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Aims/hypothesis <p>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.</p> Methods <p>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<sub>1c</sub>, HOMA-IR and HOMA-B. Predicted 10 year CVD risk (SCORE2-Diabetes) of the subtypes was evaluated with and without accounting for classification uncertainty.</p> Results <p>Individuals with mild age-related diabetes (<i>n</i>=395) and mild obesity-related diabetes (<i>n</i>=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 (<i>n</i>=130) and severe insulin-deficient diabetes (<i>n</i>=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 (<i>R</i><sup>2</sup>) 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).</p> Conclusions/interpretation <p>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.</p> Graphical Abstract <p></p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月25日

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  • Tim Mori,
  • Oana P. Zaharia,
  • Klaus Straßburger,
  • John M. Dennis,
  • Knut Mai,
  • Stefan Kabisch,
  • Stefan Bornstein,
  • Julia Szendroedi,
  • Matthias Blüher,
  • Svenja Meyhöfer,
  • Jochen Seissler,
  • Andreas Birkenfeld,
  • Norbert Stefan,
  • Michael Roden,
  • Robert Wagner,
  • Oliver Kuß,
  • Hadi Al-Hasani,
  • Bengt Frederik Belgardt,
  • Gidon J. Bönhof,
  • Gerd Geerling,
  • Christian Herder,
  • Andrea Icks,
  • Karin Jandeleit-Dahm,
  • Jorg Kotzka,
  • Eckhard Lammert,
  • Wolfgang Rathmann,
  • Sabrina Schlesinger,
  • Vera Schrauwen-Hinderling,
  • Sandra Trenkamp

摘要

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, HbA1c, 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 (R2) 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.

Graphical Abstract