DADesign — DADesign-class • crmPack

This class has special requirements for the model and data slots in comparison to the parent class Design:

Usage

DADesign(model, data, safetyWindow, ...)

.DefaultDADesign()

Arguments

model

(GeneralModel)
see slot definition.

data

(DataDA)
see slot definition.

safetyWindow

(SafetyWindow)
see slot definition.

...

Arguments passed on to Design

stopping: (Stopping)
see slot definition.
increments: (Increments)
see slot definition.
pl_cohort_size: (CohortSize)
see slot definition.

Details

The safetyWindow slot should be an instance of the SafetyWindow class. It can be customized to specify the duration of the safety window for your trial. The safety window represents the time period required to observe toxicity data from the ongoing cohort before opening the next cohort. Note that even after opening the next cohort, further toxicity data will be collected and analyzed to make dose escalation decisions.

To specify a constant safety window, use the SafetyWindowConst constructor. For example:

mysafetywindow <- SafetyWindowConst(c(6, 2), 10, 20)

Slots

model: (GeneralModel)
the model to use, see in particular DALogisticLogNormal and TITELogisticLogNormal which make use of the time-to-DLT data.
data: (DataDA)
what is the dose grid, any previous data, etc.
safetyWindow: (SafetyWindow)
the safety window to apply between cohorts.

Note

Typically, end users will not use the .DefaultDADesign() function.

Examples

empty_data <- DataDA(doseGrid = c(
  0.1, 0.5, 1, 1.5, 3, 6,
  seq(from = 10, to = 80, by = 2)
), Tmax = 60)

npiece <- 10
t_max <- 60

lambda_prior <- function(k) {
  npiece / (t_max * (npiece - k + 0.5))
}

model <- DALogisticLogNormal(
  mean = c(-0.85, 1),
  cov = matrix(c(1, -0.5, -0.5, 1), nrow = 2),
  ref_dose = 56,
  npiece = npiece,
  l = as.numeric(t(apply(as.matrix(c(1:npiece), 1, npiece), 2, lambda_prior))),
  c_par = 2
)

my_increments <- IncrementsRelative(
  intervals = c(0, 20),
  increments = c(1, 0.33)
)

my_next_best <- NextBestNCRM(
  target = c(0.2, 0.35),
  overdose = c(0.35, 1),
  max_overdose_prob = 0.25
)

my_size1 <- CohortSizeRange(
  intervals = c(0, 30),
  cohort_size = c(1, 3)
)

my_size2 <- CohortSizeDLT(
  intervals = c(0, 1),
  cohort_size = c(1, 3)
)

my_size <- maxSize(my_size1, my_size2)

my_stopping1 <- StoppingTargetProb(
  target = c(0.2, 0.35),
  prob = 0.5
)

my_stopping2 <- StoppingMinPatients(nPatients = 50)

my_stopping <- (my_stopping1 | my_stopping2)

my_safety_window <- SafetyWindowConst(c(6, 2), 7, 7)

design <- DADesign(
  model = model,
  increments = my_increments,
  nextBest = my_next_best,
  stopping = my_stopping,
  cohort_size = my_size,
  data = empty_data,
  safetyWindow = my_safety_window,
  startingDose = 3
)