ArticleThe Journal of clinical endocrinology and metabolism2021
A Panel of 6 Biomarkers Significantly Improves the Prediction of Type 2 Diabetes in the MONICA/KORA Study Population.
Article in The Journal of clinical endocrinology and metabolism, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- [Biobanking in internal medicine : Structures, opportunities and cultural responsibility].Innere Medizin (Heidelberg, Germany) · 2026Article
- Hierarchical random forest model, inflammation and oxidative stress as predictors of the atherogenic index of plasma and diabetes progression.Scientific reports · 2025Article
- Omics Approach for Personalised Prevention of Type 2 Diabetes Mellitus for African and European Populations (OPTIMA): a protocol paper.BMJ open · 2025Article
- Longitudinal metabolite and protein trajectories prior to diabetes mellitus diagnosis in Danish blood donors: a nested case-control study.Diabetologia · 2024Article
- Association of plasma proteomics with mortality in individuals with and without type 2 diabetes: Results from two population-based KORA cohort studies.BMC medicine · 2024Article
- Multi-omics analysis of diabetic pig lungs reveals molecular derangements underlying pulmonary complications of diabetes mellitus.Disease models & mechanisms · 2024Article
- Air pollution, traffic noise, greenness, and temperature and the risk of incident type 2 diabetes: Results from the KORA cohort study.Environmental epidemiology (Philadelphia, Pa.) · 2024Article
- Associations of plasma proteomics with type 2 diabetes and related traits: results from the longitudinal KORA S4/F4/FF4 Study.Diabetologia · 2023Article
- Development of a 5-year risk prediction model for type 2 diabetes in individuals with incident HbA1c-defined pre-diabetes in Denmark.BMJ open diabetes research & care · 2022Article
- Adiponectin, IGFBP-1 and -2 are independent predictors in forecasting prediabetes and type 2 diabetes.Frontiers in endocrinology · 2022Article
- A Panel of 6 Biomarkers Significantly Improves the Prediction of Type 2 Diabetes in the MONICA/KORA Study Population.The Journal of clinical endocrinology and metabolism · 2021Article
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15 authors.
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Abstract
contextImproved strategies to identify persons at high risk of type 2 diabetes are important to target costly preventive efforts to those who will benefit most.
objectiveThis work aimed to assess whether novel biomarkers improve the prediction of type 2 diabetes beyond noninvasive standard clinical risk factors alone or in combination with glycated hemoglobin A1c (HbA1c).
methodsWe used a population-based case-cohort study for discovery (689 incident cases and 1850 noncases) and an independent cohort study (262 incident cases, 2549 noncases) for validation. An L1-penalized (lasso) Cox model was used to select the most predictive set among 47 serum biomarkers from multiple etiological pathways. All variables available from the noninvasive German Diabetes Risk Score (GDRSadapted) were forced into the models. The C index and the category-free net reclassification index (cfNRI) were used to evaluate the predictive performance of the selected biomarkers beyond the GDRSadapted model (plus HbA1c).
resultsInterleukin-1 receptor antagonist, insulin-like growth factor binding protein 2, soluble E-selectin, decorin, adiponectin, and high-density lipoprotein cholesterol were selected as the most relevant biomarkers. The simultaneous addition of these 6 biomarkers significantly improved the predictive performance both in the discovery (C index [95% CI], 0.053 [0.039-0.066]; cfNRI [95% CI], 67.4% [57.3%-79.5%]) and the validation study (0.034 [0.019-0.053]; 48.4% [35.6%-60.8%]). Significant improvements by these biomarkers were also seen on top of the GDRSadapted model plus HbA1c in both studies.
conclusionThe addition of 6 biomarkers significantly improved the prediction of type 2 diabetes when added to a noninvasive clinical model or to a clinical model plus HbA1c.
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