Backfill-class

.Backfill

Backfill

.DefaultBackfill

<a href="https://lifecycle.r-lib.org/articles/stages.html#experimental"><img src="figures/lifecycle-experimental.svg?package=crmPack&version=2.1.0" alt="[Experimental]"></a>
Class representing a backfilling rule in a clinical trial design.

Implements a wide range of dose escalation
designs. The focus is on model-based designs, ranging from classical and
modern continual reassessment methods (CRMs) based on dose-limiting toxicity
endpoints to dual-endpoint designs taking into account a biomarker/efficacy
outcome. Bayesian inference is performed via MCMC sampling in JAGS, and it is easy
to setup a new design with custom JAGS code. However, it is also possible to
implement 3+3 designs for comparison or models with non-Bayesian estimation.
The whole package is written in a modular form in the S4 class system, making it
very flexible for adaptation to new models, escalation or stopping rules.
Further details are presented in
Sabanés Bové et al. (2019) <doi:10.18637/jss.v089.i10>.

Daniel Sabanes Bove

crmPack

Object-Oriented Implementation of Dose Escalation Designs

Daniel Sabanés Bové

Wai Yin Yeung

Burak Kuersad Guenhan

Giuseppe Palermo

Thomas Jaki

Jiawen Zhu

Ziwei Liao

Dimitris Kontos

Marlene Schulte-Goebel

Doug Kelkhoff

Oliver Boix

Robert Adams

Clara Beck

John Kirkpatrick

Wojciech Wójciak

Guanya Peng

Prerana Chandratre

F. Hoffmann-La Roche AG 

Merck Healthcare KGaA 

Bayer AG 

RPACT GmbH 

Backfill-class function

<dl><dt>cohort_size</dt>
<dd>(<code>CohortSize</code>) see the slot definition.</dd>
<dt>opening</dt>
<dd>(<code>Opening</code>) see the slot definition.</dd>
<dt>recruitment</dt>
<dd>(<code>Recruitment</code>) see the slot definition.</dd>
<dt>max_size</dt>
<dd>(<code>count</code>) see the slot definition.</dd>
<dt>priority</dt>
<dd>(<code>character</code>) see the slot definition.</dd></dl>

Arguments

<dl>
<dt><code>cohort_size</code></dt>
<dd>(<code>CohortSize</code>) the size of cohorts to be backfilled.</dd></dl>
<dt><code>opening</code></dt>
<dd>(<code>Opening</code>) the opening criteria for backfilling.</dd>
<dt><code>recruitment</code></dt>
<dd>(<code>Recruitment</code>) recruitment criteria for backfilling.</dd>
<dt><code>max_size</code></dt>
<dd>(<code>count</code>) the maximum number of patients to be backfilled.</dd>
<dt><code>priority</code></dt>
<dd>(<code>character</code>) the priority rule for backfilling,
one of "highest", "lowest", or "random".</dd>

Slots

<a href='https://lifecycle.r-lib.org/articles/stages.html#experimental'><img src='figures/lifecycle-experimental.svg' alt='[Experimental]' /></a>
Class representing a backfilling rule in a clinical trial design.

Backfill class — Backfill-class

<dl>

<dt>cohort_size</dt>
<dd>(<code>CohortSize</code>) see the slot definition.</dd>


<dt>opening</dt>
<dd>(<code>Opening</code>) see the slot definition.</dd>


<dt>recruitment</dt>
<dd>(<code>Recruitment</code>) see the slot definition.</dd>


<dt>max_size</dt>
<dd>(<code>count</code>) see the slot definition.</dd>


<dt>priority</dt>
<dd>(<code>character</code>) see the slot definition.</dd>

</dl>

<dl>
<dt><code>cohort_size</code></dt>
<dd>(<code>CohortSize</code>) the size of cohorts to be backfilled.</dd>


<dt><code>opening</code></dt>
<dd>(<code>Opening</code>) the opening criteria for backfilling.</dd>


<dt><code>recruitment</code></dt>
<dd>(<code>Recruitment</code>) recruitment criteria for backfilling.</dd>


<dt><code>max_size</code></dt>
<dd>(<code>count</code>) the maximum number of patients to be backfilled.</dd>


<dt><code>priority</code></dt>
<dd>(<code>character</code>) the priority rule for backfilling,
one of "highest", "lowest", or "random".</dd>


</dl>

<code>Backfill</code> class

Backfill-class: `Backfill` class

Description

Usage

Value

Arguments

Slots