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Calculation of sample size for stroke trials assessing functional outcome: comparison of binary and ordinal approaches

Optimising Analysis of Stroke Trials (OAST) Collaboration. (2008) Calculation of sample size for stroke trials assessing functional outcome: comparison of binary and ordinal approaches. International Journal of Stroke. 3(2), pp. 78-84. 1747-4949.

Item Type: Article
Abstract: Background: Many acute stroke trials have given neutral results. Sub-optimal statistical analyses may be failing to detect efficacy. Methods which take account of the ordinal nature of functional outcome data are more efficient. We compare sample size calculations for dichotomous and ordinal outcomes for use in stroke trials. Methods Data from stroke trials studying the effects of interventions known to positively or negatively alter functional outcome – Rankin Scale and Barthel Index – were assessed. Sample size was calculated using comparisons of proportions, means, medians (according to Payne), and ordinal data (according to Whitehead). The sample sizes gained from each method were compared using Friedman 2 way ANOVA. Results Fifty-five comparisons (54 173 patients) of active vs. control treatment were assessed. Estimated sample sizes differed significantly depending on the method of calculation (P<0·0001). The ordering of the methods showed that the ordinal method of Whitehead and comparison of means produced significantly lower sample sizes than the other methods. The ordinal data method on average reduced sample size by 28% (inter-quartile range 14–53%) compared with the comparison of proportions; however, a 22% increase in sample size was seen with the ordinal method for trials assessing thrombolysis. The comparison of medians method of Payne gave the largest sample sizes. Conclusions Choosing an ordinal rather than binary method of analysis allows most trials to be, on average, smaller by approximately 28% for a given statistical power. Smaller trial sample sizes may help by reducing time to completion, complexity, and financial expense. However, ordinal methods may not be optimal for interventions which both improve functional outcome and cause hazard in a subset of patients, e.g. thrombolysis
Uncontrolled Keywords: power, randomised controlled trial, sample size, statistical analysis, stroke
Subjects: R Medicine > RC Internal medicine > RC388.5 Cerebrovascular diseases. Stroke
Corporate Creators: Optimising Analysis of Stroke Trials (OAST) Collaboration
Publisher: Wiley Interscience
Faculties, Divisions and Institutes: University Faculties, Divisions and Research Centres - OLD > Faculty of Health & Society > Occupational Therapy
Faculties > Faculty of Health & Society > Occupational Therapy
Date: May 2008
Date Type: Publication
Page Range: pp. 78-84
Journal or Publication Title: International Journal of Stroke
Volume: 3
Number: 2
Language: English
ISSN: 1747-4949
Status: Published / Disseminated
Refereed: Yes
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