Multivariable Associations Across Time Points
We next examined the biomarkers selected by LASSO within each time point, with the goal of assembling a model that leverages information across time points while minimizing the number of biomarkers involved. For the sake of parsimony, we included only the 3 most selected biomarkers from the baseline and day 4 models (we excluded day 2 biomarker concentrations from the final model as they generally performed less well than the baseline and day 4 concentrations). Because many biomarkers were highly correlated across time points, we did not include repeated measures of any biomarker. The model was adjusted for HIE severity, treatment assignment, and site.To determine whether adding the information from circulating biomarkers improved our ability to project outcomes compared with data available clinically at the time of study entry, we fit our adjusted model with the following clinical measurements: 5-minute Apgar score, lowest blood pH, highest base deficit, whether there was resuscitation after 10 minutes, and sex. To evaluate how these models performed, we calculated area under the receiver operating characteristic (ROC) curve (AUC) using repeated 10-fold cross-validation. We compared paired ROC curves using the DeLong method using the algorithm of Sun and Xu.