Literature DB >> 20191595

Noninferiority trial designs for odds ratios and risk differences.

Joan F Hilton1.   

Abstract

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. 2010 John Wiley & Sons, Ltd.

Mesh:

Year:  2010        PMID: 20191595     DOI: 10.1002/sim.3846

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  4 in total

1.  The impact of covariate adjustment at randomization and analysis for binary outcomes: understanding differences between superiority and noninferiority trials.

Authors:  Katherine Nicholas; Sharon D Yeatts; Wenle Zhao; Jody Ciolino; Keith Borg; Valerie Durkalski
Journal:  Stat Med       Date:  2015-02-02       Impact factor: 2.373

2.  Non-inferiority Testing for Risk Ratio, Odds Ratio and Number Needed to Treat in Three-arm Trial.

Authors:  Shrabanti Chowdhury; Ram C Tiwari; Samiran Ghosh
Journal:  Comput Stat Data Anal       Date:  2018-09-15       Impact factor: 1.681

3.  Bayesian Approach for Assessing Non-inferiority in Three-arm Trials for Risk Ratio and Odds Ratio.

Authors:  Shrabanti Chowdhury; Ram C Tiwari; Samiran Ghosh
Journal:  Stat Biopharm Res       Date:  2019-04-22       Impact factor: 1.452

4.  Choosing and changing the analysis scale in non-inferiority trials with a binary outcome.

Authors:  Zhong Li; Matteo Quartagno; Stefan Böhringer; Nan van Geloven
Journal:  Clin Trials       Date:  2021-10-24       Impact factor: 2.486

  4 in total

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