h_enroll_backfill_patients

This function executes backfill enrollment according to the priority rule,
updating the data object, backfill cohort queue, and patient counter.

internal

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 

h_enroll_backfill_patients function

<dl><dt>backfill_cohorts</dt>
<dd>(<code>list</code>) current queue of backfill cohorts.</dd>
<dt>data</dt>
<dd>(<code>Data</code>) current trial data.</dd>
<dt>backfill</dt>
<dd>(<code>Backfill</code>) with priority and recruitment rules.</dd>
<dt>cohort_size</dt>
<dd>(<code>count</code>) size of the active cohort.</dd>
<dt>backfill_patients</dt>
<dd>(<code>count</code>) number of enrolled backfill patients.</dd>
<dt>current_args</dt>
<dd>(<code>data.frame</code>) arguments for the truth function.</dd>
<dt>truth</dt>
<dd>(<code>function</code>) defining true DLT probability.</dd>
<dt>truthResponse</dt>
<dd>(<code>function</code>) defining true response probability.</dd></dl>

Arguments

Helper Function to Enroll Backfill Patients — h_enroll_backfill_patients

<dl>

<dt>backfill_cohorts</dt>
<dd>(<code>list</code>) current queue of backfill cohorts.</dd>


<dt>data</dt>
<dd>(<code>Data</code>) current trial data.</dd>


<dt>backfill</dt>
<dd>(<code>Backfill</code>) with priority and recruitment rules.</dd>


<dt>cohort_size</dt>
<dd>(<code>count</code>) size of the active cohort.</dd>


<dt>backfill_patients</dt>
<dd>(<code>count</code>) number of enrolled backfill patients.</dd>


<dt>current_args</dt>
<dd>(<code>data.frame</code>) arguments for the truth function.</dd>


<dt>truth</dt>
<dd>(<code>function</code>) defining true DLT probability.</dd>


<dt>truthResponse</dt>
<dd>(<code>function</code>) defining true response probability.</dd>

</dl>

Helper Function to Enroll Backfill Patients

h_enroll_backfill_patients: Helper Function to Enroll Backfill Patients

Description

Usage

Value

Arguments