Literature DB >> 24697678

Efficient and ethical response-adaptive randomization designs for multi-arm clinical trials with Weibull time-to-event outcomes.

Oleksandr Sverdlov1, Yevgen Ryeznik, Weng-Kee Wong.   

Abstract

We consider a design problem for a clinical trial with multiple treatment arms and time-to-event primary outcomes that are modeled using the Weibull family of distributions. The D-optimal design for the most precise estimation of model parameters is derived, along with compound optimal allocation designs that provide targeted efficiencies for various estimation problems and ethical considerations. The proposed optimal allocation designs are studied theoretically and are implemented using response-adaptive randomization for a clinical trial with censored Weibull outcomes. We compare the merits of our multiple-objective response-adaptive designs with traditional randomization designs and show that our designs are more flexible, realistic, generally more ethical, and frequently provide higher efficiencies for estimating different sets of parameters.

Keywords:  Censoring; D-optimal design; Ethical concern; Response-adaptive randomization; Weibull distribution

Mesh:

Year:  2014        PMID: 24697678     DOI: 10.1080/10543406.2014.903261

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


  4 in total

1.  Implementing Optimal Designs for Dose-Response Studies Through Adaptive Randomization for a Small Population Group.

Authors:  Yevgen Ryeznik; Oleksandr Sverdlov; Andrew C Hooker
Journal:  AAPS J       Date:  2018-07-19       Impact factor: 4.009

2.  Adaptive Optimal Designs for Dose-Finding Studies with Time-to-Event Outcomes.

Authors:  Yevgen Ryeznik; Oleksandr Sverdlov; Andrew C Hooker
Journal:  AAPS J       Date:  2017-12-28       Impact factor: 4.009

3.  RARtool: A MATLAB Software Package for Designing Response-Adaptive Randomized Clinical Trials with Time-to-Event Outcomes.

Authors:  Yevgen Ryeznik; Oleksandr Sverdlov; Weng Kee Wong
Journal:  J Stat Softw       Date:  2015-08-01       Impact factor: 6.440

4.  Multiple-Objective Optimal Designs for Studying the Dose Response Function and Interesting Dose Levels.

Authors:  Seung Won Hyun; Weng Kee Wong
Journal:  Int J Biostat       Date:  2015-11       Impact factor: 0.968

  4 in total

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