational analysis of cancer patients receiving cannabis-based symptom management through a structured care-planning program. Baseline demographics, cannabis experience, THC dosing, and number of care-plan adjustments were collected. Patients provided longitudinal feedback on symptom outcomes and tolerability at serial check-ins. Significant symptom relief was defined as a ≥3-point reduction in PROMIS T-scores across pain, sleep, anxiety, and appetite/nausea domains. Side-effect burden was assessed as the percentage of follow-up check-ins with reported side effects. Logistic regression examined associations between care-plan adjustments and symptom relief, adjusting for age, cannabis experience, and final THC dose. Results: A total of 136 patients receiving active cancer treatment were included (mean age 61 years; range 26–91). Overall, 56% reported significant relief across all symptom domains. Rates of global symptom relief increased with care-plan iteration: 34.6% among patients with no adjustments, 72.4% among those with 1–2 adjustments, and 96.6% among those with ≥3 adjustments, demonstrating a strong relationship. Care-plan iteration was also associated with lower longitudinal side-effect burden, with side effects reported at 25.6% of check-ins among patients with no adjustments, 17.5% with 1–2 adjustments, and 11.7% with ≥3 adjustments. In adjusted analyses, each additional adjustment was independently associated with higher odds of global symptom relief, while baseline demographic and clinical characteristics were not strong predictors of response. Conclusions: Symptom response to cannabis therapy among oncology patients is heterogeneous and not reliably predicted by baseline characteristics. In this real-world cohort, iterative cannabis care plans incorporating ongoing monitoring and adjustment were associated with substantially higher rates of meaningful symptom relief and a lower burden of side effects over time. These findings support adaptive, feedback-driven cannabis care models over fixed dosing strategies in supportive oncology.