Methods for working with dose-finding clinical trials. We provide
implementations of many dose-finding clinical trial designs, including the
continual reassessment method (CRM) by O'Quigley et al. (1990)
<doi:10.2307/2531628>, the toxicity probability interval (TPI) design by Ji
et al. (2007) <doi:10.1177/1740774507079442>, the modified TPI (mTPI) design
by Ji et al. (2010) <doi:10.1177/1740774510382799>, the Bayesian optimal
interval design (BOIN) by Liu & Yuan (2015) <doi:10.1111/rssc.12089>, EffTox
by Thall & Cook (2004) <doi:10.1111/j.0006-341X.2004.00218.x>; the design of
Wages & Tait (2015) <doi:10.1080/10543406.2014.920873>, and the 3+3
described by Korn et al. (1994) <doi:10.1002/sim.4780131802>. All designs
are implemented with a common interface. We also offer optional additional
classes to tailor the behaviour of all designs, including avoiding skipping
doses, stopping after n patients have been treated at the recommended dose,
stopping when a toxicity condition is met, or demanding that n patients are
treated before stopping is allowed. By daisy-chaining together these classes
using the pipe operator from 'magrittr', it is simple to tailor the
behaviour of a dose-finding design so it behaves how the trialist wants.
Having provided a flexible interface for specifying designs, we then provide
functions to run simulations and calculate dose-paths for future cohorts of
patients.

Modular Approach to Dose Finding Clinical Trials

package-ubuntu-20.04-r-4.0.5#cran#escalation-0.1.4

<p>This function does not need to be called by users. It is used internally.
</p>

<table summary="R argblock"><tr valign="top">
<td><code>selector_factory</code></td>
<td>
<p>Object of type <code><a href="selector_factory.html">selector_factory</a></code>.</p>
</td>
</tr></table>

package-ubuntu-20.04-r-4.0.5#cran#escalation-0.1.4#docs#simulation_function

simulation_function

Description

Usage

Arguments

Value

escalation

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