titecrm {titecrm} | R Documentation |
Returns an object of class mtd
that summarizes the dose
assignments and recommends a dose for the next patient
in a phase I trial using TITE-CRM.
titecrm(prior, target, tox, level, n=length(level), weights=NULL, followup=NULL, obswin=NULL, scheme="linear", dosename=NULL, include=1:n, pid=1:n, method="bayes", scale=sqrt(1.34), model.detail=TRUE, patient.detail=TRUE)
prior |
A vector of initial estimates 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 . |
weights |
A vector of weights assigned to observations. A
weight must be between 0 and 1. If given, the arguments
followup , obswin , and scheme will be ignored.
If not supplied, users must provide followup and
obswin . The length of weights must be equal to that
of tox . |
n |
The number of enrollments. |
followup |
A vector of follow-up times of patients. If not
supplied, users must provide weights . |
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''. Adaptive weight using Kaplan-Meier ``KM'' is to be made available. |
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. Estimation using ``mle'' is to be made available. |
scale |
Standard deviation of the normal prior of the model parameter. Default is sqrt(1.34). |
model.detail |
If TRUE, the model content of an ``mtd'' object will be displayed in detail. |
patient.detail |
If TRUE, patient summary will be given in detail. |
Dose-toxicity relationship is assumed as an empiric power model $a_i^{exp(β)}$ where $a_i$ is the initial estimate of toxicity probability of dose level i and the model parameter $β$ has a normal prior with mean 0 and scale to be provided by users.
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 estimates of toxicity probabilities. |
ptox |
Updated estimates of toxicity probabilities. |
target |
The target probability of toxicity at the MTD. |
recommend |
The recommended dose level for the next patient. |
scale |
The standard deviation of the normal prior. |
estimate |
Estimate of the model parameter. |
level |
Dose levels assigned to patients. |
tox |
Patients' toxicity indications. |
followup |
Follow-up times of patients. |
obswin |
Observation window with respect to which the MTD is defined. |
weights |
Weights assigned to 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(3,4,4,3,3,4,3,2,2,2) y <- c(0,0,1,0,0,1,1,0,0,0) u <- c(1,1,0.8,1,1,0.6,0.45,0.25,1/6,1/12) tau <- 1 foo <- titecrm(prior,target,y,level,followup=u,obswin=1) rec <- foo$recommend # recommend a dose level for next patient