CFO2d.simu {CFO}

Conduct one simulation using the two-dimensional calibration-free odds (2dCFO) design.

Description

In the 2dCFO design, the function is used to conduct one single simulation and find the maximum tolerated dose (MTD).

Usage

CFO2d.simu(target, p.true, init.level = c(1,1), ncohort, cohortsize, 
                 prior.para = list(alp.prior = target, bet.prior = 1 - target),
                 cutoff.eli = 0.95, early.stop = 0.95, seed = NULL)

Arguments

target

the target DLT rate.

p.true

a matrix representing the true DIL rates under the different dose levels.

init.level

the dose level assigned to the first cohort. The default value init.level is c(1,1).

ncohort

the total number of cohorts.

cohortsize

the number of patients of each cohort.

prior.para

the prior parameters for a beta distribution, where set as list(alp.prior = target, bet.prior = 1 - target) by default, alp.prior and bet.prior represent the parameters of the prior distribution for the true DLT rate at any dose level. This prior distribution is specified as Beta(alpha.prior, beta.prior).

cutoff.eli

the cutoff to eliminate overly toxic doses for safety. We recommend the default value of (cutoff.eli = 0.95) for general use.

early.stop

the threshold value for early stopping. The default value early.stop = 0.95 generally works well.

seed

an integer to be set as the seed of the random number generator for reproducible results. The default is set to NULL.

Details

The CFO2d.simu() function simulates the operating characteristics of the 2dCFO design in a dose-combination trial. The early stopping and dose elimination rules are incorporated into the 2dCFO design to ensure patient safety and benefit.

Value

The CFO2d.simu() function returns a list with the following components:

• target: the target DLT rate.

• MTD: a vector of length 2 representing the recommended dose level. MTD = (99, 99) indicates that this trial is terminated due to early stopping.

• correct: a binary indicator of whether the recommended dose level matches the target DLT rate (1 for yes).

• npatients: a matrix of the number of patients allocated to different doses.

• ntox: a matrix of the number of DLT observed for different doses.

• npercent: the percentage of patients assigned to the target DLT rate.

• over.doses: a matrix indicating whether each dose is overdosed or not (1 for yes).

• cohortdose: the dose combination assigned to each cohort.

• ptoxic: the percentage of subjects assigned to dose levels with a DLT rate greater than the target.

• patientDLT: the DLT observed at each cohort.

• sumDLT: the total number of DLT observed.

• earlystop: a binary indicator of whether the trial is early stopped (1 for yes).

Author(s)

Jialu Fang, Wenliang Wang, and Guosheng Yin

References

Jin H, Yin G (2022). CFO: Calibration-free odds design for phase I/II clinical trials. Statistical Methods in Medical Research, 31(6), 1051-1066.
Wang W, Jin H, Zhang Y, Yin G (2023). Two-dimensional calibration-free odds (2dCFO) design for phase I drug-combination trials. Frontiers in Oncology, 13, 1294258.

Examples

## Simulate a two-dimensional dose-finding trial with 20 cohorts of size 3.
p.true <- matrix(c(0.05, 0.10, 0.15, 0.30, 0.45,
                   0.10, 0.15, 0.30, 0.45, 0.55,
                   0.15, 0.30, 0.45, 0.50, 0.60), 
                 nrow = 3, ncol = 5, byrow = TRUE)
target <- 0.3; ncohort <- 20; cohortsize <- 3
CFO2dtrial <- CFO2d.simu(target, p.true, init.level = c(1,1), ncohort, cohortsize, seed = 1)
summary(CFO2dtrial)
plot(CFO2dtrial)