Operating Characteristics of the BOIN Drug-Combination Design Across Scenarios

Run sim_comb_boin under a list of matrices of true DLT probabilities that share the same design, and collect the main results into one table.

Usage

sim_comb_boin_multi(
  target,
  scenarios,
  n_cohort,
  cohort_size,
  n_trials = 10000,
  start_dose = c(1, 1),
  n_earlystop = 18,
  p_saf = NULL,
  p_tox = NULL,
  cutoff_eli = 0.95,
  extrasafe = FALSE,
  offset = 0.05,
  titration = FALSE,
  bound_mtd = FALSE,
  overdose_cutoff = NULL,
  keep_trials = FALSE,
  verbose = FALSE,
  seed = 123
)

Arguments

target

Numeric scalar. Target DLT probability.

scenarios

A list of scenarios. Each element is a list with a name and a p_true matrix, or a plain matrix of true DLT probabilities in which case the list names are used as scenario names. Every matrix must have the same numbers of rows (levels of drug A) and columns (levels of drug B).

n_cohort

Integer scalar. Number of cohorts in a trial.

cohort_size

Integer scalar or vector. Number of patients per cohort.

n_trials

Integer scalar. Number of trials per scenario. Defaults to 10000.

start_dose

Integer vector of length two. Dose levels of drug A and drug B for the first cohort. Defaults to c(1, 1).

n_earlystop

Integer scalar. Early stopping sample size at the current combination. Defaults to 18.

p_saf

Numeric scalar. Highest DLT probability deemed subtherapeutic. Defaults to 0.6 * target.

p_tox

Numeric scalar. Lowest DLT probability deemed overly toxic. Defaults to 1.4 * target.

cutoff_eli

Numeric scalar. Posterior probability cutoff for eliminating a combination. Defaults to 0.95.

extrasafe

Logical scalar. Apply the stricter safety stopping rule at the lowest combination.

offset

Numeric scalar between 0 and 0.5. Relaxation of cutoff_eli for the safety stopping rule. Defaults to 0.05.

titration

Logical scalar. Treat one patient per combination until the first DLT.

bound_mtd

Logical scalar. Require the isotonic estimate at the selected combination to be below the de-escalation boundary.

overdose_cutoff

Numeric scalar or NULL. Combinations whose true DLT probability exceeds this value count as overdoses. Defaults to NULL, which uses target.

keep_trials

Logical scalar. Keep the trial by trial data of every scenario.

verbose

Logical scalar. Report progress while the simulations run.

seed

Integer scalar or NULL. Random seed, applied to every scenario, so that a scenario simulated here matches the same scenario simulated on its own with sim_comb_boin.

Value

An object of class comb_boin_oc_multi, which is a list with components

results

Named list of comb_boin_oc objects, one per scenario.

summary_table

Data frame with one row per scenario: the true MTD combinations (those closest to target), the percentage of trials selecting one of them, the percentage of patients treated at them, the percentage of trials without an MTD, the percentage of trials selecting a combination above overdose_cutoff, the percentage of patients treated above it, and the average numbers of patients and DLTs.

scenario_names

Character vector of scenario names.

n_rows

Number of dose levels of drug A.

n_cols

Number of dose levels of drug B.

call

The matched call.

See also

sim_comb_boin

Examples

scenarios <- list(
  "Two MTD combinations" = matrix(c(0.05, 0.10, 0.20,
                                    0.10, 0.20, 0.30,
                                    0.20, 0.30, 0.45), 3, byrow = TRUE),
  "All toxic" = matrix(c(0.40, 0.50, 0.60,
                         0.50, 0.60, 0.70,
                         0.60, 0.70, 0.80), 3, byrow = TRUE)
)

oc <- sim_comb_boin_multi(
  target = 0.30,
  scenarios = scenarios,
  n_cohort = 12,
  cohort_size = 3,
  n_trials = 200,
  seed = 123
)
oc
#> BOIN drug-combination operating characteristics across 2 scenarios
#>   target DLT rate : 0.3
#>   dose levels     : 3 of drug A, 3 of drug B
#>   trials each     : 200
#>   max sample size : 36
#>   overdose cutoff : 0.3
#> 
#>              Scenario   True MTD MTD selected (%) Patients at MTD (%)
#>  Two MTD combinations A3B2, A2B3             57.0                33.1
#>             All toxic       A1B1             60.5                76.9
#>  No MTD (%) Above cutoff selected (%) Patients above cutoff (%) Patients DLTs
#>         0.0                      11.5                      11.9     34.7  8.1
#>        34.5                      65.5                     100.0     19.0  8.0

# The full results of one scenario
oc$results[["All toxic"]]
#> BOIN drug-combination operating characteristics
#>   target DLT rate : 0.3
#>   dose levels     : 3 of drug A, 3 of drug B
#>   trials          : 200
#>   cohorts         : 12 of size 3
#>   max sample size : 36
#>   lambda_e / _d   : 0.2365 / 0.3585
#> 
#>               Item Drug A   B1   B2   B3
#>  True DLT rate (%)     A1 40.0 50.0 60.0
#>                        A2 50.0 60.0 70.0
#>                        A3 60.0 70.0 80.0
#>   MTD selected (%)     A1 60.5  2.0  0.0
#>                        A2  3.0  0.0  0.0
#>                        A3  0.0  0.0  0.0
#>   Patients treated     A1 14.6  2.2  0.1
#>                        A2  1.8  0.2  0.0
#>                        A3  0.1  0.0  0.0
#>  Patients with DLT     A1  5.7  1.1  0.0
#>                        A2  0.9  0.1  0.0
#>                        A3  0.1  0.0  0.0
#> 
#> No MTD selected                      : 34.5%
#> Average number of patients           : 19
#> Average number of DLTs               : 8
#> 
#> True MTD (closest to the target)     : A1B1
#>   Selected as the MTD                : 60.5%
#>   Patients treated there             : 76.9%
#> 
#> Combinations above a true DLT rate of 0.3: 9 of 9
#>   Patients treated there             : 100%
#>   Trials treating any patient there  : 100%
#>   Trials treating over 60% there     : 31.5%
#>   Trials treating over 80% there     : 17.5%
#>   Trials selecting an MTD there      : 65.5%