Literature DB >> 25805512

[Modern study designs and analysis methods in clinical research].

J Gerß1, M Eveslage, A Faldum, R Schmidt.   

Abstract

BACKGROUND: Progress in the field of medical research requires further development of clinical trial methodology to overcome the challenges resulting from small patient populations and restricted resources.
METHODS: Classical single-stage designs with fixed sample sizes do not allow for interim analyses or design modifications. In contrast, adaptive designs adhere to established quality criteria while providing flexibility when conducting a clinical trial. In the face of new discoveries or information collected in the course of a trial, sample size adjustment, the selection of the target population and further design modifications can be performed. This enhances the chance of success of a clinical trial. Besides adaptive designs, classical approaches may be replaced or complemented by Bayesian methods. In a Bayesian approach prior knowledge can be efficiently included and hence the amount of information utilized in statistical analyses is increased. Furthermore, Bayes procedures allow the results of a statistical evaluation to be displayed very clearly.
CONCLUSION: Modern approaches, such as adaptive designs and Bayesian designs overcome the challenges in clinical research due to enhanced flexibility and efficiency. In addition, both approaches can be combined.

Entities:  

Mesh:

Year:  2015        PMID: 25805512     DOI: 10.1007/s00393-014-1450-8

Source DB:  PubMed          Journal:  Z Rheumatol        ISSN: 0340-1855            Impact factor:   1.372


  9 in total

1.  Combining different phases in the development of medical treatments within a single trial.

Authors:  P Bauer; M Kieser
Journal:  Stat Med       Date:  1999-07-30       Impact factor: 2.373

2.  Modification of the sample size and the schedule of interim analyses in survival trials based on data inspections.

Authors:  H Schäfer; H H Müller
Journal:  Stat Med       Date:  2001-12-30       Impact factor: 2.373

3.  Adaptive sample size calculations in group sequential trials.

Authors:  W Lehmacher; G Wassmer
Journal:  Biometrics       Date:  1999-12       Impact factor: 2.571

4.  Two-stage adaptive designs with correlated test statistics.

Authors:  Gerhard Hommel; Verena Lindig; Andreas Faldum
Journal:  J Biopharm Stat       Date:  2005       Impact factor: 1.051

5.  Strategies for including patients recruited during interim analysis of clinical trials.

Authors:  Andreas Faldum; Gerhard Hommel
Journal:  J Biopharm Stat       Date:  2007       Impact factor: 1.051

6.  Adaptive designs with correlated test statistics.

Authors:  Heiko Götte; Gerhard Hommel; Andreas Faldum
Journal:  Stat Med       Date:  2009-05-01       Impact factor: 2.373

7.  Adaptive designs with arbitrary dependence structure.

Authors:  Rene Schmidt; Andreas Faldum; Olaf Witt; Joachim Gerss
Journal:  Biom J       Date:  2013-11-11       Impact factor: 2.207

8.  A multiple testing procedure for clinical trials.

Authors:  P C O'Brien; T R Fleming
Journal:  Biometrics       Date:  1979-09       Impact factor: 2.571

9.  Confirmatory adaptive designs with Bayesian decision tools for a targeted therapy in oncology.

Authors:  Werner Brannath; Emmanuel Zuber; Michael Branson; Frank Bretz; Paul Gallo; Martin Posch; Amy Racine-Poon
Journal:  Stat Med       Date:  2009-05-01       Impact factor: 2.373

  9 in total

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