Get Operating Characteristics for the BF-BOIN Design
get.oc.bf(
ntrial = 1000,
seed = 3262,
target = 0.25,
p.true = c(0.1, 0.3, 0.5),
ncohort = 10,
cohortsize = 3,
n.earlystop = 100,
startdose = 1,
titration = FALSE,
p.saf = 0.6 * target,
p.tox = 1.4 * target,
cutoff.eli = 0.95,
extrasafe = FALSE,
offset = 0.05,
boundMTD = FALSE,
n.cap = 12,
end.backfill = TRUE,
n.per.month = 3,
dlt.window = 1,
p.response.true = c(1, 1, 1),
three.plus.three = FALSE,
accrual = "uniform",
backfill.assign = "highest"
)get.oc.bf() returns the operating characteristics of the BOIN design as a list,
including:
(1) selection percentage at each dose level ($selpercent),
(2) the average number of patients treated at each dose level ($npatients),
(3) the percentage of patients treated at each dose level on average ($percentpatients),
(4) the average number of toxicities observed at each dose level ($ntox),
(5) the average number of toxicities in total ($totaltox),
(6) the average number of patients in total($totaln),
(7) the percentage of early stopping without selecting the MTD ($percentstop),
(8) the average duration of the trial (duration).
the total number of trials to be simulated
the random number seed for simulation
the target DLT rate
a vector containing the true toxicity probabilities of the investigational dose levels.
the total number of cohorts
the cohort size
the early stopping parameter. If the number of patients
treated at the current dose reaches n.earlystop,
stop the trial and select the MTD based on the observed data.
The default value n.earlystop=100 essentially turns
off this type of early stopping.
the starting dose level for the trial
set titration=TRUE to perform dose escalation with cohort size = 1 to accelerate dose escalation at the begining of the trial.
the highest toxicity probability that is deemed subtherapeutic
(i.e. below the MTD) such that dose escalation should be undertaken.
The default value is p.saf=0.6*target.
the lowest toxicity probability that is deemed overly toxic such
that deescalation is required. The default value is
p.tox=1.4*target).
the cutoff to eliminate an overly toxic dose for safety.
We recommend the default value of (cutoff.eli=0.95) for general use.
set extrasafe=TRUE to impose a more stringent stopping rule
a small positive number (between 0 and 0.5) to control how strict the
stopping rule is when extrasafe=TRUE. A larger value leads to a more
strict stopping rule. The default value offset=0.05 generally works well.
set boundMTD=TRUE to impose the condition: the isotonic estimate of toxicity probability
for the selected MTD must be less than de-escalation boundary.
permanently close a dose for backfilling if the number of patients assigned
to the dose reaches n.cap
when the dose escalation ends, the backfilling by definition also ends. Default is TRUE.
patient accrual rate per month
DLT assessment window (months)
a vector containing the true response probabilities of the investigational dose levels
modify the decision from de-escalation to stay when observing 1 DLT out of 3 patients
"uniform" or "poisson", according to whether accrual distribution is uniform (consistent with Shiny App) or a Poisson process (consistent with publication)
How to assign backfill dose given the open backfill doses. Options are "highest" (default), "lowest", or "random".
Zhao Y, Yuan Y, Korn EL, Freidlin B. Backfilling patients in phase I dose-escalation trials using Bayesian optimal interval design (BOIN). Clinical Cancer Research. 2024 Feb 16;30(4):673-9.
get.oc.bf(ntrial = 1000,
seed = 9,
target = 0.25,
p.true = c(0.1, 0.5),
ncohort = 10,
cohortsize = 3,
n.earlystop = 9,
startdose = 1,
titration = FALSE,
cutoff.eli = 0.95,
extrasafe = TRUE,
offset = 0.1,
boundMTD=FALSE,
n.cap = 12,
end.backfill = TRUE,
n.per.month = 1,
dlt.window = 1,
p.response.true = c(0.001, 0.001))
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