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

Description Usage Arguments Value Examples

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

1	eff.stg1(dose, dose.tox, p1, p2, K, coh.size, m, v, nbb = 100)

`dose`	number of doses to be tested (scalar)
`dose.tox`	vector of true toxicities for each dose. Values range from 0 - 1.
`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)
`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)

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)

# Number of pre-specified dose levels
dose <- 5
# Vector of true toxicities associated with each dose
dose.tox <- c(0.05, 0.10, 0.20, 0.35, 0.45)       
# Acceptable (p2) and unacceptable (p1) DLT rates used for establishing safety
p1 <- 0.40                                     
p2 <- 0.15   

# Likelihood-ratio (LR) threshold
K <- 2                                          

# Cohort size used in stage 1
coh.size <- 3 

# Vector of true mean efficacies per dose (here mean percent persistence per dose)
m <- c(5, 15, 40, 65, 80)   # MUST BE THE SAME LENGTH AS dose.tox                  

# Efficacy (equal) variance per dose
v <- rep(0.01, 5) 

# Total sample size (stages 1&2)                            
N <- 25                                        

# Stopping rule: if dose 1 is the only safe dose, allocate up to 9 pts.
stop.rule <- 9 

eff.stg1(dose = dose, dose.tox = dose.tox, p1 = p1, p2 = p2, K = K, 
coh.size = coh.size, m, v, nbb = 100)