Backfill Bayesian Optimal Interval Design Using Efficacy and Toxicity.

bfboinet

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) <DOI>.

Installation

You can install the development version of bfboinet from GitHub with:

# install.packages("devtools")
devtools::install_github("jingzhuzhuzhu/bfboinet")

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### **3. Usage Example**

Basic Example

library(bfboinet)

Simulate a dose-finding trial

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 )