R/boin_comb_selector.R
get_boin_comb.RdGet an object to fit the BOIN COMB model using the BOIN package.
get_boin_comb(
parent_selector_factory = NULL,
num_doses,
target,
use_stopping_rule = TRUE,
...
)optional object of type
selector_factory that is in charge of dose selection before
this class gets involved. Leave as NULL to just use CRM from the start.
integer vector of the number of doses of treatment 1, 2
We seek a dose with this probability of toxicity.
TODO
Extra args are passed to next.comb.
an object of type selector_factory that can fit the
BOIN COMB model to outcomes.
Lin, R., & Yin, G. (2017). Bayesian optimal interval design for dose finding in drug-combination trials. Statistical methods in medical research, 26(5), 2155-2167.
num_doses <- c(3, 4)
target <- 0.25
boin_fitter <- get_boin_comb(num_doses = num_doses, target = target)
x1 <- fit(boin_fitter, outcomes = "1.1NNN")
x1
#> Patient-level data:
#> # A tibble: 3 × 5
#> Cohort Patient Dose_string Dose Tox
#> <int> <int> <chr> <list> <int>
#> 1 1 1 1.1 <int [2]> 0
#> 2 1 2 1.1 <int [2]> 0
#> 3 1 3 1.1 <int [2]> 0
#>
#> Dose-level data:
#> Warning: `...` must be empty in `format.tbl()`
#> Caused by error in `format_tbl()`:
#> ! `...` must be empty.
#> ✖ Problematic argument:
#> • digits = 3
#> # A tibble: 13 × 8
#> dose tox n empiric_tox_rate mean_prob_tox median_prob_tox admissible
#> <ord> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl>
#> 1 NoDose 0 0 0 0 0 TRUE
#> 2 1.1 0 3 0 0.0161 0.000000215 TRUE
#> 3 1.2 0 0 NaN 0.5 0.500 TRUE
#> 4 1.3 0 0 NaN 0.5 0.500 TRUE
#> 5 1.4 0 0 NaN 0.5 0.500 TRUE
#> 6 2.1 0 0 NaN 0.5 0.500 TRUE
#> 7 2.2 0 0 NaN 0.5 0.500 TRUE
#> 8 2.3 0 0 NaN 0.5 0.500 TRUE
#> 9 2.4 0 0 NaN 0.5 0.500 TRUE
#> 10 3.1 0 0 NaN 0.5 0.500 TRUE
#> 11 3.2 0 0 NaN 0.5 0.500 TRUE
#> 12 3.3 0 0 NaN 0.5 0.500 TRUE
#> 13 3.4 0 0 NaN 0.5 0.500 TRUE
#> # ℹ 1 more variable: recommended <lgl>
#>
#> The model targets a toxicity level of 0.25.
#> The model advocates continuing at dose 2.1.
x2 <- fit(boin_fitter, outcomes = "1.1NNN 2.1TNT")
x2
#> Patient-level data:
#> # A tibble: 6 × 5
#> Cohort Patient Dose_string Dose Tox
#> <int> <int> <chr> <list> <int>
#> 1 1 1 1.1 <int [2]> 0
#> 2 1 2 1.1 <int [2]> 0
#> 3 1 3 1.1 <int [2]> 0
#> 4 2 4 2.1 <int [2]> 1
#> 5 2 5 2.1 <int [2]> 0
#> 6 2 6 2.1 <int [2]> 1
#>
#> Dose-level data:
#> Warning: `...` must be empty in `format.tbl()`
#> Caused by error in `format_tbl()`:
#> ! `...` must be empty.
#> ✖ Problematic argument:
#> • digits = 3
#> # A tibble: 13 × 8
#> dose tox n empiric_tox_rate mean_prob_tox median_prob_tox admissible
#> <ord> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl>
#> 1 NoDose 0 0 0 0 0 TRUE
#> 2 1.1 0 3 0 0.0161 0.000000215 TRUE
#> 3 1.2 0 0 NaN 0.5 0.500 TRUE
#> 4 1.3 0 0 NaN 0.5 0.500 TRUE
#> 5 1.4 0 0 NaN 0.5 0.500 TRUE
#> 6 2.1 2 3 0.667 0.632 0.525 TRUE
#> 7 2.2 0 0 NaN 0.632 0.525 TRUE
#> 8 2.3 0 0 NaN 0.632 0.525 TRUE
#> 9 2.4 0 0 NaN 0.632 0.525 TRUE
#> 10 3.1 0 0 NaN 0.632 0.525 TRUE
#> 11 3.2 0 0 NaN 0.632 0.525 TRUE
#> 12 3.3 0 0 NaN 0.632 0.525 TRUE
#> 13 3.4 0 0 NaN 0.632 0.525 TRUE
#> # ℹ 1 more variable: recommended <lgl>
#>
#> The model targets a toxicity level of 0.25.
#> The model advocates continuing at dose 1.1.