Literature DB >> 29298604

Clinical trials with nested subgroups: Analysis, sample size determination and internal pilot studies.

Marius Placzek1, Tim Friede1.   

Abstract

The importance of subgroup analyses has been increasing due to a growing interest in personalized medicine and targeted therapies. Considering designs with multiple nested subgroups and a continuous endpoint, we develop methods for the analysis and sample size determination. First, we consider the joint distribution of standardized test statistics that correspond to each (sub)population. We derive multivariate exact distributions where possible, providing approximations otherwise. Based on these results, we present sample size calculation procedures. Uncertainties about nuisance parameters which are needed for sample size calculations make the study prone to misspecifications. We discuss how a sample size review can be performed in order to make the study more robust. To this end, we implement an internal pilot study design where the variances and prevalences of the subgroups are reestimated in a blinded fashion and the sample size is recalculated accordingly. Simulations show that the procedures presented here do not inflate the type I error significantly and maintain the prespecified power as long as the sample size of the smallest subgroup is not too small. We pay special attention to the case of small sample sizes and attain a lower boundary for the size of the internal pilot study.

Keywords:  Subgroup analysis; adaptive design; internal pilot study; multiple testing; sample size recalculation

Mesh:

Year:  2017        PMID: 29298604     DOI: 10.1177/0962280217696116

Source DB:  PubMed          Journal:  Stat Methods Med Res        ISSN: 0962-2802            Impact factor:   3.021


  4 in total

1.  Robustness of testing procedures for confirmatory subpopulation analyses based on a continuous biomarker.

Authors:  Alexandra Christine Graf; Gernot Wassmer; Tim Friede; Roland Gerard Gera; Martin Posch
Journal:  Stat Methods Med Res       Date:  2018-06-11       Impact factor: 3.021

2.  Design and estimation in clinical trials with subpopulation selection.

Authors:  Yi-Da Chiu; Franz Koenig; Martin Posch; Thomas Jaki
Journal:  Stat Med       Date:  2018-08-07       Impact factor: 2.373

3.  Reporting of health equity considerations in cluster and individually randomized trials.

Authors:  Jennifer Petkovic; Janet Jull; Manosila Yoganathan; Omar Dewidar; Sarah Baird; Jeremy M Grimshaw; Kjell Arne Johansson; Elizabeth Kristjansson; Jessie McGowan; David Moher; Mark Petticrew; Bjarne Robberstad; Beverley Shea; Peter Tugwell; Jimmy Volmink; George A Wells; Margaret Whitehead; Luis Gabriel Cuervo; Howard White; Monica Taljaard; Vivian Welch
Journal:  Trials       Date:  2020-04-03       Impact factor: 2.279

4.  Randomized test-treatment studies with an outlook on adaptive designs.

Authors:  Werner Vach; Antonia Zapf; Amra Hot; Patrick M Bossuyt; Oke Gerke; Simone Wahl
Journal:  BMC Med Res Methodol       Date:  2021-06-01       Impact factor: 4.615

  4 in total

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