Point estimation for adaptive trial designs

Robertson, David S, Choodari-Oskooei, Babak, Dimairo, Munya, Flight, Laura, Pallmann, Philip ORCID: https://orcid.org/0000-0001-8274-9696 and Jaki, Thomas 2021. Point estimation for adaptive trial designs. [Online]. Cornell University. Available at: https://arxiv.org/abs/2105.08836

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Abstract

Recent FDA guidance on adaptive clinical trial designs defines bias as "a systematic tendency for the estimate of treatment effect to deviate from its true value", and states that it is desirable to obtain and report estimates of treatment effects that reduce or remove this bias. In many adaptive designs, the conventional end-of-trial point estimates of the treatment effects are prone to bias, because they do not take into account the potential and realised trial adaptations. While much of the methodological developments on adaptive designs have tended to focus on control of type I error rates and power considerations, in contrast the question of biased estimation has received less attention. This article addresses this issue by providing a comprehensive overview of proposed approaches to remove or reduce the potential bias in point estimation of treatment effects in an adaptive design, as well as illustrating how to implement them. We first discuss how bias can affect standard estimators and critically assess the negative impact this can have. We then describe and compare proposed unbiased and bias-adjusted estimators of treatment effects for different types of adaptive designs. Furthermore, we illustrate the computation of different estimators in practice using a real trial example. Finally, we propose a set of guidelines for researchers around the choice of estimators and the reporting of estimates following an adaptive design.

Item Type:	Website Content
Date Type:	Submission
Status:	Submitted
Schools:	Medicine Centre for Trials Research (CNTRR)
Publisher:	Cornell University
Last Modified:	20 Nov 2024 12:15
URI:	https://orca.cardiff.ac.uk/id/eprint/141478

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