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FIND (version 0.1.1)

FIND-package: FIND: Compare Objective Decision Tables for Phase I Dose-Finding Designs

Description

The FIND package provides tools to compare decision tables and evaluate operating characteristics for Phase I dose-finding trial designs. It implements five popular designs: 3+3, i3+3 (Interval-based 3+3), BOIN (Bayesian Optimal Interval), G3+3 (Generalized 3+3), and mTPI-2 (Modified Toxicity Probability Interval).

Arguments

Main Functions

Design Constructors: design_boin(), design_i3plus3(), design_mtpi2(), design_g3plus3(), design_3plus3()

Generic Functions: get_decision(), run_simulation()

Wrapper Functions: decision_table(), oc_plot()

Utility Functions: load_true(), select_mtd(), summarize_metric()

Getting Started

The S3 interface provides the cleanest workflow:


# Create design specifications
boin <- design_boin(pT = 0.25, EI = c(0.15, 0.35), npts = 12)
i3 <- design_i3plus3(pT = 0.25, EI = c(0.2, 0.3), npts = 12)

# Generate decision tables decision_table(boin, i3)

# Run simulations p.true <- c(0.05, 0.10, 0.20, 0.30, 0.45) mtd.true <- c(0, 0, 1, 0, 0)

boin_sim <- design_boin(pT = 0.25, EI = c(0.15, 0.35), ncohort = 10) results <- run_simulation(boin_sim, p.true = p.true, mtd.true = mtd.true)

# Compare operating characteristics oc_plot(results)

Vignettes

See vignette("Generate_decision_tables"), vignette("Obtain_operating_characteristics"), and vignette("S3_interface_guide") for detailed examples.

Author

Maintainer: Yunxuan Zhang yunxuanz@uchicago.edu

Authors:

References

Storer, B. E. (1989). Design and analysis of phase I clinical trials. Biometrics, 45, 925-937.

Liu S. and Yuan, Y. (2015). Bayesian Optimal Interval Designs for Phase I Clinical Trials. Journal of the Royal Statistical Society: Series C, 64, 507-523.

Guo, W., Wang, S. J., Yang, S., Lynn, H. S., and Ji, Y. (2017). A Bayesian interval dose-finding design addressing Ockham's razor: mTPI-2. Contemporary Clinical Trials, 58, 23-33.

Liu, M., Wang, S. J., and Ji, Y. (2020). The i3+3 design for phase I clinical trials. Journal of Biopharmaceutical Statistics, 30(2), 294-304.