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
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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><p><strong>Results: </strong>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<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><p><strong>Conclusions/interpretation: </strong>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>","PeriodicalId":11164,"journal":{"name":"Diabetologia","volume":" ","pages":"2139-2150"},"PeriodicalIF":10.2000,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12423224/pdf/","citationCount":"0","resultStr":"{\"title\":\"Recognising, quantifying and accounting for classification uncertainty in type 2 diabetes subtypes.\",\"authors\":\"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\",\"doi\":\"10.1007/s00125-025-06486-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Aims/hypothesis: </strong>Despite continued interest in precision diagnostics and type 2 diabetes subtypes, the challenge of uncertainty in the classification of individuals into subtypes remains. 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引用次数: 0
摘要
目的/假设：尽管人们对精确诊断和2型糖尿病亚型持续感兴趣，但个体亚型分类的不确定性仍然存在。本研究介绍了一种量化和核算2型糖尿病亚型分类不确定性的新方法。方法：基于ADA/EASD糖尿病精准医学倡议的建议，我们使用归一化相对熵（NRE）来量化分类不确定性，从到聚类质心的距离计算。NRE值越低，表明个体聚类分配的不确定性越大。我们对来自前瞻性、观察性德国糖尿病研究（GDS）的859例新发2型糖尿病患者的NRE进行了研究，并将其与先前确定的糖尿病亚型进行了比较，这些亚型由年龄、BMI、HbA1c、HOMA-IR和HOMA-B定义。在考虑和不考虑分类不确定性的情况下，对这些亚型的预测10年心血管疾病风险（score2 -糖尿病）进行评估。结果：轻度年龄相关性糖尿病患者（n=395）和轻度肥胖相关性糖尿病患者（n=316）的中位NRE分别为0.155 （95% CI 0.142, 0.177）和0.119 （95% CI 0.107, 0.131）。相比之下，严重胰岛素抵抗型糖尿病（n=130）和严重胰岛素缺乏型糖尿病（n=18）患者的NRE中位数较低，分别为0.086 （95% CI 0.075, 0.108）和0.082 （95% CI 0.071, 0.109）。通过分类确定性对个体进行加权后，SCORE2-Diabetes中由亚型解释的变异比例（R2）从17.4% （95% CI 12.8, 23.0）增加到31.5% （95% CI 26.4, 37.1）。轻度年龄相关糖尿病亚型的10年CVD预测风险从10.3% （95% CI 9.8, 10.7）增加到11.6% （95% CI 11.2, 12.0）。结论/解释：NRE提供了一种量化和比较2型糖尿病亚型个体分类不确定性的方法。不同亚型和2型糖尿病患者之间的分类不确定性有所不同，考虑到这一点可以提高亚型预测10年心血管疾病风险的能力。
Recognising, quantifying and accounting for classification uncertainty in type 2 diabetes subtypes.
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.
期刊介绍：
Diabetologia, the authoritative journal dedicated to diabetes research, holds high visibility through society membership, libraries, and social media. As the official journal of the European Association for the Study of Diabetes, it is ranked in the top quartile of the 2019 JCR Impact Factors in the Endocrinology & Metabolism category. The journal boasts dedicated and expert editorial teams committed to supporting authors throughout the peer review process.
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