Literature DB >> 30215881

A practical guide to pre-trial simulations for Bayesian adaptive trials using SAS and BUGS.

Christian Holm Hansen1, Pamela Warner2, Allan Walker2,3, Richard A Parker2,3, Lucy Whitaker4, Hilary O D Critchley4, Christopher J Weir2.   

Abstract

It is often unclear what specific adaptive trial design features lead to an efficient design which is also feasible to implement. Before deciding on a particular design, it is generally advisable to carry out a simulation study to characterise the properties of candidate designs under a range of plausible assumptions. The implementation of such pre-trial simulation studies presents many challenges and requires considerable statistical programming effort and time. Despite the scale and complexity, there is little existing literature to guide the implementation of such projects using commonly available software. This Teacher's Corner article provides a practical step-by-step guide to implementing such simulation studies including how to specify and fit a Bayesian model in WinBUGS or OpenBUGS using SAS, and how results from the Bayesian analysis may be pulled back into SAS and used for adaptation of allocation probabilities before simulating subsequent stages of the trial. The interface between the two software platforms is described in detail along with useful tips and tricks. A key strength of our approach is that the entire exercise can be defined and controlled from within a single SAS program.
© 2018 The Authors. Pharmaceutical Statistics Published by John Wiley & Sons Ltd.

Entities:  

Keywords:  Bayesian modelling; OpenBUGS; SAS; WinBUGS; adaptive trials; simulations

Mesh:

Year:  2018        PMID: 30215881      PMCID: PMC6283249          DOI: 10.1002/pst.1897

Source DB:  PubMed          Journal:  Pharm Stat        ISSN: 1539-1604            Impact factor:   1.894


  5 in total

1.  Adaptive designs in clinical drug development--an Executive Summary of the PhRMA Working Group.

Authors:  Paul Gallo; Christy Chuang-Stein; Vladimir Dragalin; Brenda Gaydos; Michael Krams; José Pinheiro
Journal:  J Biopharm Stat       Date:  2006-05       Impact factor: 1.051

2.  A practical guide to pre-trial simulations for Bayesian adaptive trials using SAS and BUGS.

Authors:  Christian Holm Hansen; Pamela Warner; Allan Walker; Richard A Parker; Lucy Whitaker; Hilary O D Critchley; Christopher J Weir
Journal:  Pharm Stat       Date:  2018-09-14       Impact factor: 1.894

3.  The BUGS project: Evolution, critique and future directions.

Authors:  David Lunn; David Spiegelhalter; Andrew Thomas; Nicky Best
Journal:  Stat Med       Date:  2009-11-10       Impact factor: 2.373

4.  Low-dose dexamethasone as a treatment for women with heavy menstrual bleeding: protocol for response-adaptive randomised placebo-controlled dose-finding parallel group trial (DexFEM).

Authors:  P Warner; C J Weir; C H Hansen; A Douglas; M Madhra; S G Hillier; P T K Saunders; J P Iredale; S Semple; B R Walker; H O D Critchley
Journal:  BMJ Open       Date:  2015-01-14       Impact factor: 2.692

5.  Development of a Bayesian response-adaptive trial design for the Dexamethasone for Excessive Menstruation study.

Authors:  Christian Holm Hansen; Pamela Warner; Richard A Parker; Brian R Walker; Hilary Od Critchley; Christopher J Weir
Journal:  Stat Methods Med Res       Date:  2015-09-30       Impact factor: 3.021

  5 in total
  2 in total

1.  A practical guide to pre-trial simulations for Bayesian adaptive trials using SAS and BUGS.

Authors:  Christian Holm Hansen; Pamela Warner; Allan Walker; Richard A Parker; Lucy Whitaker; Hilary O D Critchley; Christopher J Weir
Journal:  Pharm Stat       Date:  2018-09-14       Impact factor: 1.894

2.  Systematic review and network meta-analysis comparing Chinese herbal injections with chemotherapy for treating patients with esophageal cancer.

Authors:  Dan Zhang; Jiarui Wu; Haojia Wang; Wei Zhou; Mengwei Ni; Xinkui Liu; Xiaomeng Zhang
Journal:  J Int Med Res       Date:  2020-01       Impact factor: 1.671

  2 in total

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