Literature DB >> 20876163

Group sequential trials revisited: simple implementation using SAS.

John Whitehead1.   

Abstract

The methodology of group sequential trials is now well established and widely implemented. The benefits of the group sequential approach are generally acknowledged, and its use, when applied properly, is accepted by researchers and regulators. This article describes how a wide range of group sequential designs can easily be implemented using two accessible SAS functions. One of these, PROBBNRM is a standard function, while the other, SEQ, is part of the interactive matrix language of SAS, PROC IML. The account focuses on the essentials of the approach and reveals how straightforward it can be. The design of studies is described, including their evaluation in terms of the distribution of final sample size. The conduct of the interim analyses is discussed, with emphasis on the consequences of inevitable departures from the planned schedule of information accrual. The computations required for the final analysis, allowing for the sequential design, are closely related to those conducted at the design stage. Illustrative examples are given and listings of suitable of SAS code are provided.

Mesh:

Year:  2010        PMID: 20876163     DOI: 10.1177/0962280210379036

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


  8 in total

1.  To compare the efficacy of two kinds of Zhizhu pills in the treatment of functional dyspepsia of spleen-deficiency and qi-stagnation syndrome: a randomized group sequential comparative trial.

Authors:  Hongli Wu; Zhiwei Jing; Xudong Tang; Xinyue Wang; Shengsheng Zhang; Yanan Yu; Zhong Wang; Hongxin Cao; Luqi Huang; Youhua Yu; Yongyan Wang
Journal:  BMC Gastroenterol       Date:  2011-07-15       Impact factor: 3.067

2.  Evaluating clinical trial designs for investigational treatments of Ebola virus disease.

Authors:  Ben S Cooper; Maciej F Boni; Wirichada Pan-ngum; Nicholas P J Day; Peter W Horby; Piero Olliaro; Trudie Lang; Nicholas J White; Lisa J White; John Whitehead
Journal:  PLoS Med       Date:  2015-04-14       Impact factor: 11.069

3.  Correction: GOST: A generic ordinal sequential trial design for a treatment trial in an emerging pandemic.

Authors:  John Whitehead; Peter Horby
Journal:  PLoS Negl Trop Dis       Date:  2018-04-13

4.  GOST: A generic ordinal sequential trial design for a treatment trial in an emerging pandemic.

Authors:  John Whitehead; Peter Horby
Journal:  PLoS Negl Trop Dis       Date:  2017-03-09

5.  Generalizing boundaries for triangular designs, and efficacy estimation at extended follow-ups.

Authors:  Annabel Allison; Tansy Edwards; Raymond Omollo; Fabiana Alves; Dominic Magirr; Neal D E Alexander
Journal:  Trials       Date:  2015-11-16       Impact factor: 2.279

6.  Estimation of treatment effects following a sequential trial of multiple treatments.

Authors:  John Whitehead; Yasin Desai; Thomas Jaki
Journal:  Stat Med       Date:  2020-03-23       Impact factor: 2.373

7.  Adding flexibility to clinical trial designs: an example-based guide to the practical use of adaptive designs.

Authors:  Thomas Burnett; Pavel Mozgunov; Philip Pallmann; Sofia S Villar; Graham M Wheeler; Thomas Jaki
Journal:  BMC Med       Date:  2020-11-19       Impact factor: 8.775

8.  Efficient Adaptive Designs for Clinical Trials of Interventions for COVID-19.

Authors:  Nigel Stallard; Lisa Hampson; Norbert Benda; Werner Brannath; Thomas Burnett; Tim Friede; Peter K Kimani; Franz Koenig; Johannes Krisam; Pavel Mozgunov; Martin Posch; James Wason; Gernot Wassmer; John Whitehead; S Faye Williamson; Sarah Zohar; Thomas Jaki
Journal:  Stat Biopharm Res       Date:  2020-07-29       Impact factor: 1.452

  8 in total

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