# Improving Patient Classification and Outcome Measurement in Traumatic Brain Injury (TBI)

> **NIH NIH R01** · MEDICAL COLLEGE OF WISCONSIN · 2021 · $606,306

## Abstract

Abstract
Traumatic brain injury (TBI) is a common injury that causes chronic symptoms and disabilities
for many patients. Unfortunately, effective treatment options to reduce TBI-related mortality and
reduce morbidity are glaringly absent. The failure of prior clinical trials of TBI is thought to be a
consequence of inadequate understanding of patient heterogeneity, lack of objective biomarkers
of TBI, and blunt approaches to outcome measurement. The proposed R01 study will use
modern quantitative modeling approaches to (a) advance understanding of patterns of patient
heterogeneity and (b) improve the efficiency of clinical outcome measurement. The study will
perform secondary analyses of data from the Transforming Research and Clinical Knowledge in
TBI (TRACK-TBI) study, which has accrued the largest prospective sample of civilian patients
with TBI to date, and will additionally collect a smaller new sample to address the aims. The
specific aims of the study are to (1) identify the optimal clinical phenotypic model of TBI across
the continuum of severity, validating the model by demonstrating that patients with distinct
patterns of acute clinical presentation differ in their levels of acute TBI blood biomarkers and (2)
use item-response theory (IRT) analyses, an extension of the modeling tools used in Aim 1, to
develop new ways measure the full spectrum of TBI-related disability with more precision than
current approaches. The study will be innovative in leveraging advanced quantitative modeling
tools proven valuable in other settings to address current methodological challenges in TBI.
Although this work will leverage the expertise and data available through TRACK-TBI, it will
bring new expertise and an innovative approach that will go beyond the work being undertaken
in any existing study. Our investigative team is uniquely suited to lead this effort given our
extensive experience applying the proposed analytic approaches to TBI, psychiatric,
Alzheimer’s, and measurement research. The findings could transform how TBI is diagnosed,
how patients are selected for clinical and translational studies, and how outcomes are
measured, to fuel the development of precision medicine treatment studies and increase the
chances of identifying effective treatments for TBI.

## Key facts

- **NIH application ID:** 10130645
- **Project number:** 5R01NS110856-03
- **Recipient organization:** MEDICAL COLLEGE OF WISCONSIN
- **Principal Investigator:** Lindsay Nelson
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $606,306
- **Award type:** 5
- **Project period:** 2019-05-15 → 2024-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10130645

## Citation

> US National Institutes of Health, RePORTER application 10130645, Improving Patient Classification and Outcome Measurement in Traumatic Brain Injury (TBI) (5R01NS110856-03). Retrieved via AI Analytics 2026-06-11 from https://api.ai-analytics.org/grant/nih/10130645. Licensed CC0.

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