examples/design-method-simulate-DualDesign.R

In Roche/crmPack: Object-Oriented Implementation of CRM Designs

# nolint start

# Define the dose-grid
emptydata <- DataDual(doseGrid = c(1, 3, 5, 10, 15, 20, 25, 40, 50, 80, 100))

# Initialize the CRM model
model <- DualEndpointRW(
  mean = c(0, 1),
  cov = matrix(c(1, 0, 0, 1), nrow = 2),
  sigma2betaW = 0.01,
  sigma2W = c(a = 0.1, b = 0.1),
  use_log_dose = TRUE,
  ref_dose = 2,
  rho = c(a = 1, b = 1),
  rw1 = TRUE
)

# Choose the rule for selecting the next dose
myNextBest <- NextBestDualEndpoint(
  target = c(0.9, 1),
  overdose = c(0.35, 1),
  max_overdose_prob = 0.25
)

# Choose the rule for the cohort-size
mySize1 <- CohortSizeRange(
  intervals = c(0, 30),
  cohort_size = c(1, 3)
)
mySize2 <- CohortSizeDLT(
  intervals = c(0, 1),
  cohort_size = c(1, 3)
)
mySize <- maxSize(mySize1, mySize2)

# Choose the rule for stopping
myStopping4 <- StoppingTargetBiomarker(
  target = c(0.9, 1),
  prob = 0.5
)
myStopping <- myStopping4 | StoppingMinPatients(10)

# Choose the rule for dose increments
myIncrements <- IncrementsRelative(
  intervals = c(0, 20),
  increments = c(1, 0.33)
)

# Initialize the design
design <- DualDesign(
  model = model,
  data = emptydata,
  nextBest = myNextBest,
  stopping = myStopping,
  increments = myIncrements,
  cohort_size = mySize,
  startingDose = 3
)

# define scenarios for the TRUE toxicity and efficacy profiles
betaMod <- function(dose, e0, eMax, delta1, delta2, scal) {
  maxDens <- (delta1^delta1) * (delta2^delta2) / ((delta1 + delta2)^(delta1 + delta2))
  dose <- dose / scal
  e0 + eMax / maxDens * (dose^delta1) * (1 - dose)^delta2
}

trueBiomarker <- function(dose) {
  betaMod(dose, e0 = 0.2, eMax = 0.6, delta1 = 5, delta2 = 5 * 0.5 / 0.5, scal = 100)
}

trueTox <- function(dose) {
  pnorm((dose - 60) / 10)
}

# Draw the TRUE profiles
par(mfrow = c(1, 2))
curve(trueTox(x), from = 0, to = 80)
curve(trueBiomarker(x), from = 0, to = 80)

# Run the simulation on the desired design
# We only generate 1 trial outcome here for illustration, for the actual study
# this should be increased of course, similarly for the McmcOptions -
# they also need to be increased.
mySims <- simulate(design,
  trueTox = trueTox,
  trueBiomarker = trueBiomarker,
  sigma2W = 0.01,
  rho = 0,
  nsim = 1,
  parallel = FALSE,
  seed = 3,
  startingDose = 6,
  mcmcOptions =
    McmcOptions(
      burnin = 100,
      step = 1,
      samples = 300
    )
)

# nolint end