Phase123 (version 2.1)

SimPhase3: Performs one replication of phase 3 for the phase 123 design, given phase 12 data.

Description

This function simulates the phase 3 potion of the phase 123 trial, given phase 12 outcomes.

Usage

SimPhase3(Dose, Phase12, PE, PT, Hypermeans, Hypervars, betaA, ProbC,
  betaC, Family, alpha, Nmax, Opt, Accrue, Time12, Twait, NLookSwitch,
  NLook, Sup, Fut)

Arguments

Dose

Vector of standardized doses considered in the trial.

Phase12

Matrix Consisting of patient data from a phase 12 trial. The columns are in order: Doses given, YE, YT, Accrual Times

PE

True efficacy dose-toxicity vector.

PT

True toxicity dose-toxicity vector.

Hypermeans

Prior Means for the Eff-Tox design of length 6.

Hypervars

Prior Variances for the Eff-Tox design of length 6.

betaA

True linear term for the rate or mean parameter (beta_1,exp(beta_E),-exp(beta_T),beta_2,beta_0) for agent A.

ProbC

Probability of efficacy and toxicity for the control therapy.

betaC

Linear term for efficacy, toxicity and beta_0 for the control group.

Family

Time to event distribution. Options include: Exponential, Gamma, Weibull, Lognormal.

alpha

Shape parameter or standard deviation of a lognormal distribution.

Nmax

Maximum number of patients to enroll in phase 3.

Opt

Dose used for A to begin randomization in phase 3.

Accrue

Accrual rate for patients in phase 3.

Time12

Time window for phase 12.

Twait

Waiting time in between phase 12 and phase 3.

NLookSwitch

Number of patient events to determine if we re-optimize doses for A.

NLook

Vector of information criteria for making interim looks.

Sup

Vector of superiority boundaries.

Fut

Vector of futility boundaries.

References

[1] Chapple and Thall (2018).A Hybrid Phase I-II/III Clinical Trial Design Allowing Dose Re-Optimization in Phase III. Biometrics. In Press,

Examples

# NOT RUN {
library(survival)
##True Efficacy and Toxicity Probabilities
PT = c(.1,.15,.25,.35,.5)
PE=c(.2,.4,.6,.65,.7)
##Dose Levels considered
Dose = c(1,2,3,3.5,5)
Dose=(Dose-mean(Dose))/sd(Dose)
##Average accrual rate for phase III
Accrue = 10
#'##Hypermeans for Eff-Tox
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
Contour = c(.35, .75,.7,.4)
PiLim = c(.3,.4)
ProbLim=c(.1,.1)
###Family of Distributions
Family="Exponential"
###Shape parameter ## Doesn't matter for exponential distribution
alpha=1
###True Beta vector
betaA = c(.75,-.5, .3, -.25,2.143)
##True beta vector for efficacy, toxicity and intercept of the control treatment
betaC=c(.3,-.25,2.389)
##True efficacy and toxicity probability for control group
ProbC = c(.4,.15)
##Waiting time in between
Twait=1
###How long is the time window in phase 12?
Time12=1
##Dose to start phase 3 with
Opt=3
##Make matrix with old phase 12 data
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)
##Accrual Times for old data
Accrue12=2
##Size of phase 12 cohort
cohort=3
ACC1=cumsum(rexp(length(YT),Accrue12))
##Accrual times are the same for each cohort in phase 12
Grab = rep(NA,length(YT)/cohort)
for(m in 1:length(Grab)){Grab[m]=ACC1[m*3]}
for(m in 1:length(Grab)){ACC1[((m-1)*cohort+1):((m-1)*cohort+cohort)]=rep(Grab[m],cohort)}
Phase12 = cbind(Doses,YE,YT,ACC1)
betaC=c(.3,-.25,2.389)
##True efficacy and toxicity probability for control group
ProbC = c(.4,.15)
##Max Sample Size
Nmax=500
###Number of patient events to Re-optimize doses
NLookSwitch = 50
##Number of patient events for interim looks
NLook = c(200,300,400)
##Superiority Boundaries
Sup = c(2.96, 2.53,1.99)
##Futility Boundaries (0 means no futility decision)
Fut = c(0,1.001,0)
##Starting Dose, hat(x)_ET
Opt=3
##Number of simulations to run
nSims=10
SimPhase3(Dose,Phase12,PE,PT,Hypermeans,Hypervars,betaA,
ProbC,betaC,Family,alpha,Nmax,Opt,Accrue,
Time12,Twait,NLookSwitch,NLook,Sup,Fut)
# }