Literature DB >> 25811018

Adaptive clinical trial designs in oncology.

Yong Zang1, J Jack Lee1.   

Abstract

Adaptive designs have become popular in clinical trial and drug development. Unlike traditional trial designs, adaptive designs use accumulating data to modify the ongoing trial without undermining the integrity and validity of the trial. As a result, adaptive designs provide a flexible and effective way to conduct clinical trials. The designs have potential advantages of improving the study power, reducing sample size and total cost, treating more patients with more effective treatments, identifying efficacious drugs for specific subgroups of patients based on their biomarker profiles, and shortening the time for drug development. In this article, we review adaptive designs commonly used in clinical trials and investigate several aspects of the designs, including the dose-finding scheme, interim analysis, adaptive randomization, biomarker-guided randomization, and seamless designs. For illustration, we provide examples of real trials conducted with adaptive designs. We also discuss practical issues from the perspective of using adaptive designs in oncology trials.

Entities:  

Keywords:  Adaptive design; adaptive randomization; biomarker-guided design; interim analysis; seamless design

Year:  2014        PMID: 25811018      PMCID: PMC4369921          DOI: 10.3978/j.issn.2304-3865.2014.06.04

Source DB:  PubMed          Journal:  Chin Clin Oncol        ISSN: 2304-3865


  78 in total

Review 1.  Adaptive clinical trials in oncology.

Authors:  Donald A Berry
Journal:  Nat Rev Clin Oncol       Date:  2011-11-08       Impact factor: 66.675

2.  Sequential continual reassessment method for two-dimensional dose finding.

Authors:  Ying Yuan; Guosheng Yin
Journal:  Stat Med       Date:  2008-11-29       Impact factor: 2.373

3.  Statistical issues in the validation of prognostic, predictive, and surrogate biomarkers.

Authors:  Daniel J Sargent; Sumithra J Mandrekar
Journal:  Clin Trials       Date:  2013-08-27       Impact factor: 2.486

4.  A seamless phase II/III design with sample-size re-estimation.

Authors:  Wolfgang Bischoff; Frank Miller
Journal:  J Biopharm Stat       Date:  2009-07       Impact factor: 1.051

5.  A confirmatory seamless phase II/III clinical trial design incorporating short-term endpoint information.

Authors:  Nigel Stallard
Journal:  Stat Med       Date:  2010-02-26       Impact factor: 2.373

6.  Bayesian sequential monitoring designs for single-arm clinical trials with multiple outcomes.

Authors:  P F Thall; R M Simon; E H Estey
Journal:  Stat Med       Date:  1995-02-28       Impact factor: 2.373

7.  A strategy for dose-finding and safety monitoring based on efficacy and adverse outcomes in phase I/II clinical trials.

Authors:  P F Thall; K E Russell
Journal:  Biometrics       Date:  1998-03       Impact factor: 2.571

8.  Issues in clinical trial design for tumor marker studies.

Authors:  Daniel Sargent; Carmen Allegra
Journal:  Semin Oncol       Date:  2002-06       Impact factor: 4.929

9.  A comparison of Bayesian adaptive randomization and multi-stage designs for multi-arm clinical trials.

Authors:  James M S Wason; Lorenzo Trippa
Journal:  Stat Med       Date:  2014-01-14       Impact factor: 2.373

10.  Some recommendations for multi-arm multi-stage trials.

Authors:  James Wason; Dominic Magirr; Martin Law; Thomas Jaki
Journal:  Stat Methods Med Res       Date:  2012-12-12       Impact factor: 3.021

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  2 in total

1.  Prediction-Oriented Marker Selection (PROMISE): With Application to High-Dimensional Regression.

Authors:  Soyeon Kim; Veerabhadran Baladandayuthapani; J Jack Lee
Journal:  Stat Biosci       Date:  2016-09-26

2.  PIPELINEs: Creating Comparable Clinical Knowledge Efficiently by Linking Trial Platforms.

Authors:  M R Trusheim; A A Shrier; Z Antonijevic; R A Beckman; R K Campbell; C Chen; K T Flaherty; J Loewy; D Lacombe; S Madhavan; H P Selker; L J Esserman
Journal:  Clin Pharmacol Ther       Date:  2016-10-19       Impact factor: 6.875

  2 in total

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