Abstract

Adaptive designs allow planned modifications based on data accumulating within a study. The promise of greater flexibility and efficiency stimulates increasing interest in adaptive designs from clinical, academic, and regulatory parties. When adaptive designs are used properly, efficiencies can include a smaller sample size, a more efficient treatment development process, and an increased chance of correctly answering the clinical question of interest. However, improper adaptations can lead to biased studies. A broad definition of adaptive designs allows for countless variations, which creates confusion as to the statistical validity and practical feasibility of many designs. Determining properties of a particular adaptive design requires careful consideration of the scientific context and statistical assumptions. We first review several adaptive designs that garner the most current interest. We focus on the design principles and research issues that lead to particular designs being appealing or unappealing in particular applications. We separately discuss exploratory and confirmatory stage designs in order to account for the differences in regulatory concerns. We include adaptive seamless designs, which combine stages in a unified approach. We also highlight a number of applied areas, such as comparative effectiveness research, that would benefit from the use of adaptive designs. Finally, we describe a number of current barriers and provide initial suggestions for overcoming them in order to promote wider use of appropriate adaptive designs. Given the breadth of the coverage all mathematical and most implementation details are omitted for the sake of brevity. However, the interested reader will find that we provide current references to focused reviews and original theoretical sources which lead to details of the current state of the art in theory and practice.

Highlights

  • In traditional clinical trials, key elements such as primary endpoint, clinically meaningful treatment difference, and measure of variability are pre-specified during planning in order to design the study

  • Adaptive Designs (ADs) give one way to address uncertainty about choices made during planning

  • In the remainder of the paper we summarize specific AD types used in clinical research and address current concerns with the use of the designs

Read more

Summary

Introduction

Key elements such as primary endpoint, clinically meaningful treatment difference, and measure of variability are pre-specified during planning in order to design the study. The participants stressed that the use of ADs may require a different way of thinking about the structure and conduct of Data and Safety Monitoring Boards (DSMBs) They agreed that there is a great need for further education and communication regarding the strengths and weaknesses of various types of ADs. For example, researchers should be encouraged to publish manuscripts describing experiences (both positive and negative) associated with completed trials that used an AD. The participants are studying the development and acceptance of a wide range of adaptive designs within the existing infrastructure of the National Institute of Neurological Disorders and Stroke (NINDS)-supported Neurological Emergencies Treatment Trials (NETT) network [70]. Additional infrastructure with flexibility is needed in other disease areas to advance the use of ADs, in the publicly funded environment

Conclusions
12. Storer BE
16. Garrett-Mayer E
35. Wang SJ
37. Temple R
42. Proschan MA
48. Proschan MA
60. Levin B
63. Tsiatis AA
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call