A Simple Approach to Incorporating Historical Control Data in Clinical Trial Design and Analysis

Lanju Zhang (), Zailong Wang, Li Wang, Lu Cui, Jeremy Sokolove and Ivan Chan
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Lanju Zhang: Vertex Pharmaceuticals
Zailong Wang: AbbVie Inc
Li Wang: AbbVie Inc
Lu Cui: UCB Biosciences Inc
Jeremy Sokolove: GlaxoSmithKline
Ivan Chan: Bristol Myers Squibb

Statistics in Biosciences, 2022, vol. 14, issue 2, No 3, 216-236

Abstract: Abstract With rising costs and prolonged timelines for drug development, more innovative trial designs are critical to improve efficiency. Use of available historical control data in a new trial can reduce the number of control patients and accordingly reduce costs and timelines. A major limitation of historical data borrowing is potential prior-data conflict. This difference can increase false decision rates and confound the outcome interpretation. The potential inflation in both type I error rate and type II error rate should be clearly characterized and controlled during the trial design stage. In this paper, we develop a simple approach to incorporating historical control data in clinical trial design and analysis. First we provide a simple statistical approach to evaluating design properties when using a Bayesian approach to incorporating historical data. We then propose a six-step process for trial design including selection and summarization of historical control data, sample size determination with and without borrowing, design property evaluation, and how much historical data should be borrowed to control false positive/negative rate inflation based on trial variability. A detailed procedure to select historical control data is also provided. Finally, we use an example to illustrate our approach. The simplicity of methodology (no simulation required), the streamlined processes for data selection, and explicit evaluation of the impact of prior-data conflict on type I error rate and power make the proposed approach statistically rigorous and easy to understand and implement.

Keywords: Bayesian method; Frequentist method; Historical control data; Power; Prior-data conflict; Type I error rate (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s12561-022-09342-w

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