Cureus. 2025 Sep;17(9): e91395
Cancer-related pain (CRP) is a complex, multidimensional challenge in oncology that undermines quality of life, psychological well-being, and treatment adherence. This narrative, mechanism-informed review synthesizes pathophysiology, classification systems, and multidisciplinary management strategies to provide clinical insights and research priorities. It connects nociceptive, neuropathic, and mixed pain mechanisms to practical interventions, emphasizing peripheral and central sensitization in chronicity. Major frameworks, including the WHO analgesic ladder, International Classification of Diseases, 11th Revision, Edmonton Classification System for Cancer Pain, and European Pain Federation standards, are appraised alongside assessment tools such as the Visual Analogue Scale, Brief Pain Inventory, and Hospital Anxiety and Depression Scale, with examples of their clinical application. Management is framed within a flexible, mechanism-based, multimodal model that integrates pharmacologic, adjuvant, interventional, and psychosocial approaches, delivered through coordinated, multidisciplinary teams. Evidence for complementary modalities, such as acupuncture and mindfulness-based stress reduction, remains preliminary and heterogeneous, requiring further high-quality trials, whereas opioid-based pharmacologic approaches and structured psychosocial interventions such as cognitive behavioral therapy are supported by more robust, established evidence. Similarly, innovations like AI-driven monitoring and pharmacogenomics hold promise but are still in the early validation phase, underscoring the need to distinguish between evolving and well-established domains of cancer pain management. The principal actionable priorities are to adopt mechanism-based classification, embed multidisciplinary collaboration, expand multimodal access in low-resource settings, and rigorously validate emerging pharmacogenomic and digital health innovations before widespread clinical integration.
Keywords: artificial intelligence; cancer-related pain; mechanism-based treatment; precision oncology; translational pain research