, Volume 7, Issue 1, pp 127–134 | Cite as

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

  • Andrew I. R. MaasEmail author
  • Ewout W. Steyerberg
  • Anthony Marmarou
  • Gillian S. McHugh
  • Hester F. Lingsma
  • Isabella Butcher
  • Juan Lu
  • James Weir
  • Bob Roozenbeek
  • Gordon D. Murray
Review Article


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.

Key Words

Traumatic brain injury clinical trials study design sliding dichotomy covariate adjustment prognosis 


  1. 1.
    Maas AIR, Roozenbeek B, Manley GT. Clinical trials in traumatic brain injury: past experience and current development. Neurotherapeutics 2010;7: 115–126.PubMedCrossRefGoogle Scholar
  2. 2.
    Maas AIR, Marmarou A, Murray GD, Teasdale GM, Steyerberg EW. Prognosis and clinical trial design in traumatic brain injury: The IMPACT Study. J Neurotrauma 2007;24: 232–238.PubMedCrossRefGoogle Scholar
  3. 3.
    Marmarou A, Lu J, Butcher I, et al. IMPACT database of traumatic brain injury: design and description. J Neurotrauma 2007;24: 239–250.PubMedCrossRefGoogle Scholar
  4. 4.
    Hernandez AV, Steyerberg EW, Butcher I, et al. Adjustment for strong predictors of outcome in traumatic brain injury trials: 25% reduction in sample size requirements in the IMPACT Study. J Neurotrauma 2006;23: 1295–1303.PubMedCrossRefGoogle Scholar
  5. 5.
    Murray GD, Barer D, Choi S, et al. Design and analysis of phase III trials with ordered outcome scales—the concept of the sliding dichotomy. J Neurotrauma 2005;22: 511–517.PubMedCrossRefGoogle Scholar
  6. 6.
    Roozenbeek B, Maas AI, Lingsma HF, et al. Baseline characteristics and statistical power in randomized controlled trials: selection, prognostic targeting, or covariate adjustment? Crit Care Med 2009;37: 2683–2690.PubMedCrossRefGoogle Scholar
  7. 7.
    Lu J, Murray GD, Steyerberg EW, et al. Effects of glasgow outcome scale misclassification on traumatic brain injury clinical trials. J Neurotrauma 2008;25: 641–651.PubMedCrossRefGoogle Scholar
  8. 8.
    Knoller N, Levi L, Shoshan I, et al. Dexanabinol (HU-211) in the treatment of severe closed head injury: a randomized, placebo-controlled, phase II clinical trial. Crit Care Med 2002;30: 548–554.PubMedCrossRefGoogle Scholar
  9. 9.
    McHugh GS, Butcher I, Steyerberg EW, et al. Statistical approaches to the univariate prognostic analysis of the IMPACT database on traumatic brain injury. J Neurotrauma 2007;24: 251–258.PubMedCrossRefGoogle Scholar
  10. 10.
    Mushkudiani NA, Engel DC, Steyerberg EW, et al. Prognostic value of demographic characteristics in traumatic brain injury: results from the IMPACT study. J Neurotrauma 2007;24: 259–269.PubMedCrossRefGoogle Scholar
  11. 11.
    Marmarou A, Lu J, Butcher I, et al. Prognostic value of the Glasgow coma scale and pupil reactivity in traumatic brain injury assessed pre-hospital and on enrollment: an IMPACT analysis. J Neurotrauma 2007;24: 270–280.PubMedCrossRefGoogle Scholar
  12. 12.
    Butcher I, Maas AI, Lu J, et al. Prognostic value of admission blood pressure in traumatic brain injury: results from the IMPACT study. J Neurotrauma 2007;24: 294–302.PubMedCrossRefGoogle Scholar
  13. 13.
    McHugh GS, Engel DC, Butcher I, et al. Prognostic value of secondary insults in traumatic brain injury: results from the IMPACT study. J Neurotrauma 2007;24: 287–293.PubMedCrossRefGoogle Scholar
  14. 14.
    Butcher I, McHugh GS, Lu J, et al. Prognostic value of cause of injury in traumatic brain injury: results from the IMPACT study. J Neurotrauma 2007;24: 281–286.PubMedCrossRefGoogle Scholar
  15. 15.
    Maas AI, Steyerberg EW, Butcher I, et al. Prognostic value of computerized tomography scan characteristics in traumatic brain injury: results from the IMPACT study. J Neurotrauma 2007;24: 303–314.PubMedCrossRefGoogle Scholar
  16. 16.
    Van Beek JG, Mushkudiani NA, Steyerberg EW, et al. Prognostic value of admission laboratory parameters in traumatic brain injury: results from the IMPACT study. J Neurotrauma 2007;24: 315–328.PubMedCrossRefGoogle Scholar
  17. 17.
    Murray GD, Butcher I, McHugh GS, et al. Multivariable prognostic analysis in traumatic brain injury: results from the IMPACT Study. J Neurotrauma 2007;24: 329–337.PubMedCrossRefGoogle Scholar
  18. 18.
    Steyerberg EW, Mushkudiani N, Perel P, et al. Predicting outcome after traumatic brain injury: development and international validation of prognostic scores based on admission characteristics. PLoS Med 2008;5: e165.PubMedCrossRefGoogle Scholar
  19. 19.
    Perel P, Edwards P, Wentz R, Roberts I. Systematic review of prognostic models in traumatic brain injury. BMC Med Inform Decis Mak 2006;6: 38.PubMedCrossRefGoogle Scholar
  20. 20.
    Mushkudiani NA, Hukkelhoven CW, Hernandez AV, et al. A systematic review finds methodological improvements necessary for prognostic models in determining traumatic brain injury outcomes. J Clin Epidemiol 2008;61: 331–343.PubMedCrossRefGoogle Scholar
  21. 21.
    MRC CRASH Trial Collaborators, Perel P, Arango M, Clayton T, et al. Predicting outcome after traumatic brain injury: practical prognostic models based on large cohort of international patients. BMJ 2008;336: 425–429.PubMedCrossRefGoogle Scholar
  22. 22.
    Machado SG, Murray GD, Teasdale GM. Evaluation of designs for clinical trials of neuroprotective agents in head injury. J Neurotrauma 1999;16: 1131–1138.PubMedCrossRefGoogle Scholar
  23. 23.
    Steyerberg EW, Bossuyt PM, Lee KL. Clinical trials in acute myocardial infarction: should we adjust for baseline characteristics? Am Heart J 2000; 139: 745–751.PubMedCrossRefGoogle Scholar
  24. 24.
    Altman DG, Royston P. The cost of dichotomising continuous variables. BMJ 2006;332: 1080.PubMedCrossRefGoogle Scholar
  25. 25.
    Saver JL. Novel end point analytical techniques and interpreting shifts across the entire range of outcome scales in acute stroke trials. Stroke 2007;38: 3055–3062.PubMedCrossRefGoogle Scholar
  26. 26.
    Mendelow AD, Gregson BA, Femandes HM, et al. for the STICH investigators. Early surgery versus initial conservative treatment in patients with spontaneous supratentorial intracerebral haematomas in the International Surgical Trial in Intracerebral Haemorrhage (STICH): a randomised trial. Lancet 2005;365: 387–397.PubMedGoogle Scholar
  27. 27.
    Maas AI, Murray G, Henney H III, et al. Efficacy and safety of dexanabinol in severe traumatic brain injury: results of a phase III randomised, placebo-controlled, clinical trial. Lancet Neurology 2006;5: 38–45.PubMedCrossRefGoogle Scholar
  28. 28.
    Steyerberg EW, Borsboom GJ, van Houwelingen HC, Eijkemans MJ, Habbema JD. Validation and updating of predictive logistic regression models: a study on sample size and shrinkage. Stat Med 2004;23: 2567–2586.PubMedCrossRefGoogle Scholar
  29. 29.
    Saatman KE, Duhaime AC, Bullock R, Maas AI, Valadka A, Manley GT. Classification of traumatic brain injury for targeted therapies. J Neurotrauma 2008;25: 719–738.PubMedCrossRefGoogle Scholar
  30. 30.
    Choi SC, Clifton GL, Marmarou A, Miller ER. Misclassification and treatment effect on primary outcome measures in clinical trials of severe neurotrauma. J Neurotrauma 2002;19: 17–22.PubMedCrossRefGoogle Scholar
  31. 31.
    Wilson JT, Slieker FJ, Legrand V, Murray G, Stocchetti N, Maas AI. Observer variation in the assessment of outcome in traumatic brain injury: experience from a multicenter, international randomized clinical trial. Neurosurgery 2007;61: 123–129.PubMedCrossRefGoogle Scholar

Copyright information

© Springer New York 2010

Authors and Affiliations

  • Andrew I. R. Maas
    • 1
    Email author
  • Ewout W. Steyerberg
    • 2
  • Anthony Marmarou
    • 3
  • Gillian S. McHugh
    • 4
  • Hester F. Lingsma
    • 2
  • Isabella Butcher
    • 4
  • Juan Lu
    • 3
  • James Weir
    • 4
  • Bob Roozenbeek
    • 1
  • Gordon D. Murray
    • 4
  1. 1.Department of NeurosurgeryUniversity Hospital AntwerpEdegemBelgium
  2. 2.Center for Medical Decision Making, Department of Public HealthErasmus MC, University Medical CenterRotterdamThe Netherlands
  3. 3.Department of NeurosurgeryVirginia Commonwealth University Medical CenterRichmond
  4. 4.Public Health Sciences, Centre for Population Health SciencesUniversity of Edinburgh Medical SchoolEdinburghUK

Personalised recommendations