Recognising, quantifying and accounting for classification uncertainty in type 2 diabetes subtypes.

ABSTRACT:

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 c

SUBMITTER: Mori T 

PROVIDER: S-EPMC12423224 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature