Adaptive therapy: a balanced triangle for chronic cancer management

The increasing complexity of cancer treatment, which requires balancing curative-intent therapy, long-term disease control with treatment-related adverse events (TRAEs), underscores the need for a dynamic approach. We propose an expanded definition of modern adaptive therapy in oncology, which focuses on balancing tumor burden, therapeutic efficacy, and TRAEs to optimize outcomes across the entire cancer care continuum, from curative-intent treatment to long-term disease management. This approach is enabled by biomarker-guided patient selection, dynamic tumor burden assessment, and longitudinal monitoring of treatment response and treatment-related adverse events. Within this framework, treatment intensity is modulated through escalation, de-escalation, or intermittent ("holiday") strategies, supported by advanced imaging, liquid biopsy, and emerging artificial intelligence tools for real-time disease assessment. By integrating these principles, modern adaptive therapy aims to maximize clinical benefit while minimizing avoidable toxicity, enhancing quality of life, improving survival, and promoting more sustainable and cost-effective cancer care.