ewoc_d1extended: Escalation With Overdose Control
In dnzmarcio/ewoc: Escalation with Overdose Control

Description Usage Arguments Value References Examples

Finding the next dose for a phase I clinical trial based on the Escalation with Overdose Control (EWOC) design considering the extended parametrization for binary response and single agent.

ewoc_d1extended(
  formula,
  theta,
  alpha,
  rho_prior,
  min_dose,
  max_dose,
  type = c("continuous", "discrete"),
  first_dose = NULL,
  last_dose = NULL,
  dose_set = NULL,
  max_increment = NULL,
  no_skip_dose = TRUE,
  rounding = c("down", "nearest"),
  n_adapt = 5000,
  burn_in = 1000,
  n_mcmc = 1000,
  n_thin = 1,
  n_chains = 1
)

`formula`	an object of class `Formula`: a symbolic description of the model to be fitted with only one regressor term corresponding to the dose for the right side and a numeric vector as a response containing number of DLT for the left side.
`theta`	a numerical value defining the proportion of expected patients to experience a medically unacceptable, dose-limiting toxicity (DLT) if administered the MTD.
`alpha`	a numerical value defining the probability that the dose selected by EWOC is higher than the MTD.
`rho_prior`	a matrix 3 x 2 of hyperparameters for the Beta prior distribution associated with each parameter rho. Each row corresponds to a parameter.
`min_dose`	a numerical value defining the lower bound of the support of the MTD.
`max_dose`	a numerical value defining the upper bound of the support of the MTD.
`type`	a character describing the type of the Maximum Tolerable Dose (MTD) variable.
`first_dose`	a numerical value for the first allowable dose in the trial.
`last_dose`	a numerical value for the last allowable dose in the trial.
`dose_set`	a numerical vector of allowable doses in the trial. It is only necessary if type = "discrete".
`max_increment`	a numerical value indicating the maximum increment from the current dose to the next dose. It is only applied if type = 'continuous'.
`no_skip_dose`	a logical value indicating if it is allowed to skip doses. It is only necessary if type = 'discrete'. The default is TRUE.
`rounding`	a character indicating how to round a continuous dose to the one of elements of the dose set. It is only necessary if type = "discrete".
`n_adapt`	the number of iterations for adaptation. See `adapt` for details.
`burn_in`	the number of iterations before to start monitoring.
`n_mcmc`	the number of iterations to monitor.
`n_thin`	thinning interval for monitors.
`n_chains`	the number of parallel chains for the model.

next_dose the next recommend dose.

mtd a numerical vector for the posterior MTD distribution considering the next patient covariable.

rho a matrix for the posterior rho_0 and rho_1 distributions.

sample a list of the MCMC chains distribution.

trial a list of the trial conditions.

Tighiouart, M., Cook-Wiens, G., & Rogatko, A. (2018). A Bayesian adaptive design for cancer phase I trials using a flexible range of doses. Journal of biopharmaceutical statistics, 28(3), 562-574.

DLT <- 0
dose <- 20

test <- ewoc_d1extended(DLT ~ dose, type = 'discrete',
                       theta = 0.33, alpha = 0.25,
                       dose_set = seq(20, 100, 20),
                       min_dose = 20, max_dose = 100,
                       rho_prior = matrix(1, ncol = 2, nrow = 2),
                       rounding = "nearest")
summary(test)
plot(test)