Package: iAdapt 2.0.1

Alyssa Vanderbeek

iAdapt: Two-Stage Adaptive Dose-Finding Clinical Trial Design

Simulate and implement early phase two-stage adaptive dose-finding design for binary and quasi-continuous toxicity endpoints. See Chiuzan et al. (2018) for further reading <doi:10.1080/19466315.2018.1462727>.

Authors:Alyssa Vanderbeek [aut, cre], Laura Cosgrove [ctb], Elizabeth Garrett-Mayer [ctb], Cody Chiuzan [ctb]

iAdapt_2.0.1.tar.gz
iAdapt_2.0.1.tar.gz(r-4.5-noble)iAdapt_2.0.1.tar.gz(r-4.4-noble)
iAdapt_2.0.1.tgz(r-4.4-emscripten)iAdapt_2.0.1.tgz(r-4.3-emscripten)
iAdapt.pdf |iAdapt.html✨
iAdapt/json (API)

# Install 'iAdapt' in R:

install.packages('iAdapt', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

TOX - Sample array of toxicity probabilities for 6 doses. Taken from Du et al.

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.18 score 7 scripts 148 downloads 20 exports 33 dependencies

Last updated 3 years agofrom:48db1d3f47. Checks:OK: 2. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Dec 23 2024
R-4.5-linux	OK	Dec 23 2024

Exports:beta.ab dlt.prob eff.stg1 eff.stg1.nTTP get.thresh LRtox LRtox.nTTP nTTP.indiv.sim rand.prob rand.stg2 rand.stg2.nTTP runExample safe.dose safe.dose.nTTP sim.plot sim.summary sim.trials sim.trials.nTTP tox.profile tox.profile.nTTP

Dependencies:base64enc bslib cachem cli commonmark crayon digest fastmap fontawesome fs glue htmltools httpuv jquerylib jsonlite later lattice lifecycle magrittr Matrix memoise mime promises R6 rappdirs Rcpp rlang sass shiny shinydashboard sourcetools withr xtable

Trial implementation

Rendered fromImplementation_example.Rmdusingknitr::rmarkdownon Dec 23 2024.

Last update: 2021-08-06
Started: 2019-08-29

Trial simulation with binary toxicity measure

Rendered fromDLT_simulation_example.Rmdusingknitr::rmarkdownon Dec 23 2024.

Last update: 2021-08-06
Started: 2020-09-02

Trial simulation with quasi-continuous toxicity measure

Rendered fromnTTP_simulation_example.Rmdusingknitr::rmarkdownon Dec 23 2024.

Last update: 2021-08-06
Started: 2020-09-02

Citation

Readme and manuals

Help Manual

Help page	Topics
Calculate DLT probability corresponding to average nTTP for each dose	dlt.prob
Generates efficacy outcomes for stage 1 when using binary toxicity	eff.stg1
Generates efficacy outcomes for stage 1 when using nTTP to measure toxicity	eff.stg1.nTTP
Obtain average nTTP at each dose level	get.thresh
Calculates likelihood of safety for single dose	LRtox
Calculates likelihood of safety for single dose, using nTTP	LRtox.nTTP
Simulate full trial (both stages) x times when using nTTP to measure toxicity	nTTP.indiv.sim
Calculates randomization probabilities and dose allocation for next patient	rand.prob
Stage 2 Adaptive Randomization	rand.stg2
Stage 2 Adaptive Randomization with nTTP to monitor toxicity	rand.stg2.nTTP
Identify safe/acceptable doses from stage 1 based on observed binary toxicity	safe.dose
Identify safe/acceptable doses from stage 1 based on nTTP scores.	safe.dose.nTTP
Generate plots for estimated percent allocation and response per dose.	sim.plot
Visualize simulation results (Stages 1&2)	sim.summary
Simulate full trial (both stages) x times	sim.trials
Simulate full trial (both stages) x times when using nTTP to measure toxicity	sim.trials.nTTP
Sample array of toxicity probabilities for 6 doses. Taken from Du et al.	TOX
Generates DLTs and calculates the likelihood-ratio (LR) for each dose	tox.profile
Generate nTTPs toxicity scores and the likelihhood-ratio (LR) per dose	tox.profile.nTTP