CFO.simu {CFO}

Conduct one simulation using the Calibration-free odds (CFO) or accumulative CFO (aCFO) design.

Description

In the CFO and aCFO designs, the function is used to conduct one single simulation and find the maximum tolerated dose (MTD).

Usage

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

Arguments

design

option for selecting different designs, which can be set as 'CFO' and 'aCFO'.

target

the target DLT rate.

p.true

the true DLT rates under the different dose levels.

init.level

the dose level assigned to the first cohort. The default value init.level is 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 value is set to NULL.

Value

The CFO.simu function returns a list object comprising the following components:

• target: the target DLT rate.

• MTD: the selected MTD. MTD = 99 indicates that the simulation 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: the total number of patients allocated to all dose levels.

• ntox: the total number of DLTs observed for all dose levels.

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

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

• cohortdose: a vector including the dose level assigned to each cohort.

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

• patientDLT: a vector including the DLT outcome observed for each patient.

• sumDLT: the total number of DLT observed.

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

Note

The CFO.simu() function is designed to conduct a single CFO or aCFO simulation. If design = 'CFO', it corresponds to the CFO design. If design = 'aCFO', it corresponds to the aCFO design.
The early stopping and dose elimination rules are incorporated into the CFO or aCFO design to ensure patient safety and benefit. If there is substantial evidence indicating that the current dose level exhibits excessive toxicity, we exclude the current dose level as well as higher dose levels from the trial. If the lowest dose level is overly toxic, the trial will be terminated according to the early stopping rule. Upon the predefined maximum sample size is reached or the lowest dose level is over-toxicity, the experiment is concluded, and the MTD is determined using isotonic regression.

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.
Fang J, Yin G (2024). Fractional accumulative calibration‐free odds (f‐aCFO) design for delayed toxicity in phase I clinical trials. Statistics in Medicine.

Examples

target <- 0.2; ncohort <- 12; cohortsize <- 3; init.level <- 1
p.true <- c(0.01, 0.07, 0.20, 0.35, 0.50, 0.65, 0.80)
### find the MTD for a single CFO simulation
CFOtrial <- CFO.simu(design = 'CFO', target, p.true, init.level, ncohort, cohortsize, seed = 1)
summary(CFOtrial)
plot(CFOtrial)

# This test may take longer than 5 seconds to run
# It is provided for illustration purposes only
# Users can run this code directly
### find the MTD for a single aCFO simulation
aCFOtrial <- CFO.simu(design = 'aCFO', target, p.true, init.level, ncohort, cohortsize, seed = 1)
summary(aCFOtrial)
plot(aCFOtrial)