Traumatic brain injury (TBI) is a leading cause of death and disability. A reliable prediction of outcome on admission is of great clinical relevance. We aimed to develop prognostic models with readily available traditional and novel predictors.
Prospectively collected individual patient data were analyzed from 11 studies. We considered predictors available at admission in logistic regression models to predict mortality and unfavorable outcome according to the Glasgow Outcome Scale at 6 mo after injury. Prognostic models were developed in 8,509 patients with severe or moderate TBI, with cross-validation by omission of each of the 11 studies in turn. External validation was on 6,681 patients from the recent Medical Research Council Corticosteroid Randomisation after Significant Head Injury (MRC CRASH) trial. We found that the strongest predictors of outcome were age, motor score, pupillary reactivity, and CT characteristics, including the presence of traumatic subarachnoid hemorrhage. A prognostic model that combined age, motor score, and pupillary reactivity had an area under the receiver operating characteristic curve (AUC) between 0.66 and 0.84 at cross-validation. This performance could be improved (AUC increased by approximately 0.05) by considering CT characteristics, secondary insults (hypotension and hypoxia), and laboratory parameters (glucose and hemoglobin). External validation confirmed that the discriminative ability of the model was adequate (AUC 0.80). Outcomes were systematically worse than predicted, but less so in 1,588 patients who were from high-income countries in the CRASH trial.
Prognostic models using baseline characteristics provide adequate discrimination between patients with good and poor 6 mo outcomes after TBI, especially if CT and laboratory findings are considered in addition to traditional predictors. The model predictions may support clinical practice and research, including the design and analysis of randomized controlled trials.
Funding:
Grant support was provided by NIH NS 42691 of which Andrew Maas is PI. The funding organization had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; nor in the preparation, review, decision to publish, or approval of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
Academic Editor: Mervyn Singer, University College London, United Kingdom
Citation: Steyerberg EW, Mushkudiani N, Perel P, Butcher I, Lu J, et al. (2008) Predicting Outcome after Traumatic Brain Injury: Development and International Validation of Prognostic Scores Based on Admission Characteristics. PLoS Med 5(8): e165 doi:10.1371/journal.pmed.0050165
Received: November 13, 2007; Accepted: June 25, 2008; Published: August 5, 2008
Copyright: © © 2008 Steyerberg et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abbreviations: AUC, area under the receiver operating characteristic curve; CRASH, Corticosteroid Randomisation after Significant Head Injury; CT, computed tomography; EDH, epidural hematoma; GCS, Glasgow Coma Scale; GOS, Glasgow Outcome Scale; IMPACT, International Mission for Prognosis and Analysis of Clinical Trials in TBI; OR, odds ratio; RCT, randomized controlled trial; TBI, traumatic brain injury; tSAH, traumatic subarachnoid hemorrhage
* To whom correspondence should be addressed. E-mail: E.Steyerberg@ErasmusMC.nl
