The heterogeneity of traumatic brain injury (TBI) is considered one of the most significant barriers to finding effective therapeutic interventions. In October, 2007, the National Institute of Neurological Disorders and Stroke, with support from the Brain Injury Association of America, the Defense and Veterans Brain Injury Center, and the National Institute of Disability and Rehabilitation Research, convened a workshop to outline the steps needed to develop a reliable, efficient and valid classification system for TBI that could be used to link specific patterns of brain and neurovascular injury with appropriate therapeutic interventions. Currently, the Glasgow Coma Scale (GCS) is the primary selection criterion for inclusion in most TBI clinical trials. While the GCS is extremely useful in the clinical management and prognosis of TBI, it does not provide specific information about the pathophysiologic mechanisms which are responsible for neurological deficits and targeted by interventions. On the premise that brain injuries with similar pathoanatomic features are likely to share common pathophysiologic mechanisms, participants proposed that a new, multidimensional classification system should be developed for TBI clinical trials. It was agreed that preclinical models were vital in establishing pathophysiologic mechanisms relevant to specific pathoanatomic types of TBI and verifying that a given therapeutic approach improves outcome in these targeted TBI types. In a clinical trial, patients with the targeted pathoanatomic injury type would be selected using an initial diagnostic entry criterion, including their severity of injury. Coexisting brain injury types would be identified and multivariate prognostic modeling used for refinement of inclusion/exclusion criteria and patient stratification. Outcome assessment would utilize endpoints relevant to the targeted injury type. Advantages and disadvantages of currently available diagnostic, monitoring, and assessment tools were discussed. Recommendations were made for enhancing the utility of available or emerging tools in order to facilitate implementation of a pathoanatomic classification approach for clinical trials.
Traumatic brain injury (TBI) remains a major cause of death and disability. Although much has been learned about the molecular and cellular mechanisms of TBI in the past 20 years, these advances have failed to translate into a successful clinical trial, and thus there has been no significant improvement in treatment. Among the numerous barriers to finding effective interventions to improve outcomes after TBI, the heterogeneity of the injury and identification and classification of patients most likely to benefit from the treatment are considered some of the most significant challenges (Doppenberg et al., 2004; Marshall, 2000; Narayan et al., 2002).
The type of classification one develops depends on the available data and the purpose of the classification system. An etiological classification describes the factors to change in order to prevent the condition. A symptom classificationdescribes the clinical manifestation of the problem to be solved. A prognostic classification describes the factors associated with outcome, and a pathoanatomic classification describes the abnormality to be targeted by the treatment. Most diseases were originally classified on the basis of the clinical picture using a symptom-based classification system. Beginning in the 18th century, autopsies became more routine, and an increasing number of disease conditions were classified by their pathoanatomic lesions. With improvement of diagnostic tools, modern disease classification in most fields of medicine uses a mixture of anatomically, physiologically, metabolically, immunologically, and genetically defined parameters.
Currently, the primary selection criterion for inclusion in a TBI clinical trial is the Glasgow Coma Scale (GCS), a clinical scale that assesses the level of consciousness after TBI. Patients are typically divided into the broad categories of mild, moderate, and severe injury. While the GCS has proved to be extremely useful in the clinical management and prognosis of TBI, it does not provide specific information about the pathophysiologic mechanisms responsible for the neurological deficits. This is clearly demonstrated in Figure 1, in which all six patients are classified as having a severe TBI. Given the heterogeneity of the pathoanatomic features depicted in these computed tomography (CT) scans, it is difficult to see how a therapy targeted simply for severe TBI could effectively treat all of these different types of injury. Many tools such as CT scans and magnetic resonance imaging (MRI) already exist to help differentiate the multiple types of brain injury and variety of host factors and other confounders that might influence the yield of clinical trials. In addition, newer advances in neuroimaging, biomarkers, and bioinformatics may increase the effectiveness of clinical trials by helping to classify patients into groups most likely to benefit from specific treatments.