get_boin12: Get an object to fit the BOIN12 model for phase I/II...

In escalation: A Modular Approach to Dose-Finding Clinical Trials

Get an object to fit the BOIN12 model for phase I/II dose-finding.

Description

This function returns an object that can be used to fit the BOIN12 model for phase I/II dose-finding, i.e. it selects doses according to efficacy and toxicity outcomes.

Usage

get_boin12(
  num_doses,
  phi_t,
  phi_e,
  u1 = 100,
  u2,
  u3,
  u4 = 0,
  n_star = 6,
  c_t = 0.95,
  c_e = 0.9,
  start_dose = 1,
  prior_alpha = 1,
  prior_beta = 1,
  ...
)

Arguments

num_doses	integer, num of doses under investigation
phi_t	Probability of toxicity threshold
phi_e	Probability of efficacy threshold
u1	utility of efficacy without toxicity, 100 by default
u2	utility of no efficacy and no toxicity, between u1 and u4
u3	utility of efficacy and toxicity, between u1 and u4
u4	utility of toxicity without efficacy , 0 by default
n_star	when tox is within bounds, stop exploring higher doses when n at dose is greater than or equal to this value. 6 by default.
c_t	certainty required to flag excess toxicity, 0.95 by default
c_e	certainty required to flag deficient efficacy, 0.9 by default
start_dose	index of starting dose, 1 by default (i.e. lowest dose)
prior_alpha	first shape param for prior on beta prior, 1 by default
prior_beta	second shape param for prior on beta prior, 1 by default
...	Extra args are passed onwards.

Value

an object of type selector_factory that can fit the BOIN12 model to outcomes.

References

Lin, R., Zhou, Y., Yan, F., Li, D., & Yuan, Y. (2020). BOIN12: Bayesian optimal interval phase I/II trial design for utility-based dose finding in immunotherapy and targeted therapies. JCO precision oncology, 4, 1393-1402.

Examples

# Examples in Lin et al.
model <- get_boin12(num_doses = 5, phi_t = 0.35, phi_e = 0.25,
                    u2 = 40, u3 = 60, n_star = 6)
fit <- model %>% fit('1NNN 2ENT 3ETT 2EEN')
fit %>% recommended_dose()
fit %>% continue()
fit %>% is_randomising()
fit %>% dose_admissible()
fit %>% prob_administer()

escalation documentation built on June 27, 2024, 5:09 p.m.