This method selects dose by the algorithm for identifying the maximum
tolerable dose (MTD) described in Yan et al. (2019). This class is intended
to be used when a BOIN trial has reached its maximum sample size. Thus, it
intends to make the final dose recommendation after the regular BOIN dose
selection algorithm, as implemented by get_boin, including any
additional behaviours that govern stopping (etc), has gracefully concluded a
dose-finding trial. However, the class can be used in any scenario where
there is a target toxicity rate. See Examples. Note - this class will not
override the parent dose selector when the parent is advocating no dose. Thus
this class will not reinstate a dangerous dose.
select_boin_mtd(
parent_selector_factory,
when = c("finally", "always"),
target = NULL,
...
)Object of type selector_factory.
Either of: 'finally' to select dose only when the parent dose-selector has finished, by returning continue() == FALSE; or 'always' to use this dose-selection algorithm for every dose decision. As per the authors' original intentions, the default is 'finally'.
We seek a dose with this probability of toxicity. If not provided, the value will be sought from the parent dose-selector.
Extra args are passed to select.mtd.
an object of type selector_factory.
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.v000.i00
# This class is intended to make the final dose selection in a BOIN trial:
target <- 0.25
model <- get_boin(num_doses = 5, target = target) %>%
stop_at_n(n = 12) %>%
select_boin_mtd()
outcomes <- '1NNN 2NTN 2NNN 3NTT'
model %>% fit(outcomes) %>% recommended_dose()
#> [1] 2
# However, since behaviour is modular in this package, we can use this method
# to select dose at every dose decision if we wanted:
model2 <- get_boin(num_doses = 5, target = target) %>%
select_boin_mtd(when = 'always')
model2 %>% fit('1NNT') %>% recommended_dose()
#> [1] 1
model2 %>% fit('1NNN 2NNT') %>% recommended_dose()
#> [1] 2
# and with any underlying model:
skeleton <- c(0.05, 0.1, 0.25, 0.4, 0.6)
model3 <- get_dfcrm(skeleton = skeleton, target = target) %>%
select_boin_mtd(when = 'always')
model3 %>% fit('1NNT') %>% recommended_dose()
#> [1] 1
model3 %>% fit('1NNN 2NNT') %>% recommended_dose()
#> [1] 2