simFastBOIN (version 1.3.2)

get_boin_stopping_boundaries: Generate Trial Stopping Rule Table

Description

Create a lookup table to determine whether the entire trial should be stopped if excessive toxicity is observed at the lowest dose. This table is applied only at the lowest dose level to monitor trial safety.

Usage

get_boin_stopping_boundaries(target, max_sample_size, cutoff_stop)

Value

A character matrix with stopping decisions:

• Rows represent cumulative number of DLTs at lowest dose (0 to max_sample_size)

• Columns represent cumulative number of patients at lowest dose (1 to max_sample_size)

• Cell values are "STOP" or "GO"

• NA values for logically impossible combinations (n_tox > n_pts) or n_pts < 3

Arguments

target

Numeric. The target toxicity probability (e.g., 0.30 for 30%).

max_sample_size

Numeric. Maximum sample size (number of patients) for table columns. Typically 18-30 for phase I trials.

cutoff_stop

Numeric. Cutoff probability for trial stopping. Default is 0.90. If Pr(p > target | data) > cutoff_stop at lowest dose, the trial is stopped.

Details

The trial stopping rule is based on Bayesian monitoring of safety at the lowest dose level. The rationale is that if even the lowest dose shows excessive toxicity with high posterior probability, all doses in the trial may be too toxic, warranting early trial termination.

The posterior probability Pr(p > target | data) is computed using Beta-Binomial conjugate prior with uniform prior (Beta(1,1)). The stopping rule is not evaluated until at least 3 patients have been treated at the lowest dose.

References

Liu S. and Yuan, Y. (2015). Bayesian Optimal Interval Designs for Phase I Clinical Trials. Journal of the Royal Statistical Society: Series C, 64, 507-523.

Examples

# Generate stopping rule table for 30% target toxicity rate
STOP_DL1 <- get_boin_stopping_boundaries(
  target = 0.30,
  max_sample_size = 18,
  cutoff_stop = 0.90
)
print(STOP_DL1)