Pancreatic cancer is an aggressive malignancy with a poor prognosis and complex supportive-care needs. Individualized tumor-directed treatment remains the central axis of care, while evolving nutritional and metabolic status, biliary complications, pain, inflammatory burden, thrombotic risk, and psychological distress may affect treatment readiness, tolerance, continuity, and quality of life. This review proposes the Six-Domain Supportive Care Framework, which organizes 6 clinically relevant and interacting priorities longitudinally around individualized tumor-directed treatment: Cancer Cachexia and Metabolic Derangement, Obstructive Jaundice and Infection Risk, Perineural Invasion and Neuropathic Pain, Chronic Cholangitis and Inflammatory Burden, Cancer-Associated Thrombosis and Coagulopathy, and Psychological Distress and quality of life. We focus on pancreatic cancer-specific evidence across these domains and draw on relevant gastrointestinal and broader oncology studies when direct evidence is limited. The 6 domains also involve longitudinal information from clinical records, laboratory tests, imaging, and patient-reported outcomes. Advances in digital health and artificial intelligence (AI) create new opportunities to integrate these heterogeneous data for risk identification, longitudinal monitoring, clinical prioritization, and clinician-supervised decision support. By linking current clinical evidence with AI-assisted data integration and decision support, this framework provides a clinically oriented perspective on coordinated longitudinal supportive care in pancreatic cancer and highlights priorities for future validation and clinical translation.
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Guo et al. (2026) studied this question.
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