`R/boin12_selector.R`

`get_boin12.Rd`

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.

```
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,
...
)
```

- 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.

an object of type `selector_factory`

that can fit the
BOIN12 model to outcomes.

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 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()
#> [1] 2
fit %>% continue()
#> [1] TRUE
fit %>% is_randomising()
#> [1] FALSE
fit %>% dose_admissible()
#> [1] TRUE TRUE TRUE FALSE FALSE
fit %>% prob_administer()
#> 1 2 3 4 5
#> 0.25 0.50 0.25 0.00 0.00
```