A Benchmark for Dose Finding Studies with Unknown Ordering

Mozgunov, Pavel and Paoletti, Xavier and Jaki, Thomas (2022) A Benchmark for Dose Finding Studies with Unknown Ordering. Biostatistics, 23 (3). pp. 721-737. ISSN 1465-4644

[img]
Text (Combo-Benchmark-Final)
samplebibtex.pdf - Accepted Version
Restricted to Repository staff only until 4 January 2023.
Available under License Creative Commons Attribution.

Download (372kB)

Abstract

An important tool to evaluate the performance of a dose finding design is the non-parametric optimal benchmark that provides an upper bound on the performance of a design under a given scenario. A fundamental assumption of the benchmark is that the investigator can arrange doses in monotonically increasing toxicity order. While the benchmark can be still applied to combination studies in which not all dose combinations can be ordered, it does not account for the uncertainty in the ordering. In this work, we propose a generalization of the benchmark that accounts for this uncertainty and, as a result, provides a sharper upper bound on the performance. The benchmark assesses how probable the occurrence of each ordering is, given the complete information about each patient. The proposed approach can also be applied to trials with an arbitrary number of endpoints with discrete or continuous distributions. We illustrate the utility of the benchmark using recently proposed dose finding designs for Phase I combination trials with a binary toxicity endpoint and Phase I/II combination trials with binary toxicity and continuous efficacy endpoints.

Item Type:
Journal Article
Journal or Publication Title:
Biostatistics
Additional Information:
This is a pre-copy-editing, author-produced PDF of an article accepted for publication in British Journal for the Philosophy of Science following peer review. The definitive publisher-authenticated version Pavel Mozgunov, Xavier Paoletti, Thomas Jaki, A benchmark for dose-finding studies with unknown ordering, Biostatistics, Volume 23, Issue 3, July 2022, Pages 721–737 is available online at: https://academic.oup.com/biostatistics/article/23/3/721/6066695
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2700
Subjects:
ID Code:
149316
Deposited By:
Deposited On:
23 Nov 2020 12:05
Refereed?:
Yes
Published?:
Published
Last Modified:
22 Nov 2022 09:41