mtaBin_sim: Design Simulator for MTA with binary outcomes

In dfmta: Phase I/II Adaptive Dose-Finding Design for MTA

Design Simulator for MTA with binary outcomes

Description

mtaBin_sim is used to generate simulation replicates of Phase I/II clinical trial for Molecularly Targeted Agent using the design proposed by Riviere et al. entitled "Phase I/II Dose-Finding Design for Molecularly Targeted Agent: Plateau Determination using Adaptive Randomization".

Usage

mtaBin_sim(ngroups=1, ndose, p_tox, p_eff, tox_max, eff_min, prior_tox,
prior_eff, poisson_rate=1, n, cohort_start=3, cohort=3, tite=TRUE, time_full,
method="MTA-RA", s_1=function(n_cur){0.2}, s_2=0.07, cycle, nsim, c_tox=0.90,
c_eff=0.40, seed=8, threads=0)

Arguments

ngroups	Number of groups for the dose-finding process leading to the recommendation of different dose levels. Several groups of efficacy (e.g. based on biomarker) sharing the same toxicity can be considered. The default value is set at 1.
ndose	Number of dose levels.
p_tox	A vector of the true toxicity probabilities associated with the doses.
p_eff	A vector (or matrix if several groups) of the true efficacy probabilities associated with the doses.
tox_max	Toxicity upper bound, i.e. maximum acceptable toxicity probability.
eff_min	Efficacy lower bound, i.e. minimum acceptable efficacy probability.
prior_tox	A vector of initial guesses of toxicity probabilities associated with the doses. Must be of same length as p_tox.
prior_eff	A vector (or matrix if several groups) of initial guesses of efficacy probabilities associated with the doses. Must be of same length as p_eff.
poisson_rate	(A Vector, if several groups, of the) Rate(s) for the Poisson process used to simulate patient arrival (for each group), i.e. expected number of arrivals per observation window. The default value is set at 1.
n	Total number of patients (per groups if several) to include in the dose-finding trial.
cohort_start	Cohort size for the start-up phase. The default value is set at 3.
cohort	Cohort size for the model phase. The default value is set at 3.
tite	A boolean indicating if the efficacy is considered as a time-to-event (default value TRUE), or if it is a binary outcome (FALSE).
time_full	Full follow-up time window. This argument is used only if tite=TRUE.
method	A character string to specify the method for dose allocation (<=> plateau determination). The default method "MTA-RA" use adaptive randomization on posterior probabilities for the plateau location. Method based on difference in efficacy probabilities is specified by "MTA-PM".
s_1	A function depending on the number of patients included used for adaptive randomization in plateau determination, only used if the estimation method chosen is "MTA-RA". The default function is function(n_cur)0.2.
s_2	Cutoff for plateau determination, only used if the estimation method chosen is "MTA-PM". Can be seen as the minimal efficacy difference of practical importance. The default value is 0.07.
cycle	Minimum waiting time between two dose cohorts (usually a toxicity cycle). This argument is used only if tite=TRUE.
nsim	Number of simulations.
c_tox	Tocixity threshold for decision rules. The default value is set at 0.90.
c_eff	Efficacy threshold for decision rules. The default value is set at 0.40.
seed	Seed of the random number generator. Default value is set at 8.
threads	Number of threads to use to do the computations. If 0, it uses as many threads as available processors.

Value

An object of class "mtaBin_sim" is returned, consisting of the operating characteristics of the design specified. Objects generated by mtaBin_sim contain at least the following components:

p_tox	True toxicities.
p_eff	True efficacies (for each group).
prior_tox	Prior toxicities.
prior_eff	Prior efficacies (for each group).
rec_dose	Percentage of Selection (for each group).
n_pat_dose	Number of patients at each dose (for each group).
n_tox	Number of toxicities at each dose (for each group).
n_eff	Number of efficacies at each dose (for each group).
inconc	Percentage of inclusive trials (for each group).
method	Allocation method.
nsim	Number of simulations.
n_pat_tot	Total patients accrued.
tox_max	Toxicity upper bound.
eff_min	Efficacy lower bound.
poisson_rate	Rate for Poisson process.
c_tox	Toxicity threshold.
c_eff	Efficacy threshold.
cohort_start	Cohort size start-up phase.
cohort	Cohort size model phase.
tite	Type of outcome for efficacy (time-to-event or binary).
time_full	If efficacy is a time-to-event, full follow-up time is also reminded.
cycle	If efficacy is a time-to-event, minimum waiting time between two dose cohorts (cycle) is also reminded.
duration	If efficacy is a time-to-event, trial mean duration is also returned.

Note

The "MTA-PM" method is not implemented for non-binary efficacy, as "MTA-RA" is recommended for general use.

Author(s)

Jacques-Henri Jourdan and Marie-Karelle Riviere-Jourdan [e-mail]

References

Riviere, M-K., Yuan, Y., Jourdan, J-H., Dubois, F., and Zohar, S. Phase I/II Dose-Finding Design for Molecularly Targeted Agent: Plateau Determination using Adaptive Randomization.

See Also

mtaBin_next.

Examples

p_tox_sc1 = c(0.005, 0.01, 0.02, 0.05, 0.10, 0.15)
p_eff_sc1_g1 = c(0.01, 0.10, 0.30, 0.50, 0.80, 0.80)
p_tox_sc2 = c(0.01, 0.05, 0.10, 0.25, 0.50, 0.70)
p_eff_sc2_g2 = matrix(c(0.40, 0.01, 0.40, 0.02, 0.40, 0.05, 0.40, 0.10, 0.40,
0.35, 0.40, 0.55), nrow=2)
prior_tox = c(0.02, 0.06, 0.12, 0.20, 0.30, 0.40)
prior_eff = c(0.12, 0.20, 0.30, 0.40, 0.50, 0.59)
prior_eff2 = rbind(prior_eff, prior_eff)
s_1=function(n_cur){0.2}
n=60


# With only one group and efficacy as time-to-event
sim1 = mtaBin_sim(ngroups=1, ndose=6, p_tox= p_tox_sc1, p_eff= p_eff_sc1_g1,
       tox_max=0.35, eff_min=0.20, prior_tox=prior_tox, prior_eff= prior_eff,
       poisson_rate=0.28, n=60, cohort_start=3, cohort=3, tite=TRUE,
       time_full=7, cycle=3, nsim=1)
sim1

# With only one group and efficacy binary
sim2 = mtaBin_sim(ngroups=1, ndose=6, p_tox= p_tox_sc1, p_eff= p_eff_sc1_g1,
       tox_max=0.35, eff_min=0.20, prior_tox=prior_tox, prior_eff= prior_eff,
       n=n, cohort_start=3, cohort=3, tite=FALSE, method="MTA-RA",
       s_1=function(n_cur){0.2*(1-n_cur/n)}, nsim=1)
sim2

# With only two groups and efficacy as time-to-event
sim3 = mtaBin_sim(ngroups=2, ndose=6, p_tox= p_tox_sc2, p_eff= p_eff_sc2_g2,
               tox_max=0.35, eff_min=0.20, prior_tox=prior_tox,
               prior_eff= prior_eff2, poisson_rate=c(0.40,0.25) , n=60,
               cohort_start=3, cohort=3, tite=TRUE, time_full=7,
               method="MTA-PM", s_2=0.07, cycle=3, nsim=1, c_tox=0.90,
               c_eff=0.40)
sim3

dfmta documentation built on May 4, 2022, 1:06 a.m.