Ess_multiple_tte

Given phase II results are promising enough to get the "go"-decision to go to phase III this function now calculates the expected sample size for phase III.
The results of this function are necessary for calculating the utility of the program, which is then in a further step maximized by the <code>optimal_multiple_tte()</code> function

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

Ess_multiple_tte function

<dl><dt>HRgo</dt>
<dd>threshold value for the go/no-go decision rule;</dd>
<dt>n2</dt>
<dd>total sample size for phase II; must be even number</dd>
<dt>alpha</dt>
<dd>one- sided significance level</dd>
<dt>beta</dt>
<dd><code>1-beta</code> power for calculation of the number of events for phase III by Schoenfeld (1981) formula</dd>
<dt>hr1</dt>
<dd>assumed true treatment effect on HR scale for endpoint OS</dd>
<dt>hr2</dt>
<dd>assumed true treatment effect on HR scale for endpoint PFS</dd>
<dt>id1</dt>
<dd>amount of information for <code>hr1</code> in terms of number of events</dd>
<dt>id2</dt>
<dd>amount of information for <code>hr2</code> in terms of number of events</dd>
<dt>fixed</dt>
<dd>choose if true treatment effects are fixed or random</dd>
<dt>rho</dt>
<dd>correlation between the two endpoints</dd></dl>

Arguments

Expected sample size for phase III for multiple endpoints with normally distributed outcomes — Ess_multiple_tte

<dl>

<dt>HRgo</dt>
<dd>threshold value for the go/no-go decision rule;</dd>


<dt>n2</dt>
<dd>total sample size for phase II; must be even number</dd>


<dt>alpha</dt>
<dd>one- sided significance level</dd>


<dt>beta</dt>
<dd><code>1-beta</code> power for calculation of the number of events for phase III by Schoenfeld (1981) formula</dd>


<dt>hr1</dt>
<dd>assumed true treatment effect on HR scale for endpoint OS</dd>


<dt>hr2</dt>
<dd>assumed true treatment effect on HR scale for endpoint PFS</dd>


<dt>id1</dt>
<dd>amount of information for <code>hr1</code> in terms of number of events</dd>


<dt>id2</dt>
<dd>amount of information for <code>hr2</code> in terms of number of events</dd>


<dt>fixed</dt>
<dd>choose if true treatment effects are fixed or random</dd>


<dt>rho</dt>
<dd>correlation between the two endpoints</dd>

</dl>

Ess_multiple_tte: Expected sample size for phase III for multiple endpoints with normally distributed outcomes

Description

Usage

Value

Arguments