Background: Traumatic brain injury (TBI) remains one of the greatest unmet needs in military and civilian medicine. Recent workshops sponsored by the National Institute of Neurological Disorders and Stroke (NINDS), Defense and Veterans Brain Injury Center (DVBIC), Defense Centers of Excellence (DCOE), and National Institute on Disability and Rehabilitation (NIDRR) identified important reasons for the lack of progress that include lack of standardization in data collection and outdated approaches to TBI diagnosis and prognosis. With broad-agency support from the Department of Defense (DoD) and the National Institutes of Health (NIH), a multidisciplinary group of thought leaders proposed standards for data collection across TBI studies referred to as the TBI Common Data Elements (TBI-CDEs). In 2009, the NINDS funded a 2-year multicenter pilot study entitled "TRACK-TBI: Transforming Research and Clinical Knowledge" in TBI to validate the feasibility of the TBI-CDEs. This highly successful effort validated the feasibility of implementing the TBICDE recommendations and collected detailed clinical data on 652 subjects along with CT/MRI (computed tomography/magnetic resonance imaging) and blood biospecimens. TRACK-TBI represents the largest multivariate TBI database across the injury spectrum from concussion to coma. The TRACK-TBI II project builds on the success of TRACK-TBI and provides a unique opportunity to extensively analyze a modern highly granular cohort of TBI subjects. The results obtained from the TRACK-TBI II grant along with TRACK-TBI will advance our understanding of TBI, improve diagnostic methods for early diagnosis of TBI, and improve prognostic methods to identify individuals at risk for persistent cognitive and psychological heath disorders following TBI.
Objective/Hypotheses: The overall goal of the study is extensively analyze the existing TRACK-TBI data set to improve diagnosis, prognosis, and outcome assessment in TBI. We will test the following hypotheses:
Hypothesis 1: Highly granular patient data will improve prognosis, diagnosis, and outcome assessment in TBI.
Hypothesis 2: Neuroimaging will improve diagnosis and prognosis in TBI.
Hypothesis 3: Targeted proteomic and genomic analyses will improve diagnosis and prognosis in TBI.
Study Design: The TRACK-TBI II study will analyze the highly granular data set obtained as part of the recently completed TRACK-TBI grant with 652 subjects. It contains detailed clinical data, CT scans, and early MRIs. It also contains blood biospecimens for proteomic and genomic analyses. The comprehensive TBI-CDE outcome measures allow for analyses of biomarker association with a variety of measures. Available prognostic models will be evaluated and new prognostic models for mild TBI/concussion will be developed. A multivariate approach to outcome will be established. A diagnostic model that goes beyond the crude definitions of Mild, Moderate, and Severe TBI will be created. The rich imaging data will be analyzed using the latest methods including Quantitative CT, DTI (diffusion tensor imaging), and resting-state functional MRI. Targeted proteomic and genomic biomarkers will be examined to validate existing biomarkers and identify new biomarkers. Preliminary analysis of TRACK-TBI data has confirmed the utility and transformative potential of this rich data set.
Relevance: There is an urgent need to improve the diagnosis of TBI in military and civilian trauma. In order to do this, better diagnostic tools are needed. Two target areas for improved diagnosis emerged during the development of the TBI-CDEs: imaging and protein biomarkers. Preliminary efforts have indicated that such protein and imaging biomarkers likely exist, but they need to be validated in a large, well-defined group of TBI patients such as the TRACK-TBI cohort. The prognosis of TBI is also challenging. When an injury occurs, it is difficult to predict who can return to duty/work or who will go on to develop cognitive or psychosocial issues, especially for patients with mild TBI/concussion. The large sample size and multivariate outcome measures of TRACK-TBI provide an unmatched opportunity to have the detailed data and statistical power to improve diagnosis, prognosis, and outcome assessment in TBI. TRACK-TBI II will also further refine TBI-CDEs for the new DoD/NIH Federated Interagency TBI Research (FITBIR) database and provide new biomarkers that can be used to improve research and clinical care for military and civilian TBI patients.