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()