Literature DB >> 32222766

Resist the Temptation of Response-Adaptive Randomization.

Michael Proschan1, Scott Evans2.   

Abstract

Response-adaptive randomization (RAR) has recently gained popularity in clinical trials. The intent is noble: minimize the number of participants randomized to inferior treatments and increase the amount of information about better treatments. Unfortunately, RAR causes many problems, including (1) bias from temporal trends, (2) inefficiency in treatment effect estimation, (3) volatility in sample-size distributions that can cause a nontrivial proportion of trials to assign more patients to an inferior arm, (4) difficulty of validly analyzing results, and (5) the potential for selection bias and other issues inherent to being unblinded to ongoing results. The problems of RAR are most acute in the very setting for which RAR has been proposed, namely long-duration "platform" trials and infectious disease settings where temporal trends are ubiquitous. Response-adaptive randomization can eliminate the benefits that randomization, the most powerful tool in clinical trials, provides. Use of RAR is discouraged. Published by Oxford University Press for the Infectious Diseases Society of America 2020.

Entities:  

Keywords:  Bayesian approach; frequentist approach; platform trials; response-adaptive randomization; temporal trend

Mesh:

Year:  2020        PMID: 32222766      PMCID: PMC7947972          DOI: 10.1093/cid/ciaa334

Source DB:  PubMed          Journal:  Clin Infect Dis        ISSN: 1058-4838            Impact factor:   9.079


  10 in total

1.  Adaptive clinical trials: the promise and the caution.

Authors:  Donald A Berry
Journal:  J Clin Oncol       Date:  2010-12-20       Impact factor: 44.544

2.  On the usefulness of outcome-adaptive randomization.

Authors:  Ying Yuan; Guosheng Yin
Journal:  J Clin Oncol       Date:  2011-03-21       Impact factor: 44.544

3.  A Randomized, Controlled Trial of ZMapp for Ebola Virus Infection.

Authors:  Richard T Davey; Lori Dodd; Michael A Proschan; James Neaton; Jacquie Neuhaus Nordwall; Joseph S Koopmeiners; John Beigel; John Tierney; H Clifford Lane; Anthony S Fauci; Moses B F Massaquoi; Foday Sahr; Denis Malvy
Journal:  N Engl J Med       Date:  2016-10-13       Impact factor: 91.245

4.  Statistical controversies in clinical research: scientific and ethical problems with adaptive randomization in comparative clinical trials.

Authors:  P Thall; P Fox; J Wathen
Journal:  Ann Oncol       Date:  2015-05-15       Impact factor: 32.976

5.  Adaptive Randomization of Neratinib in Early Breast Cancer.

Authors:  John W Park; Minetta C Liu; Douglas Yee; Christina Yau; Laura J van 't Veer; W Fraser Symmans; Melissa Paoloni; Jane Perlmutter; Nola M Hylton; Michael Hogarth; Angela DeMichele; Meredith B Buxton; A Jo Chien; Anne M Wallace; Judy C Boughey; Tufia C Haddad; Stephen Y Chui; Kathleen A Kemmer; Henry G Kaplan; Claudine Isaacs; Rita Nanda; Debasish Tripathy; Kathy S Albain; Kirsten K Edmiston; Anthony D Elias; Donald W Northfelt; Lajos Pusztai; Stacy L Moulder; Julie E Lang; Rebecca K Viscusi; David M Euhus; Barbara B Haley; Qamar J Khan; William C Wood; Michelle Melisko; Richard Schwab; Teresa Helsten; Julia Lyandres; Sarah E Davis; Gillian L Hirst; Ashish Sanil; Laura J Esserman; Donald A Berry
Journal:  N Engl J Med       Date:  2016-07-07       Impact factor: 91.245

Review 6.  Adaptive Designs for Clinical Trials: Application to Healthcare Epidemiology Research.

Authors:  W Charles Huskins; Vance G Fowler; Scott Evans
Journal:  Clin Infect Dis       Date:  2018-03-19       Impact factor: 9.079

7.  Outcome--adaptive randomization: is it useful?

Authors:  Edward L Korn; Boris Freidlin
Journal:  J Clin Oncol       Date:  2010-12-20       Impact factor: 44.544

8.  UK collaborative randomised trial of neonatal extracorporeal membrane oxygenation. UK Collaborative ECMO Trail Group.

Authors: 
Journal:  Lancet       Date:  1996-07-13       Impact factor: 79.321

9.  Extracorporeal circulation in neonatal respiratory failure: a prospective randomized study.

Authors:  R H Bartlett; D W Roloff; R G Cornell; A F Andrews; P W Dillon; J B Zwischenberger
Journal:  Pediatrics       Date:  1985-10       Impact factor: 7.124

10.  Evaluating interventions for Ebola: The need for randomized trials.

Authors:  Thomas R Fleming; Susan S Ellenberg
Journal:  Clin Trials       Date:  2016-01-14       Impact factor: 2.486

  10 in total
  9 in total

Review 1.  Challenges and opportunities in biomarker-driven trials: adaptive randomization.

Authors:  Yeonhee Park
Journal:  Ann Transl Med       Date:  2022-09

2.  Quantifying Efficiency Gains of Innovative Designs of Two-Arm Vaccine Trials for COVID-19 Using an Epidemic Simulation Model.

Authors:  Rob Johnson; Chris Jackson; Anne Presanis; Sofia S Villar; Daniela De Angelis
Journal:  Stat Biopharm Res       Date:  2021-07-30       Impact factor: 1.452

Review 3.  The Bayesian Design of Adaptive Clinical Trials.

Authors:  Alessandra Giovagnoli
Journal:  Int J Environ Res Public Health       Date:  2021-01-10       Impact factor: 3.390

4.  Should RECOVERY have used response adaptive randomisation? Evidence from a simulation study.

Authors:  Tamir Sirkis; Benjamin Jones; Jack Bowden
Journal:  BMC Med Res Methodol       Date:  2022-08-06       Impact factor: 4.612

5.  Analysis of adaptive platform trials using a network approach.

Authors:  Ian C Marschner; I Manjula Schou
Journal:  Clin Trials       Date:  2022-08-22       Impact factor: 2.599

6.  Adding flexibility to clinical trial designs: an example-based guide to the practical use of adaptive designs.

Authors:  Thomas Burnett; Pavel Mozgunov; Philip Pallmann; Sofia S Villar; Graham M Wheeler; Thomas Jaki
Journal:  BMC Med       Date:  2020-11-19       Impact factor: 8.775

7.  Statistical consideration when adding new arms to ongoing clinical trials: the potentials and the caveats.

Authors:  Kim May Lee; Louise C Brown; Thomas Jaki; Nigel Stallard; James Wason
Journal:  Trials       Date:  2021-03-10       Impact factor: 2.279

8.  Efficient Adaptive Designs for Clinical Trials of Interventions for COVID-19.

Authors:  Nigel Stallard; Lisa Hampson; Norbert Benda; Werner Brannath; Thomas Burnett; Tim Friede; Peter K Kimani; Franz Koenig; Johannes Krisam; Pavel Mozgunov; Martin Posch; James Wason; Gernot Wassmer; John Whitehead; S Faye Williamson; Sarah Zohar; Thomas Jaki
Journal:  Stat Biopharm Res       Date:  2020-07-29       Impact factor: 1.452

9.  Interpreting recent clinical studies for COVID-19: A continual process with more new data.

Authors:  Jean M Connors; Matthew Moll; Jerrold H Levy
Journal:  Anaesth Crit Care Pain Med       Date:  2021-12-24       Impact factor: 4.132

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.