Trajectories of clinical characteristics, complications and treatment choices in data-driven subgroups of type 2 diabetes
Li, Xinyu Donnelly, Louise A Slieker, Roderick C Beulens, Joline WJ 't Hart, Leen M Elders, Petra JM Pearson, Ewan R van Giessen, Anoukh Leal, Jose Feenstra, Talitha
Li, Xinyu
Donnelly, Louise A
Slieker, Roderick C
Beulens, Joline WJ
't Hart, Leen M
Elders, Petra JM
Pearson, Ewan R
van Giessen, Anoukh
Leal, Jose
Feenstra, Talitha
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Open Access
Type
Article
Language
en
Date
2024-04-16
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Title
Trajectories of clinical characteristics, complications and treatment choices in data-driven subgroups of type 2 diabetes
Translated Title
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Diabetologia 2024; 67(7):1343-1355
Abstract
This study aimed to explore the added value of subgroups that categorise individuals with type 2 diabetes by k-means clustering for two primary care registries (the Netherlands and Scotland), inspired by Ahlqvist's novel diabetes subgroups and previously analysed by Slieker et al. METHODS: We used two Dutch and Scottish diabetes cohorts (N=3054 and 6145; median follow-up=11.2 and 12.3 years, respectively) and defined five subgroups by k-means clustering with age at baseline, BMI, HbA1c, HDL-cholesterol and C-peptide. We investigated differences between subgroups by trajectories of risk factor values (random intercept models), time to diabetes-related complications (logrank tests and Cox models) and medication patterns (multinomial logistic models). We also compared directly using the clustering indicators as predictors of progression vs the k-means discrete subgroups. Cluster consistency over follow-up was assessed.