Section 57
Chapter 56,802

Use of ordinal outcomes in vascular prevention trials: comparison with binary outcomes in published trials

Bath, P.M.W.; Geeganage, C.; Gray, L.J.; Collier, T.; Pocock, S.

Stroke 39(10): 2817-2823


ISSN/ISBN: 0039-2499
PMID: 18669897
DOI: 10.1161/strokeaha.107.509893
Accession: 056801365

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Vascular prevention trials mostly count "yes/no" (binary) outcome events, eg, stroke/no stroke. Analysis of ordered categorical vascular events (eg, fatal stroke/nonfatal stroke/no stroke) is clinically relevant and could be more powerful statistically. Although this is not a novel idea in the statistical community, ordinal outcomes have not been applied to stroke prevention trials in the past. Summary data on stroke, myocardial infarction, combined vascular events, and bleeding were obtained by treatment group from published vascular prevention trials. Data were analyzed using 10 statistical approaches which allow comparison of 2 ordinal or binary treatment groups. The results for each statistical test for each trial were then compared using Friedman 2-way analysis of variance with multiple comparison procedures. Across 85 trials (335 305 subjects) the test results differed substantially so that approaches which used the ordinal nature of stroke events (fatal/nonfatal/no stroke) were more efficient than those which combined the data to form 2 groups (P<0.0001). The most efficient tests were bootstrapping the difference in mean rank, Mann-Whitney U test, and ordinal logistic regression; 4- and 5-level data were more efficient still. Similar findings were obtained for myocardial infarction, combined vascular outcomes, and bleeding. The findings were consistent across different types, designs and sizes of trial, and for the different types of intervention. When analyzing vascular events from prevention trials, statistical tests which use ordered categorical data are more efficient and are more likely to yield reliable results than binary tests. This approach gives additional information on treatment effects by severity of event and will allow trials to be smaller.

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