titecrm {dfcrm} | R Documentation |
titecrm
is used to compute a dose for the next patient in a
phase I trial according to the TITE-CRM.
titecrm(prior, target, tox, level, n = length(level), weights = NULL, followup = NULL, entry = NULL, exit = NULL, obswin = NULL, scheme = "linear", conf.level = 0.9, dosename = NULL, include = 1:n, pid = 1:n, method = "bayes", model = "empiric", var.est = TRUE, scale = sqrt(1.34), intcpt = 3, model.detail = TRUE, patient.detail = TRUE, tite = TRUE)
prior |
A vector of initial guesses of toxicity probabilities associated the doses. |
target |
The target DLT rate. |
tox |
A vector of patient outcomes; 1 indicates a toxicity, 0 otherwise. |
level |
A vector of dose levels assigned to patients. The length
of level must be equal to that of tox . |
n |
The number of patients enrolled. |
weights |
A vector of weights assigned to observations. A
weight must be between 0 and 1. If given, the arguments
followup , entry , exit , obswin ,
and scheme will be ignored.
If not supplied, users must provide follow-up information via
the argument followup or entry and exit , as
well as the observation window obswin . The length of
weights must be equal to that of tox . |
followup |
A vector of follow-up times of patients. If given,
the arguments entry and exit will be ignored. |
entry |
A vector of entry times of the patients. |
exit |
A vector of exit times of the patients due to either end of follow-up or toxicity. |
obswin |
The observation window with respect to which the MTD is
defined. If not supplied, users must provide weights . |
scheme |
A character string to specify the method for assigning weights. Default is ``linear''. An adaptive weight function is specified by ``adaptive''. |
conf.level |
Confidence level for the probability/confidence interval of the returned dose-toxicity curve. |
dosename |
A vector containing the names of the regimens/doses
used. The length of dosename must be equal to that of
prior . |
include |
A subset of patients included in the dose calculation. |
pid |
Patient ID provided in the study. Its length must be equal
to that of level . |
method |
A character string to specify the method for parameter estimation. The default method ``bayes'' estimates the model parameter by the posterior mean. Maximum likelihood estimation is specified by ``mle''. |
model |
A character string to specify the working model used in the method. The default model is ``empiric''. A one-parameter logistic model is specified by ``logistic''. |
var.est |
If TRUE, variance of the estimate of the model parameter and probability/confidence interval for the dose-toxicity curve will be computed. |
scale |
Standard deviation of the normal prior of the model parameter. Default is sqrt(1.34). |
intcpt |
The intercept of the working logistic model. The
default is 3. If model =``empiric'', this argument will be
ignored. |
model.detail |
If FALSE, the model content of an ``mtd'' object will not be displayed. Default is TRUE. |
patient.detail |
If FALSE, patient summary of an ``mtd'' object will not be displayed. Default is TRUE. |
tite |
If FALSE, the time components in patient summary of an ``mtd'' object will be omitted. Default in TRUE. |
The adaptive weighting scheme is given in Cheung and Chappell (2000) given in the reference list.
An object of class ``mtd'' is returned, consisting of the summary of dose assignments thus far and the recommendation of dose for the next patient.
prior |
Initial guesses of toxicity rates. |
target |
The target probability of toxicity at the MTD. |
ptox |
Updated estimates of toxicity rates. |
ptoxL |
Lower confidence/probability limits of toxicity rates. |
ptoxU |
Upper confidence/probability limits of toxicity rates. |
mtd |
The updated estimate of the MTD. |
prior.var |
The variance of the normal prior. |
post.var |
The posterior variance of the model parameter. |
estimate |
Estimate of the model parameter. |
method |
The method of estimation. |
model |
The working model. |
dosescaled |
The scaled doses obtained via backward substitution. |
tox |
Patients' toxicity indications. |
level |
Dose levels assigned to patients. |
followup |
Follow-up times of patients. |
obswin |
Observation window with respect to which the MTD is defined. |
weights |
Weights assigned to patients. |
entry |
Entry times of patients. |
exit |
Exit times of patients. |
scheme |
Weighting scheme. |
Cheung, Y. K. and Chappell, R. (2000). Sequential designs for phase I clinical trials with late-onset toxicities. Biometrics 56:1177-1182.
# Create a simple data set prior <- c(0.05,0.10,0.20,0.35,0.50,0.70) target <- 0.2 level <- c(3,3,3,4,4,3,2,2,2,3) y <- c(0,0,1,0,1,0,0,0,0,0) u <- c(178,181,168,181,24,181,179, 102, 42, 3) tau <- 180 foo <- titecrm(prior,target,y,level,followup=u,obswin=tau) rec <- foo$mtd # recommend a dose level for next patient # An example with adaptive weight foo2 <- titecrm(prior,target,y,level,followup=u,obswin=tau,scheme="adaptive") wts <- foo2$weights # The `weights' argument makes `followup' and `obswin' obsolete foo3 <- titecrm(prior,target,y,level,weights=wts,followup=u,obswin=tau) ## Not run: plot(foo3,ask=T) # Patient time information via `entry' and `exit' arguments entry <- c(7, 29, 49, 76, 92, 133, 241, 303, 363, 402) # entry time (days since study begins) exit <- c(185,210,217,257,116,314,420,405,405,405) # exit time (days since study begins) foo4 <- titecrm(prior,target,y,level,exit=exit,entry=entry,obswin=tau) ## Not run: plot(foo4,ask=T)