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The bfboinet package implements the Backfill Bayesian
Optimal Interval Design (BF-BOIN-ET), a novel clinical trial methodology
for dose optimization that simultaneously consider both efficacy and
toxicity outcome as described in Takeda et al (2025) <
https://doi.org/10.1002/pst.2470>. The package has been extended to
include a seamless two-stage phase I/II trial design with backfill and
joint efficacy and toxicity monitoring as described in Takeda et al
(2016)
You can install the development version of bfboinet from GitHub with: ```r # install.packages(“devtools”) devtools::install_github(“jingzhuzhuzhu/bfboinet”)
```markdown ## Basic Example
library(bfboinet)
result <- get.oc.backboinet( target_T = 0.3, toxprob, target_E = 0.25, effprob, n.dose, startdose, ncohort, cohortsize, pT.saf = 0.6 * target_T, pT.tox = 1.4 * target_T, pE.saf = 0.6 * target_E, alpha.T1 = 0.5, alpha.E1 = 0.5, tau.T, tau.E, te.corr = 0.2, gen.event.time = “weibull”, accrual, gen.enroll.time = “uniform”, n.elimination = 6, stopping.npts = 12, suspend = 0, stopping.prob.T = 0.95, stopping.prob.E = 0.9, ppsi01 = 0, ppsi00 = 40, ppsi11 = 60, ppsi10 = 100, n.sim = 1000, seed.sim = 100 )
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.
Health stats visible at Monitor.