nsim: Simulate a single or n prospective clinical trial(s) using...

In dfpk: Bayesian Dose-Finding Designs using Pharmacokinetics (PK) for Phase I Clinical Trials

Description

nsim is used to simulate a single or "n" prospective clinical trial(s) using the PK data and then link them to toxicity under a specified dose-toxicity configuration. The objective is to determine the maximum tolerated dose (MTD).

Usage

 
nsim(doses, N, cohort, icon, theta, model, simulatedData, TR, prob = 0.9, AUCmethod = 2, 
     options = list(nchains = 4, niter = 4000, nadapt = 0.8), betapriors = NULL,
     thetaL=NULL, p0 = 0, L = 0, CI = FALSE, seed = 190591)

Arguments

doses	A vector with the doses panel.
N	The total sample size per trial.
cohort	The cohort size in the trial.
icon	A vector containing the index of real blood sampling.
theta	The toxicity threshold.
model	A character string to specify the selected dose-finding model. See for details dtox, pkcov, pkcrm, pktox, pkpop, pklogit.
simulatedData	A list for each trial containing the simulated datasets; a "scen" object. See for details sim.data.
TR	The total number of trials to be simulated.
prob	The threshold of the posterior probability of toxicity for the stopping rule in the selected model; defaults to 0.9. See for details dtox, pkcov, pkcrm, pktox, pkpop, pklogit.
AUCmethod	A string number specifying the estimation method for AUC. Valid choices are "1" for a "compartmental method" and "2" for non-compartmental method; defaults to 2.
options	A list with the Stan model's options; the number of chains, how many iterations for each chain and the number of warmup iterations; defaults to options = list(nchains = 4, niter = 4000, nadapt = 0.8)
betapriors	A vector with the value for the prior distribution of the regression parameters in the selected model; defaults to NULL.
thetaL	A second threshold of AUC in the pkcrm model; defaults to theta in the PKCRM model and NULL for the models dtox, pkcov, pktox, pkpop and pklogit.
p0	The skeleton of CRM for pkcrm; defaults to NULL.
L	The AUC threshold to be set before starting the trial for pkcrm; defaults to NULL.
CI	A logical constant indicating the estimated 95% credible interval; defaults to FALSE.
seed	The seed of the random number generator that is used at the beginning of each trial; defaults to 190591.

Value

An object of class "dosefinding" is returned, consisting of determination of the next recommended dose and estimations. Objects generated by nsim contain at least the following components:

pid	The patient's ID during the trial.
N	The total sample size per trial.
time	The sampling time points.
doses	A vector with the doses panel.
conc	The estimated concentration values for each patient at each dose.
nchains	The number of chains in the Stan model.
niter	The number of iterations for each chain in the Stan model.
nadapt	The number of warmup iterations.
newDose	The next maximum tolerated dose (MTD) if TR=1 otherwise the percentage of MTD selection for each dose level after all trials starting from dose 0; equals to 0 if the TR=1 has stopped before the end, according to the stopping rules.
MTD	A vector containing the next maximum tolerated doses (MTD) of each trial (TR); equals to 0 if the trial has stopped before the end, according to the stopping rules.
theta	The tocixity threshold.
doseLevels	A vector of dose levels assigned to patients in the trial.
toxicity	The estimated toxicity outcome.
AUCs	A vector with the computed AUC values of each patient.
TR	The total number of trials to be simulated.
preal	The prior toxicity probabilities.
pstim	The mean values of the estimated probabilities of toxicity.
pstimQ1	The 1st quartile of the estimated probabilities of toxicity if CI = TRUE, otherwise is NULL.
pstimQ3	The 3rd quartile of the estimated probabilities of toxicity if CI = TRUE, otherwise is NULL.
model	A character string to specify the selected dose-finding model. See for details dtox, pkcov, pkcrm, pktox, pkpop, pklogit.
seed	The seed of the random number generator that is used at the beginning of each trial.

Author(s)

Artemis Toumazi [e-mail], Moreno Ursino [e-mail], Sarah Zohar [e-mail]

References

Ursino, M., et al, (2017) Dose-finding methods for Phase I clinical trials using pharmacokinetics in small populations, Biometrical Journal, <doi:10.1002/bimj.201600084>.

Toumazi, A., et al, (2018) dfpk: An R-package for Bayesian dose-finding designs using pharmacokinetics (PK) for phase I clinical trials, Computer Methods and Programs in Biomedicine, <doi:10.1016/j.cmpb.2018.01.023>.

See Also

sim.data

Examples

    ## Not run: 
        TR = 10                                 # Total number of simulations                 
        N = 30                         
        limitTox <- 10.96 
        PKparameters <- c(2, 10, 100)             # PK parameters ka,CL,V
        omegaIIV <- 0.7                        
        omegaAlpha <- 0
        doses <- c(12.59972, 34.65492, 44.69007, 60.80685, 83.68946, 100.37111)     
        timeSampling <- seq(0, 24, length.out=48)    
        sigma <- rep(0.2, length(timeSampling))         

        gen.scen <- sim.data(PKparameters,omegaIIV,omegaAlpha,sigma,doses,
                             limitTox,timeSampling, N, TR)

        cohort = 1
        simulatedData <- gen.scen  
        icon <- c(2:6, round(seq(9, 48, ((48-9)/4))))      
        theta <- 0.2                           

        ##############################################
        ############### Select a model ###############
        ##############################################

        model = "pktox"

        ############################################
        ############ Run the simulation(s) #########
        ############################################
        
        results_sim <- nsim(doses, N, cohort, icon, theta, model, simulatedData, TR, 
                            AUCmethod = 1)
        results_sim 
    
## End(Not run)

dfpk documentation built on May 2, 2019, 8:31 a.m.