Document Detail


Interim analysis of continuous long-term endpoints in clinical trials with longitudinal outcomes.
MedLine Citation:
PMID:  12754715     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
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.
Authors:
Sally Galbraith; Ian C Marschner
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Statistics in medicine     Volume:  22     ISSN:  0277-6715     ISO Abbreviation:  Stat Med     Publication Date:  2003 Jun 
Date Detail:
Created Date:  2003-05-19     Completed Date:  2003-09-17     Revised Date:  2007-11-15    
Medline Journal Info:
Nlm Unique ID:  8215016     Medline TA:  Stat Med     Country:  England    
Other Details:
Languages:  eng     Pagination:  1787-805     Citation Subset:  IM    
Copyright Information:
Copyright 2003 John Wiley & Sons, Ltd.
Affiliation:
School of Mathematics, The University of New South Wales, NSW 2052, Australia. sallyg@maths.unsw.edu.au
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MeSH Terms
Descriptor/Qualifier:
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:
57-88-5/Cholesterol

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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