Description Usage Arguments Details Value Examples
RunRMD estimate the dosage for the next patient cohort using TTP measured multidimensional toxicity data collected from multiple treatemnt cycles of the existing patients.
1 2 |
data |
Toxicty data collected from the multiple treatment cycles of existing patient cohorts. |
control |
Prior distributions as specified by |
trlSize |
Total number of patients in the trial. |
tox.target |
Target toxicity score (default = 0.28). |
sdose |
Total number of patients in the trial. |
strDose |
Start dose. |
iter |
Total number of MCMC simulations (default = 4000). |
burnin |
Number of burn-ins in the MCMC simulation (default = 1000). |
thin |
Thinning parameter (default = 1). |
chains |
Number of chains in the MCMC simulation (default = 1). |
The RunRMD
function uses the patient data structure patdata
to fit the linear mixed model as specified by formula
based on the prior distributions as specified by control
. The parameters of the MCMC simulation are specified by iter
: the number of iterations, burnin
: burn-ins, thin
: thinning parameter and chains
: number of chains in the MCMC simulation. The target nTTP score is defined by tox.target
, default = 0.28.
A list containing the following elements:
nxtdose |
Recommended dose for the next patient cohort. |
tox.est |
Mean, SD, median estimates and 2.5%, 25%, 50%, 75%, 97.5% quantile estimates of the toxicity score at each dose level. |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | # Setup the prior distributions for the phase I dose-finding model:
control <- list(
beta.dose = parm("normal", mean = 0, var = 1000),
beta.other = parm("normal", mean = 0, var = 1000 ),
gamma = parm("normal", mean = 0, var = 100 ),
s2.gamma = parm("invgamma", shape = 0.001, scale = 0.001),
s2.epsilon = parm("invgamma", shape = 0.001, scale = 0.001)
)
# Load the example patient toxicity data:
# data(patdata)
# Estimate the dose-recommendation of the next patient cohort based on the toxicity data:
# fit <- RunRMD(data = patdata, control = control, trlSize = 36, tox.target = 0.28,
# sdose = 1:6, strDose = 1, iter = 2000, burnin = 500, thin = 1, chains = 1)
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