get.oc.pop {PoPdesign}

Operating characteristics for single-agent trials

Description

Generate the operating characteristics of the PoP design by simulating trials.

Usage

get.oc.pop(target,n,cohortsize,titration,skeleton,n.trial,cutoff,cutoff_e,
                     risk.cutoff,earlyterm,start,seed)

Arguments

target

the target DLT rate

n

total sample size

cohortsize

the cohort size

titration

default is TRUE. Set titration=TRUE to perform dose escalation with cohort size = 1 to accelerate dose escalation at the beginning of the trial.

skeleton

a vector containing the true toxicity probabilities of the investigational dose levels.

n.trial

the total number of trials to be simulated

cutoff

the cutoff for the predictive Bayes Factor (PrBF). Users can specify either a value or a function for cutoff. If PrBF < cutoff, we assign the next cohort of patients to an adjacent dose based on observed DLT. Otherwise, the evidence is in favor of H_{0j} and we need to retain the current dose.

cutoff_e

the cutoff for the dose exclusion rule. If PrBF_{0,1}<E(n_j), the evidence is in favor of H_{1j}. If \hat{\pi}_j < \phi, the current dose is deemed as subtherapeutic and we exclude the current dose and lower doses; If \hat{\pi}_j > \phi, the current dose is overly toxic and we exclude the current dose and higher doses.

risk.cutoff

the cutoff to eliminate an over/under toxic dose. We recommend the default value of (risk.cutoff=0.8) for general use.

earlyterm

the early termination parameter.

start

specify the starting dose level. Default value is 1.

seed

the seed for random number generation. Default is 123.

Details

TBD

Value

get.oc.pop() returns the operating characteristics of the PoP design as a list, including:

(1) selection percentage at each dose level ($sel.pct),

(2) the number of patients treated at each dose level ($num.p),

(3) the number of toxicities observed at each dose level ($num.tox),

(4) the average number of toxicities,

(5) the average number of patients,

(6) the percentage of early stopping without selecting the MTD ($early),

(7) risk of underdosing 80% or more of patients ($risk.under),

(8) risk of overdosing 80% or more of patients ($risk.over)

References

Brunk, H., Barlow, R. E., Bartholomew, D. J. & Bremner, J. M (1972, ISBN-13: 978-0471049708).

Examples

## get the operating characteristics for single-agent trials
oc <- get.oc.pop(target=0.3,n=15,cohortsize=3,titration=TRUE,
                 cutoff=2.5,cutoff_e=5/24,
                 skeleton=c(0.3,0.4,0.5,0.6),n.trial=1000,
                     risk.cutoff=0.8,earlyterm=TRUE,start=1, seed=123)

summary(oc) # summarize design operating characteristics
plot(oc)