Literature DB >> 24392984

Adaptive designs for confirmatory clinical trials with subgroup selection.

Nigel Stallard1, Thomas Hamborg, Nicholas Parsons, Tim Friede.   

Abstract

Growing interest in stratified medicine is leading to increasing importance of subgroup analyses in confirmatory clinical trials. Conventionally, confirmatory clinical trials either focus on a subgroup identified in advance or assess subgroup effects once the trial is completed. The focus of this article is methodology for adaptive clinical trials that both identify whether a treatment is particularly effective in a predefined subgroup, potentially enabling alteration of recruitment, and assess the effectiveness in the subgroup and/or whole population. Methods for such adaptive trials are described and compared, and the logistical and regulatory issues associated with such approaches are discussed.

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Year:  2014        PMID: 24392984     DOI: 10.1080/10543406.2013.857238

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


  15 in total

Review 1.  Design, data monitoring, and analysis of clinical trials with co-primary endpoints: A review.

Authors:  Toshimitsu Hamasaki; Scott R Evans; Koko Asakura
Journal:  J Biopharm Stat       Date:  2017-10-30       Impact factor: 1.051

2.  Perspective: Randomized Controlled Trials Are Not a Panacea for Diet-Related Research.

Authors:  James R Hébert; Edward A Frongillo; Swann A Adams; Gabrielle M Turner-McGrievy; Thomas G Hurley; Donald R Miller; Ira S Ockene
Journal:  Adv Nutr       Date:  2016-05-16       Impact factor: 8.701

3.  Optimal decision rules for biomarker-based subgroup selection for a targeted therapy in oncology.

Authors:  Johannes Krisam; Meinhard Kieser
Journal:  Int J Mol Sci       Date:  2015-05-07       Impact factor: 5.923

4.  Twenty-five years of confirmatory adaptive designs: opportunities and pitfalls.

Authors:  Peter Bauer; Frank Bretz; Vladimir Dragalin; Franz König; Gernot Wassmer
Journal:  Stat Med       Date:  2015-03-16       Impact factor: 2.373

Review 5.  Clinical trial designs incorporating predictive biomarkers.

Authors:  Lindsay A Renfro; Himel Mallick; Ming-Wen An; Daniel J Sargent; Sumithra J Mandrekar
Journal:  Cancer Treat Rev       Date:  2016-01-05       Impact factor: 12.111

6.  Adaptive designs for subpopulation analysis optimizing utility functions.

Authors:  Alexandra C Graf; Martin Posch; Franz Koenig
Journal:  Biom J       Date:  2014-11-14       Impact factor: 2.207

Review 7.  Methods for identification and confirmation of targeted subgroups in clinical trials: A systematic review.

Authors:  Thomas Ondra; Alex Dmitrienko; Tim Friede; Alexandra Graf; Frank Miller; Nigel Stallard; Martin Posch
Journal:  J Biopharm Stat       Date:  2016       Impact factor: 1.051

8.  Estimation after subpopulation selection in adaptive seamless trials.

Authors:  Peter K Kimani; Susan Todd; Nigel Stallard
Journal:  Stat Med       Date:  2015-04-22       Impact factor: 2.373

9.  Missing steps in a staircase: a qualitative study of the perspectives of key stakeholders on the use of adaptive designs in confirmatory trials.

Authors:  Munyaradzi Dimairo; Jonathan Boote; Steven A Julious; Jonathan P Nicholl; Susan Todd
Journal:  Trials       Date:  2015-09-28       Impact factor: 2.279

10.  Subgroup identification for treatment selection in biomarker adaptive design.

Authors:  Tzu-Pin Lu; James J Chen
Journal:  BMC Med Res Methodol       Date:  2015-12-09       Impact factor: 4.615

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