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Statistical considerations when using a composite endpoint for comparing treatment groups
When comparing two treatment groups in a time‐to‐event analysis, it is common to use a composite event consisting of two or more distinct outcomes. The goal of this paper is to develop a statistical methodology to derive efficiency guidelines for deciding whether to expand a study primary endpoint f...
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Published in: | Statistics in medicine 2013-02, Vol.32 (5), p.719-738 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | When comparing two treatment groups in a time‐to‐event analysis, it is common to use a composite event consisting of two or more distinct outcomes. The goal of this paper is to develop a statistical methodology to derive efficiency guidelines for deciding whether to expand a study primary endpoint from E1 (for example, non‐fatal myocardial infarction and cardiovascular death) to the composite of E1 and E2 (for example, non‐fatal myocardial infarction, cardiovascular death or revascularisation). We investigate this problem by considering the asymptotic relative efficiency of a log‐rank test for comparing treatment groups with respect to a primary relevant endpoint E1 versus the composite primary endpoint, say E蜧, of E1 and E2, where E2 is some additional endpoint. Copyright © 2012 John Wiley & Sons, Ltd. |
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ISSN: | 0277-6715 1097-0258 |
DOI: | 10.1002/sim.5547 |