Assessment of the performance of non-invasive risk models to predict incident type 2 diabetes in a Swedish population – Västerbotten Intervention Programme

All models required recalibration to improve prediction accuracy. The Framingham personal model is recommended for risk predictions and will be the easiest to implement.

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Publication Details

Journal
Diabetes & Metabolic Syndrome Clinical Research & Reviews
Published
2026-01-30
DOI
https://doi.org/10.1016/j.dsx.2026.103379
Citations
1
Primary Topic
Diabetes, Cardiovascular Risks, and Lipoproteins
Type
article
Field-Weighted Citation Impact
30.73
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article

Assessment of the performance of non-invasive risk models to predict incident type 2 diabetes in a Swedish population – Västerbotten Intervention Programme

Mary L. Smidt, Simon J. Griffin
1 citations
Diabetes & Metabolic Syndrome Clinical Research & Reviews
Diabetes, Cardiovascular Risks, and Lipoproteins
30.73
article

Assessment of the performance of non-invasive risk models to predict incident type 2 diabetes in a Swedish population – Västerbotten Intervention Programme

Mary L. Smidt, Simon J. Griffin
article en
1 citations

Abstract

All models required recalibration to improve prediction accuracy. The Framingham personal model is recommended for risk predictions and will be the easiest to implement.

Diabetes & Metabolic Syndrome Clinical Research & ReviewsVol. 20(2)
Cambridge School (PT), MRC Epidemiology Unit (GB), Umeå University (SE)
Openalex Percentile: Top 1%
Diabetes, Cardiovascular Risks, and Lipoproteins
30.73
DOIOpen Access PDFOpenAlex
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