The normative modelling framework for traumatic brain injury

This review examines the principles, applications and methodological foundations of normative modelling, emphasizing its potential to assist in mitigating longstanding challenges in traumatic brain injury (TBI) research and management. TBI remains a major global health concern, with an incidence exceeding 50-60 million cases worldwide. Progress in research and clinical practice has been hindered by the complex and heterogeneous nature of TBI, arising from diverse aetiologies, injury mechanisms and pathophysiological processes that lead to variable clinical presentations. A significant obstacle, particularly present within neuroimaging, is the continued reliance on classification scales and analytical models that do not account for nuanced differences among patients. For example, the Glasgow Coma Scale and many prevalent models categorize injury severity levels by assuming homogeneity within groups, which inevitably results in heterogeneity and obscures individual variability. Similarly, traditional case-control research designs separate injury and control groups to conduct group difference testing, diluting valuable individual data by focusing on mean comparisons. We advocate for a paradigm shift towards normative modelling-a flexible framework that assesses individual differences by comparing patients to a reference cohort. This approach moves beyond traditional methods that emphasize group differences, addressing the limitations of conventional classification by avoiding the aggregation of TBI patients into heterogeneous categories based on simplistic measures. By capturing the full spectrum of variability, normative modelling has the potential to improve patient selection in clinical trials and foster more personalized treatment strategies. Adopting this innovative approach aims to enhance outcomes for TBI patients by emphasizing individual variability rather than relying on broad group classifications. Normative modelling promises to transform the translation of TBI research into clinical practice, ultimately driving progress towards more effective, tailored interventions.

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Publication Details

Journal
Brain
Published
2025-08-08
DOI
https://doi.org/10.1093/brain/awaf296
Citations
1
Primary Topic
Trauma and Emergency Care Studies
Type
article
Field-Weighted Citation Impact
2.25

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article

The normative modelling framework for traumatic brain injury

Meng Law, David Sharp, James C. Mitchell, André F. Marquand et al.
1 citations
Brain
Trauma and Emergency Care Studies
2.25
article

The normative modelling framework for traumatic brain injury

Meng Law, David Sharp, James C. Mitchell, André F. Marquand, Cheryl L. Wellington, Gershon Spitz, Gabriela Gan, Jennie Louise Ponsford, Stuart J. McDonald, Sandy R. Shultz
article en
1 citations

Abstract

This review examines the principles, applications and methodological foundations of normative modelling, emphasizing its potential to assist in mitigating longstanding challenges in traumatic brain injury (TBI) research and management. TBI remains a major global health concern, with an incidence exceeding 50-60 million cases worldwide. Progress in research and clinical practice has been hindered by the complex and heterogeneous nature of TBI, arising from diverse aetiologies, injury mechanisms and pathophysiological processes that lead to variable clinical presentations. A significant obstacle, particularly present within neuroimaging, is the continued reliance on classification scales and analytical models that do not account for nuanced differences among patients. For example, the Glasgow Coma Scale and many prevalent models categorize injury severity levels by assuming homogeneity within groups, which inevitably results in heterogeneity and obscures individual variability. Similarly, traditional case-control research designs separate injury and control groups to conduct group difference testing, diluting valuable individual data by focusing on mean comparisons. We advocate for a paradigm shift towards normative modelling-a flexible framework that assesses individual differences by comparing patients to a reference cohort. This approach moves beyond traditional methods that emphasize group differences, addressing the limitations of conventional classification by avoiding the aggregation of TBI patients into heterogeneous categories based on simplistic measures. By capturing the full spectrum of variability, normative modelling has the potential to improve patient selection in clinical trials and foster more personalized treatment strategies. Adopting this innovative approach aims to enhance outcomes for TBI patients by emphasizing individual variability rather than relying on broad group classifications. Normative modelling promises to transform the translation of TBI research into clinical practice, ultimately driving progress towards more effective, tailored interventions.

BrainVol. 148(11)
Vancouver Coastal Health (CA), University of British Columbia (CA), Radboud University Nijmegen (NL), Wellcome Centre for Human Neuroimaging (GB), The Alfred Hospital (AU), Radboud University Medical Center (NL), Vancouver Island University (CA), UK Dementia Research Institute (GB), Alfred Health (AU), Imperial College London (GB), Monash University (AU)
Michael Smith Health Research BC
Openalex Percentile: Top 11%
Trauma and Emergency Care Studies
2.25
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