Literature DB >> 32529689

Using a dose-finding benchmark to quantify the loss incurred by dichotomization in Phase II dose-ranging studies.

Pavel Mozgunov1, Thomas Jaki1, Xavier Paoletti2,3.   

Abstract

While there is recognition that more informative clinical endpoints can support better decision-making in clinical trials, it remains a common practice to categorize endpoints originally measured on a continuous scale. The primary motivation for this categorization (and most commonly dichotomization) is the simplicity of the analysis. There is, however, a long argument that this simplicity can come at a high cost. Specifically, larger sample sizes are needed to achieve the same level of accuracy when using a dichotomized outcome instead of the original continuous endpoint. The degree of "loss of information" has been studied in the contexts of parallel-group designs and two-stage Phase II trials. Limited attention, however, has been given to the quantification of the associated losses in dose-ranging trials. In this work, we propose an approach to estimate the associated losses in Phase II dose-ranging trials that is free of the actual dose-ranging design used and depends on the clinical setting only. The approach uses the notion of a nonparametric optimal benchmark for dose-finding trials, an evaluation tool that facilitates the assessment of a dose-finding design by providing an upper bound on its performance under a given scenario in terms of the probability of the target dose selection. After demonstrating how the benchmark can be applied to Phase II dose-ranging trials, we use it to quantify the dichotomization losses. Using parameters from real clinical trials in various therapeutic areas, it is found that the ratio of sample sizes needed to obtain the same precision using continuous and binary (dichotomized) endpoints varies between 70% and 75% under the majority of scenarios but can drop to 50% in some cases.
© 2020 The Authors. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Keywords:  continuous endpoint; dichotomization; dose-ranging trials; nonparametric optimal benchmark; phase II

Year:  2020        PMID: 32529689     DOI: 10.1002/bimj.201900332

Source DB:  PubMed          Journal:  Biom J        ISSN: 0323-3847            Impact factor:   2.207


  1 in total

1.  Efficient Adaptive Designs for Clinical Trials of Interventions for COVID-19.

Authors:  Nigel Stallard; Lisa Hampson; Norbert Benda; Werner Brannath; Thomas Burnett; Tim Friede; Peter K Kimani; Franz Koenig; Johannes Krisam; Pavel Mozgunov; Martin Posch; James Wason; Gernot Wassmer; John Whitehead; S Faye Williamson; Sarah Zohar; Thomas Jaki
Journal:  Stat Biopharm Res       Date:  2020-07-29       Impact factor: 1.452

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.