LRtox.nTTP {iAdapt}

Calculates likelihood of safety for single dose, using nTTP

Description

(nTTP) Function LRtox.nTTP() calculates the likelihood of safety for a single dose and designates whether to escalate to the next dose (safe) or stop dose escalation and move onto stage 2 (unsafe).

Usage

LRtox.nTTP(tox_grades, ntox, coh.size, W, p1, p2, K = 2, std.nTTP = 0.15)

Arguments

tox_grades

data frame of observed AE grades for each patient (rows) across all toxicity types (columns). e.g. for one patient, grades for 3 toxicity types might be c(3, 2, 4), where they experienced a grade 3 AE for tox type 1, grade 2 AE for tox type 2, etc.

ntox

number (integer) of different toxicity types

coh.size

cohort size (number of patients) per dose (Stage 1)

W

matrix defining burden weight of each grade level for all toxicity types. The dimensions are ntox rows by 5 columns (for grades 0-4). See Ezzalfani et al. (2013) for details.

p1

toxicity under null (unsafe DLT rate). Values range from 0 - 1.

p2

toxicity under alternative (safe DLT rate). Values range from 0 - 1; p1 > p2

K

threshold for LR. Takes integer values: 1,2,...(recommended K=2)

std.nTTP

the standard deviation of nTTP scores at each dose level (constant across doses)

Value

List object that gives the likelihood ratio of safety and indicates whether to escalate to the next highest dose level, or stop dose escalation and move onto stage 2.

Examples

ntox = 3 # three different types of toxicity 
coh.size = 3 # number of patients enrolled per dose

# Observed AE grades for each patient on tested dose
obs = data.frame(tox1 = c(3, 2, 4),
                 tox2 = c(1, 1, 2),
                 tox3 = c(2, 3, 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) 
             
# Acceptable (p2) and unacceptable nTTP values
p1 <- 0.35                                     
p2 <- 0.10       
             
LRtox.nTTP(obs, ntox, coh.size, W, p1, p2, K = 2, std.nTTP = 0.15)