Get an object to fit the BOIN model using the BOIN package.

Get an object to fit the BOIN model using the BOIN package.

Usage

get_boin(
  num_doses,
  target,
  use_stopping_rule = TRUE,
  stop_when_deescalation_impossible = FALSE,
  ...
)

Arguments

num_doses

Number of doses under investigation.

target

We seek a dose with this probability of toxicity.

use_stopping_rule

TRUE to use the toxicity stopping rule described in Yan et al. (2019). FALSE to suppress the authors' stopping rule, with the assumption being that you will test the necessity to stop early in some other way.

stop_when_deescalation_impossible

TRUE to stop a trial and recommend no dose when the advice is to de-escalate but de-escalation is impossible because we are already at the lowest dose. Note that this feature was requested by a user. This param is FALSE by default so that behaviour matches what was described in the publication. The original authors do advocate this behaviour.

...

Extra args are passed to get.boundary.

Value

an object of type selector_factory that can fit the BOIN model to outcomes.

References

Yan, F., Pan, H., Zhang, L., Liu, S., & Yuan, Y. (2019). BOIN: An R Package for Designing Single-Agent and Drug-Combination Dose-Finding Trials Using Bayesian Optimal Interval Designs. Journal of Statistical Software, 27(November 2017), 0–35. https://doi.org/10.18637/jss.v094.i13

Liu, S., & Yuan, Y. (2015). Bayesian optimal interval designs for phase I clinical trials. J. R. Stat. Soc. C, 64, 507–523. https://doi.org/10.1111/rssc.12089

Examples

target <- 0.25
model1 <- get_boin(num_doses = 5, target = target)

outcomes <- '1NNN 2NTN'
model1 %>% fit(outcomes) %>% recommended_dose()
#> [1] 1