Murray, G.D.

The added value of ordinal analysis in clinical trials: An example in traumatic brain injury (Article)

2011-05-17T00:00:00Z

Introduction: In 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.Methods: We 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.Results: Dichotomous 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.Conclusions: Analysis 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 (Article)

2011-03-01T00:00:00Z

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.

Early prognosis in traumatic brain injury: from prophecies to predictions (Article)

2010-05-01T00:00:00Z

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.

A simulation study evaluating approaches to the analysis of ordinal outcome data in randomized controlled trials in traumatic brain injury: Results from the IMPACT Project (Article)

2010-02-01T00:00:00Z

Background Clinical trials in traumatic brain injury have a disappointing track record, with a long history of ĝ€negative' Phase III trials. One contributor to this lack of success is almost certainly the low efficiency of the conventional approach to the analysis, which discards information by dichotomizing an ordinal outcome scale. Purpose Our goal was to evaluate the potential efficiency gains, which can be achieved by using techniques, which extract additional information from ordinal outcome data - the proportional odds model and the sliding dichotomy. In addition, we evaluated the additional efficiency gains, which can be achieved through covariate adjustment. Methods The study was based on simulations, which were built around a database of patient-level data extracted from eight Phase III trials and three observational studies in traumatic brain injury. Two different putative treatment effects were explored, one which followed the proportional odds model, and the other which assumed that the effect of the intervention was to reduce the risk of death without changing the distribution of outcomes within survivors. The results are expressed as efficiency gains, reported as the percentage reduction in sample size that can be used with the ordinal analyses without loss of statistical power relative to the conventional binary analysis. Results The simulation results show substantial efficiency gains. Use of the sliding dichotomy allows sample sizes to be reduced by up to 40% without loss of statistical power. The proportional odds model gives modest additional gains over and above the gains achieved by use of the sliding dichotomy. Limitations As with any simulation study, it is difficult to know how far the findings may be extrapolated beyond the actual situations that were modeled. Conclusions Both ordinal techniques offer substantial efficiency gains relative to the conventional binary analysis. The choice between the two techniques involves subtle value judgments. In the situations examined, the proportional odds model gave efficiency gains over and above the sliding dichotomy, but arguably, the sliding dichotomy is more intuitive and clinically appealing.

IMPACT Recommendations for Improving the Design and Analysis of Clinical Trials in Moderate to Severe Traumatic Brain Injury (Article)

2010-01-01T00:00:00Z

Clinical 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.

Baseline characteristics and statistical power in randomized controlled trials: Selection, prognostic targeting, or covariate adjustment? (Article)

2009-10-01T00:00:00Z

Objective: Heterogeneity of patients is a common problem in randomized controlled trials (RCTs) in various fields of clinical research. We aimed to investigate the potential benefits of different approaches for dealing with heterogeneity in a case study on traumatic brain injury (TBI). Design and Setting: Statistical modeling studies in three surveys and six randomized controlled trials. Patients: Individual patient data (n = 8033) from the IMPACT database. Interventions: We investigated the statistical power and efficiency of randomized controlled trials (RCTs) in relation to (1) selection according to baseline characteristics, (2) prognostic targeting (i.e., excluding those with a relatively extreme prognosis), and (3) covariate-adjusted analysis. Statistical power was expressed as the required sample size for obtaining 80% power and efficiency as the relative change in study duration, reflecting both gains in power and adverse effects on recruitment. Uniform and targeted treatment effects were simulated for 6 month unfavorable outcome. Results: For a uniform treatment effect, selection resulted in a sample size reduction of 33% in the surveys and 5% in the RCTs, but decreased recruitment by 65% and 41%, respectively. Hence, the relative study duration was prolonged (surveys: +95%; RCTs: +60%). Prognostic targeting resulted in sample size reductions of 28% and 17%, and increased relative study duration by +5% in surveys and +11% in the RCTs. Covariate adjustment reduced sample sizes by 30% and 16%, respectively, and did not affect recruitment. For a targeted treatment effect, the sample size reductions by selection (surveys: 47%; RCTs: 20%) and prognostic targeting (surveys: 49%; RCTs: 41%) were larger and adverse effects on recruitment smaller. Conclusions: The benefits of selection and prognostic targeting in terms of statistical power are reversed by adverse effects on recruitment. Covariate adjusted analysis in a broadly selected group of patients is advisable if a uniform treatment effect is assumed, since there is no decrease in recruitment.

The influence of enrollment criteria on recruitment and outcome distribution in traumatic brain injury studies: Results from the impact study (Article)

2009-07-01T00:00:00Z

Substantial heterogeneity exists among patients who suffer from traumatic brain injury (TBI). Strict enrollment criteria may diminish heterogeneity in randomized controlled trials (RCTs), but will also decrease recruitment and may affect the outcome distribution. The aim of this study was to investigate the influences of commonly used enrollment criteria for RCTs in TBI on potential recruitment and on outcome distribution. We used individual patient data from the International Mission on Prognosis and Analysis of Clinical Trials in TBI (IMPACT) database, including six therapeutic phase III RCTs (n = 5816) and three surveys (n = 2217) in TBI. The primary outcome was the Glasgow Outcome Scale (GOS) at 6 months after injury, which we dichotomized as favorable/unfavorable. We investigated the influences of commonly used enrollment criteria on recruitment and outcome distribution: time window between injury and admission to study hospital ≤ 8 h; age at injury ≤ 65 years; ≥ 1 reactive pupil; motor score > 1; Glasgow Coma Scale ≤ 8. Application of all enrollment criteria resulted in a large reduction of recruitment in both the surveys (up to 65%) and the RCTs (up to 41%). Among the remaining patients, fewer had an unfavorable outcome in both the surveys (original, 60%; remaining, 44%) and the RCTs (original, 43%; remaining, 38%). Applying these enrollment criteria to patients from the surveys resulted in an outcome distribution that approximated the outcome observed in the RCTs. The use of strict enrollment criteria leads to substantial reductions in the recruitment of RCTs in TBI. The outcome in TBI studies depends strongly on the enrollment criteria.

Predicting outcome after traumatic brain injury: development and international validation of prognostic scores based on admission characteristics (Article)

2008-08-07T00:00:00Z

BACKGROUND: 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. METHODS & FINDINGS: 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 months after injury. Prognostic models were developed in 8509 patients with severe or moderate TBI, with cross-validation by omitting each of the 11 studies in turn. External validation was on 6681 patients from the recent MRC CRASH trial. We found that the strongest predictors 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 increase approximately 0.05) by considering CT characteristics, secondary insults (hypotension, hypoxia), and laboratory parameters (glucose and hemoglobin). External validation confirmed the adequate discriminative ability (AUC 0.80). Outcomes were systematically worse than predicted, but less so in 1588 patients from high income countries in the CRASH trial. CONCLUSIONS: Prognostic models using baseline characteristics provide adequate discrimination between patients with good and poor 6 month 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 randomised controlled trials.

Classification of traumatic brain injury for targeted therapies (Article)

2008-07-01T00:00:00Z

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.

Effects of Glasgow outcome scale misclassification on traumatic brain injury clinical trials (Article)

2008-06-01T00:00:00Z

The Glasgow Outcome Scale (GOS) is the primary endpoint for efficacy analysis of clinical trials in traumatic brain injury (TBI). Accurate and consistent assessment of outcome after TBI is essential to the evaluation of treatment results, particularly in the context of multicenter studies and trials. The inconsistent measurement or interobserver variation on GOS outcome, or for that matter, on any outcome scales, may adversely affect the sensitivity to detect treatment effects in clinical trial. The objective of this study is to examine effects of nondifferential misclassification of the widely used five-category GOS outcome scale and in particular to assess the impact of this misclassification on detecting a treatment effect and statistical power. We followed two approaches. First, outcome differences were analyzed before and after correction for misclassification using a dataset of 860 patients with severe brain injury randomly sampled from two TBI trials with known differences in outcome. Second, the effects of misclassification on outcome distribution and statistical power were analyzed in simulation studies on a hypothetical 800-patient dataset. Three potential patterns of nondifferential misclassification (random, upward and downward) on the dichotomous GOS outcome were analyzed, and the power of finding treatments differences was investigated in detail. All three patterns of misclassification reduce the power of detecting the true treatment effect and therefore lead to a reduced estimation of the true efficacy. The magnitude of such influence not only depends on the size of the misclassification, but also on the magnitude of the treatment effect. In conclusion, nondifferential misclassification directly reduces the power of finding the true treatment effect. An awareness of this procedural error and methods to reduce misclassification should be incorporated in TBI clinical trials.

Importance of screening logs in clinical trials for severe traumatic brain injury (Article)

2008-06-01T00:00:00Z

OBJECTIVE: The primary intent for obtaining screening logs in a randomized clinical trial is to assess selection bias in patient recruitment. This is particularly relevant to focused trials in heterogeneous populations such as traumatic brain injury (TBI) patients. We aimed to investigate the benefits of collecting screening logs in two randomized clinical trials conducted in TBI. METHODS: Screening logs were collected as part of the conduct of two multicenter trials of neuroprotective agents in TBI: the Salzburg Atherosclerosis Prevention Program in Subjects at High Individual Risk study (n = 924) and the dexanabinol study (n = 861). Centers were requested to submit monthly information on all patients with TBI admitted to the intensive care unit, including demographics, time of injury and admission, injury severity, and, if not recruited, the reason(s) for exclusion. RESULTS: In the Salzburg Atherosclerosis Prevention Program in Subjects at High Individual Risk study, 52 centers submitted admission data on 4166 patients. In the dexanabinol trial, 96 centers submitted data on 7052 patients. On average, only 20% of patients screened for the Salzburg Atherosclerosis Prevention Program in Subjects at High Individual Risk study and 10% for the dexanabinol trial were enrolled. The main reasons for exclusion were neurological status (29 and 26%, respectively), age (24 and 30%, respectively), and admission outside of the time window (17 and 21%, respectively). Differences in patient characteristics between screened and enrolled patients, with substantial country-specific variation, were observed. CONCLUSION: The collection of screening logs is necessary to report trial results according to the Consolidated Standards of Reporting Trials guidelines and to assess the generalizability of findings. Our experience shows the feasibility of collecting screening logs and illustrates how the potential for selection bias may creep into well-designed randomized clinical trials as a result of factors outside the control of investigators. Consistency and accuracy in screening log completion may further serve as an early indicator of center performance in a trial.

A systematic review finds methodological improvements necessary for prognostic models in determining traumatic brain injury outcomes (Article)

2008-04-01T00:00:00Z

Objectives: To describe the modeling techniques used for early prediction of outcome in traumatic brain injury (TBI) and to identify aspects for potential improvements. Study Design and Setting: We reviewed key methodological aspects of studies published between 1970 and 2005 that proposed a prognostic model for the Glasgow Outcome Scale of TBI based on admission data. Results: We included 31 papers. Twenty-four were single-center studies, and 22 reported on fewer than 500 patients. The median of the number of initially considered predictors was eight, and on average five of these were selected for the prognostic model, generally including age, Glasgow Coma Score (or only motor score), and pupillary reactivity. The most common statistical technique was logistic regression with stepwise selection of predictors. Model performance was often quantified by accuracy rate rather than by more appropriate measures such as the area under the receiver-operating characteristic curve. Model validity was addressed in 15 studies, but mostly used a simple split-sample approach, and external validation was performed in only four studies. Conclusion: Although most models agree on the three most important predictors, many were developed on small sample sizes within single centers and hence lack generalizability. Modeling strategies have to be improved, and include external validation.

IMPACT database of traumatic brain injury: Design and description (Article)

2007-02-01T00:00:00Z

The objective of this report is to describe the design and content of the International Mission for Prognosis And Clinical Trial (IMPACT) database of traumatic brain injury which contains the complete dataset from most clinical trials and organized epidemiologic studies conducted over the past 20 years. This effort, funded by the U.S. National Institutes of Health, has led to the accumulation thus far of data from 9205 patients with severe and moderate brain injuries from eight randomized placebo controlled trials and three observational studies. Data relevant to the design and analysis of pragmatic Phase III clinical trials, including pre-hospital, admission, and post-resuscitation assessments, information on the acute management, and short- and long-term outcome were merged into a top priority data set (TPDS). The major emphasis during the first phase of study is on information from time of injury to post-resuscitation and outcome at 6 months thereby providing a unique resource for prognostic analysis and for studies aimed at optimizing the design and analysis of Phase III trials in traumatic brain injury.

Prognosis and clinical trial design in traumatic brain injury: The IMPACT study (Article)

2007-02-01T00:00:00Z

Traumatic brain injury (TBI) is a major health and socio-economic problem throughout the world. Many randomized controlled trials (RCTs) have been performed to investigate the effectiveness of new therapies, but none have convincingly demonstrated benefit. Clinical trials in TBI pose complex methodological challenges and meeting these requires new approaches. The challenges are related to the heterogeneity of head injuries, to optimum analysis of outcome and to aspects of the design of trials. To address these, we have created the IMPACT database on TBI through merging individual patient data from eight RCTs and three observational surveys. This database forms a culture medium in which innovative approaches to improving trial design and analysis are being explored. We hypothesize that the statistical power of TBI trials may be increased by adjusting for heterogeneity with covariate adjustment and/or prognostic targeting, by exploiting the ordinal nature of the Glasgow Outcome Scale and by relating the outcome obtained in individual patients to their baseline prognostic risk. Extensive prognostic analysis was required as a first step towards our aim of optimizing the chance of demonstrating benefit of new therapies in future trials. The fruits of this analysis are reported in detail in the subsequent reports in this issue of the Journal of Neurotrauma. The results will lead to the development and validation of new prognostic models, which will be applied to deal with heterogeneity. The findings will be synthesized into recommendations for the design and analysis of future RCTs, with the expectation of increasing the likelihood of demonstrating the benefit of a truly effective new therapy or therapeutic agent in victims of a head injury.

Prognostic value of demographic characteristics in traumatic brain injury: Results from the IMPACT study (Article)

2007-02-01T00:00:00Z

Outcome following traumatic brain injury (TBI) is not only dependent on the nature and severity of injury and subsequent treatment, but also on constituent characteristics of injured individuals. We aimed to describe and quantify the relationship between demographic characteristics and six month outcome assessed by the Glasgow Outcome Scale (GOS) after TBI. Individual patient data on age (n = 8719), gender (n = 8720), race (n = 5320), and education (n = 2201) were extracted from eight therapeutic Phase III randomized clinical trials and three surveys in moderate or severe TBI, contained in the IMPACT database. The strength of prognostic effects was analyzed with binary and proportional odds regression analysis and expressed as an odds ratio. Age was analyzed as a continuous variable with spline functions, and the odds ratio calculated over the difference between the 75thand 25thpercentiles. Associations with other predictors were explored. Increasing age was strongly related to poorer outcome (OR 2.14; 95% CI 2.00-2.28) in a continuous fashion that could be approximated by a linear function. No gender differences in outcome were found (OR: 1.01; CI 0.92-1.11), and exploratory analysis failed to show any gender/age interaction. The studies included predominantly Caucasians (83%); outcome in black patients was poorer relative to this group (OR 1.30; CI 1.09-1.56). This relationship was sustained on adjusted analyses, and requires further study into mediating factors. Higher levels of education were weakly related to a better outcome (OR: 0.70; CI 0.52-0.94). On multivariable analysis adjusting for age, motor score, and pupils, the prognostic effect of race and education were sustained. We conclude that outcome following TBI is dependent on age, race, to a lesser extent on education, but not on gender.

Prognostic value of secondary insults in traumatic brain injury: Results from the IMPACT study (Article)

2007-02-01T00:00:00Z

We determined the relationship between secondary insults (hypoxia, hypotension, and hypothermia) occurring prior to or on admission to hospital and 6-month outcome after traumatic brain injury (TBI). A meta-analysis of individual patient data, from seven Phase III randomized clinical trials (RCT) in moderate or severe TBI and three TBI population-based series, was performed to model outcome as measured by the Glasgow Outcome Scale (GOS). Proportional odds modeling was used to relate the probability of a poor outcome to hypoxia (N = 5661), hypotension (N = 6629), and hypothermia (N = 4195) separately. We additionally analyzed the combined effects of hypoxia and hypotension and performed exploratory analysis of associations with computerized tomography (CT) classification and month of injury. Having a pre-enrollment insult of hypoxia, hypotension or hypothermia is strongly associated with a poorer outcome (odds ratios of 2.1 95% CI [1.7-2.6], 2.7 95% CI [2.1-3.4], and 2.2 95% CI [1.6-3.2], respectively). Patients with both hypoxia and hypotension had poorer outcomes than those with either insult alone. Radiological signs of raised intracranial pressure (CT class III or IV) were more frequent in patients who had sustained hypoxia or hypotension. A significant association was observed between month of injury and hypothermia. The occurrence of secondary insults prior to or on admission to hospital in TBI patients is strongly related to poorer outcome and should therefore be a priority for emergency department personnel.

Prognostic value of admission laboratory parameters in traumatic brain injury: Results from the IMPACT study (Article)

2007-02-01T00:00:00Z

Abnormalities in laboratory parameters are frequent following traumatic brain injury (TBI), but few studies have investigated their predictive value. We aimed to describe and quantify the relation between laboratory parameters that are routinely determined on admission and final outcome following TBI. Individual patient data were available in the IMPACT database from six Phase III randomized controlled trials and one observational study in TBI. We studied glucose (N = 4834), sodium (N = 5270), pH (N = 3398), hemoglobin (Hb, N = 3875), platelet count (N = 1629), and prothrombin time (PT; N = 840) for their associations with outcome at 6 months (Glasgow Outcome Scale [GOS]). We used logistic regression models with linear, quadratic, and restricted cubic spline functions. The strength of the associations was expressed as an unadjusted odds ratio, calculated over the shift in outcome between the 25th and 75th percentiles. Proportional odds methodology was further applied to quantify the strength of the associations across the full range of the GOS. All parameters were consistently associated with outcome in a continuous relationship: glucose and prothrombin time showed a positive linear relation to outcome (i.e., increasing values associated with poorer outcome) and Hb, platelets., and pH an inverse linear relation (i.e., low values associated with poorer outcome). Sodium demonstrated a U-shaped relation to outcome, with low levels being more strongly related to poorer outcome. Effects were strongest for increasing levels of glucose (odds ratio 1.7; 95% CI 1.54-1.83) and decreasing levels of Hb (odds ratio 0.7; CI 0.60-0.78). Higher glucose values were associated with increasing age, but on adjusted analysis, the strength of the association with outcome remained. Whether treatment of abnormal values may improve outcome needs further rigorous study.

Prognostic value of computerized tomography scan characteristics in traumatic brain injury: Results from the IMPACT study (Article)

2007-02-01T00:00:00Z

Computerized tomography (CT) scanning provides an objective assessment of the structural damage to the brain following traumatic brain injury (TBI). We aimed to describe and quantify the relationship between CT characteristics and 6-month outcome, assessed by the Glasgow Outcome Scale (COS). Individual patient data from the IMPACT database were available on CT classification (N = 5209), status of basal cisterns (N = 3861), shift (N = 4698), traumatic subarachnoid hemorrhage (tSAH) (N = 7407), and intracranial lesions (N = 7613). We used binary logistic and proportional odds regression for prognostic analyses. The CT classification was strongly related to outcome, with worst outcome for patients with diffuse injuries in CT class III (swelling; OR 2.50; CI 2.09-3.0) or CT class IV (shift; OR 3.03; CI 2.12-4.35). The prognosis in patients with mass lesions was better for patients with an epidural hematoma (OR 0.64; CI 0.56-0.72) and poorer for an acute subdural hematoma (OR 2.14; CI 1.87-2.45). Partial obliteration of the basal cisterns (OR 2.45; CI 1.88-3.20), tSAH (OR 2.64; CI 2.42-2.89), or midline shift (1-5 mm-OR 1.36; CI 1.09-1.68); >5 mm-OR 2.20; CI 1.64-2.96) were strongly related to poorer outcome. Discrepancies were found between the scoring of basal cisterns/shift and the CT classification, indicating observer variation. These were less marked in studies that had used a central review process. Multivariable analysis indicated that individual CT characteristics added substantially to the prognostic value of the CT classification alone. We conclude that both the CT classification and individual CT characteristics are important predictors of outcome in TBI. For clinical trials, a central review process is advocated to minimize observer variability in CT assessment.

Prognostic value of admission blood pressure in traumatic brain injury: Results from the IMPACT study (Article)

2007-02-01T00:00:00Z

Hypotension following traumatic brain injury (TBI) is recognized as an important secondary insult that is associated with adverse outcome. We aimed to describe the relationship between actual levels of admission blood pressure and Glasgow Outcome Scale (GOS) at 6 months. Individual patient data from the IMPACT database were available on systolic (N = 6801) and mean arterial (N = 6647) blood pressure. Regression models with restricted cubic spline functions were used to explore the shape of the relationships between blood pressure and outcome in unadjusted and adjusted analyses. Proportional odds methodology was applied to quantify the strength of the associations across the full range of the GOS. Analyses were performed to search for threshold values. A smooth U-shaped relationship was observed between systolic (SBP) and mean arterial (MABP) blood pressures and outcome, without any evidence of an abrupt threshold effect. Best outcomes were observed for values of SBP of the order of 135 mm Hg and for values of MABP of the order of 90 mm Hg. Both lower (OR 1.53; 95% CI: 1.31-1.80) and higher levels (OA 1.42; CI: 1.20-1.68) of SBP and lower (OR 1.30; CI 1.12-1.51) and higher levels of MABP (OR 1.45; CI 1.19-1.76) were associated with poorer outcome. These findings were consistent across studies. The relationship between high blood pressure level and poorer outcome largely disappeared on adjusted analysis. Current guidelines for the management of blood pressure in TBI focus on the avoidance of hypotension as defined by SBP < 90 mm Hg. Our finding of a smooth relationship with improving outcome as SBP increases up to 135 mm Hg, while not supporting a strong causal inference, does suggest that current guidelines need to be reconsidered.

Multivariable prognostic analysis in traumatic brain injury: Results from the IMPACT study (Article)

2007-02-01T00:00:00Z

We studied the prognostic value of a wide range of conventional and novel prognostic factors on admission after traumatic brain injury (TBI) using both univariate and multivariable analysis. The outcome measure was Glasgow Outcome Scale at 6 months after injury. Individual patient data were available on a cohort of 8686 patients drawn from eight randomized controlled trials and three observational studies. The most powerful independent prognostic variables were age, Glasgow Coma Scale (GCS) motor score, pupil response, and computerized tomography (CT) characteristics, including the Marshall CT classification and traumatic subarachnoid hemorrhage. Prothrombin time was also identified as a powerful independent prognostic factor, but it was only available for a limited number of patients coming from three of the relevant studies. Other important prognostic factors included hypotension, hypoxia, the eye and verbal components of the GCS, glucose, platelets, and hemoglobin. These results on prognostic factors will underpin future work on the IMPACT project, which is focused on the development of novel approaches to the design and analysis of clinical trials in TBI. In addition, the results provide pointers to future research, including further analysis of the prognostic value of prothrombin time, and the evaluation of the clinical impact of intervening aggressively to correct abnormalities in hemoglobin, glucose, and coagulation.

Statistical approaches to the univariate prognostic analysis of the IMPACT database on traumatic brain injury (Article)

2007-02-01T00:00:00Z

The univariate prognostic analysis of the IMPACT database on traumatic brain injury (TBI) poses the formidable challenge of how best to summarize a highly complex set of data in a way which is accessible without being overly simplistic. In this paper, we describe and illustrate the battery of statistical methods that have been used. Boxplots, histograms, tabulations, and splines were used for initial data checking and in identifying appropriate transformations for more formal statistical modeling. Imputation techniques were used to minimize the problems associated with the analysis of incomplete data due to missing values. The associations between covariates and outcome (Glasgow Outcome Scale [GOS] assessed at 6 months) were expressed as odds ratios with supporting confidence intervals when the GO1S was collapsed to a dichotomous scale. This was extended to use common odds ratios from proportional odds models to express associations over the full range of the GOS. Forest plots were used to illustrate the consistency of results from study to study within the IMPACT database. The overall prognostic strength of the prognostic factors was expressed as the proportion of variance explained (Nagelkerke's R2statistic). Many of our approaches are based on simple graphical displays of the data, but, where appropriate, we have also used methods that although established in the statistical literature are relatively novel in their application to TBI.

Prognostic value of the Glasgow Coma Scale and pupil reactivity in traumatic brain injury assessed pre-hospital and on enrollment: An IMPACT analysis (Article)

2007-02-01T00:00:00Z

We studied the prognostic strength of the individual components of the Glasgow Coma Scale (GCS) and pupil reactivity to Glasgow Outcome Score (GOS) at 6 months post-injury. A total of 8721 moderate or severe traumatic brain injury (TBI) patient data from the IMPACT database on traumatic brain injury comprised the study cohort. The associations between motor score and pupil reactivity and 6-montli GOS were analyzed by binary logistic regression and proportional odds methodology. The strength of prognostic effects were expressed as the unadjusted odds ratios presented for all individual studies as well as in meta-analysis. We found a consistent strong association between motor score and 6-month GOS across all studies (OR 1.74-7.48). The Eye and Verbal components were also strongly associated with GOS. In the pooled population, one or both un-reactive pupils and lower motor scores were significantly associated with unfavorable outcome (range 2.71-7.31). We also found a significant change in motor score from pre-hospital direct to study hospital enrollment (p < 0.0001) and from the first in-hospital to study enrollment scores (p < 0.0001). Pupil reactivity was more robust between these time points. It is recommended that the study hospital enrollment GCS and pupil reactivity be used for prognostic analysis.

Prognostic value of cause of injury in traumatic brain injury: Results from the IMPACT study (Article)

2007-02-01T00:00:00Z

We aimed to describe and quantify the relationship between cause of injury and final outcome following traumatic brain injury (TBI). Individual patient data (N = 8708) from eight therapeutic Phase III randomized clinical trials in moderate or severe TBI, and three TBI surveys were used to investigate the relationship between cause of injury and outcome, as assessed by the Glasgow Outcome Scale (GOS) at 6 months. Proportional odds methodology was applied to quantify the strength of the association and expressed as an odds ratio in a meta-analysis. Heterogeneity across studies was assessed and associations with other predictive factors explored. In a univariate analysis, a strong association between the cause of injury and long-term outcome in moderate to severe TBI patients was observed, with consistent results across the studies. Road traffic accidents (OR 0.66, 95% CI 0.60-0.73), assaults (OR 0.66, 95% CI 0.52-0.84), and injuries sustained during sporting or recreational activities (OR 0.45, 95% CI 0.28-0.71) were all associated with better outcomes than the reference category of falls. Falls were found to be associated with an older age and with a higher incidence of mass lesions. Following adjustment for age in the analysis, the relationship between cause of injury and outcome was lost.

Magnesium for neuroprotection after traumatic brain injury (Article)

2007-01-01T00:00:00Z