Revisiting Diabetes Classification: Insights Challenges and Clinical Relevance of the ANDIS Framework in the Indian Context.

Diabetes mellitus exhibits significant heterogeneity in clinical presentation, progression, and treatment response, rendering the traditional binary classification into type 1 and type 2 diabetes increasingly inadequate. The All New Diabetics in Scania (ANDIS) framework, introduced in 2018, proposed a novel data-driven classification system that stratifies adult-onset diabetes into five distinct subgroups based on clinical and biochemical characteristics. This manuscript critically examines the scientific rationale, methodology, and clinical implications of the ANDIS classification, while evaluating its utility through evidence drawn from Indian (INSPIRED and WellGen) and global validation studies (DEVOTE, LEADER, DD2, NHANES, and FoCus cohorts). Findings from these cohorts affirm the biological relevance of clusters like severe insulin-deficient diabetes (SIDD) and severe insulin-resistant diabetes (SIRD). However, their prevalence varies across ethnic and regional populations. Despite its theoretical strengths, the ANDIS model faces major implementation barriers, including diagnostic complexity, high costs, and limited therapeutic differentiation over existing guidelines. Furthermore, access to required diagnostics such as glutamic acid decarboxylase (GAD) antibody testing and homeostatic model assessment 2 (HOMA2) indices is limited even in high-income countries (HICs). The framework's real-world applicability can be simplified using accessible markers such as hemoglobin A1C (HbA1c), body mass index (BMI), and abdominal circumference. The manuscript emphasizes the need for dynamic, low-cost, and population-specific adaptations to make stratified diabetes care feasible and impactful globally.