↓ Skip to main content

PLOS

Designing and Analyzing Clinical Trials with Composite Outcomes: Consideration of Possible Treatment Differences between the Individual Outcomes

Overview of attention for article published in PLOS ONE, April 2012
Altmetric Badge

Citations

dimensions_citation
39 Dimensions

Readers on

mendeley
49 Mendeley
citeulike
1 CiteULike
Title
Designing and Analyzing Clinical Trials with Composite Outcomes: Consideration of Possible Treatment Differences between the Individual Outcomes
Published in
PLOS ONE, April 2012
DOI 10.1371/journal.pone.0034785
Pubmed ID
Authors

Janice Pogue, P. J. Devereaux, Lehana Thabane, Salim Yusuf

Abstract

When the individual outcomes within a composite outcome appear to have different treatment effects, either in magnitude or direction, researchers may question the validity or appropriateness of using this composite outcome as a basis for measuring overall treatment effect in a randomized controlled trial. The question remains as to how to distinguish random variation in estimated treatment effects from important heterogeneity within a composite outcome. This paper suggests there may be some utility in directly testing the assumption of homogeneity of treatment effect across the individual outcomes within a composite outcome. We describe a treatment heterogeneity test for composite outcomes based on a class of models used for the analysis of correlated data arising from the measurement of multiple outcomes for the same individuals. Such a test may be useful in planning a trial with a primary composite outcome and at trial end with final analysis and presentation. We demonstrate how to determine the statistical power to detect composite outcome treatment heterogeneity using the POISE Trial data. Then we describe how this test may be incorporated into a presentation of trial results with composite outcomes. We conclude that it may be informative for trialists to assess the consistency of treatment effects across the individual outcomes within a composite outcome using a formalized methodology and the suggested test represents one option.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 2%
Hungary 1 2%
France 1 2%
Unknown 46 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 29%
Student > Ph. D. Student 7 14%
Student > Master 6 12%
Student > Postgraduate 4 8%
Professor > Associate Professor 4 8%
Other 10 20%
Unknown 4 8%
Readers by discipline Count As %
Medicine and Dentistry 25 51%
Mathematics 3 6%
Agricultural and Biological Sciences 3 6%
Pharmacology, Toxicology and Pharmaceutical Science 2 4%
Biochemistry, Genetics and Molecular Biology 2 4%
Other 8 16%
Unknown 6 12%