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Cited by 112Statistical Methods in Clinical TrialsStatistical Methods and Bayesian InferenceStatistical Methods in Epidemiology

The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.

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

McHugh, Gillian S, Butcher, Isabella, Steyerberg, Ewout W, Marmarou, Anthony, Lu, Juan, Lingsma, Hester F, Weir, James, Maas, Andrew I R, Murray, Gordon D·2010·Clinical Trials
DOI 10.1177/1740774509356580
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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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  1. Maas AIR, 1999, Neurosurgery, 44, 1286
  2. 10.1016/S0140-6736(05)70233-6 · DOI

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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)
ORCID
Venue
Clinical Trials
Publisher
SAGE Publications
Published
2010-02
Volume
7
Issue
1
Pages
44-57
ISSN
  • 1740-7745 (ISSN-L)
  • 1740-7753
DOI
10.1177/1740774509356580
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
Licence
journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
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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