eff.stg1.nTTP: Generates efficacy outcomes for stage 1 when using nTTP to...
In iAdapt: Two-Stage Adaptive Dose-Finding Clinical Trial Design

Description Usage Arguments Value Examples

Function eff.stg1.nTTP() uses a beta-binomial distribution to generate outcomes (Ys) corresponding to acceptable dose assignments from stage 1.

eff.stg1.nTTP(
  dose,
  p1,
  p2,
  K,
  coh.size,
  m,
  v,
  nbb = 100,
  W,
  TOX,
  ntox,
  std.nTTP
)

`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)
`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 (assumed constant across doses)

List of efficacy outcomes for subjects enrolled during stage 1 (dose-escalation)

Y.safe - vector of efficacy outcomes for each subject assigned to an acceptable safe dose
d.safe - vector of dose allocation for each subject assigned to an acceptable safe dose
tox.safe - number of dose-limiting toxicities for each safe dose level
Y.alloc - vector of efficacy outcomes for all subjects from stage 1 (acceptable and unsafe doses)
d.alloc - vector of dose allocation for all subjects from stage 1 (acceptable and unsafe doses)
all_nttp - all observed nTTP values

# 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 

# 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 values
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)

eff.stg1.nTTP(dose = dose, p1 = p1, p2 = p2, K = K, coh.size = coh.size, 
m = m, v = v, nbb = 100, W = W, TOX = TOX, ntox = ntox, std.nTTP = std.nTTP)