boin12_rds | R Documentation |
Tabulate rank-based desirability scores for a BOIN12 trial
boin12_rds(
sample_sizes,
phi_t,
phi_e,
u1 = 100,
u2,
u3,
u4 = 0,
c_t = 0.95,
c_e = 0.9,
prior_alpha = 1,
prior_beta = 1
)
sample_sizes |
integer vector, cohort sample sizes to consider |
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 |
c_t |
certainty required to flag excess toxicity, 0.95 by default |
c_e |
certainty required to flag deficient efficacy, 0.9 by default |
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 |
data.frame with columns Patients, Toxicity, Efficacy containing the numbers of patients, patients with toxicitiy, and patients with efficacy; Admissble, containing the character labels Admissble or Not Admissible; RDS, containing a character label of the numerical desirability score or the character string "E", where a combination is eliminated; and RDS_x, containing the desirability scores as numbers, with NA where a combination should be eliminated.
Bharat Bhushan, Kristian Brock
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.
# Table 3 in Lin et al.
x <- boin12_rds(
sample_sizes = c(0, 3, 6, 9),
phi_t = 0.35,
phi_e = 0.25,
u1 = 100,
u2 = 40,
u3 = 60,
u4 = 0,
c_t = 0.95,
c_e = 0.9,
prior_alpha = 1,
prior_beta = 1
)
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