Type 5 diabetes mellitus: redefining pancreatogenic diabetes through molecular, imaging, and AI-driven evidence

Abstract

BACKGROUND: Type 5 Diabetes Mellitus (T5DM), denoting pancreatogenic diabetes from fibro-inflammatory pancreatic injury, is a distinct yet under-recognised entity. Current WHO and ADA classifications overlook its complex, concurrent endocrine-exocrine failures, contributing to misdiagnosis, treatment gaps, and suboptimal outcomes. OBJECTIVES: This review aims to critically analyze current scientific understanding of the pathogenesis, diagnostic criteria, metabolic consequences, and therapeutic needs of T5DM and suggest a precise framework of medicine that justifies the need for T5DM to be formally recognized as a sub-type of diabetes. METHODS: An integrative review was conducted using recent literature on pancreatic pathophysiology, molecular biomarkers, radiomics, diagnostic imaging, glycemic control technologies, and machine learning. The focus was on the recent literature to elucidate the biological, diagnostic, and treatment aspects of the clinical studies, guidelines, and mechanistic research available from the publications. KEY FINDINGS: T5DM involves loss of insulin and glucagon alongside exocrine pancreatic insufficiency, malnutrition, and significant glycaemic variability. A tiered diagnostic framework-integrating pancreatic imaging, endocrine-exocrine testing, autoimmune exclusion, and emerging biomarkers-enhances accuracy. Management requires coordinated hormonal and enzyme replacement, structured nutritional support, and targeted surveillance for malignancy and micronutrient deficits. Radiomics, quantitative imaging, and AI-driven analytics offer valuable tools for earlier detection, improved risk stratification, and personalised therapy. CONCLUSION: T5DM warrants recognition as a distinct diabetes entity owing to its unique pathophysiology, clinical behaviour, and therapeutic needs. Harmonised diagnostic criteria, validated biomarker and imaging pathways, and multicentre registries are essential to integrate T5DM into global classification systems and advance mechanism-based, personalised care.