| rand.stg2.nTTP {iAdapt} | R Documentation |
Stage 2 Adaptive Randomization with nTTP to monitor toxicity
Description
Function rand.stg2.nTTP() fits a linear regression for the continuous
efficacy outcomes, computes the randomization probabilities/dose and allocates the next patient
to a dose that is considered acceptably safe and has the highest efficacy. Dose safety
(with nTTP) is still monitored using LR and doses that become unacceptable are discarded
(never re-visited).
Usage
rand.stg2.nTTP(
dose,
p1,
p2,
K,
coh.size,
m,
v,
N,
stop.rule = 9,
cohort = 1,
samedose = TRUE,
nbb = 100,
W,
TOX,
ntox,
std.nTTP = 0.15
)
Arguments
dose |
number of doses to be tested (scalar) |
p1 |
toxicity under null (unsafe nTTP). Values range from 0 - 1. |
p2 |
toxicity under alternative (safe nTTP). Values range from 0 - 1; p1 > p2 |
K |
threshold for LR. Takes integer values: 1,2,...(recommended K=2) |
coh.size |
cohort size (number of patients) per dose (Stage 1) |
m |
vector of mean efficacies per dose. Values range from 0 - 100. (e.g, T cell persistence - values b/w 5 and 80 per cent) |
v |
vector of efficacy variances per dose. Values range from 0 - 1. (e.g., 0.01) |
N |
total sample size for stages 1&2 |
stop.rule |
if only dose 1 safe, allocate up to 9 (default) patients at dose 1 to collect more info |
cohort |
cohort size (number of patients) per dose (Stage 2). Default is 1. |
samedose |
designates whether the next patient is allocated to the same dose as the previous patient. Default is TRUE. Function adjusts accordingly. |
nbb |
binomial parameter (default = 100 cells per patient) |
W |
matrix defining burden weight of each grade level for all toxicity types. The dimensions are ntox rows by 4 columns (for grades 0-4). See Ezzalfani et al. (2013) for details. |
TOX |
matrix array of toxicity probabilities. There should be ntox matrices. Each matrix represents one toxicity type, where probabilities of each toxicity grade are specified across each dose. Each matrix has the same dimensions: n rows, representing number of doses, and 5 columns (for grades 0-4). Probabilities across each dose (rows) must sum to 1. See Ezzalfani et al. (2013) for details. |
ntox |
number (integer) of different toxicity types |
std.nTTP |
the standard deviation of nTTP scores at each dose level (constant across doses) |
Value
List of the following objects:
Y.final - vector of all efficacy outcomes (Ys) corresponding to dose assignments (Stages 1&2)
d.final - vector of all dose assignments(Stage 1&2)
n1 - Stage 1 sample size
If dose allocation stops early, put NAs in d.final and y.final until it reaches the total sample size.
Examples
# Number of pre-specified dose levels
dose <- 6
# Acceptable (p2) and unacceptable nTTP values
p1 <- 0.35
p2 <- 0.10
# Likelihood-ratio (LR) threshold
K <- 2
# Cohort size used in stage 1
coh.size <- 3
# Total sample size (stages 1&2)
N <- 25
# Efficacy (equal) variance per dose
v <- rep(0.01, 6)
# Dose-efficacy curve
m = c(10, 20, 30, 40, 70, 90)
# Number of toxicity types
ntox <- 3
# Toxicity burden weight matrix
W = matrix(c(0, 0.5, 0.75, 1.0, 1.5, # Burden weight for grades 0-4 for toxicity 1
0, 0.5, 0.75, 1.0, 1.5, # Burden weight for grades 0-4 for toxicity 2
0, 0.00, 0.00, 0.5, 1), # Burden weight for grades 0-4 for toxicity 3
nrow = ntox, byrow = TRUE)
# Standard deviation of nTTP value
std.nTTP = 0.15
# Array of toxicity event probabilities
TOX <- array(NA, c(dose, 5, ntox))
TOX[, , 1] = matrix(c(0.823, 0.152, 0.022, 0.002, 0.001,
0.791, 0.172, 0.032, 0.004, 0.001,
0.758, 0.180, 0.043, 0.010, 0.009,
0.685, 0.190, 0.068, 0.044, 0.013,
0.662, 0.200, 0.078, 0.046, 0.014,
0.605, 0.223, 0.082, 0.070, 0.020),
nrow = 6, byrow = TRUE)
TOX[, , 2] = matrix(c(0.970, 0.027, 0.002, 0.001, 0.000,
0.968, 0.029, 0.002, 0.001, 0.000,
0.813, 0.172, 0.006, 0.009, 0.000,
0.762, 0.183, 0.041, 0.010, 0.004,
0.671, 0.205, 0.108, 0.011, 0.005,
0.397, 0.258, 0.277, 0.060, 0.008),
nrow = 6, byrow = TRUE)
TOX[, , 3] = matrix(c(0.930, 0.060, 0.005, 0.001, 0.004,
0.917, 0.070, 0.007, 0.001, 0.005,
0.652, 0.280, 0.010, 0.021, 0.037,
0.536, 0.209, 0.031, 0.090, 0.134,
0.015, 0.134, 0.240, 0.335, 0.276,
0.005, 0.052, 0.224, 0.372, 0.347),
nrow = 6, byrow = TRUE)
rand.stg2.nTTP(dose = dose, p1 = p1, p2 = p2, K = K, coh.size = coh.size,
m = m, v = v, N = N, stop.rule = 9,
cohort = 1, samedose = TRUE, nbb = 100, W = W, TOX = TOX, ntox = ntox, std.nTTP = std.nTTP)