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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Statistics in Medici...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Statistics in Medicine
Article . 2008 . Peer-reviewed
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Dose‐escalation designs in oncology: ADEPT and the CRM

Authors: John O'Quigley; Jianfen Shu;

Dose‐escalation designs in oncology: ADEPT and the CRM

Abstract

AbstractThe ADEPT software package is not a statistical method in its own right as implied by Gerke and Siedentop (Statist. Med. 2008; DOI: 10.1002/sim.3037). ADEPT implements two‐parameter CRM models as described in O'Quigley et al. (Biometrics 1990; 46(1):33–48). All of the basic ideas (use of a two‐parameter logistic model, use of a two‐dimensional prior for the unknown slope and intercept parameters, sequential estimation and subsequent patient allocation based on minimization of some loss function, flexibility to use cohorts instead of one by one inclusion) are strictly identical. The only, and quite trivial, difference arises in the setting of the prior. O'Quigley et al. (Biometrics 1990; 46(1):33–48) used priors having an analytic expression whereas Whitehead and Brunier (Statist. Med. 1995; 14:33–48) use pseudo‐data to play the role of the prior. The question of interest is whether two‐parameter CRM works as well, or better, than the one‐parameter CRM recommended in O'Quigley et al. (Biometrics 1990; 46(1):33–48). Gerke and Siedentop argue that it does. The published literature suggests otherwise. The conclusions of Gerke and Siedentop stem from three highly particular, and somewhat contrived, situations. Unlike one‐parameter CRM (Biometrika 1996; 83:395–405; J. Statist. Plann. Inference 2006; 136:1765–1780; Biometrika 2005; 92:863–873), no statistical properties appear to have been studied for two‐parameter CRM. In particular, for two‐parameter CRM, the parameter estimates are inconsistent. This ought to be a source of major concern to those proposing its use. Worse still, for finite samples the behavior of estimates can be quite wild despite having incorporated the kind of dampening priors discussed by Gerke and Siedentop. An example in which we illustrate this behavior describes a single patient included at level 1 of 6 levels and experiencing a dose limiting toxicity. The subsequent recommendation is to experiment at level 6! Such problematic behavior is not common. Even so, we show that the allocation behavior of two‐parameter CRM is very much less stable than that of one‐parameter CRM. Copyright © 2008 John Wiley & Sons, Ltd.

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Keywords

Models, Statistical, Clinical Trials, Phase I as Topic, Dose-Response Relationship, Drug, Maximum Tolerated Dose, Antineoplastic Agents, Bayes Theorem, Medical Oncology, Research Design, Humans, Computer Simulation

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
13
Average
Average
Average
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