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Open / recruit backfill patients into a cohort?

Source: R/Backfill-methods.R
openCohort.Rd

[Experimental]

Usage 

openCohort(opening, cohort, data, dose, ...)

# S4 method for class 'OpeningMinDose'
openCohort(opening, cohort, data, dose, ...)

# S4 method for class 'OpeningMinCohorts'
openCohort(opening, cohort, data, dose, ...)

# S4 method for class 'OpeningNone'
openCohort(opening, cohort, data, dose, ...)

# S4 method for class 'OpeningMinResponses'
openCohort(opening, cohort, data, dose, ...)

# S4 method for class 'OpeningList'
openCohort(opening, cohort, data, dose, summary_fun, ...)

# S4 method for class 'OpeningAll'
openCohort(opening, cohort, data, dose, ...)

# S4 method for class 'OpeningAny'
openCohort(opening, cohort, data, dose, ...)

Arguments

opening

(Opening)
opening rule to be applied.

cohort

(int)
backfill cohort index.

data

(Data)
current trial data.

dose

(numeric)
the recommended next best dose.

...

further arguments (not used).

summary_fun

(function)
to apply to the list of results (e.g., all or any). Only used for OpeningList and its subclasses.

Value

TRUE if this backfill cohort can be opened / recruited into, FALSE otherwise.

Functions

  • openCohort(OpeningMinDose): method for OpeningMinDose class.

  • openCohort(OpeningMinCohorts): method for OpeningMinCohorts class.

  • openCohort(OpeningNone): method for OpeningNone class, which never opens a cohort, i.e. the trial design will not use backfilling.

  • openCohort(OpeningMinResponses): method for OpeningMinResponses class.

  • openCohort(OpeningList): method for OpeningList class.

  • openCohort(OpeningAll): method for OpeningAll class. Returns TRUE if ALL opening criteria are satisfied.

  • openCohort(OpeningAny): method for OpeningAny class. Returns TRUE if ANY opening criteria are satisfied.

Examples 

# Create a simple data object with some dose information
data <- Data(
  x = c(0.1, 0.5, 1.5, 3, 6, 10, 10, 10),
  y = c(0, 0, 0, 0, 0, 0, 1, 0),
  cohort = c(1, 2, 3, 4, 5, 6, 6, 6),
  doseGrid = c(0.1, 0.5, 1.5, 3, 6, seq(from = 10, to = 80, by = 2))
)
#> Used default patient IDs!

# Define the opening rule: open backfill cohorts when dose is at least 5
my_opening <- OpeningMinDose(min_dose = 5)

# Check if the first backfill cohort can be opened when the
# cohort has a dose 6, i.e. larger than 5.
# Note that `dose` is not used in this rule.
can_open <- openCohort(my_opening, cohort = 5, data = data, dose = 7)
can_open
#> [1] TRUE

# Check if the first backfill cohort can be opened when the
# cohort has a dose 3, i.e. smaller than 5.
# (should return FALSE because dose < min_dose)
can_open_low <- openCohort(my_opening, cohort = 4, data = data, dose = 15)
can_open_low
#> [1] FALSE
# Create a data object with multiple cohorts
data <- Data(
  x = c(0.1, 0.5, 1.5, 3, 6, 10, 10, 10),
  y = c(0, 0, 0, 0, 0, 0, 1, 0),
  cohort = c(0, 1, 2, 3, 4, 5, 5, 5),
  doseGrid = c(0.1, 0.5, 1.5, 3, 6, seq(from = 10, to = 80, by = 2))
)
#> Used default patient IDs!

# Define the opening rule: open backfill cohorts after at least 3 cohorts
my_opening <- OpeningMinCohorts(min_cohorts = 3)

# Check if a backfill cohort can be opened
# Current number of cohorts is 6, so it should open (6 >= 3)
can_open <- openCohort(my_opening, cohort = 1, data = data, dose = 25)
can_open
#> [1] TRUE
# Create an OpeningNone object which never opens backfill cohorts
opening <- OpeningNone()

# Create sample trial data
data <- Data(
  x = c(20, 30, 40, 50),
  y = c(0, 0, 1, 0),
  cohort = c(1, 2, 3, 4),
  doseGrid = seq(10, 100, by = 10)
)
#> Used default patient IDs!

# Create dose recommendation
dose <- 60

# Check if backfill cohort should be opened for cohort 5
# OpeningNone always returns FALSE
should_open <- openCohort(opening, cohort = 5, data = data, dose = dose)
print(should_open) # FALSE
#> [1] FALSE
# Create an OpeningMinResponses object requiring 2 responses at the cohort dose
opening <- OpeningMinResponses(min_responses = 2, include_lower_doses = FALSE)

# Create sample trial data with responses at different dose levels
data <- Data(
  x = c(10, 10, 20, 20, 20, 30, 30, 30),
  y = c(0, 1, 0, 1, 0, 1, 1, 0),
  response = c(1, 1, NA, 0, 1, NA, 1, 0),
  cohort = c(1, 1, 2, 2, 2, 3, 3, 3),
  doseGrid = seq(10, 100, by = 10)
)
#> Used default patient IDs!

# Check if backfill cohort can be opened at dose 20
# At dose 20, there is 1 response
should_open <- openCohort(opening, cohort = 2, data = data, dose = 30)
print(should_open) # FALSE
#> [1] FALSE

# Check at dose 10 where there are 2 responses
should_open_2 <- openCohort(opening, cohort = 1, data = data, dose = 30)
print(should_open_2) # TRUE
#> [1] TRUE
# Create sample trial data
data <- Data(
  x = c(0.1, 0.5, 1.5, 3, 6, 10, 10, 10),
  y = c(0, 0, 0, 0, 0, 0, 1, 0),
  cohort = c(1, 2, 3, 4, 5, 6, 6, 6),
  doseGrid = c(0.1, 0.5, 1.5, 3, 6, seq(from = 10, to = 80, by = 2))
)
#> Used default patient IDs!

# Create opening criteria:
# - opening1: open if dose >= 10
# - opening2: open if at least 5 cohorts have been treated
opening1 <- OpeningMinDose(min_dose = 10)
opening2 <- OpeningMinCohorts(min_cohorts = 5)

# Combine with AND logic: both must be true
opening_all <- opening1 & opening2

# Test if backfill cohort 7 can be opened
# Cohort 6 dose is 10 (>= 10: TRUE), max cohort is 6 (>= 5: TRUE), so AND is TRUE
should_open <- openCohort(opening_all, cohort = 6, data = data, dose = 20)
print(should_open) # TRUE
#> [1] TRUE

# Test if backfill cohort at dose 6 can be opened
# Cohort 4 dose is 3 (>= 10: FALSE), so AND is FALSE
should_open_2 <- openCohort(opening_all, cohort = 4, data = data, dose = 20)
print(should_open_2) # FALSE
#> [1] FALSE
# Create sample trial data
data <- Data(
  x = c(0.1, 0.5, 1.5, 3, 6, 10, 10, 10),
  y = c(0, 0, 0, 0, 0, 0, 1, 0),
  cohort = c(1, 2, 3, 4, 5, 6, 6, 6),
  doseGrid = c(0.1, 0.5, 1.5, 3, 6, seq(from = 10, to = 80, by = 2))
)
#> Used default patient IDs!

# Create opening criteria:
# - opening1: open if dose >= 20
# - opening2: open if at least 5 cohorts have been treated
opening1 <- OpeningMinDose(min_dose = 20)
opening2 <- OpeningMinCohorts(min_cohorts = 5)

# Combine with OR logic: at least one must be true
opening_any <- opening1 | opening2

# Test if backfill cohort 7 can be opened at dose 10
# Cohort 6 dose is 10 (>= 20: FALSE), max cohort is 6 (>= 5: TRUE), so OR is TRUE
should_open <- openCohort(opening_any, cohort = 6, data = data, dose = 20)
print(should_open) # TRUE
#> [1] TRUE

# Test with a different scenario:
# It does not matter which cohort index we give, because
# the number of cohorts is already above 5.
should_open_2 <- openCohort(opening_any, cohort = 1, data = data, dose = 25)
print(should_open_2) # TRUE
#> [1] TRUE