Original Article
Covariate adjustment increased power in randomized controlled trials: an example in traumatic brain injury

https://doi.org/10.1016/j.jclinepi.2011.08.012Get rights and content

Abstract

Objective

We aimed to determine to what extent covariate adjustment could affect power in a randomized controlled trial (RCT) of a heterogeneous population with traumatic brain injury (TBI).

Study Design and Setting

We analyzed 14-day mortality in 9,497 participants in the Corticosteroid Randomization After Significant Head Injury (CRASH) RCT of corticosteroid vs. placebo. Adjustment was made using logistic regression for baseline covariates of two validated risk models derived from external data (International Mission on Prognosis and Analysis of Clinical Trials in Traumatic Brain Injury [IMPACT]) and from the CRASH data. The relative sample size (RESS) measure, defined as the ratio of the sample size required by an adjusted analysis to attain the same power as the unadjusted reference analysis, was used to assess the impact of adjustment.

Results

Corticosteroid was associated with higher mortality compared with placebo (odds ratio = 1.25, 95% confidence interval = 1.13–1.39). RESS of 0.79 and 0.73 were obtained by adjustment using the IMPACT and CRASH models, respectively, which, for example, implies an increase from 80% to 88% and 91% power, respectively.

Conclusion

Moderate gains in power may be obtained using covariate adjustment from logistic regression in heterogeneous conditions such as TBI. Although analyses of RCTs might consider covariate adjustment to improve power, we caution against this approach in the planning of RCTs.

Introduction

What is new?

  • Covariate adjustment in post-hoc statistical analyses applied to the largest trial in traumatic brain injury (TBI) to date led to relative sample sizes of approximately 0.75 to attain the same power as the unadjusted reference analysis.

  • Application of the strict selection and prognostic targeting strategies previously used in TBI included approximately 25% of the study population.

  • Potential reductions in sample size can also be viewed in terms of the gain in power achievable for the same sample size. For example, a 20% reduction in sample size for a trial powered at 80% is equivalent to an increase in power to 87%.

The randomized controlled trial (RCT) is the most important tool to estimate effects of medical interventions [1]. When trials are designed to detect unrealistically large treatment effects, they are underpowered to detect more realistic moderate effects [2], [3], [4]. Traumatic brain injury (TBI) is an area where trials have frequently been underpowered [5], [6]. This is perhaps one of the reasons why current treatment guidelines do not include any class I recommendations (i.e., based on evidence from RCTs) [7]. Yet, with large numbers of deaths and high global burden of disease, treatments for TBI with even modest effects could have substantial public health benefits.

RCT populations, such as those in TBI, are typically heterogeneous in baseline characteristics and prognostic risk. More heterogeneous populations may require larger RCTs to detect differences because of treatment. Alternatively, such heterogeneity can be accounted for by the use of baseline characteristics in both the design and analysis phases of trials. In the design phase, these include the use of strict study enrolment criteria (strict selection) [8] or the selection of those with a specified level of risk of the outcome of interest (prognostic targeting) [9], [10], so that only individuals thought to gain most benefit from the treatment are enrolled in the trial. In the analysis phase, adjustment for baseline characteristics (covariate adjustment) can be used to account for differences between individuals in important prognostic factors of outcome [11], [12].

The three strategies of covariate adjustment, strict selection, and prognostic targeting were previously applied to the International Mission on Prognosis and Analysis of Clinical Trials in Traumatic Brain Injury (IMPACT) database to assess their effect on power in six trials and three surveys of TBI, containing data from 8,033 individuals [13], [14], [15]. Because no significant treatment effects were demonstrated in the constituting studies, two such effects were simulated based on the odds ratio (OR) effect measure; one equally effective in all individuals, a so-called uniform effect and the second equally effective only in individuals with risk of the outcome of 20–80%, a so-called targeted effect. Although gains in power could be obtained with each of the three strategies, the design strategies of prognostic targeting and strict selection were inefficient because of up to 60% increases in study duration. Covariate adjustment led to gains around 25% for the required sample size in an earlier simulation study using the IMPACT database [16].

We aimed to evaluate the effects of covariate adjustment and related design strategies to deal with heterogeneity in a trial with a real, rather than simulated, treatment effect. We herein analyzed data from the Corticosteroid Randomization After Significant Head Injury (CRASH) trial of corticosteroid vs. placebo in 10,008 individuals [17], with its large, heterogeneous population.

Section snippets

Patient population and known results

The CRASH, randomized placebo-controlled trial is both the largest trial in TBI to date and the only such trial to have found a significant, albeit detrimental, treatment effect [17]. CRASH examined the effect of intravenous corticosteroid on death and disability following TBI involving 239 hospitals from 49 countries. The trial, designed to recruit 20,000 individuals in total, was stopped after 10,008 individuals were randomized (5,007 corticosteroid and 5,001 placebo) because of elevated

Results

Baseline distributions of the covariates were generally well balanced between the treatment groups (Table 1). Increased age, lower (more severe) GCS, lower (more severe) GMS, and worse pupil reactivity were associated with increased mortality (Table 1). Corticosteroid was associated with 25% higher odds of 14-day mortality compared with placebo (OR = 1.25, 95% CI = 1.13–1.39). The Z-score corresponding to that OR was 4.23 from unadjusted analyses of data from all 9,497 individuals. This analysis is

Discussion

This study presents comparisons of two models for covariate adjustment to increase power in RCTs by accounting for heterogeneity between individuals. It is the first comparison in a large trial in TBI that had shown evidence of a treatment difference whereby an external risk model could be applied to real patient data. Relative reductions in sample size were observed in both cases, with a natural advantage of the CRASH risk model (RESScorr of 0.73 vs. 0.79 for the IMPACT model). Equivalently,

Acknowledgments

The authors wish to thank all CRASH collaborators for their involvement in the trial. Professor Chris Frost provided many helpful comments and advice on an earlier manuscript and the methods. Two reviewers provided helpful comments and references, which greatly improved the final version. Financial support (E.W.S.) was provided by National Institute of Health (NS-42691).

References (29)

  • A.I. Maas et al.

    Why have recent trials of neuroprotective agents in head injuries failed to show convincing efficacy? A pragmatic analysis and theoretical considerations

    Neurosurgery

    (1999)
  • Brain Trauma Foundation. Joint Project of the Brain Trauma Foundation and American Association of Neurological Surgeons (AANS), Congress of Neurological Surgeons (CNS) and AANS/CNS Joint Section on Neurotrauma and Critical Care

    Guidelines for the management of severe traumatic brain injury. 3rd ed

    J Neurotrauma

    (2007)
  • K.E. Saatman et al.

    Classification of traumatic brain injury for targeted therapies

    J Neurotrauma

    (2008)
  • S.G. Machado et al.

    Evaluation of designs for clinical trials of neuroprotective agents in head injury. European Brain Injury Consortium

    J Neurotrauma

    (1999)
  • Cited by (0)

    View full text