| Interim analysis of continuous long-term endpoints in clinical trials with longitudinal outcomes. | |
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MedLine Citation:
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PMID: 12754715 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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This paper discusses interim analysis for clinical trials where the primary endpoint is observed at a specific long-term follow-up time, but where repeated measures of the same outcome are also taken at earlier times. Methods are considered for improving the efficiency with which the long-term treatment difference is estimated, making use of information from shorter-term follow-up times. This approach to interim analysis has previously been studied for binary endpoints assessed at two time points during follow-up. Here we adapt and extend this methodology to include continuous endpoints assessed at an arbitrary number of follow-up times, making use of methods for analysing multivariate normal data subject to monotone missingness and unstructured mean and covariance relationships. The magnitude of efficiency gains obtained by using short-term measurements is considered, as well as how these gains depend on the number and timing of the short-term measurements. Sequential analysis of treatment differences is discussed, including the extent to which efficiency gains translate into reductions in the expected duration of a sequentially monitored trial. The methods are illustrated on a data set involving a placebo-controlled comparison of longitudinal cholesterol measurements. |
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Authors:
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Sally Galbraith; Ian C Marschner |
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Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: Statistics in medicine Volume: 22 ISSN: 0277-6715 ISO Abbreviation: Stat Med Publication Date: 2003 Jun |
Date Detail:
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Created Date: 2003-05-19 Completed Date: 2003-09-17 Revised Date: 2007-11-15 |
Medline Journal Info:
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Nlm Unique ID: 8215016 Medline TA: Stat Med Country: England |
Other Details:
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Languages: eng Pagination: 1787-805 Citation Subset: IM |
Copyright Information:
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Copyright 2003 John Wiley & Sons, Ltd. |
Affiliation:
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School of Mathematics, The University of New South Wales, NSW 2052, Australia. sallyg@maths.unsw.edu.au |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Australia Cholesterol / blood Clinical Trials as Topic / methods, statistics & numerical data* Data Interpretation, Statistical* Humans Longitudinal Studies Multivariate Analysis Outcome Assessment (Health Care)* |
| Chemical | |
Reg. No./Substance:
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57-88-5/Cholesterol |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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