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The New England Journal of Statistics in Data Science


Up-and-Down: The Most Popular, Most Reliable, and Most Overlooked Dose-Finding Design
Pub. online: 17 December 2024      Type: Statistical Methodology      Open accessOpen Access
Accepted
5 November 2024
Published
17 December 2024

Abstract

Up-and-Down designs (UDDs) are ubiquitous for dose-finding in a wide variety of scientific, engineering, and clinical fields. They are defined by a few simple rules that generate a random walk around the target percentile. UDDs’ combination of robust, tractable behavior, straightforward usage, and good dose-finding performance, has won the trust of practitioners and their consulting analysts across fields and continents. In contrast, in recent decades the statistical dose-finding design field has turned a cold shoulder towards UDDs, and it is quite possible that many younger dose-finding methods researchers are not even aware of this design approach.
We present a concise overview of UDDs and their current state-of-the-art methodology, with references for further inquiry. We also revisit the performance comparison between UDDs and novel, more complicated design approaches such as the Continual Reassessment Method and the Bayesian Optimal Interval design, which we group under the term “Aim-for-Target” designs. UDDs fare very well in the comparison, particularly in terms of robustness to sources of variability.

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Keywords
Adaptive designs Dose-finding Up-and-Down Staircase method

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