dfpk (version 1.0)

pkcrm: Dose finding method PKCRM

Description

This model is a modification of CRM model which is constructed in order to avoid the problem that we need to know the target AUC related to DLTs. Thus, we proposed a new model PKCRM, with power working model and normal prior on the parameter.

Usage

pkcrm(y, auc, doses, lev, theta, p_0, L, betapriors, D_AUC, options)

Arguments

y

A vector of patient outcomes; TRUE indicates a toxicity, FALSE otherwise.

auc

The AUC numbers of each patient.

doses

The doses levels of the drug.

lev

A vector of dose levels assigned to patients.

theta

The toxicity (probability) target.

p_0

Skeleton of CRM.

L

A threshold set before starting the trial.

betapriors

A vector of the regression parameters in pkcrm model.

D_AUC

A vector specifying the difference between the AUCs and AUC_pop; defaults to NULL.

options

A list of three integers specifying the stan model's number of chains, how many iterations for each chain and the number of warmup iterations. defaults to options <- list(nchains = 4, niter = 4000, nadapt = 0.8)

References

Ursino, M., et al, (2016) Dose-finding methods using pharmacokinetics in small populations (under review).

Patterson, S., Francis, S., Ireson, M., Webber, D., and Whitehead, J. (1999) A novel bayesian decision procesure for early-phase dose-finding studies. Journal of Biopharmaceutical Statistics, 9 (4), 583-597.

Whitehead, J., Patterson, S., Webber, D., Francis, S., and Zhou, Y. (2001) Easy-to-implement bayesian methods for dose-escalation studies in healthy volunteers. Biostatistics, 2 (1), 47-61.

See Also

scenarios, sim

Examples

p_0 <- c(.01,.05,.1,.2,.35,0.45)      # Skeleton of CRM
L = log(15.09)
d <- c(12.59972,34.65492,44.69007,60.80685,83.68946,100.37111)
theta <- 0.2                # choice
options <- list(nchains = 2,
                niter = 4000,
                nadapt = 0.8)  
AUCs <-  c(0.43, 1.4, 5.98, 7.98, 11.90, 3.45)
x <- c(1,2,3,4,5,6)                
y <- c(FALSE,FALSE,FALSE,FALSE,TRUE,FALSE)
D_AUC <- NULL

### Betapriors ###
betapriors = NULL
pkcrm(y, AUCs, d, x, theta, p_0, L, betapriors, D_AUC,options)