Data-driven assessment, contextualisation and implementation of 134 variables in the risk for type 2 diabetes:an analysis of Lifelines, a prospective cohort study in the Netherlands
Aims/hypothesis We aimed to assess and contextualise 134 potential risk variables for the development of type 2 diabetes and to determine their applicability in risk prediction. Methods A total of 96,534 people without baseline diabetes (372,007 person-years) from the Dutch Lifelines cohort were included. We used a risk variable-wide association study (RV-WAS) design to independently screen and replicate risk variables for 5-year incidence of type 2 diabetes. For identified variables, we contextualised HRs, calculated correlations and assessed their robustness and unique contribution in differ... Mehr ...
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Dokumenttyp: | Artikel |
Erscheinungsdatum: | 2021 |
Reihe/Periodikum: | van der Meer , T P , Wolffenbuttel , B H R & Patel , C J 2021 , ' Data-driven assessment, contextualisation and implementation of 134 variables in the risk for type 2 diabetes : an analysis of Lifelines, a prospective cohort study in the Netherlands ' , Diabetologia , vol. 64 , no. 6 , pp. 1268-1278 . https://doi.org/10.1007/s00125-021-05419-1 |
Schlagwörter: | Contextualisation / Data-driven / Identification / Lasso regression / Machine learning / Prediction models / Prospective / Risk variable-wide association study / Type 2 diabetes |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-29192549 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | https://hdl.handle.net/11370/d98a8360-d3cf-47a6-8e79-8993be3a77ba |