Document Detail

How to deal with multiple treatment or dose groups in randomized clinical trials?
MedLine Citation:
PMID:  17391286     Owner:  NLM     Status:  MEDLINE    
Multiplicity adjustment in general is currently a controversial topic. This review focuses on the proof of efficacy in randomized clinical trials. The ICH guidelines mandate control of the familywise error rate. Confidence intervals are clinically more appropriate than P-values or yes/no decisions. Therefore, simultaneous confidence intervals are proposed for several designs and aims in clinical trials. The computation of simultaneous confidence intervals for the difference or the ratio is demonstrated by means of real data examples using the R-packages multcomp and mratios. A special problem is the evaluation of dose-finding trials with and without the assumption that the effects increase with increasing doses. Simultaneous intervals are presented not only for one-way layouts and normal distributed endpoints, but also for higher way layouts, generalized linear models, and mixed models. Under importance ordering, the conditional testing of all hypotheses at level alpha will be shown using the intersection-union test principle. Other multiplicity issues (i.e. multiple endpoints, multiple analyses, and subgroup analyses) are discussed.
L A Hothorn
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Publication Detail:
Type:  Journal Article; Review    
Journal Detail:
Title:  Fundamental & clinical pharmacology     Volume:  21     ISSN:  0767-3981     ISO Abbreviation:  Fundam Clin Pharmacol     Publication Date:  2007 Apr 
Date Detail:
Created Date:  2007-03-29     Completed Date:  2007-06-05     Revised Date:  2007-11-15    
Medline Journal Info:
Nlm Unique ID:  8710411     Medline TA:  Fundam Clin Pharmacol     Country:  England    
Other Details:
Languages:  eng     Pagination:  137-54     Citation Subset:  IM    
Institute of Biostatistics, Leibniz University of Hannover, Herrenhaeuser Str. 2, D-30419 Hannover, Germany.
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MeSH Terms
Clinical Protocols
Confidence Intervals
Control Groups
Data Interpretation, Statistical*
Dose-Response Relationship, Drug
Models, Statistical*
Randomized Controlled Trials as Topic / methods,  statistics & numerical data*
Research Design
Comment In:
Fundam Clin Pharmacol. 2007 Apr;21(2):155-6   [PMID:  17391287 ]

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

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