Characterisation of type 2 diabetes subgroups and their association with ethnicity and clinical outcomes: a UK real-world data study using the East London Database

Abstract

Background: Subgroups of type 2 diabetes (T2DM) have been well characterised in experimental studies. However, it is unclear whether T2DM subgroups can be identified in UK based real-world populations and if they impact clinical outcomes. Aim: To derive T2DM subgroups using primary care data from a multi-ethnic population, evaluate associations with glycaemic control, treatment initiation and vascular outcomes, and understand how these vary by ethnicity. Design and setting: An observational cohort study in the East London Primary Care Database from 2008-2018. Method: Latent class analysis using age, sex, glycated haemoglobin, and body mass index at diagnosis was used to derive T2DM subgroups in White, South Asian, and Black groups. Time to treatment initiation and vascular outcomes was estimated using multivariable Cox-proportional hazards regression. Results: 31,931 adults with T2DM were included: 47% south Asian, 25% White, 20% Black. We replicated two previously described subgroups, "Mild Age-Related Diabetes" (MARD), "Mild Obesity-related Diabetes" (MOD), and characterised a third "Severe Hyperglycaemic Diabetes" (SHD). Compared to MARD, SHD had the poorest long term glycaemic control, fastest initiation of antidiabetic treatment (HR 2.02, 1.76-2.32), and highest risk of microvascular complications (HR 1.38, 1.28-1.49). MOD had the highest risk of macrovascular complications (HR 1.50, 1.23-1.83). Subgroup differences in treatment initiation were most pronounced for the White group, and vascular complications for the Black group. Conclusions: Clinically useful T2DM subgroups, identified at diagnosis, can be generated in routine real-world multi-ethnic populations, and may offer a pragmatic means to develop stratified primary care pathways and improve healthcare resource allocation.