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

摘要

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.