Statistical models for outcome prediction are central to traumatic brain injury research and critical to baseline risk adjustment. Glasgow coma score (GCS) and pupil reactivity are crucial covariates in all such models but may be measured at multiple time points between the time of injury and hospital and are subject to a variable degree of unreliability and/or missingness. Imputation of missing data may be undertaken using full multiple imputation or by simple substitution of measurements from other time points. However, it is unknown which strategy is best or which time points are more predictive. We evaluated the pseudo-R2 of logistic regression models (dichotomous survival) and proportional odds models (Glasgow Outcome Score-extended) using different imputation strategies on the The Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study dataset. Substitution strategies were easy to implement, achieved low levels of missingness (<< 10%) and could outperform multiple imputation without the need for computationally costly calculations and pooling multiple final models. While model performance was sensitive to imputation strategy, this effect was small in absolute terms and clinical relevance. A strategy of using the emergency department discharge assessments and working back in time when these were missing generally performed well. Full multiple imputation had the advantage of preserving time-dependence in the models: The pre-hospital assessments were found to be relatively unreliable predictors of survival or outcome. The predictive performance of later assessments was model-dependent. In conclusion, simple substitution strategies for imputing baseline GCS and pupil response can perform well and may be a simple alternative to full multiple imputation in many cases.
|Issue number||8 August|
|Publication status||Published - 6 Aug 2021|
Bibliographical noteFunding Information:
Funding:CENTER-TBIissupportedbyThe EuropeanUnionFP7thFrameworkprogram(grant 602150)withadditionalfundingprovidedbythe HanneloreKohlFoundation(Germany),IntegraLife Sciencesandbythenon-profitorganizationOne MindForResearch(directlytoINCF).SBis currentlyfundedbyaGatesCambridgefellowship. FAZissupportedbytheUniversityofManitoba VPRIResearchInvestmentFund(RIF),Winnipeg HealthSciencesCentre(HSC)Foundation,andthe UniversityofManitobaRudyFalkClinician-Scientist Professorship.Thefundershadnoroleinstudy design,datacollectionandanalysis,decisionto publish,orpreparationofthemanuscript.
© 2021 Ercole et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.