Novel clusters of type 2 Diabetes: A tailored therapeutic approach

Abstract

Type 2 diabetes is a heterogeneous disease for which etiological mechanisms are incompletely understood and subclassification may improve patient care. In this paper, we aimed to stratify a cohort of Portuguese patients with adult-onset diabetes followed at our Diabetic clinic into subgroups and assess the impact of the clusters on outcomes and therapy. Methods: We performed a cluster analysis on 1280 patients followed at our Diabetic clinic. Clusters were based on three variables: presence of glutamic acid decarboxylase antibodies, age at diagnosis and body mass index. Clinical data was retrieved from patient records. Statistical analysis was performed using SPSS v.25.0. Results: We identified four replicable clusters of adult-onset diabetes, with significantly different patient characteristics and risk of diabetic complications. Clusters 1 and 2 were characterized by early-onset disease, higher HbA1c and insulin treatment. More than half of patients were included in cluster 3, requiring combined therapy. Cluster 4 was characterized by late-onset disease, low HbA1c and monotherapy. Cluster 1 had the highest risk of retinopathy. Conclusion:The recently proposed cluster analysis is easily replicable in real-world clinical practice and applicable to different populations, including other Portuguese settings. This new subclassification may contribute patient tailored therapy, therefore representing a first step towards precision medicine in type 2 diabetes.