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Simple benchmark for complex dose finding studies
Author(s) -
Cheung Ying Kuen
Publication year - 2014
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/biom.12158
Subject(s) - benchmark (surveying) , nonparametric statistics , context (archaeology) , computer science , outcome (game theory) , simple (philosophy) , clinical trial , machine learning , mathematics , statistics , medicine , paleontology , philosophy , geodesy , mathematical economics , epistemology , pathology , biology , geography
Summary While a general goal of early phase clinical studies is to identify an acceptable dose for further investigation, modern dose finding studies and designs are highly specific to individual clinical settings. In addition, as outcome‐adaptive dose finding methods often involve complex algorithms, it is crucial to have diagnostic tools to evaluate the plausibility of a method's simulated performance and the adequacy of the algorithm. In this article, we propose a simple technique that provides an upper limit, or a benchmark, of accuracy for dose finding methods for a given design objective. The proposed benchmark is nonparametric optimal in the sense of O'Quigley et al. (2002, Biostatistics 3, 51–56), and is demonstrated by examples to be a practical accuracy upper bound for model‐based dose finding methods. We illustrate the implementation of the technique in the context of phase I trials that consider multiple toxicities and phase I/II trials where dosing decisions are based on both toxicity and efficacy, and apply the benchmark to several clinical examples considered in the literature. By comparing the operating characteristics of a dose finding method to that of the benchmark, we can form quick initial assessments of whether the method is adequately calibrated and evaluate its sensitivity to the dose–outcome relationships.