AI-Assisted Chemotherapy Side Effect Management

This two-stage adaptive randomized controlled trial evaluates the feasibility and preliminary efficacy of large language model (LLM)-assisted intervention for managing chemotherapy side effects in patients with solid tumors. Adults with histologically confirmed breast or colorectal cancer scheduled for at least 3 months of systemic chemotherapy will be randomly assigned (1:1) to receive either LLM-assisted care or standard care. The study employs an adaptive design with initial enrollment of 60 patients (30 per arm), followed by interim analysis. Unless enrollment is stopped for safety reasons identified at interim analysis, an additional 114 patients will be enrolled for a maximum total of 174 patients (87 per arm). In the intervention group, healthcare providers input anonymized patient symptom data into an LLM system using sessions where data is not retained, which generates evidenc