Literature DB >> 24979706

Assessing additional benefit in noninferiority trials.

Meinhard Kieser1, Kathrin Stucke1.   

Abstract

A method for simultaneously assessing noninferiority with respect to efficacy and superiority with respect to another endpoint in two-arm noninferiority trials is presented. The procedure controls both the average type I error rate for the intersection-union test problem and the frequentist type I error rate for the noninferiority test by α while allowing an increased level for the superiority test. For normally distributed outcomes, two methods are presented to deal with the uncertainty about the correlation between the endpoints which defines the adjusted levels. The operating characteristics of these procedures are investigated. Furthermore, the sample size required when applying the proposed method is compared with that of alternative procedures. Application of the method in the situation of binary endpoints and mixed normal and binary endpoints, respectively, is sketched. An illustrative example is provided demonstrating implementation of the proposed approach in a clinical trial.
© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Keywords:  Additional benefit; Average type I error rate; Coprimary endpoints; Multiplicity; Noninferiority trials

Mesh:

Year:  2014        PMID: 24979706     DOI: 10.1002/bimj.201300227

Source DB:  PubMed          Journal:  Biom J        ISSN: 0323-3847            Impact factor:   2.207


  3 in total

1.  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

2.  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

3.  New approaches for testing non-inferiority for three-arm trials with Poisson distributed outcomes.

Authors:  Samiran Ghosh; Erina Paul; Shrabanti Chowdhury; Ram C Tiwari
Journal:  Biostatistics       Date:  2022-01-13       Impact factor: 5.899

  3 in total

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