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April 30, 1993Statistics in Medicine136 citations

Sequential monitoring of clinical trials: The role of information and brownian motion

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KLK. K. Gordon LanDZDavid M. Zucker

Key Points

  • To establish a unified conceptual framework for sequential monitoring in clinical trials based on statistical information and Brownian motion approximations.
  • Formulated a mathematical framework linking statistical information metrics to standardized summaries of accumulating trial data.
  • Modeled interim data accumulation as a continuous-time stochastic process that asymptotically approximates classical Brownian motion.
  • Illustrated application across multiple clinical trial designs using step-by-step theoretical examples.
  • Demonstrated that diverse sequential monitoring rules can be represented under a single standardized Brownian motion framework.
  • Showed that summarizing accumulating information allows consistent computation of stopping boundaries across different trial settings.

Abstract

Sequential monitoring has been a topic of major interest in clinical trials methodology over the past two decades. This paper presents a unified conceptual framework for sequential monitoring that covers a wide variety of monitoring procedures in a wide variety of clinical trial settings. The central elements of this framework consist of a suitable concept of statistical information and a scheme for using this concept as a basis for summarizing the accumulating results of a trial in a standardized form, through a stochastic process that can be shown to approximate classical Brownian motion. The ideas are developed in a simple step-by-step fashion and illustrated by several practical examples.

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Cite This Study

Lan et al. (1993) studied this question.

synapsesocial.com/papers/6a16e9cab13aec50ea6ba1e4https://doi.org/10.1002/sim.4780120804
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