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.

Implementation of risk variables in models for different clinical contexts To determine which variables predict disease risk, we assigned a score to each variable by (1) using 10-fold cross-validated lasso regression to select the optimal model as a function of the tentatively replicated variables [ 15 ], (2) assigning one point to the variables that were retained and nominally significant ( p < 0.05) and (3) bootstrapping the previous steps 100 times.

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