maxDose: Determine the maximum possible next dose
In 0liver0815/onc-crmpack-test: Object-Oriented Implementation of CRM Designs
Description
Usage
Arguments
Details
Value
Functions
Examples
Description
Determine the upper limit of the next dose based on the increments rule.
Increments control based on number of dose levels
Increment rule to determine the maximum possible next dose based on
maximum dose levels to increment for the next dose.
Increment rule can be applied to last dose or maximum dose given so far.
Determine the maximum possible dose for escalation.
Determine the maximum possible dose for escalation.
Usage
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maxDose(increments, data, ...)
## S4 method for signature 'IncrementsRelative,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementsNumDoseLevels,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementsHSRBeta,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementsRelativeParts,DataParts'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementsRelativeDLT,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementMin,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementsHSRBeta_dk,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementsHSRBeta,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementsRelativeSafety,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementsRelativeSafetyFix,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementsNumDoseLevelsBaySafetyFix,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementsNlastDL,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementMinDLT1N1,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementsAbsoluteMax,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementsRelativeDLTmax,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementsRelativeMax,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementsSafetyStop,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementsSafetyStopFix,Data'
maxDose(increments, data, ...)
Arguments
increments
The rule, an object of class
Increments
data
The data input, an object of class Data
...
further arguments
Details
This function outputs the maximum possible next dose, based on the
corresponding rule increments and the data.
Value
the maximum possible next dose
Functions
-
maxDose,IncrementsRelative,Data-method: Determine the maximum possible next dose based on
relative increments
-
maxDose,IncrementsRelativeParts,DataParts-method: Determine the maximum possible next dose based on
relative increments and part 1 and 2
-
maxDose,IncrementsRelativeDLT,Data-method: Determine the maximum possible next dose based on
relative increments determined by DLTs so far
-
maxDose,IncrementMin,Data-method: Determine the maximum possible next dose based on
multiple increment rules (taking the minimum across individual increments).
-
maxDose,IncrementsHSRBeta_dk,Data-method: Determine the maximum possible next dose based on
maximum eligible dose level to increment for the next dose
below the target toxicity, by a % probability based on the Beta(a,b) distribution.
this can be calculated for any number of patients in a cohort with a defined probability threshold of 90%
i.e. 1- pbeta(target, x+a, n-x+b) < 0.90
where x=DLTs, n=patients for a dose and use Beta(a=1,b=1) (or probably a=b=0.5)
if a dose satisfies the above criterio then eligible doses, are only the ones that that lower than that dose
-
maxDose,IncrementsRelativeSafety,Data-method: Determine the maximum possible dose for escalation
-
maxDose,IncrementsRelativeSafetyFix,Data-method: Determine the maximum possible dose for escalation
-
maxDose,IncrementsNumDoseLevelsBaySafetyFix,Data-method: Determine the maximum possible dose for escalation
-
maxDose,IncrementsNlastDL,Data-method: Determine the maximum possible next dose based on
relative increments determined by DLTs so far
-
maxDose,IncrementMinDLT1N1,Data-method: Determine the maximum possible next dose based on
multiple increment rules (taking the minimum across individual increments).
-
maxDose,IncrementsAbsoluteMax,Data-method: Determine the maximum possible next dose based on
absolute increments
-
maxDose,IncrementsRelativeDLTmax,Data-method: Determine the maximum possible next dose based on
relative increments determined by DLTs so far
-
maxDose,IncrementsRelativeMax,Data-method: Determine the maximum possible next dose based on
relative increments
-
maxDose,IncrementsSafetyStop,Data-method: Determine the maximum possible dose for escalation
-
maxDose,IncrementsSafetyStopFix,Data-method: Determine the maximum possible dose for escalation
Examples
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# Create the data
data <- Data(x=c(0.1, 0.5, 1.5, 3, 6, 8, 8, 8),
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, 8,
seq(from=10, to=80, by=2)))
# In this example we define a rule for dose increments which would allow:
# - doubling the dose if the last dose was below 20
# - only increasing the dose by 1.33 if the last dose was equal or above 20
myIncrements <- IncrementsRelative(intervals=c(0, 20),
increments=c(1, 0.33))
# Based on the rule above, we then calculate the maximum dose allowed
nextMaxDose <- maxDose(myIncrements,
data=data)
# Create the data
data <- Data(x = c(0.1, 0.5, 1.5, 3, 6, 8, 8, 8, 12, 12, 12, 16, 16, 16, 10, 10, 10),
y = c(0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1, 0, 1, 0),
cohort = c(0, 1, 2, 3, 4, 5, 5, 5, 6, 6, 6, 7, 7, 7, 8, 8, 8),
doseGrid =
c(0.1, 0.5, 1.5, 3, 6, 8,
seq(from = 10, to = 80, by = 2)
)
)
# In this first example we define a rule for dose increments which would allow:
# Maximum skip one dose level, that is 2 dose levels higher than the last dose
# given. Maximum increment is explicitly defined as:
increments <- IncrementsNumDoseLevels(maxLevels = 2, basisLevel = "last")
# Since the default method is based on the last dose given, maximum increment
# can also be defined as:
increments <- IncrementsNumDoseLevels(maxLevels = 2)
# Based on the rule above, we then calculate the maximum dose allowed
max_dose <- maxDose(increments, data = data)
# In this second example we define a rule for dose increments which would allow:
# Maximum skip one dose level, that is 2 dose levels higher than the max dose
# given. Maximum increment is explicitly defined as:
increments <- IncrementsNumDoseLevels(maxLevels = 2, basisLevel = "max")
# Based on the rule above, we then calculate the maximum dose allowed
max_dose <- maxDose(increments, data = data)
# Create the data.
my_data <- Data(
x = c(0.1, 0.5, 1.5, 3, 6, 8, 8, 8, 6, 6, 6),
y = c(0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 1),
cohort = c(0, 1, 2, 3, 4, 5, 5, 5, 6, 6, 6),
doseGrid = c(0.1, 0.5, 1.5, 3, 6, 8,
seq(from = 10, to = 80, by = 2)
)
)
# In this example we define a rule for dose increments that limits the further
# dose escalation to doses below 6, because dose 6 is above the probability
# toxicity threshold.
my_increments <- IncrementsHSRBeta(target = 0.3, prob = 0.95)
# Based on the rule above, we then calculate the maximum dose allowed.
my_next_max_dose <- maxDose(my_increments, data = my_data)
# create an object of class 'DataParts'
myData <- DataParts(x=c(0.1,0.5,1.5),
y=c(0,0,0),
doseGrid=c(0.1,0.5,1.5,3,6,
seq(from=10,to=80,by=2)),
part=c(1L,1L,1L),
nextPart=1L,
part1Ladder=c(0.1,0.5,1.5,3,6,10))
myIncrements <- IncrementsRelativeParts(dltStart=0,
cleanStart=1)
nextMaxDose <- maxDose(myIncrements,
data=myData)
# Create the 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(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)))
# In this example we define a rule for dose increments which would allow:
# - doubling the dose if no DLTs were yet observed
# - only increasing the dose by 1.33 if 1 or 2 DLTs were already observed
# - only increasing the dose by 1.2 if at least 3 DLTs were already observed
myIncrements <- IncrementsRelativeDLT(DLTintervals = c(0, 1, 3),
increments = c(1, 0.33, 0.2))
# Based on the rule above, we then calculate the maximum dose allowed
nextMaxDose <- maxDose(myIncrements,
data=data)
# Create the data
data <- Data(x=c(0.1, 0.5, 1.5, 3, 6, 8, 8, 8),
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, 8,
seq(from=10, to=80, by=2)))
# As example, here we are combining 2 different increment rules.
# The first rule is the following:
# maximum doubling the dose if no DLTs were observed at the current dose
# or maximum increasing the dose by 1.33 if 1 or 2 DLTs were observed at the current dose
# or maximum increasing the dose by 1.22 if 3 or more DLTs were observed
# The second rule is the following:
# maximum doubling the dose if the current dose is <20
# OR only maximum increasing the dose by 1.33 if the current dose is >=20
myIncrements1 <- IncrementsRelativeDLT(DLTintervals = c(0, 1, 3),
increments = c(1, 0.33, 0.2))
myIncrements2 <- IncrementsRelative(intervals=c(0, 20),
increments=c(1, 0.33))
# Now we combine the 2 rules
combIncrement <- IncrementMin(IncrementsList=
list(myIncrements1,myIncrements2))
# Finally we then calculate the maximum dose allowed by taking the minimum of the two rules
nextMaxDose <- maxDose(combIncrement,
data)
# Create the data
my_data <- Data(
x = c(0.1, 0.5, 1.5, 3, 6, 8, 8, 8, 6, 6, 6),
y = c(0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 1),
cohort = c(0, 1, 2, 3, 4, 5, 5, 5, 6, 6, 6),
doseGrid = c(0.1, 0.5, 1.5, 3, 6, 8,
seq(from = 10, to = 80, by = 2)
)
)
# In this example we define a rule for dose increments that limits the further
# dose escalation to doses below 6
my_increments <- IncrementsHSRBeta(target = 0.3, prob = 0.95)
# Based on the rule above, we then calculate the maximum dose allowed
my_next_max_dose <- maxDose(my_increments, data = my_data)
# Create the data
data <- Data(x=c(0.1, 0.5, 1.5, 3, 6, 8, 8, 8),
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, 8,
seq(from=10, to=80, by=2)))
# In this example we define a rule for dose increments which would allow:
# - doubling the dose if the last dose was below 20
# - only increasing the dose by 1.33 if the last dose was equal or above 20
myIncrements <- IncrementsRelative(intervals=c(0, 20),
increments=c(1, 0.33))
# Based on the rule above, we then calculate the maximum dose allowed
nextMaxDose <- maxDose(myIncrements,
data=data)
# Create the 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(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)))
# In this example we define a rule for dose increments which would allow:
# - doubling the dose if no DLTs were yet observed
# - only increasing the dose by 1.33 if 1 or 2 DLTs were already observed
# - only increasing the dose by 1.2 if at least 3 DLTs were already observed
myIncrements <- IncrementsRelativeDLT(DLTintervals = c(0, 1, 3),
increments = c(1, 0.33, 0.2))
# Based on the rule above, we then calculate the maximum dose allowed
nextMaxDose <- maxDose(myIncrements,
data=data)
# Create the data
data <- Data(x=c(0.1, 0.5, 1.5, 3, 6, 8, 8, 8),
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, 8,
seq(from=10, to=80, by=2)))
# In this example we define a rule for dose increments which would allow:
# - doubling the dose if the last dose was below 20
# - only increasing the dose by 1.33 if the last dose was equal or above 20
myIncrements <- IncrementsRelative(intervals=c(0, 20),
increments=c(1, 0.33))
# Based on the rule above, we then calculate the maximum dose allowed
nextMaxDose <- maxDose(myIncrements,
data=data)
0liver0815/onc-crmpack-test documentation built on Feb. 19, 2022, 12:25 a.m.
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Description Usage Arguments Details Value Functions Examples
Description
Determine the upper limit of the next dose based on the increments rule.
Increments control based on number of dose levels Increment rule to determine the maximum possible next dose based on maximum dose levels to increment for the next dose. Increment rule can be applied to last dose or maximum dose given so far.
Determine the maximum possible dose for escalation.
Determine the maximum possible dose for escalation.
Usage
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 | maxDose(increments, data, ...)
## S4 method for signature 'IncrementsRelative,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementsNumDoseLevels,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementsHSRBeta,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementsRelativeParts,DataParts'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementsRelativeDLT,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementMin,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementsHSRBeta_dk,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementsHSRBeta,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementsRelativeSafety,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementsRelativeSafetyFix,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementsNumDoseLevelsBaySafetyFix,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementsNlastDL,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementMinDLT1N1,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementsAbsoluteMax,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementsRelativeDLTmax,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementsRelativeMax,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementsSafetyStop,Data'
maxDose(increments, data, ...)
## S4 method for signature 'IncrementsSafetyStopFix,Data'
maxDose(increments, data, ...)
|
Arguments
increments |
The rule, an object of class
|
data |
The data input, an object of class |
... |
further arguments |
Details
This function outputs the maximum possible next dose, based on the
corresponding rule increments and the data.
Value
the maximum possible next dose
Functions
-
maxDose,IncrementsRelative,Data-method: Determine the maximum possible next dose based on relative increments -
maxDose,IncrementsRelativeParts,DataParts-method: Determine the maximum possible next dose based on relative increments and part 1 and 2 -
maxDose,IncrementsRelativeDLT,Data-method: Determine the maximum possible next dose based on relative increments determined by DLTs so far -
maxDose,IncrementMin,Data-method: Determine the maximum possible next dose based on multiple increment rules (taking the minimum across individual increments). -
maxDose,IncrementsHSRBeta_dk,Data-method: Determine the maximum possible next dose based on maximum eligible dose level to increment for the next dose below the target toxicity, by a % probability based on the Beta(a,b) distribution. this can be calculated for any number of patients in a cohort with a defined probability threshold of 90% i.e. 1- pbeta(target, x+a, n-x+b) < 0.90 where x=DLTs, n=patients for a dose and use Beta(a=1,b=1) (or probably a=b=0.5) if a dose satisfies the above criterio then eligible doses, are only the ones that that lower than that dose -
maxDose,IncrementsRelativeSafety,Data-method: Determine the maximum possible dose for escalation -
maxDose,IncrementsRelativeSafetyFix,Data-method: Determine the maximum possible dose for escalation -
maxDose,IncrementsNumDoseLevelsBaySafetyFix,Data-method: Determine the maximum possible dose for escalation -
maxDose,IncrementsNlastDL,Data-method: Determine the maximum possible next dose based on relative increments determined by DLTs so far -
maxDose,IncrementMinDLT1N1,Data-method: Determine the maximum possible next dose based on multiple increment rules (taking the minimum across individual increments). -
maxDose,IncrementsAbsoluteMax,Data-method: Determine the maximum possible next dose based on absolute increments -
maxDose,IncrementsRelativeDLTmax,Data-method: Determine the maximum possible next dose based on relative increments determined by DLTs so far -
maxDose,IncrementsRelativeMax,Data-method: Determine the maximum possible next dose based on relative increments -
maxDose,IncrementsSafetyStop,Data-method: Determine the maximum possible dose for escalation -
maxDose,IncrementsSafetyStopFix,Data-method: Determine the maximum possible dose for escalation
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 | # Create the data
data <- Data(x=c(0.1, 0.5, 1.5, 3, 6, 8, 8, 8),
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, 8,
seq(from=10, to=80, by=2)))
# In this example we define a rule for dose increments which would allow:
# - doubling the dose if the last dose was below 20
# - only increasing the dose by 1.33 if the last dose was equal or above 20
myIncrements <- IncrementsRelative(intervals=c(0, 20),
increments=c(1, 0.33))
# Based on the rule above, we then calculate the maximum dose allowed
nextMaxDose <- maxDose(myIncrements,
data=data)
# Create the data
data <- Data(x = c(0.1, 0.5, 1.5, 3, 6, 8, 8, 8, 12, 12, 12, 16, 16, 16, 10, 10, 10),
y = c(0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1, 0, 1, 0),
cohort = c(0, 1, 2, 3, 4, 5, 5, 5, 6, 6, 6, 7, 7, 7, 8, 8, 8),
doseGrid =
c(0.1, 0.5, 1.5, 3, 6, 8,
seq(from = 10, to = 80, by = 2)
)
)
# In this first example we define a rule for dose increments which would allow:
# Maximum skip one dose level, that is 2 dose levels higher than the last dose
# given. Maximum increment is explicitly defined as:
increments <- IncrementsNumDoseLevels(maxLevels = 2, basisLevel = "last")
# Since the default method is based on the last dose given, maximum increment
# can also be defined as:
increments <- IncrementsNumDoseLevels(maxLevels = 2)
# Based on the rule above, we then calculate the maximum dose allowed
max_dose <- maxDose(increments, data = data)
# In this second example we define a rule for dose increments which would allow:
# Maximum skip one dose level, that is 2 dose levels higher than the max dose
# given. Maximum increment is explicitly defined as:
increments <- IncrementsNumDoseLevels(maxLevels = 2, basisLevel = "max")
# Based on the rule above, we then calculate the maximum dose allowed
max_dose <- maxDose(increments, data = data)
# Create the data.
my_data <- Data(
x = c(0.1, 0.5, 1.5, 3, 6, 8, 8, 8, 6, 6, 6),
y = c(0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 1),
cohort = c(0, 1, 2, 3, 4, 5, 5, 5, 6, 6, 6),
doseGrid = c(0.1, 0.5, 1.5, 3, 6, 8,
seq(from = 10, to = 80, by = 2)
)
)
# In this example we define a rule for dose increments that limits the further
# dose escalation to doses below 6, because dose 6 is above the probability
# toxicity threshold.
my_increments <- IncrementsHSRBeta(target = 0.3, prob = 0.95)
# Based on the rule above, we then calculate the maximum dose allowed.
my_next_max_dose <- maxDose(my_increments, data = my_data)
# create an object of class 'DataParts'
myData <- DataParts(x=c(0.1,0.5,1.5),
y=c(0,0,0),
doseGrid=c(0.1,0.5,1.5,3,6,
seq(from=10,to=80,by=2)),
part=c(1L,1L,1L),
nextPart=1L,
part1Ladder=c(0.1,0.5,1.5,3,6,10))
myIncrements <- IncrementsRelativeParts(dltStart=0,
cleanStart=1)
nextMaxDose <- maxDose(myIncrements,
data=myData)
# Create the 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(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)))
# In this example we define a rule for dose increments which would allow:
# - doubling the dose if no DLTs were yet observed
# - only increasing the dose by 1.33 if 1 or 2 DLTs were already observed
# - only increasing the dose by 1.2 if at least 3 DLTs were already observed
myIncrements <- IncrementsRelativeDLT(DLTintervals = c(0, 1, 3),
increments = c(1, 0.33, 0.2))
# Based on the rule above, we then calculate the maximum dose allowed
nextMaxDose <- maxDose(myIncrements,
data=data)
# Create the data
data <- Data(x=c(0.1, 0.5, 1.5, 3, 6, 8, 8, 8),
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, 8,
seq(from=10, to=80, by=2)))
# As example, here we are combining 2 different increment rules.
# The first rule is the following:
# maximum doubling the dose if no DLTs were observed at the current dose
# or maximum increasing the dose by 1.33 if 1 or 2 DLTs were observed at the current dose
# or maximum increasing the dose by 1.22 if 3 or more DLTs were observed
# The second rule is the following:
# maximum doubling the dose if the current dose is <20
# OR only maximum increasing the dose by 1.33 if the current dose is >=20
myIncrements1 <- IncrementsRelativeDLT(DLTintervals = c(0, 1, 3),
increments = c(1, 0.33, 0.2))
myIncrements2 <- IncrementsRelative(intervals=c(0, 20),
increments=c(1, 0.33))
# Now we combine the 2 rules
combIncrement <- IncrementMin(IncrementsList=
list(myIncrements1,myIncrements2))
# Finally we then calculate the maximum dose allowed by taking the minimum of the two rules
nextMaxDose <- maxDose(combIncrement,
data)
# Create the data
my_data <- Data(
x = c(0.1, 0.5, 1.5, 3, 6, 8, 8, 8, 6, 6, 6),
y = c(0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 1),
cohort = c(0, 1, 2, 3, 4, 5, 5, 5, 6, 6, 6),
doseGrid = c(0.1, 0.5, 1.5, 3, 6, 8,
seq(from = 10, to = 80, by = 2)
)
)
# In this example we define a rule for dose increments that limits the further
# dose escalation to doses below 6
my_increments <- IncrementsHSRBeta(target = 0.3, prob = 0.95)
# Based on the rule above, we then calculate the maximum dose allowed
my_next_max_dose <- maxDose(my_increments, data = my_data)
# Create the data
data <- Data(x=c(0.1, 0.5, 1.5, 3, 6, 8, 8, 8),
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, 8,
seq(from=10, to=80, by=2)))
# In this example we define a rule for dose increments which would allow:
# - doubling the dose if the last dose was below 20
# - only increasing the dose by 1.33 if the last dose was equal or above 20
myIncrements <- IncrementsRelative(intervals=c(0, 20),
increments=c(1, 0.33))
# Based on the rule above, we then calculate the maximum dose allowed
nextMaxDose <- maxDose(myIncrements,
data=data)
# Create the 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(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)))
# In this example we define a rule for dose increments which would allow:
# - doubling the dose if no DLTs were yet observed
# - only increasing the dose by 1.33 if 1 or 2 DLTs were already observed
# - only increasing the dose by 1.2 if at least 3 DLTs were already observed
myIncrements <- IncrementsRelativeDLT(DLTintervals = c(0, 1, 3),
increments = c(1, 0.33, 0.2))
# Based on the rule above, we then calculate the maximum dose allowed
nextMaxDose <- maxDose(myIncrements,
data=data)
# Create the data
data <- Data(x=c(0.1, 0.5, 1.5, 3, 6, 8, 8, 8),
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, 8,
seq(from=10, to=80, by=2)))
# In this example we define a rule for dose increments which would allow:
# - doubling the dose if the last dose was below 20
# - only increasing the dose by 1.33 if the last dose was equal or above 20
myIncrements <- IncrementsRelative(intervals=c(0, 20),
increments=c(1, 0.33))
# Based on the rule above, we then calculate the maximum dose allowed
nextMaxDose <- maxDose(myIncrements,
data=data)
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