| Type: | Package |
| Title: | Simulates SPSO and Efftox Phase 12 Trials with Correlated Outcomes |
| Version: | 1.5 |
| Author: | Andrew G Chapple |
| Maintainer: | Andrew G Chapple <achapp@lsuhsc.edu> |
| Description: | Simulating and conducting four phase 12 clinical trials with correlated binary bivariate outcomes described. Uses the 'Efftox' (efficacy and toxicity tradeoff, https://biostatistics.mdanderson.org/SoftwareDownload/SingleSoftware/Index/2) and SPSO (Semi-Parametric Stochastic Ordering) models with Utility and Desirability based objective functions for dose finding. |
| License: | GPL-2 |
| Imports: | Rcpp (≥ 0.12.18), mvtnorm |
| LinkingTo: | Rcpp, RcppArmadillo |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.1.1 |
| NeedsCompilation: | yes |
| Repository: | CRAN |
| Packaged: | 2020-07-31 16:38:52 UTC; achapp |
| Date/Publication: | 2020-07-31 17:00:02 UTC |
Determines the optimal dose to assign the next patient cohort.
Description
This function returns the optimal acceptable dose number to assign the next patient cohort or stops the trial if no dose is deemed acceptable.
Usage
AssignEffTox(
YE,
YT,
Doses,
Dose,
DosesTried,
Hypermeans,
Hypervars,
Contour,
PiLim,
ProbLim,
B
)
Arguments
YE |
Vector containing observed efficacy indicators. |
YT |
Vector containing observed toxicity indicators. |
Doses |
Vector containing numbered Doses of patients in trial. |
Dose |
Vector containing the standardized doses considered. |
DosesTried |
Binary vector corresponding to which doses have been tried. |
Hypermeans |
Vector containing prior hypermeans of length 6 for Eff-Tox parameters. |
Hypervars |
Vector containing prior hypervariances of length 6 for Eff-Tox parameters. |
Contour |
Vector containing 4 entries used to make the desireability function. Contour[1] contains a desired toxicity probability given efficacy, Countour[2] contains a desired efficacy probability given toxicity, and (Contour[3],Contour[4]) is an equally desireable pair of efficacy and toxicity probabilities that are non-zero or one. |
PiLim |
Vector of length two with PiLim[1] containing the acceptable lower limit on efficacy probability and PiLim[2] containing the acceptable upper limit on toxicity probability. |
ProbLim |
Vector of length two with ProbLim[1] containing the probability cutoff for acceptable efficacy probability and ProbLim[2] containing the probability cutoff for acceptable toxicity probability. |
B |
Number of iterations to perform in the MCMC. |
Value
The optimal dose level to administer the next patient cohort.
Examples
##Doses, YE,YT
Doses= c(1,1,1,2,2,2,1,1,1,3,3,3,1,1,1,2,2,2)
YE = c(0,0,1,1,1,0,0,0,0,1,1,1,0,0,1,1,1,0)
YT=c(0,0,0,1,1,0,1,0,0,1,1,1,0,0,0,1,0,0)
##Vector of Numerical Doses
Dose = c(1,2,3,3.5,5)
Dose=(Dose-mean(Dose))/sd(Dose)
##Five doses, but only 3 tried so we have
DosesTried=c(1,1,1,0,0)
## Contour Vector
Contour = c(.35, .75,.7,.4)
##Hypermeans
Hypermeans = c(.022,3.45,0,-4.23,3.1,0)
Hypervars = c(2.6761, 2.6852, .2, 3.1304, 3.1165, 1)
Hypervars=Hypervars^2
##Acceptability Criteria
PiLim = c(.3,.4)
ProbLim=c(.1,.1)
##Number of iterations
B=2000
AssignEffTox(YE,YT, Doses, Dose, DosesTried, Hypermeans, Hypervars, Contour, PiLim, ProbLim, B )
Determines the optimal dose to assign the next patient cohort.
Description
This function returns the optimal acceptable dose number to assign the next patient cohort or stops the trial if no dose is deemed acceptable.
Usage
AssignEffToxUT(
YE,
YT,
Doses,
Dose,
DosesTried,
Hypermeans,
Hypervars,
UT,
PiLim,
ProbLim,
B
)
Arguments
YE |
Vector containing observed efficacy indicators. |
YT |
Vector containing observed toxicity indicators. |
Doses |
Vector containing numbered Doses of patients in trial. |
Dose |
Vector containing the standardized doses considered. |
DosesTried |
Binary vector corresponding to which doses have been tried. |
Hypermeans |
Vector containing prior hypermeans of length 6 for Eff-Tox parameters. |
Hypervars |
Vector containing prior hypervariances of length 6 for Eff-Tox parameters. |
UT |
2x2 utility matrix. |
PiLim |
Vector of length two with PiLim[1] containing the acceptable lower limit on efficacy probability and PiLim[2] containing the acceptable upper limit on toxicity probability. |
ProbLim |
Vector of length two with ProbLim[1] containing the probability cutoff for acceptable efficacy probability and ProbLim[2] containing the probability cutoff for acceptable toxicity probability. |
B |
Number of iterations to perform in the MCMC. |
Value
The optimal dose level to administer the next patient cohort.
Generate binary bivariate data.
Description
Generates binary bivariate data from a 2x2 matrix of probabilities.
Usage
GETBIN(PVEC)
Arguments
PVEC |
Contains TRUE pi00,pi10, pi01, pi11 for each dose |
Value
Binary bivariate random variate (YE,YT).
Returns the desireability value of a dose.
Description
Takes estimated posterior mean efficacy and toxicity values and returns the posterior mean desireability score for a given tradeoff contour.
Usage
GetDesire(PE, PT, Contour)
Arguments
PE |
True or estimated probability of efficacy. |
PT |
True of estimated probability of toxicity. |
Contour |
Vector containing 4 entries used to make the desireability function. Contour(1) contains a desired toxicity probability given efficacy, Countour(2) contains a desired efficacy probability given toxicity, and (Contour(3),Contour(4)) is an equally desireable pair of efficacy and toxicity probabilities that are non zero or one. |
Value
Computes the real-valued desireability for an estimated (PE, PT) pair and elicited co
Examples
PE=.6
PT=.2
##Contour values
Contour=c(.35,.7,.8,.6)
GetDesire(PE,PT,Contour)
Assigns next patient cohort based on the Efftox model with a Desirability based objective function.
Description
Provides the optimal dose level as determined by the Efftox model, posterior mean toxicity probability, efficacy probability, and desirability of each dose level. Doses that are unacceptably toxic or inefficous have a desirability of 0.
Usage
GetEfftoxContour(
YE,
YT,
Doses,
Dose,
Dosetried,
cohort,
Contour,
CutE,
CutT,
AcceptE,
AcceptT,
HypermeansEFF,
HypervarsEFF,
B
)
Arguments
YE |
Length n binary indicator vector of efficacy status. |
YT |
Length n binary indicator vector of toxicity status. |
Doses |
Length n vector of integer Doses given to patients. |
Dose |
Vector of standardized log-dose levels considered in the trial. |
Dosetried |
Binary vector corresponding to which doses have been tried. |
cohort |
Cohort size for the trial. |
Contour |
Contour vector for desirability function. Contains in order: (pi_1,E,pi_2,T,pi_3,E,pi_4,T). |
CutE |
Cutoff for efficacy probability acceptability. Dose-efficacy probabilities must be larger than this for patient assignment. |
CutT |
Cutoff for toxicity probability acceptability. Dose-toxicity probabilities must be smaller than this for patient assignment. |
AcceptE |
Posterior probability threshold for efficacy acceptability. |
AcceptT |
Posterior probability threshold for toxicity acceptability. |
HypermeansEFF |
Hypermeans for the Efftox model. In order, entries are hypermeans for (beta_0,E,beta_1,E,beta_2,E,beta_0,T,beta_1,T,psi). |
HypervarsEFF |
Hypervariances for the Efftox model. In order, entries are hypervariances for (beta_0,E,beta_1,E,beta_2,E,beta_0,T,beta_1,T,psi). |
B |
Number of iterations to run for the MCMC. |
Value
A list containing the optimal dose level to assign the next patient cohort in the first entry and a matrix in the second entry, with rows corresponding to (1) the dose #, (2) mean posterior toxicity probability at each dose, mean posterior efficacy probability at each dose, and acceptable posterior desirability score of each dose level (0s indicate the dose is not acceptably efficous or toxic).
Examples
##Get the Data
##True Tox Prob
PT = c(.1,.2,.25,.5,.7)
##True EFF Prob
PE = c(.3,.4,.7,.5,.5)
Doses=c(1,1,1,2,2,2,3,3,3,2,2,2,1,1,1,2,2,2,3,3,3)
YE=Doses
YT=Doses
Dosetried=rep(0,length(PE))
##Generate data
for(k in 1:length(PE)){
if(sum(Doses==k)){
##Dose level has been tried
Dosetried[k]=1
YE[Doses==k]=rbinom(sum(Doses==k),1,PE[k])
YT[Doses==k]=rbinom(sum(Doses==k),1,PT[k])
}
}
##Hypermeans and hypervariances
HypermeansEFF = c(.022,3.45,0,-4.23,3.1,0)
HypervarsEFF = c(2.6761, 2.6852, .2, 3.1304, 3.1165, 1)
HypervarsEFF=HypervarsEFF^2
##Vector of Numerical Doses
Dose = c(1,2,3,3.5,5)
##Dose for Eff-Tox
Dose=log(Dose)-mean(log(Dose))
##Trial parameters
cohort=3
##Contour vector
Contour = c(.35, .75,.7,.4)
CutE=.3 ##Efficacy threshold
CutT=.4 ##Toxicity threshold
AcceptE=.3 ##Eff acceptability threshold
AcceptT= .3 ##Tox acceptability threshold
B=100##Number of iterations
GetEfftoxContour(YE, YT,Doses,Dose, Dosetried,
cohort, Contour,CutE, CutT, AcceptE, AcceptT,
HypermeansEFF, HypervarsEFF,B )
Assigns next patient cohort based on the Efftox model with a Utility based objective function.
Description
Provides the optimal dose level as determined by the Efftox model, posterior mean toxicity probability, efficacy probability, and mean utility of each dose level. Doses that are unacceptably toxic or inefficous have a utility of 0.
Usage
GetEfftoxUt(
YE,
YT,
Doses,
Dose,
Dosetried,
cohort,
UT,
CutE,
CutT,
AcceptE,
AcceptT,
HypermeansEFF,
HypervarsEFF,
B
)
Arguments
YE |
Length n binary indicator vector of efficacy status. |
YT |
Length n binary indicator vector of toxicity status. |
Doses |
Length n vector of integer Doses given to patients. |
Dose |
Vector of standardized log-dose levels considered in the trial. |
Dosetried |
Binary vector corresponding to which doses have been tried. |
cohort |
Cohort size for the trial. |
UT |
Utility matrix for the four bivariate (efficacy, toxicity) events. |
CutE |
Cutoff for efficacy probability acceptability. Dose-efficacy probabilities must be larger than this for patient assignment. |
CutT |
Cutoff for toxicity probability acceptability. Dose-toxicity probabilities must be smaller than this for patient assignment. |
AcceptE |
Posterior probability threshold for efficacy acceptability. |
AcceptT |
Posterior probability threshold for toxicity acceptability. |
HypermeansEFF |
Hypermeans for the Efftox model. In order, entries are hypermeans for (beta_0,E,beta_1,E,beta_2,E,beta_0,T,beta_1,T,psi). |
HypervarsEFF |
Hypervariances for the Efftox model. In order, entries are hypervariances for (beta_0,E,beta_1,E,beta_2,E,beta_0,T,beta_1,T,psi). |
B |
Number of iterations to run for the MCMC. |
Value
A list containing the optimal dose level to assign the next patient cohort in the first entry and a matrix in the second entry, with rows corresponding to (1) the dose #, (2) mean posterior toxicity probability at each dose, mean posterior efficacy probability at each dose, and acceptable posterior utility score of each dose level (0s indicate the dose is not acceptably efficous or toxic).
Examples
##Get the Data
##True Tox Prob
PT = c(.1,.2,.25,.5,.7)
##True EFF Prob
PE = c(.3,.4,.7,.5,.5)
Doses=c(1,1,1,2,2,2,3,3,3,2,2,2,1,1,1,2,2,2,3,3,3)
YE=Doses
YT=Doses
Dosetried=rep(0,length(PE))
##Generate data
for(k in 1:length(PE)){
if(sum(Doses==k)){
##Dose level has been tried
Dosetried[k]=1
YE[Doses==k]=rbinom(sum(Doses==k),1,PE[k])
YT[Doses==k]=rbinom(sum(Doses==k),1,PT[k])
}
}
##Hypermeans and hypervariances
HypermeansEFF = c(.022,3.45,0,-4.23,3.1,0)
HypervarsEFF = c(2.6761, 2.6852, .2, 3.1304, 3.1165, 1)
HypervarsEFF=HypervarsEFF^2
##Vector of Numerical Doses
Dose = c(1,2,3,3.5,5)
##Dose for Eff-Tox
Dose=log(Dose)-mean(log(Dose))
##Trial parameters
cohort=3
##Utility Matrix
UT = matrix(c(38.23529,100,0,61.76471),nrow=2,byrow=TRUE)
CutE=.3 ##Efficacy threshold
CutT=.4 ##Toxicity threshold
AcceptE=.3 ##Eff acceptability threshold
AcceptT= .3 ##Tox acceptability threshold
B=100##Number of iterations
GetEfftoxUt(YE, YT,Doses,Dose, Dosetried,
cohort, UT,CutE, CutT, AcceptE, AcceptT,
HypermeansEFF, HypervarsEFF,B )
Returns prior dose-specific means and prior ESS for the SPSO model.
Description
Uses elicited efficacy and toxicity dose-specific parameters along withlatent prior variance, dose-specific mean hypervariance, frailty variance, and global probability of monotonicity to determine dose-specific prior means for efficacy and toxicityand prints the prior effective sample size associated with the specified prior parameters.
Usage
GetPriorsSPSO(PROBST, PROBSE, tau, Var, HypVar, PGLOBAL)
Arguments
PROBST |
Elicited prior toxicity probability at each dose. |
PROBSE |
Elicted prior efficacy probability at each dose. |
tau |
Frailty variance parameter. |
Var |
Latent parameter variance for normal probability of efficacy and toxicity. |
HypVar |
Hypervariance on dose specific mean efficacy and toxicity parameters. |
PGLOBAL |
Global monotonicity probability of dose-efficacy curve. |
Value
A list contianing (1) the prior effective sample size, (2) the vector of dose-specific efficacy probability prior mean parameters and, (3) the vector of dose-specific toxicity probability prior mean parameters.
Examples
library(mvtnorm)
##Elicited probabilities of toxicity
PROBST=c(.05,.10,.15,.20,.30)
##Elicited probabilities of efficacy
PROBSE=c(.2,.4,.6,.65,.7)
##Sigma_0
Var=1
##Sigma_mu
HypVar=16
##Frailty Variance
tau=1
##Global Monotonicity Probability
PGLOBAL=.1
Z=GetPriorsSPSO(PROBST,PROBSE,tau,Var,HypVar,PGLOBAL)
Z
Assigns next patient cohort based on the SPSOP model with a Utility based objective function.
Description
Provides the optimal dose level as determined by the SPSO model, posterior mean toxicity probability, efficacy probability, and desirability of each dose level. Doses that are unacceptably toxic or inefficous have a desirability of 0.
Usage
GetSpsoContour(
YE,
YT,
Doses,
Dosetried,
cohort,
Contour,
CutE,
CutT,
AcceptE,
AcceptT,
HypermeansE,
HypermeansT,
Hypervars,
B
)
Arguments
YE |
Length n binary indicator vector of efficacy status. |
YT |
Length n binary indicator vector of toxicity status. |
Doses |
Length n vector of integer Doses given to patients. |
Dosetried |
Binary vector corresponding to which doses have been tried. |
cohort |
Cohort size for the trial. |
Contour |
Contour vector for desirability function. Contains in order: (pi_1,E,pi_2,T,pi_3,E,pi_4,T). |
CutE |
Cutoff for efficacy probability acceptability. Dose-efficacy probabilities must be larger than this for patient assignment. |
CutT |
Cutoff for toxicity probability acceptability. Dose-toxicity probabilities must be smaller than this for patient assignment. |
AcceptE |
Posterior probability threshold for efficacy acceptability. |
AcceptT |
Posterior probability threshold for toxicity acceptability. |
HypermeansE |
Hypermeans for dose-specific efficacy parameters. |
HypermeansT |
Hypermeans for dose-specific toxcity parameters. |
Hypervars |
Hypervariances needed for the SPSO model. Contains, in order (sigma_0^2, sigma_mu^2,tau). |
B |
Number of iterations to run for the MCMC. |
Value
A list containing the optimal dose level to assign the next patient cohort in the first entry and a matrix in the second entry, with rows corresponding to (1) the dose #, (2) mean posterior toxicity probability at each dose, mean posterior efficacy probability at each dose, and acceptable posterior desirability score of each dose level (0s indicate the dose is not acceptably efficous or toxic).
Examples
##Get the Data
##True Tox Prob
PT = c(.1,.2,.25,.5,.7)
##True EFF Prob
PE = c(.3,.4,.7,.5,.5)
Doses=c(1,1,1,2,2,2,3,3,3,2,2,2,1,1,1,2,2,2,3,3,3)
YE=Doses
YT=Doses
Dosetried=rep(0,length(PE))
##Generate data
for(k in 1:length(PE)){
if(sum(Doses==k)){
##Dose level has been tried
Dosetried[k]=1
YE[Doses==k]=rbinom(sum(Doses==k),1,PE[k])
YT[Doses==k]=rbinom(sum(Doses==k),1,PT[k])
}
}
##Hyperparameters
HypermeansE=c(-1,-.5,0,.5,1,2)
HypermeansT=HypermeansE
Hypervars=c(1,16,1)
##Trial parameters
cohort=3
##Contour vector
Contour = c(.35, .75,.7,.4)
CutE=.3 ##Efficacy threshold
CutT=.4 ##Toxicity threshold
AcceptE=.3 ##Eff acceptability threshold
AcceptT= .3 ##Tox acceptability threshold
B=100##Number of iterations
GetSpsoContour(YE,YT,Doses,Dosetried,cohort,Contour,CutE, CutT, AcceptE, AcceptT,
HypermeansE, HypermeansT,Hypervars,B )
Assigns next patient cohort based on the SPSOP model with a Utility based objective function.
Description
Provides the optimal dose level as determined by the SPSO model, posterior mean toxicity probability, efficacy probability, and mean utility of each dose level. Doses that are unacceptably toxic or inefficous have a utility of 0.
Usage
GetSpsoUt(
YE,
YT,
Doses,
Dosetried,
cohort,
UT,
CutE,
CutT,
AcceptE,
AcceptT,
HypermeansE,
HypermeansT,
Hypervars,
B
)
Arguments
YE |
Length n binary indicator vector of efficacy status. |
YT |
Length n binary indicator vector of toxicity status. |
Doses |
Length n vector of integer Doses given to patients. |
Dosetried |
Binary vector corresponding to which doses have been tried. |
cohort |
Cohort size for the trial. |
UT |
Utility matrix for the four bivariate (efficacy, toxicity) events. |
CutE |
Cutoff for efficacy probability acceptability. Dose-efficacy probabilities must be larger than this for patient assignment. |
CutT |
Cutoff for toxicity probability acceptability. Dose-toxicity probabilities must be smaller than this for patient assignment. |
AcceptE |
Posterior probability threshold for efficacy acceptability. |
AcceptT |
Posterior probability threshold for toxicity acceptability. |
HypermeansE |
Hypermeans for dose-specific efficacy parameters. |
HypermeansT |
Hypermeans for dose-specific toxcity parameters. |
Hypervars |
Hypervariances needed for the SPSO model. Contains, in order (sigma_0^2, sigma_mu^2,tau). |
B |
Number of iterations to run for the MCMC. |
Value
A list containing the optimal dose level to assign the next patient cohort in the first entry and a matrix in the second entry, with rows corresponding to (1) the dose #, (2) mean posterior toxicity probability at each dose, mean posterior efficacy probability at each dose, and acceptable posterior utility score of each dose level (0s indicate the dose is not acceptably efficous or toxic).
Examples
##Get the Data
##True Tox Prob
PT = c(.1,.2,.25,.5,.7)
##True EFF Prob
PE = c(.3,.4,.7,.5,.5)
Doses=c(1,1,1,2,2,2,3,3,3,2,2,2,1,1,1,2,2,2,3,3,3)
YE=Doses
YT=Doses
Dosetried=rep(0,length(PE))
##Generate data
for(k in 1:length(PE)){
if(sum(Doses==k)){
##Dose level has been tried
Dosetried[k]=1
YE[Doses==k]=rbinom(sum(Doses==k),1,PE[k])
YT[Doses==k]=rbinom(sum(Doses==k),1,PT[k])
}
}
##Hyperparameters
HypermeansE=c(-1,-.5,0,.5,1,2)
HypermeansT=HypermeansE
Hypervars=c(1,16,1)
##Trial parameters
cohort=3
#'##UTILITY Matrix
UT = matrix(c(38.23529,100,0,61.76471),nrow=2,byrow=TRUE)
CutE=.3 ##Efficacy threshold
CutT=.4 ##Toxicity threshold
AcceptE=.3 ##Eff acceptability threshold
AcceptT= .3 ##Tox acceptability threshold
B=100##Number of iterations
GetSpsoUt(YE,YT,Doses,Dosetried,cohort,UT,CutE, CutT, AcceptE, AcceptT,
HypermeansE, HypermeansT,Hypervars,B )
Obtains optimal dose level.
Description
Gives the optimal dose level to assign the next patient cohort to based on the vector of optimality function values for each dose level (desirability or utility based) and the doses tried throughout the trial.
Usage
ReturnOpt(Desire, DoseTried)
Arguments
Desire |
Vector of optimality function values for each dose level. |
DoseTried |
Binary vector containing 1 for doses that have been tried during the trial and 0 otherwise. |
Value
Optimal dose level to assign the next patient cohort.
Simulates utility based Efftox trials
Description
Simulates utility based Efftox trials
Usage
RunAdaptiveEffToxTrialCORR(
DoseStart,
Dose,
Hypermeans,
Hypervars,
UT,
PiLim,
ProbLim,
cohort,
NET,
NF,
B,
nSims,
PMAT
)
Arguments
DoseStart |
Dose level to START the EFF-Tox Trial |
Dose |
Vector of Doses considered in the trial |
Hypermeans |
6 vector of prior means |
Hypervars |
6 vector of prior standard deviations |
UT |
2x2 matrix of utilities corresponding to the four binary bivariate (toxicity, efficacy) events. |
PiLim |
2 vector of acceptable limits |
ProbLim |
2 vector of cutoff for acceptabilities |
cohort |
Cohort size |
NET |
Maximum Sample size to run the EFFtox Trial, must be divisible by cohort |
NF |
Minimum sample size to begin adaptive randomization, must be divisible by count |
B |
Number of reps to perform in MCMC |
nSims |
Number of Simulated trials to run. |
PMAT |
Contains TRUE pi00,pi10, pi01, pi11 for each dose |
Value
Trial simulation results to be processed for operating characteristics summaries.
Simulates desirability based Efftox trials
Description
Simulates Efftox trials based on the desirability tradeoff contour.
Usage
RunAdaptiveEffToxTrialCORRCONTOUR(
DoseStart,
Dose,
Hypermeans,
Hypervars,
Contour,
PiLim,
ProbLim,
cohort,
NET,
NF,
B,
nSims,
PMAT
)
Arguments
DoseStart |
Dose level to START the EFF-Tox Trial |
Dose |
Vector of Doses considered in the trial |
Hypermeans |
6 vector of prior means |
Hypervars |
6 vector of prior standard deviations |
Contour |
4 vector used to specify the tradeoff contour. |
PiLim |
2 vector of acceptable limits |
ProbLim |
2 vector of cutoff for acceptabilities |
cohort |
Cohort size |
NET |
Maximum Sample size to run the EFFtox Trial, must be divisible by cohort |
NF |
Minimum sample size to begin adaptive randomization, must be divisible by count |
B |
Number of reps to perform in MCMC |
nSims |
Number of Simulated trials to run. |
PMAT |
Contains TRUE pi00,pi10, pi01, pi11 for each dose |
Value
Trial simulation results to be processed for operating characteristics summaries.
Simulates trial replications from the Efftox model with desirability optimality function.
Description
Simulates replications from a Bayesian adaptive phase 12 clinical trial design using the Efftox model and a optimality function based on the desirability tradeoff contour.
Usage
SimEfftoxContour(
NSims,
Dose,
PE,
PT,
corET,
Nmax,
cohort,
Contour,
CutE,
CutT,
AcceptE,
AcceptT,
HypermeansEFF,
HypervarsEFF
)
Arguments
NSims |
Number of trial simulations to run. |
Dose |
Logarithm of raw dose levels - the average logarithm of the raw dose levels. |
PE |
True efficacy probability for each dose. |
PT |
True toxicity probaiblity for each dose. |
corET |
Correlation parameter between efficacy and toxicity probability. |
Nmax |
Maximum trial sample size. |
cohort |
Patient cohort size. |
Contour |
Contour vector for desirability function. Contains in order: (pi_1,E,pi_2,T,pi_3,E,pi_4,T). |
CutE |
Cutoff for efficacy probability acceptability. Dose-efficacy probabilities must be larger than this for patient assignment. |
CutT |
Cutoff for toxicity probability acceptability. Dose-toxicity probabilities must be smaller than this for patient assignment. |
AcceptE |
Posterior probability threshold for efficacy acceptability. |
AcceptT |
Posterior probability threshold for toxicity acceptability. |
HypermeansEFF |
Hypermeans for the Efftox model. In order, entries are hypermeans for (beta_0,E,beta_1,E,beta_2,E,beta_0,T,beta_1,T,psi). |
HypervarsEFF |
Hypervariances for the Efftox model. In order, entries are hypervariances for (beta_0,E,beta_1,E,beta_2,E,beta_0,T,beta_1,T,psi). |
Value
A list with the first entry corresponding to a matrix with: (1) True toxicity probabilities at each dose, (2) True efficacy probabilities at each dose, (3) True Desirability of each dose, (4) Optimal dose selection probability, (5) Average sample size of patients treated at each dose. The second entry of the list contains a vector with rows corresponding to (1) the true binary bivariate correlation between efficacy and toxicity, (2) Stopping probability of the trial, (3) Average number of efficacy events, (4) Average number of toxicity events, and (5) Delta.
Examples
library(mvtnorm)
##True toxicity probability
PT=c(.05,.10,.15,.20,.30)
##True Efficacy Probability
PE=c(.2,.4,.6,.65,.7)
#True Correlation
corET=.5
##Number of simulations
NSims=1 ##Increase this when using
##Hypermeans and hypervariances
HypermeansEFF = c(.022,3.45,0,-4.23,3.1,0)
HypervarsEFF = c(2.6761, 2.6852, .2, 3.1304, 3.1165, 1)
HypervarsEFF=HypervarsEFF^2
##Trial Parameters
##Cohort Size, N^F and N_ET
cohort=3
##Starting Dose
DoseStart=1
##Vector of Numerical Doses
Dose = c(1,2,3,3.5,5)
##Dose for Eff-Tox
Dose=log(Dose)-mean(log(Dose))
Nmax=30 ##Max Sample Size
#Acceptability Criterion
CutE=.3
CutT=.4
##Limits on acceptability
AcceptE=.1
AcceptT=.1
##Contour vector
Contour = c(.35, .75,.7,.4)
RESULTS=SimEfftoxContour(NSims, Dose,PE, PT, corET,
Nmax, cohort, Contour, CutE, CutT, AcceptE,AcceptT, HypermeansEFF, HypervarsEFF)
RESULTS
Simulates trial replications from the Efftox model with utility optimality function.
Description
Simulates replications from a Bayesian adaptive phase 12 clinical trial design using the Efftox model and a optimality function based on mean utility. Does not assign patient cohorts to unacceptably toxic or inefficous dose levels.
Usage
SimEfftoxUt(
NSims,
Dose,
PE,
PT,
corET,
Nmax,
cohort,
UT,
CutE,
CutT,
AcceptE,
AcceptT,
HypermeansEFF,
HypervarsEFF
)
Arguments
NSims |
Number of trial simulations to run. |
Dose |
Logarithm of raw dose levels - the average logarithm of the raw dose levels. |
PE |
True efficacy probability for each dose. |
PT |
True toxicity probaiblity for each dose. |
corET |
Correlation parameter between efficacy and toxicity probability. |
Nmax |
Maximum trial sample size. |
cohort |
Patient cohort size. |
UT |
Utility matrix for the four bivariate (efficacy, toxicity) events. |
CutE |
Cutoff for efficacy probability acceptability. Dose-efficacy probabilities must be larger than this for patient assignment. |
CutT |
Cutoff for toxicity probability acceptability. Dose-toxicity probabilities must be smaller than this for patient assignment. |
AcceptE |
Posterior probability threshold for efficacy acceptability. |
AcceptT |
Posterior probability threshold for toxicity acceptability. |
HypermeansEFF |
Hypermeans for the Efftox model. In order, entries are hypermeans for (beta_0,E,beta_1,E,beta_2,E,beta_0,T,beta_1,T,psi). |
HypervarsEFF |
Hypervariances for the Efftox model. In order, entries are hypervariances for (beta_0,E,beta_1,E,beta_2,E,beta_0,T,beta_1,T,psi). |
Value
A list with the first entry corresponding to a matrix with: (1) True toxicity probabilities at each dose, (2) True efficacy probabilities at each dose, (3) True mean utility of each dose, (4) Optimal dose selection probability, (5) Average sample size of patients treated at each dose. The second entry of the list contains a vector with rows corresponding to (1) the true binary bivariate correlation between efficacy and toxicity, (2) Stopping probability of the trial, (3) Average number of efficacy events, (4) Average number of toxicity events, and (5) Delta.
Examples
library(mvtnorm)
##True toxicity probability
PT=c(.05,.10,.15,.20,.30)
##True Efficacy Probability
PE=c(.2,.4,.6,.65,.7)
#True Correlation
corET=.5
##Number of simulations
NSims=1 ##Increase this when using
##Hypermeans and hypervariances
HypermeansEFF = c(.022,3.45,0,-4.23,3.1,0)
HypervarsEFF = c(2.6761, 2.6852, .2, 3.1304, 3.1165, 1)
HypervarsEFF=HypervarsEFF^2
##Trial Parameters
##Cohort Size, N^F and N_ET
cohort=3
##Starting Dose
DoseStart=1
##Vector of Numerical Doses
Dose = c(1,2,3,3.5,5)
##Dose for Eff-Tox
Dose=log(Dose)-mean(log(Dose))
Nmax=30 ##Max Sample Size
#Acceptability Criterion
CutE=.3
CutT=.4
##Limits on acceptability
AcceptE=.1
AcceptT=.1
##UTILITY Matrix
UT = matrix(c(38.23529,100,0,61.76471),nrow=2,byrow=TRUE)
RESULTS=SimEfftoxUt(NSims, Dose,PE, PT, corET,
Nmax, cohort, UT, CutE, CutT, AcceptE,AcceptT, HypermeansEFF, HypervarsEFF)
RESULTS
Simulates trial replications from the SPSO model with desirability optimality function.
Description
Simulates replications from a Bayesian adaptive phase 12 clinical trial design using the SPSO model and a optimality function based on the desirability tradeoff contour.
Usage
SimSpsoContour(
NSims,
PE,
PT,
corET,
Nmax,
cohort,
Contour,
CutE,
CutT,
AcceptE,
AcceptT,
HypermeansE,
HypermeansT,
Hypervars
)
Arguments
NSims |
Number of trial simulations to run. |
PE |
True efficacy probability for each dose. |
PT |
True toxicity probaiblity for each dose. |
corET |
Correlation parameter between efficacy and toxicity probability. |
Nmax |
Maximum trial sample size. |
cohort |
Patient cohort size. |
Contour |
Contour vector for desirability function. Contains in order: (pi_1,E,pi_2,T,pi_3,E,pi_4,T). |
CutE |
Cutoff for efficacy probability acceptability. Dose-efficacy probabilities must be larger than this for patient assignment. |
CutT |
Cutoff for toxicity probability acceptability. Dose-toxicity probabilities must be smaller than this for patient assignment. |
AcceptE |
Posterior probability threshold for efficacy acceptability. |
AcceptT |
Posterior probability threshold for toxicity acceptability. |
HypermeansE |
Hypermeans for dose-specific efficacy parameters. |
HypermeansT |
Hypermeans for dose-specific toxcity parameters. |
Hypervars |
Hypervariances needed for the SPSO model. Contains, in order (sigma_0^2, sigma_mu^2,tau). |
Value
A list with the first entry corresponding to a matrix with: (1) True toxicity probabilities at each dose, (2) True efficacy probabilities at each dose, (3) True Desirability of each dose, (4) Optimal dose selection probability, (5) Average sample size of patients treated at each dose. The second entry of the list contains a vector with rows corresponding to (1) the true binary bivariate correlation between efficacy and toxicity, (2) Stopping probability of the trial, (3) Average number of efficacy events, (4) Average number of toxicity events, and (5) Delta.
Examples
library(mvtnorm)
##True toxicity probability
PT=c(.05,.10,.15,.20,.30)
##True Efficacy Probability
PE=c(.2,.4,.6,.65,.7)
#True Correlation
corET=.5
##Number of simulations
NSims=1 ##Increase this when using
##Hypermeans and hypervariances
HypermeansE=c(-1.189, -0.357, 0.360, 0.546, 0.743)
HypermeansT=c(-2.325, -1.811, -1.464, -1.189, -0.740)
Hypervars=c(1,16,1)
##Trial Parameters
##Cohort Size, N^F and N_ET
cohort=3
##Starting Dose
DoseStart=1
Nmax=30 ##Max Sample Size
#Acceptability Criterion
CutE=.3
CutT=.4
##Limits on acceptability
AcceptE=.1
AcceptT=.1
##Contour vector
Contour = c(.35, .75,.7,.4)
RESULTS=SimSpsoContour(NSims, PE, PT, corET, Nmax, cohort, Contour,
CutE, CutT, AcceptE, AcceptT,HypermeansE, HypermeansT, Hypervars)
RESULTS
Simulates trial replications from the SPSO model with desirability optimality function.
Description
Simulates replications from a Bayesian adaptive phase 12 clinical trial design using the SPSO model and a optimality function based on the desirability tradeoff contour.
Usage
SimSpsoUt(
NSims,
PE,
PT,
corET,
Nmax,
cohort,
UT,
CutE,
CutT,
AcceptE,
AcceptT,
HypermeansE,
HypermeansT,
Hypervars
)
Arguments
NSims |
Number of trial simulations to run. |
PE |
True efficacy probability for each dose. |
PT |
True toxicity probaiblity for each dose. |
corET |
Correlation parameter between efficacy and toxicity probability. |
Nmax |
Maximum trial sample size. |
cohort |
Patient cohort size. |
UT |
Utility matrix for the four bivariate (efficacy, toxicity) events. |
CutE |
Cutoff for efficacy probability acceptability. Dose-efficacy probabilities must be larger than this for patient assignment. |
CutT |
Cutoff for toxicity probability acceptability. Dose-toxicity probabilities must be smaller than this for patient assignment. |
AcceptE |
Posterior probability threshold for efficacy acceptability. |
AcceptT |
Posterior probability threshold for toxicity acceptability. |
HypermeansE |
Hypermeans for dose-specific efficacy parameters. |
HypermeansT |
Hypermeans for dose-specific toxcity parameters. |
Hypervars |
Hypervariances needed for the SPSO model. Contains, in order (sigma_0^2, sigma_mu^2,tau). |
Value
A list with the first entry corresponding to a matrix with: (1) True toxicity probabilities at each dose, (2) True efficacy probabilities at each dose, (3) True mean utility of each dose, (4) Optimal dose selection probability, (5) Average sample size of patients treated at each dose. The second entry of the list contains a vector with rows corresponding to (1) the true binary bivariate correlation between efficacy and toxicity, (2) Stopping probability of the trial, (3) Average number of efficacy events, (4) Average number of toxicity events, and (5) Delta.
Examples
library(mvtnorm)
##True toxicity probability
PT=c(.05,.10,.15,.20,.30)
##True Efficacy Probability
PE=c(.2,.4,.6,.65,.7)
#True Correlation
corET=.5
##Number of simulations
NSims=1 ##Increase this when using
##Hypermeans and hypervariances
HypermeansE=c(-1.189, -0.357, 0.360, 0.546, 0.743)
HypermeansT=c(-2.325, -1.811, -1.464, -1.189, -0.740)
Hypervars=c(1,16,1)
##Trial Parameters
##Cohort Size, N^F and N_ET
cohort=3
##Starting Dose
DoseStart=1
Nmax=30 ##Max Sample Size
#Acceptability Criterion
CutE=.3
CutT=.4
##Limits on acceptability
AcceptE=.1
AcceptT=.1
##UTILITY Matrix
UT = matrix(c(38.23529,100,0,61.76471),nrow=2,byrow=TRUE)
RESULTS=SimSpsoUt(NSims, PE, PT, corET, Nmax, cohort, UT,
CutE, CutT, AcceptE, AcceptT,HypermeansE, HypermeansT, Hypervars)
RESULTS
Samples from the posterior of the utility based phase12 model.
Description
Takes arguments of data, hypermens and hypervariance vectors and returns a list of posterior samples from the Utility based phase12 model decribed by Chapple and Thall (2019).
Usage
UTEFFTOX(YE, YT, Doses, HypermeansEFF, HypermeansTOX, Hypervars, B)
Arguments
YE |
Binary indicator vector of efficacy status. |
YT |
Binary indicator vector of toxicity status. |
Doses |
Vector of integer Doses given to patients. |
HypermeansEFF |
Vector of length nDose for dose prior means for efficacy. |
HypermeansTOX |
Vector of length nDose for dose prior means for toxicity |
Hypervars |
Length 3 vector of hypervariances.Hypervars(1) contains sigma_0^2, Hypervars(2) contains sigma_mu, Hypervars(3) contains tau - the frailty variance. |
B |
Number of iterations to run for the MCMC. |
Value
A list of posterior samples after burnin in order: Posterior efficacy dose-vector, Posterior toxicity dose-vector, Posterior correlation.
Examples
n=100 #Generate Data
YE=rbinom(n,1,.6)
YT=rbinom(n,1,.2)
nDose=5
Doses=sample(1:nDose,n,replace=TRUE)
##Hyperparameters
HypermeansEFF=c(-1,-.5,0,.5,1,2)
HypermeansTOX=HypermeansEFF
Hypervars=c(1,16,1)
B=100
UTEFFTOX(YE, YT,Doses,HypermeansEFF,HypermeansTOX, Hypervars, B)