Original Publication Date: >15 July, 2015
Publication / Source: Biomarkers in Medicine
Authors: Andreas Jeromin, Andrew IR Maas, Andras Buki & Stefania Mondello
Traumatic brain injury (TBI) is a major cause of death and disability and one of the greatest unmet needs in medicine and public health [1,2]. It is considered “the most complex disease of our most complex organ”, strikingly heterogeneous in terms of mechanisms, pathology, severity and treatment, with widely varying outcomes . To date, traditional, unidimensional and insensitive methods discretely categorize TBI as mild/moderate/severe giving little insight into the disease phenotype and individual specific molecular pathophysiology behind the injury. On the other hand, characterization and classification of TBI would require multidimensional approaches able to encompass the clinical reality of TBI consisting of a continuum of severity and a spectrum of pathobiological processes. Thus, there is a glaring need for more objective and informative criteria to support ‘softer’ clinical criteria and enhance the pathophysiological specificity of the diagnosis and treatment.
Drug development in TBI has also faced challenges due to the heterogeneity of the target population, inappropriateness of conventional clinically based classification of TBI, lack of mechanistic measures of efficiency and safety of the treatment, limited translational value of preclinical data to human studies and the use of variable and insensitive outcomes measures . Consequently, developing a molecular taxonomy for TBI might have a substantial value in drug development setting as well as in clinical trials, which include:
Indicating whether a TBI patient is likely to benefit from a treatment and monitoring the biochemical effects of the therapeutic interventions (‘theragnostic’ biomarkers);
Reducing diagnostic uncertainty and screening for discrete and specific disease mechanisms, enabling enrollment in clinical trials of more homogeneous patient cohorts;
Being used as a surrogate end point in a clinical trial;
Generating data regarding the pathophysiological mechanisms and describing novel molecular patterns that can represent an innovative approach for drug discovery.
Markers for reliable diagnosis, accurate classification and to track disease course are indispensable for research development and patient care.
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