Bob Roozenbeek

Changing patterns in the epidemiology of traumatic brain injury

Traumatic brain injury (TBI) is a critical public health and socio-economic problem throughout the world. Reliable quantification of the burden caused by TBI is difficult owing to inadequate standardization and incomplete capture of data on the incidence and outcome of brain injury, with variability in the definition of TBI being partly to blame. Reports show changes in epidemiological patterns of TBI: the median age of individuals who experience TBI is increasing, and falls have now surpassed road traffic incidents as the leading cause of this injury. Despite claims to the contrary, no clear decrease in TBI-related mortality or improvement of overall outcome has been observed over the past two decades. In this Perspectives article, we discuss the strengths and limitations of epidemiological studies, address the variability in its definition, and highlight changing epidemiological patterns. Taken together, these analyses identify a great need for standardized epidemiological monitoring in TBI.

Early prognosis in traumatic brain injury: from prophecies to predictions

Traumatic brain injury (TBI) is a heterogeneous condition that encompasses a broad spectrum of disorders. Outcome can be highly variable, particularly in more severely injured patients. Despite the association of many variables with outcome, prognostic predictions are notoriously difficult to make. Multivariable analysis has identified age, clinical severity, CT abnormalities, systemic insults (hypoxia and hypotension), and laboratory variables as relevant factors to include in models to predict outcome in individual patients. Advances in statistical modelling and the availability of large datasets have facilitated the development of prognostic models that have greater performance and generalisability. Two prediction models are currently available, both of which have been developed on large datasets with state-of-the-art methods, and offer new opportunities. We see great potential for their use in clinical practice, research, and policy making, as well as for assessment of the quality of health-care delivery. Continued development, refinement, and validation is advocated, together with assessment of the clinical impact of prediction models, including treatment response.

Clinical Trials in Traumatic Brain Injury: Past Experience and Current Developments

SummaryIn this article, we review past and current experience in clinical trials of traumatic brain injuries (TBIs), we discuss limitations and challenges, and we summarize current directions. The focus is on severe and moderate TBIs. A systematic literature search of the years from 1980 to 2009 revealed 27 large phase III trials in TBI; we were aware of a further 6 unpublished trials. Analysis of these 33 trials yielded interesting observations:• There was a peak incidence of trial initiations that occurred in the mid-1990s with a sharp decline during the period from 2000 to 2004.• Most trials that reported a significant treatment effect were studies on a therapeutic strategy (e.g., decompressive craniectomy, hypothermia), and these were single-center studies.• Increasingly, studies have been shifting toward the Far East. The currently existing trial registries permit insight into ongoing or recently conducted trials. Compared with the past decade, the number of studies on neuroprotective agents taken forward into efficacy-oriented studies is low. In contrast, the number of studies on therapeutic strategies appears to be increasing again.The disappointing results in trials on neuroprotective agents in TBI have led to a critical reappraisal of clinical trial methodology. This has resulted in recommendations for preclinical workup and has triggered extensive analysis on approaches to improve the design and analysis of clinical trials in TBI. An interagency initiative toward standardization on selection and coding of data elements across the broad spectrum of TBI is ongoing, and will facilitate comparison of research findings across studies and encourage high-quality meta-analysis of individual patient data in the future.

Spreading depolarisations and outcome after traumatic brain injury: a prospective observational study

BACKGROUND Pathological waves of spreading mass neuronal depolarisation arise repeatedly in injured, but potentially salvageable, grey matter in 50-60% of patients after traumatic brain injury (TBI). We aimed to ascertain whether spreading depolarisations are independently associated with unfavourable neurological outcome. METHODS We did a prospective, observational, multicentre study at seven neurological centres. We enrolled 109 adults who needed neurosurgery for acute TBI. Spreading depolarisations were monitored by electrocorticography during intensive care and were classified as cortical spreading depression (CSD) if they took place in spontaneously active cortex or as isoelectric spreading depolarisation (ISD) if they took place in isoelectric cortex. Investigators who treated patients and assessed outcome were masked to electrocorticographic results. Scores on the extended Glasgow outcome scale at 6 months were fitted to a multivariate model by ordinal regression. Prognostic score (based on variables at admission, as validated by the IMPACT studies) and spreading depolarisation category (none, CSD only, or at least one ISD) were assessed as outcome predictors. FINDINGS Six individuals were excluded because of poor-quality electrocorticography. A total of 1328 spreading depolarisations arose in 58 (56%) patients. In 38 participants, all spreading depolarisations were classified as CSD; 20 patients had at least one ISD. By multivariate analysis, both prognostic score (p=0·0009) and spreading depolarisation category (p=0·0008) were significant predictors of neurological outcome. CSD and ISD were associated with an increased risk of unfavourable outcome (common odds ratios 1·56 [95% CI 0·72-3·37] and 7·58 [2·64-21·8], respectively). Addition of depolarisation category to the regression model increased the proportion of variance in outcome that could be attributed to predictors from 9% to 22%, compared with the prognostic score alone. INTERPRETATION Spreading depolarisations were associated with unfavourable outcome, after controlling for conventional prognostic variables. The possibility that spreading depolarisations have adverse effects on the traumatically injured brain, and therefore might be a target in the treatment of TBI, deserves further research. FUNDING US Army CDMRP PH/TBI research programme.

Prediction of outcome after moderate and severe traumatic brain injury: External validation of the International Mission on Prognosis and Analysis of Clinical Trials (IMPACT) and Corticoid Randomisation After Significant Head injury (CRASH) prognostic models*

Objective: The International Mission on Prognosis and Analysis of Clinical Trials and Corticoid Randomisation After Significant Head injury prognostic models predict outcome after traumatic brain injury but have not been compared in large datasets. The objective of this is study is to validate externally and compare the International Mission on Prognosis and Analysis of Clinical Trials and Corticoid Randomisation after Significant Head injury prognostic models for prediction of outcome after moderate or severe traumatic brain injury. Design: External validation study. Patients: We considered five new datasets with a total of 9,036 patients, comprising three randomized trials and two observational series, containing prospectively collected individual traumatic brain injury patient data. Measurements and Main Results: Outcomes were mortality and unfavorable outcome, based on the Glasgow Outcome Score at 6 months after injury. To assess performance, we studied the discrimination of the models (by area under the receiver operating characteristic curves), and calibration (by comparison of the mean observed to predicted outcomes and calibration slopes). The highest discrimination was found in the Trauma Audit and Research Network trauma registry (area under the receiver operating characteristic curves between 0.83 and 0.87), and the lowest discrimination in the Pharmos trial (area under the receiver operating characteristic curves between 0.65 and 0.71). Although differences in predictor effects between development and validation populations were found (calibration slopes varying between 0.58 and 1.53), the differences in discrimination were largely explained by differences in case mix in the validation studies. Calibration was good, the fraction of observed outcomes generally agreed well with the mean predicted outcome. No meaningful differences were noted in performance between the International Mission on Prognosis and Analysis of Clinical Trials and Corticoid Randomisation After Significant Head injury models. More complex models discriminated slightly better than simpler variants. Conclusions: Since both the International Mission on Prognosis and Analysis of Clinical Trials and the Corticoid Randomisation After Significant Head injury prognostic models show good generalizability to more recent data, they are valid instruments to quantify prognosis in traumatic brain injury.

IMPACT recommendations for improving the design and analysis of clinical trials in moderate to severe traumatic brain injury

SummaryClinical trials in traumatic brain injury (TBI) pose complex methodological challenges, largely related to the heterogeneity of the population. The International Mission on Prognosis and Clinical Trial Design in TBI study group has explored approaches for dealing with this heterogeneity with the aim to optimize clinical trials in TBI. Extensive prognostic analyses and simulation studies were conducted on individual patient data from eight trials and three observational studies. Here, we integrate the results of these studies into the International Mission on Prognosis and Clinical Trial Design in TBI recommendations for design and analysis of trials in TBI:• Details of the major baseline prognostic characteristics should be provided in every report on a TBI study; in trials they should be differentiated per treatment group. We also advocate the reporting of the baseline prognostic risk as determined by validated prognostic models.• Inclusion criteria should be as broad as is compatible with the current understanding of the mechanisms of action of the intervention being evaluated. This will maximize recruitment rates and enhance the generalizability of the results.• The statistical analysis should incorporate prespecified covariate adjustment to mitigate the effects of the heterogeneity.• The statistical analysis should use an ordinal approach, based on either sliding dichotomy or proportional odds methodology. Broad inclusion criteria, prespecified covariate adjustment, and an ordinal analysis will promote an efficient trial, yielding gains in statistical efficiency of more than 40%. This corresponds to being able to detect a 7% treatment effect with the same number of patients needed to demonstrate a 10% difference with an unadjusted analysis based on the dichotomized Glasgow outcome scale.

Advancing care for traumatic brain injury: findings from the IMPACT studies and perspectives on future research

Research in traumatic brain injury (TBI) is challenging for several reasons; in particular, the heterogeneity between patients regarding causes, pathophysiology, treatment, and outcome. Advances in basic science have failed to translate into successful clinical treatments, and the evidence underpinning guideline recommendations is weak. Because clinical research has been hampered by non-standardised data collection, restricted multidisciplinary collaboration, and the lack of sensitivity of classification and efficacy analyses, multidisciplinary collaborations are now being fostered. Approaches to deal with heterogeneity have been developed by the IMPACT study group. These approaches can increase statistical power in clinical trials by up to 50% and are also relevant to other heterogeneous neurological diseases, such as stroke and subarachnoid haemorrhage. Rather than trying to limit heterogeneity, we might also be able to exploit it by analysing differences in treatment and outcome between countries and centres in comparative effectiveness research. This approach has great potential to advance care in patients with TBI.

The added value of ordinal analysis in clinical trials: an example in traumatic brain injury.

IntroductionIn clinical trials, ordinal outcome measures are often dichotomized into two categories. In traumatic brain injury (TBI) the 5-point Glasgow outcome scale (GOS) is collapsed into unfavourable versus favourable outcome. Simulation studies have shown that exploiting the ordinal nature of the GOS increases chances of detecting treatment effects. The objective of this study is to quantify the benefits of ordinal analysis in the real-life situation of a large TBI trial.MethodsWe used data from the CRASH trial that investigated the efficacy of corticosteroids in TBI patients (n = 9,554). We applied two techniques for ordinal analysis: proportional odds analysis and the sliding dichotomy approach, where the GOS is dichotomized at different cut-offs according to baseline prognostic risk. These approaches were compared to dichotomous analysis. The information density in each analysis was indicated by a Wald statistic. All analyses were adjusted for baseline characteristics.ResultsDichotomous analysis of the six-month GOS showed a non-significant treatment effect (OR = 1.09, 95% CI 0.98 to 1.21, P = 0.096). Ordinal analysis with proportional odds regression or sliding dichotomy showed highly statistically significant treatment effects (OR 1.15, 95% CI 1.06 to 1.25, P = 0.0007 and 1.19, 95% CI 1.08 to 1.30, P = 0.0002), with 2.05-fold and 2.56-fold higher information density compared to the dichotomous approach respectively.ConclusionsAnalysis of the CRASH trial data confirmed that ordinal analysis of outcome substantially increases statistical power. We expect these results to hold for other fields of critical care medicine that use ordinal outcome measures and recommend that future trials adopt ordinal analyses. This will permit detection of smaller treatment effects.

Large between-center differences in outcome after moderate and severe traumatic brain injury in the international mission on prognosis and clinical trial design in traumatic brain injury (IMPACT) study.

BACKGROUND:Differences between centers in patient outcome after traumatic brain injury are of importance for multicenter studies and have seldom been studied. OBJECTIVE:To quantify the differences in centers enrolling patients in randomized clinical trials (RCTs) and surveys. METHODS:We analyzed individual patient data from 9578 patients with moderate and severe traumatic brain injury enrolled in 10 RCTs and 3 observational studies. We used random-effects logistic regression models to estimate the between-center differences in unfavorable outcome (dead, vegetative state, or severe disability measured with the Glasgow Outcome Scale) at 6 months adjusted for differences in patient characteristics. We calculated the difference in odds of unfavorable outcome between the centers at the higher end vs those at the lower end of the outcome distribution. We analyzed the total database, Europe and the United States separately, and 4 larger RCTs. RESULTS:The 9578 patients were enrolled at 265 centers, and 4629 (48%) had an unfavorable outcome. After adjustment for patient characteristics, there was a 3.3-fold difference in the odds of unfavorable outcome between the centers at the lower end of the outcome distribution (2.5th percentile) vs those at the higher end of the outcome distribution (97.5th percentile; P < .001). In the 4 larger RCTs, the differences between centers were similar. However, differences were smaller between centers in the United States (2.4-fold) than between centers in Europe (3.8-fold). CONCLUSION:Outcome after traumatic brain injury differs substantially between centers, particularly in Europe. Further research is needed to study explanations for these differences to suggest where quality of care might be improved.

Predicting 14-Day Mortality after Severe Traumatic Brain Injury: Application of the IMPACT Models in the Brain Trauma Foundation TBI-trac® New York State Database

Prognostic models for outcome prediction in patients with traumatic brain injury (TBI) are important instruments in both clinical practice and research. To remain current a continuous process of model validation is necessary. We aimed to investigate the performance of the International Mission on Prognosis and Analysis of Clinical Trials in TBI (IMPACT) prognostic models in predicting mortality in a contemporary New York State TBI registry developed and maintained by the Brain Trauma Foundation. The Brain Trauma Foundation (BTF) TBI-trac® database contains data on 3125 patients who sustained severe TBI (Glasgow Coma Scale [GCS] score ≤ 8) in New York State between 2000 and 2009. The outcome measure was 14-day mortality. To predict 14-day mortality with admission data, we adapted the IMPACT Core and Extended models. Performance of the models was assessed by determining calibration (agreement between observed and predicted outcomes), and discrimination (separation of those patients who die from those who survive). Calibration was explored graphically with calibration plots. Discrimination was expressed by the area under the receiver operating characteristic (ROC) curve (AUC). A total of 2513 out of 3125 patients in the BTF database met the inclusion criteria. The 14-day mortality rate was 23%. The models showed excellent calibration. Mean predicted probabilities were 20% for the Core model and 24% for the Extended model. Both models showed good discrimination with AUCs of 0.79 (Core) and 0.83 (Extended). We conclude that the IMPACT models validly predict 14-day mortality in the BTF database, confirming generalizability of these models for outcome prediction in TBI patients.