Type 2 diabetes (T2D) exhibits considerable heterogeneity in its pathophysiology and clinical presentation. Identifying distinct T2D subgroups, characterized by clustering of phenotypic traits, has the potential to identify subsets of patients at differential risk of complications, and who are likely to respond differentially to various anti-diabetic medications. In a recent study of the Scandinavian population,five distinct ‘clusters’ of individuals with diabetes with significantly diverse characteristics were identified,  Anjana et al, (2020) identified four replicable clusters among the Asian population. The four identifies clusters are Severe Insulin Deficient Diabetes (SIDD), Insulin Resistant Obese Diabetes (IROD), Combined Insulin Resistance and Deficient Diabetes (CIRDD), and Mild Age-Related Diabetes (MARD). 

Classifying T2D patients into phenotypic clusters provides insights into the pathophysiological processes driving diabetes, and aid in appropriate treatment selection, risk prediction, and focusing attention on individuals with the highest risk of morbidity and mortality . Though metformin is the first line of drug for T2D, not all patients respond equally well to it, necessitating the addition of other classes of antidiabetic agents to achieve glycemic targets. The selection of appropriate medication as initial therapy has the potential to minimize this delay and hasten the achievement of treatment goals. We, therefore, aim to assess the glycemic response of individuals with new-onset diabetes to different classes of anti-diabetic medications.