Decision-theoretic designs for small trials and pilot studies: A review. (June 2016)

• Record Type: Journal Article
• Authors: Hee, Siew Wan; Hamborg, Thomas; Day, Simon; Madan, Jason; Miller, Frank; Posch, Martin; Zohar, Sarah; Stallard, Nigel
• Other Names: Julious Steven A guest-editor.
• Is Part Of: Statistical methods in medical research. Volume 25:Number 3(2016:Jun.)
• Page Start: 1022
• Page End: 1038
• Publication Date: 2016-06
• Subjects: Bayesian decision theory -- optimal clinical trial design -- phase II clinical trials -- utility functions; Medicine -- Research -- Statistical methods -- Periodicals; Research -- Periodicals; Review Literature -- Periodicals; Statistics -- methods -- Periodicals; Médecine -- Recherche -- Méthodes statistiques -- Périodiques; 610.727
• DOI: 10.1177/0962280215588245
• Languages: English
• ISSNs: 0962-2802

Abstract

Pilot studies and other small clinical trials are often conducted but serve a variety of purposes and there is little consensus on their design. One paradigm that has been suggested for the design of such studies is Bayesian decision theory. In this article, we review the literature with the aim of summarizing current methodological developments in this area. We find that decision-theoretic methods have been applied to the design of small clinical trials in a number of areas. We divide our discussion of published methods into those for trials conducted in a single stage, those for multi-stage trials in which decisions are made through the course of the trial at a number of interim analyses, and those that attempt to design a series of clinical trials or a drug development programme. In all three cases, a number of methods have been proposed, depending on the decision maker's perspective being considered and the details of utility functions that are used to construct the optimal design.