SimRMDEFF {phase1RMD} | R Documentation |
Simulation for an Adaptive, Multi-Stage Phase I Dose-Finding Design
Description
A function to implement simulation for an adaptive, multi-stage phase 1 dose-finding design incorporating a continuous efficacy outcome and toxicity data from multiple treatment cycles, proposed by Du et al(2017)
Usage
SimRMDEFF(numTrials = 100, trialSize = 36, doses = 1:6, cycles = 1:6,
eff.structure = c(0.1, 0.2, 0.3, 0.4, 0.7, 0.9),
eff.sd = 0.2, tox.target = 0.28, p1 = 0.2, p2 = 0.2,
ps1 = 0.2, StrDose = 1, chSize = 3,
tox.matrix = NULL,
proxy.thrd = 0.1, thrd1 = 0.28, thrd2 = 0.28,
wm = matrix(c(0, 0.5, 0.75, 1 , 1.5,
0, 0.5, 0.75, 1 , 1.5,
0, 0 , 0 , 0.5, 1 ),
byrow = T, ncol = 5),
toxmax = 2.5, toxtype = NULL, intercept.alpha = NULL,
coef.beta = NULL, cycle.gamma = NULL,
param.ctrl = list())
Arguments
numTrials |
An integer specifying the number of simulations. |
trialSize |
The maximum sample size for trial simulation. Default is 36. Must be the multiple of cohort size, represented by |
doses |
A vector of doses that users are going to explore. Default is |
cycles |
A vector of cycles that the treatment plans to go through. Default is |
eff.structure |
A vector of the mean values of efficacy outcome for each dose level explored. Default is |
eff.sd |
The standard deviation for generating the efficacy outcome for each patient. Default is 0.2, which already gives large skewness/variation. |
tox.target |
The target toxicity at cycle 1 of the treatment. Default is 0.28. |
p1 |
The probability cutoff for cycle 1 toxicity. Default is 0.2. See Details below. |
p2 |
The probability cutoff for later cycles toxicity beyond cycle 1. Default is 0.2. See Details below. |
ps1 |
The probability cutoff for defining allowable (safe) doses in stage 1. Default is 0.2. See Details below. |
StrDose |
A number to specify the starting dose. Default is 1. |
chSize |
The cohort size of patients recruited. Default is 3. |
tox.matrix |
Optional. A four-dimension array specifying the probabilities of the occurrences of certain grades for certain types of toxicities, at each dose level and cycle under consideration. Dimension 1 refers to doses; dimension 2 corresponds to cycles of the treatment; dimension 3 regards the types of toxicities while dimenion 4 relates to grades. If null, which is default choice, the arguments |
proxy.thrd |
A distance parameter to define efficacious doses. Any dose whose predicted efficacy is within |
thrd1 |
An upper bound of toxicity for cycle 1 of the treatment. Default is 0.28. See Details below. |
thrd2 |
An upper bound of toxicity for late cycles of the treatment, beyond cycle 1. Default is 0.28. See Details below. |
wm |
Clinical weight matrix, where toxicity types define the rows while the toxicity grades define the columns. Usually solicited from physicians. |
toxmax |
The normalization constant used in computing nTTP score. For details, see Ezzalfani et al(2013). |
toxtype |
Only specified when |
intercept.alpha |
Only specified when |
coef.beta |
Only specified when |
cycle.gamma |
Only specified when |
param.ctrl |
A list specifying the prior distribution for the parameters. |
Details
p1
,p2
,thrd1
and thrd2
are used to define allowable (safe) doses through the two probability conditions:
P(tox1 < thrd1) > p1
P(tox2 < thrd2) > p2
, where tox1 and tox2 denote the toxicity at cycle 1 of the treament and later cycles, respectively. In stage 1, ps1
acts as p1
and p2
.
The user can explore different dose-efficacy patterns using the argument eff.structure
. For example, eff.structure = c(0.5, 0.5, 0.5, 0.5, 0.5, 0.5)
corresponds to a flat relationship where the efficacy does not change with dose.
When tox.matrix
is null, the probability matrices of the occurrences of certain grades for certain types of toxicities, at each dose level and cycle will be simulated from a proportional odds model that takes toxtype
, intercept.alpha
, coef.beta
and cycle.gamma
as the inputs. The model is as follows:
logit(c_j) = \alpha_j + \beta * dose + \gamma * cycle, j=0,1,2,3
where given a dose and cycle, c_j
is the cumulative probabilities of occurrences of toxicities grades up to j
; \alpha_0, \alpha_1, \alpha_2, \alpha_3
are the intercepts, making up intercept.alpha
; coef.beta
stores \beta
for different types of toxicities while cycle.gamma
acts as \gamma
, controlling the cycle effect. The probability for the occurrence of a certain grade of a certain toxicity type at a given dose and cycle is obtained from taking the corresponding differences between cumulative probabilities.
Value
A list with the following components:
op.table |
A table reporting the operating characteristics of the trial simulation. |
sc |
The assumed true mean longitudinal toxicity and efficacy structure for each dose level under investigation, along with the probability of DLT event, for cycle 1 of the treatment. |
Examples
#######Dose 5 target toxicity dose, flat cycle effect#####################
###############a flat dose-efficacy pattern###############################
# simul <- SimRMDEFF(toxtype = c("H", "L", "M"),
# intercept.alpha = c(1.9, 2.3, 2.6, 3.1),
# coef.beta = c(-0.3, -0.2, -0.25),
# cycle.gamma = 0, tox.target = 0.23,
# thrd1 = 0.23, thrd2 = 0.23,
# eff.structure = rep(0.5, 6),
# p1 = 0.1, p2 = 0.1, ps1 = 0.1,
# numTrials = 1)