optimal_multitrial_generic

Generic function for optimizing multi-trial programs

internal

Plan optimal sample size allocation and go/no-go decision rules
for phase II/III drug development programs with time-to-event, binary or
normally distributed endpoints when assuming fixed treatment effects or a
prior distribution for the treatment effect, using methods from Kirchner et al.
(2016) <doi:10.1002/sim.6624> and Preussler (2020). Optimal is in the sense of
maximal expected utility, where the utility is a function taking into account
the expected cost and benefit of the program. It is possible to extend to more
complex settings with bias correction (Preussler S et al. (2020)
<doi:10.1186/s12874-020-01093-w>), multiple phase III trials (Preussler et
al. (2019) <doi:10.1002/bimj.201700241>), multi-arm trials (Preussler et al.
(2019) <doi:10.1080/19466315.2019.1702092>), and multiple endpoints
(Kieser et al. (2018) <doi:10.1002/pst.1861>).

Lukas D. Sauer

drugdevelopR

Utility-Based Optimal Phase II/III Drug Development Planning

Stella Erdmann

Johannes Cepicka

Marietta Kirchner

Meinhard Kieser

optimal_multitrial_generic function

<dl><dt>case</dt>
<dd>choose case: "at least 1, 2 or 3 significant trials needed for approval"</dd>
<dt>strategy</dt>
<dd>choose strategy: "conduct 1, 2, 3 or 4 trials in order to achieve the case's goal"; TRUE calculates all strategies of the selected <code>case</code></dd></dl>

Arguments

In other settings, the definition of "small", "medium" and "large" effect
sizes can be user-specified using the input parameters <code>steps1</code>, <code>stepm1</code> and
<code>stepl1</code>. Due to the complexity of the multitrial setting, this feature is
not included for this setting. Instead, the effect sizes were set to
to predefined values as explained under sProg1, sProg2 and sProg3 in the
Value section.

Effect sizes

Generic function for optimizing multi-trial programs — optimal_multitrial_generic

<dl>

<dt>case</dt>
<dd>choose case: "at least 1, 2 or 3 significant trials needed for approval"</dd>


<dt>strategy</dt>
<dd>choose strategy: "conduct 1, 2, 3 or 4 trials in order to achieve the case's goal"; TRUE calculates all strategies of the selected <code>case</code></dd>

</dl>

In other settings, the definition of "small", "medium" and "large" effect
sizes can be user-specified using the input parameters <code>steps1</code>, <code>stepm1</code> and
<code>stepl1</code>. Due to the complexity of the multitrial setting, this feature is
not included for this setting. Instead, the effect sizes were set to
to predefined values as explained under sProg1, sProg2 and sProg3 in the
Value section.

optimal_multitrial_generic: Generic function for optimizing multi-trial programs

Description

Usage

Arguments

Effect sizes