Work

Developing risk prediction models for type 2 diabetes and assessing the role of circulating metabolic biomarkers in five independent Finnish cohorts with over 22,000 individuals

Year: 2025

Type: article

Abstract: OBJECTIVES: Type 2 diabetes (T2D) is a serious public health risk. It is not well known whether large scale omics data could help improve the risk prediction. We combined the use of metabolic variables with modern model selection methods to develop risk prediction models for T2D. We then assessed the incremental improvement in model performance produced by the metabolic variables, when compared to a clinical baseline. METHODS: We used five cohorts with a total of 493 cases and 21,755 controls to develop and validate risk prediction models for T2D. We first constructed a baseline model using 15 clinical variables, and then assessed the incremental improvement provided by a set of 154 metabolic variables to the prediction, using multiple different statistical methods. Model performance was assessed in terms of discrimination and calibration in multiple validation cohorts. RESULTS: The baseline model reached area under the receiver operating characteristic curve values between 0.832 and 0.913 in the validation cohorts. On adding the metabolic measures, the highest area under the receiver operating characteristic curve values reached in the validation cohorts were between 0.840 and 0.915, a small but not clinically relevant improvement over the baseline model. Most of the constructed models were miscalibrated in the validation cohorts. CONCLUSION: The baseline model with clinical variables achieved a very good discrimination in predicting T2D. Models with metabolic variables were not able to meaningfully improve on it, as the high level set by the baseline left little room for improvement. The constructed models generalize to new independent data quite well in terms of discrimination, but relatively poorly in terms of calibration.

Source: Journal of Clinical Epidemiology

DOI: 10.1016/j.jclinepi.2025.111978

Authors: Eetu Kiviniemi, Ville Karhunen, Markus Perola, Johannes Kettunen, Mikko J. Sillanpää

Institutions: Finnish Institute for Health and Welfare, University of Oulu, University of Cambridge, MRC Biostatistics Unit, Oulu University Hospital

Language: English

Topic: Diabetes, Cardiovascular Risks, and Lipoproteins

Subfield: Endocrinology, Diabetes and Metabolism

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $4,210