Heterogeneity of diabetes and disease progression with a tree-like representation: findings from the China Cardiometabolic Disease and Cancer Cohort (4C) study
Authors' conclusion
These findings characterise the heterogeneity of diabetes phenotypes and complication risks in the Chinese population, suggesting potential implications for personalised diabetes care. Given the observed phenotypic differences, management strategies should consider population-specific characteristics.
Study context
- Population
- Chinese individuals with newly diagnosed diabetes, China Cardiometabolic Disease and Cancer Cohort (4C) study; 36.8% male, mean age 59.01 years (SD 8.63)
- Participants
- 19,612 newly diagnosed diabetes
- Outcome
- Diabetes phenotypes and risks of diabetes-related outcomes across the tree
Methodological detailsDiscriminative dimensionality reduction with trees (DDRTree) algorithm based on nine clinical variables, Cox proportional hazard and logistic regression models
- DDRTree algorithm based on nine clinical variables
- Cox proportional hazard and logistic regression models
Main finding
As reported in the abstract
- All nine clinical variables were gradient distributed across the tree
- Hyperglycaemia, obesity and dyslipidaemia: elevated risks of insulin initiation, hypoglycaemia and CKD
- Hypertension and high creatinine, total cholesterol and alanine aminotransferase: higher risk of CVD
- Social determinants and lifestyle factors further contributed to the heterogeneity
Observational data: associations, not effects.
Original publication
Heterogeneity of diabetes and disease progression with a tree-like representation: findings from the China Cardiometabolic Disease and Cancer Cohort (4C) study. Diabetologia. Published 30 August 2025. doi:10.
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