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Noninferiority trial designs for odds ratios and risk differences.
MedLine Citation:
PMID:  20191595     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
This study presents constrained maximum likelihood derivations of the design parameters of noninferiority trials for binary outcomes with the margin defined on the odds ratio (ψ) or risk-difference (δ) scale. The derivations show that, for trials in which the group-specific response rates are equal under the point-alternative hypothesis, the common response rate, π(N), is a fixed design parameter whose value lies between the control and experimental rates hypothesized at the point-null, {π(C), π(E)}. We show that setting π(N) equal to the value of π(C) that holds under H(0) underestimates the overall sample size requirement. Given {π(C), ψ} or {π(C), δ} and the type I and II error rates, or algorithm finds clinically meaningful design values of π(N), and the corresponding minimum asymptotic sample size, N=n(E)+n(C), and optimal allocation ratio, γ=n(E)/n(C). We find that optimal allocations are increasingly imbalanced as ψ increases, with γ(ψ)<1 and γ(δ)≈1/γ(ψ), and that ranges of allocation ratios map to the minimum sample size. The latter characteristic allows trialists to consider trade-offs between optimal allocation at a smaller N and a preferred allocation at a larger N. For designs with relatively large margins (e.g. ψ>2.5), trial results that are presented on both scales will differ in power, with more power lost if the study is designed on the risk-difference scale and reported on the odds ratio scale than vice versa. Copyright © 2010 John Wiley & Sons, Ltd.
Authors:
Joan F Hilton
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Publication Detail:
Type:  Journal Article     Date:  2010-02-26
Journal Detail:
Title:  Statistics in medicine     Volume:  29     ISSN:  1097-0258     ISO Abbreviation:  Stat Med     Publication Date:  2010 Apr 
Date Detail:
Created Date:  2011-10-04     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8215016     Medline TA:  Stat Med     Country:  England    
Other Details:
Languages:  eng     Pagination:  982-93     Citation Subset:  IM    
Copyright Information:
Copyright © 2010 John Wiley & Sons, Ltd.
Affiliation:
Department of Epidemiology & Biostatistics, University of California San Francisco, 185 Berry Street, Suite 5700, San Francisco, CA 94107-1762, U.S.A.. joan@biostat.ucsf.edu.
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