dfpk (version 2.0.0)

dtox: Dose finding method DTOX.

Description

The DTOX model is constructed to test the behaviours of a way of estimating probabilities of toxicity. This enables us to estimate posterior probability of toxicity $p_T$ versus dose directly. It presents a statistical model to link $p_T$ and dose.

Usage

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

Arguments

y

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

auc

The AUC values of each patient.

doses

The doses levels of the drug.

lev

A vector of dose levels assigned to the patients.

theta

The toxicity (probability) target.

p_0

The skeleton of CRM; defaults to NULL. (must be defined only in the PKCRM model)

L

A threshold set before starting the trial; defaults to NULL. (must be defined only in the PKCRM model)

betapriors

A vector of the regression parameters in the 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).

See Also

scenarios, nsim, nextDose

Examples

### Betapriors ###
param_pk <- c(2,10,100)
beta0mean <- (log(param_pk[2])+log(10.96))/sqrt(0.7**2 + 0**2)
beta1mean <- 1 / 0.7
betapriors <- c(beta0mean, beta1mean)

p_0 = NULL
L = NULL
d <- c(12.59972,34.65492,44.69007,60.80685,83.68946,100.37111)
theta <- 0.2
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 <- c(0, 1.3, -0.34, -2.7,0.39, -2.45)

dtox(y, AUCs, d, x, theta, p_0, L,betapriors,D_AUC, options)