eff.stg1.nTTP {iAdapt}R Documentation

Generates efficacy outcomes for stage 1 when using nTTP to measure toxicity

Description

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

Usage

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

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)

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)

Value

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

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 

# 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) 



[Package iAdapt version 2.0.1 Index]