Key result
Accounting for diabetes subtyping uncertainty increases explained 10-year CVD risk variation to ~32%.
Why the study?
Does accounting for classification uncertainty using NRE improve the prediction of 10-year CVD risk in individuals with recent-onset type 2 diabetes?
Observational (n=859)
Does accounting for classification uncertainty using NRE improve the prediction of 10-year CVD risk in individuals with recent-onset type 2 diabetes?
Answers are grounded in this paper and cite their sources.
Accounting for classification uncertainty using normalised relative entropy significantly improves the ability of type 2 diabetes subtypes to predict 10-year cardiovascular disease risk.
Aims/hypothesis Despite continued interest in precision diagnostics and type 2 diabetes subtypes, the challenge of uncertainty in the classification of individuals into subtypes remains. This study introduces a novel method for quantifying and accounting for classification uncertainty in type 2 diabetes subtypes. Methods Building on recommendations from the ADA/EASD Precision Medicine in Diabetes Initiative, we quantified classification uncertainty using the normalised relative entropy (NRE), computed from distances to cluster centroids. A lower NRE value indicates greater uncertainty in an individual’s cluster assignment. We examined the NRE in a cohort of 859 individuals with recent-onset type 2 diabetes from the prospective, observational German Diabetes Study (GDS) and compared it across previously identified diabetes subtypes, defined by age, BMI, HbA 1c , HOMA-IR and HOMA-B. Predicted 10 year CVD risk (SCORE2-Diabetes) of the subtypes was evaluated with and without accounting for classification uncertainty. Results Individuals with mild age-related diabetes ( n =395) and mild obesity-related diabetes ( n =316) had a median NRE of 0.155 (95% CI 0.142, 0.177) and 0.119 (95% CI 0.107, 0.131), respectively. By contrast, individuals with severe insulin-resistant diabetes ( n =130) and severe insulin-deficient diabetes ( n =18) had a lower median NRE of 0.086 (95% CI 0.075, 0.108) and 0.082 (95% CI 0.071, 0.109), respectively. After weighting individuals by classification certainty, the proportion of variation in SCORE2-Diabetes explained by the subtypes ( R 2 ) increased from 17.4% (95% CI 12.8, 23.0) to 31.5% (95% CI 26.4, 37.1). The predicted 10 year CVD risk of the mild age-related diabetes subtype increased from 10.3% (95% CI 9.8, 10.7) to 11.6% (95% CI 11.2, 12.0). Conclusions/interpretation The NRE provides a means to quantify and compare individual classification uncertainty in type 2 diabetes subtypes. Classification uncertainty varied between subtypes and individuals with type 2 diabetes, and accounting for it improved the ability of the subtypes to predict 10 year CVD risk.
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Mori et al. (2025) conducted an observational in recent-onset type 2 diabetes (n=859). Accounting for classification uncertainty vs. Not accounting for classification uncertainty was evaluated on Proportion of variation in SCORE2-Diabetes explained by the subtypes (R2). Accounting for classification uncertainty increased the proportion of variation in predicted 10-year CVD risk explained by diabetes subtypes from 17.4% to 31.5%.
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