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Title: Model-Based Dose-Escalation Trials
Version: 0.3-1
Date: 2017-11-03
Description: User-friendly Shiny apps for designing and evaluating phase I cancer clinical trials, with the aim to estimate the maximum tolerated dose (MTD) of a novel drug, using a Bayesian decision procedure based on logistic regression.
License: GPL-2
Imports: knitr, rhandsontable, shiny, shinyBS
VignetteBuilder: knitr
BugReports: https://github.com/PhilipPallmann/modest/issues/
NeedsCompilation: no
Packaged: 2017-11-16 17:55:51 UTC; mcbpp
Author: Philip Pallmann [aut, cre], Fang Wan [aut]
Maintainer: Philip Pallmann <pallmannp@cardiff.ac.uk>
Repository: CRAN
Date/Publication: 2017-11-16 22:24:10 UTC

Shiny GUIs for model-based dose-escalation studies

Description

A user-friendly tool to design and evaluate phase I cancer clinical trials, with the aim to estimate the maximum tolerated dose (MTD) of a novel drug. This is a point-and-click implementation of the dose-escalation study design proposed by Zhou & Whitehead (2003) that uses a Bayesian logistic regression method. The graphical user interfaces (GUIs) are based on R's Shiny system.

Usage

design()
conduct()

Details

This package contains two separate modules:

1) The design module allows to investigate different design options and parameters, and to simulate their operating characteristics under various scenarios. Type design() and the GUI will open in a browser window.

2) The conduct module provides guidance for dose selection throughout the study, and a recommendation for the MTD at the end. Type conduct() and the GUI will open in a browser window.

Both modules generate a variety of graphs to visualise data and design properties, and create downloadable PDF reports of simulation results and study data analyses.

Author(s)

Philip Pallmann (pallmannp@cardiff.ac.uk)

References

Zhou Y, Whitehead J (2003) Practical implementation of Bayesian dose-escalation procedures. Drug Information Journal, 37(1), 45–59.

Examples


design()
conduct()

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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