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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
Abstract
Background Clinical trials in traumatic brain injury have a disappointing track record, with a long history of '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%…
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“The IMPACT Collaboration reported that ordinal approaches were more efficient than a sliding dichotomous method in a range of trials involving participants with traumatic brain injury. 21”
From Statistical Analysis of the Primary Outcome in Acute Stroke Trials (2012) · cites this paper as [21]
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“However, when compared with ordinal analysis (based on the proportional odds model), sliding dichotomous analysis was less efficient across a number of trials involving participants with traumatic brain injury. 21”
From Statistical Analysis of the Primary Outcome in Acute Stroke Trials (2012) · cites this paper as [21]
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Metadata
- Authors
- McHugh, G. S., Butcher, I., Steyerberg, E. W., Marmarou, A., Lu, J., Lingsma, H. F., Weir, J., Maas, A. I. R., & Murray, G. D.
- Affiliations
- University of Edinburgh (GB)
- Erasmus MC (NL)
- Virginia Commonwealth University Medical Center (US)
- Department of Neurosurgery, Virginia Commonwealth University Medical Center, Richmond, VA, USA
- Antwerp University Hospital (BE)
- Venue
- Clinical Trials
- Publisher
- SAGE Publications
- Published
- 2010-02
- Volume
- 7
- Issue
- 1
- Pages
- 44-57
- ISSN
- 1740-7745 (ISSN-L)
- 1740-7753
- OpenAlex
- W2039885590
- Cited by
- 108
- References
- 23
- Citations by year
- 2026: 3 · 2025: 4 · 2024: 4 · 2023: 4 · 2022: 3 · 2021: 8 · 2020: 8 · 2019: 7 · 2018: 5 · 2017: 10 · 2016: 5 · 2015: 4 · 2014: 10 · 2013: 8 · 2012: 14
- FWCI
- 9.00
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Clinical Trials (publishedVersion)
- PubMed (publishedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
- Funders
- National Institutes of Health
- National Institute of Neurological Disorders and Stroke (R01NS042691)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Keywords
- traumatic brain injury, proportional odds model, sample size efficiency, statistical power, covariate adjustment, IMPACT project
- MeSH terms
- Brain Injuries, Computer Simulation, Humans, Statistics as Topic, Proportional Hazards Models, Randomized Controlled Trials as Topic, Treatment Outcome, Outcome Assessment, Health Care
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