Literature DB >> 27295402

Blinded sample size recalculation in clinical trials with binary composite endpoints.

Anja Sander1, Geraldine Rauch1, Meinhard Kieser1.   

Abstract

We consider clinical trials with a binary composite endpoint where the trial is successful when a significant result is achieved for the composite or one prespecified main component. Appropriate sample size planning is challenging in this situation, as in addition to the Type I error rate, power, and target difference the overall event rates and the correlation between the test statistics have to be defined. Reliable estimates of these quantities, however, are usually hard to obtain and therefore there is a high risk to not achieve the intended power in a fixed sample size design. In this article, we propose an internal pilot study design where the nuisance parameters are estimated in a blinded way at an interim stage and where the sample size is then revised accordingly. We investigate the characteristics of the proposed design with respect to the actual Type I error rate, power, and sample size. The application of this design is illustrated by a clinical trial example.

Entities:  

Keywords:  Clinical trials; composite endpoints; internal pilot study design; multiple testing; sample size recalculation

Mesh:

Year:  2016        PMID: 27295402     DOI: 10.1080/10543406.2016.1198371

Source DB:  PubMed          Journal:  J Biopharm Stat        ISSN: 1054-3406            Impact factor:   1.051


  3 in total

1.  Distribution Theory Following Blinded and Unblinded Sample Size Re-estimation under Parametric Models.

Authors:  Sergey Tarima; Nancy Flournoy
Journal:  Commun Stat Simul Comput       Date:  2019-11-22       Impact factor: 1.162

2.  Sample size estimation using a latent variable model for mixed outcome co-primary, multiple primary and composite endpoints.

Authors:  Martina E McMenamin; Jessica K Barrett; Anna Berglind; James M S Wason
Journal:  Stat Med       Date:  2022-02-23       Impact factor: 2.497

3.  Sample size recalculation based on the prevalence in a randomized test-treatment study.

Authors:  Amra Hot; Norbert Benda; Patrick M Bossuyt; Oke Gerke; Werner Vach; Antonia Zapf
Journal:  BMC Med Res Methodol       Date:  2022-07-25       Impact factor: 4.612

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.