applied_crm: Execute the CRM

In dtpcrm: Dose Transition Pathways for Continual Reassessment Method

Description

applied_crm is used to execute the continual reassessment method with specified design options to determine the dose for the next subject.

Usage

applied_crm(prior, target, tox, level, no_skip_esc = TRUE,
  no_skip_deesc = TRUE, global_coherent_esc = TRUE, stop_func = NULL,
  ...)

Arguments

prior	A vector of prior estimates of toxicity probabilties for the dose levels.
target	The target DLT rate.
tox	A vector of subject outcomes; 1 indicates toxicity, 0 otherwise.
level	A vector of dose levels assigned to subjects. The length of level must be equal to that of tox.
no_skip_esc	If FALSE, the method will not enforce no skipping of doses in escalation. Default is TRUE.
no_skip_deesc	If FALSE, the method will not enforce no skipping of doses in de-escalation. Default is TRUE.
global_coherent_esc	If FALSE, the method will not enforce global coherent escalation, that is, escalation if the overall rate of toxicity seen at the current dose level is above the target rate. Default is TRUE.
stop_func	An optional argument to provide a function which will utilised alongside the CRM to determine if the trial should be stopped.
...	Any other arguments detailed in dfcrm::crm.

Details

For maximum likelihood estimation, the variance of the estimate of beta (post.var) is approximated by the posterior variance of beta with a dispersed normal prior.

The empiric model is specified as F(d, beta) = d^exp(beta). The logistic model is specified as logit (F(d,beta)) = intcpt + exp(beta) * d. For method="bayes", the prior on beta is normal with mean 0. Exponentiation of beta ensures an increasing dose-toxicity function.

This function is largely a wrapper for the dfcrm function crm. It provides functionality for additional design choices for the CRM including global coherency and stopping for excess toxicity and stopping when sufficient number of subjects are dosed at MTD.

Value

An object of class "mtd" is returned as per package "dfcrm", additional information is provided if a stopping function is used.

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.
stop	A logical variable detailing if the trial should be stopped; TRUE to stop, FALSE otherwise
stop_reason	A detailed reason for why the trial should be stopped. Only provided if stop is TRUE

References

O'Quigley, J. O., Pepe, M., and Fisher, L. (1990). Continual reassessment method: A practical design for phase I clinical trials in cancer. Biometrics 46:33-48.

Cheung, Y. K. (2011). Dose Finding by the Continual Reassessment Method. New York: Chapman & Hall/CRC Press.

Examples

prior  <- c(0.1, 0.3, 0.5)
target <- 0.2
tox    <- c(0, 0, 1, 0, 1, 1)
level  <- c(1, 1, 1, 2, 2, 2)
applied_crm(prior, target, tox, level, no_skip_esc = TRUE, no_skip_deesc = TRUE,
            global_coherent_esc = TRUE, stop_func = NULL)

dtpcrm documentation built on Aug. 20, 2019, 5:23 p.m.