Designing Multi-arm Multi-stage Clinical Studies

Thomas Jaki ()
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Thomas Jaki: Lancaster University, Medical and Pharmaceutical Statistics Research Unit, Department of Mathematics and Statistics

Chapter Chapter 3 in Developments in Statistical Evaluation of Clinical Trials, 2014, pp 51-69 from Springer

Abstract: Abstract In the early stages of drug development there often is uncertainty about the most promising among a set of different treatments, different doses of the same treatment or sets of combinations of treatments. An efficient solution to determine which intervention is most promising are multi-arm multi-stage clinical studies (MAMS). In this chapter we will discuss the general concept to designing MAMS studies within the group sequential framework and provide detailed solutions for multi-arm multi-stage studies with normally distributed endpoints in which all promising treatments are continued at the interim analyses. An approach to find optimal designs is discussed as well as asymptotic solutions for binary, ordinal and time-to event endpoints.

Keywords: Experimental Treatment; Interim Analysis; Equal Sample Size; Maximum Sample Size; Familywise Error Rate (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-55345-5_3

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DOI: 10.1007/978-3-642-55345-5_3

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