Literature DB >> 18027226

Statistical considerations for testing multiple endpoints in group sequential or adaptive clinical trials.

H M James Hung1, Sue-Jane Wang, Robert O'Neill.   

Abstract

Many clinical trials are designed with a fixed sample size or total number of events to detect a postulated size of treatment effect on a primary efficacy endpoint. When the trial is completed and the primary efficacy endpoint achieves statistical significance, formal statistical testing of other clinically important secondary endpoints often follows in order for the statistically and clinically significant results of these endpoints to be included in the label of the test pharmaceutical product. In conventional fixed designs without any interim analysis or trial extension, these endpoints are often tested in a pre-specified hierarchical order, following the closed testing principle. This testing strategy ensures a strong control of the overall type I error. However, when trials are conducted using a group-sequential design with interim analyses or can be extended using an adaptive design with an increase of sample size or total number of events, this conventional hierarchical testing strategy may violate the closure principle and the overall type I error rate may not be controlled in the strong sense.

Mesh:

Year:  2007        PMID: 18027226     DOI: 10.1080/10543400701645405

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


  8 in total

1.  Exact sequential analysis for multiple weighted binomial end points.

Authors:  Ivair R Silva; Joshua J Gagne; Mehdi Najafzadeh; Martin Kulldorff
Journal:  Stat Med       Date:  2019-11-25       Impact factor: 2.373

2.  Testing a primary and a secondary endpoint in a group sequential design.

Authors:  Ajit C Tamhane; Cyrus R Mehta; Lingyun Liu
Journal:  Biometrics       Date:  2010-12       Impact factor: 2.571

3.  Group-Sequential Strategies in Clinical Trials with Multiple Co-Primary Outcomes.

Authors:  Toshimitsu Hamasaki; Koko Asakura; Scott R Evans; Tomoyuki Sugimoto; Takashi Sozu
Journal:  Stat Biopharm Res       Date:  2015       Impact factor: 1.452

4.  Group-sequential logrank methods for trial designs using bivariate non-competing event-time outcomes.

Authors:  Tomoyuki Sugimoto; Toshimitsu Hamasaki; Scott R Evans; Susan Halabi
Journal:  Lifetime Data Anal       Date:  2019-04-12       Impact factor: 1.588

Review 5.  Innovative Clinical Trial Designs for Precision Medicine in Heart Failure with Preserved Ejection Fraction.

Authors:  Sanjiv J Shah
Journal:  J Cardiovasc Transl Res       Date:  2017-07-05       Impact factor: 4.132

6.  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

7.  On selecting the critical boundary functions in group-sequential trials with two time-to-event outcomes.

Authors:  Toshimitsu Hamasaki; H M James Hung; Chin-Fu Hsiao; Scott R Evans
Journal:  Contemp Clin Trials       Date:  2020-12-09       Impact factor: 2.226

Review 8.  Biomarker-Guided Adaptive Trial Designs in Phase II and Phase III: A Methodological Review.

Authors:  Miranta Antoniou; Andrea L Jorgensen; Ruwanthi Kolamunnage-Dona
Journal:  PLoS One       Date:  2016-02-24       Impact factor: 3.240

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.