Literature DB >> 26187736

A Bayesian sequential design using alpha spending function to control type I error.

Han Zhu1, Qingzhao Yu1.   

Abstract

We propose in this article a Bayesian sequential design using alpha spending functions to control the overall type I error in phase III clinical trials. We provide algorithms to calculate critical values, power, and sample sizes for the proposed design. Sensitivity analysis is implemented to check the effects from different prior distributions, and conservative priors are recommended. We compare the power and actual sample sizes of the proposed Bayesian sequential design with different alpha spending functions through simulations. We also compare the power of the proposed method with frequentist sequential design using the same alpha spending function. Simulations show that, at the same sample size, the proposed method provides larger power than the corresponding frequentist sequential design. It also has larger power than traditional Bayesian sequential design which sets equal critical values for all interim analyses. When compared with other alpha spending functions, O'Brien-Fleming alpha spending function has the largest power and is the most conservative in terms that at the same sample size, the null hypothesis is the least likely to be rejected at early stage of clinical trials. And finally, we show that adding a step of stop for futility in the Bayesian sequential design can reduce the overall type I error and reduce the actual sample sizes.

Keywords:  Alpha spending function; Bayesian clinical trial; sequential design; type I error

Mesh:

Year:  2015        PMID: 26187736     DOI: 10.1177/0962280215595058

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


  4 in total

1.  A Bayesian Sequential Design for Clinical Trials with Time-to-Event Outcomes.

Authors:  Lin Zhu; Qingzhao Yu; Donald E Mercante
Journal:  Stat Biopharm Res       Date:  2019-07-22       Impact factor: 1.452

2.  Do we need to adjust for interim analyses in a Bayesian adaptive trial design?

Authors:  Elizabeth G Ryan; Kristian Brock; Simon Gates; Daniel Slade
Journal:  BMC Med Res Methodol       Date:  2020-06-10       Impact factor: 4.615

3.  Comparison of Bayesian and frequentist group-sequential clinical trial designs.

Authors:  Nigel Stallard; Susan Todd; Elizabeth G Ryan; Simon Gates
Journal:  BMC Med Res Methodol       Date:  2020-01-07       Impact factor: 4.615

4.  Personalized Risk-Based Screening Design for Comparative Two-Arm Group Sequential Clinical Trials.

Authors:  Yeonhee Park
Journal:  J Pers Med       Date:  2022-03-12
  4 in total

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