next_QuasiBOIN {UnifiedDoseFinding}

Determine the dose for the next cohort of new patients based on equivalent score (ET)-defined target using gBOIN design

Description

Determine the dose for the next cohort of new patients for single-agent trials that aim to find a MTD defined by the Equivalent Score (ET) in Quasi-CRM design (Yuan et al. 2007) and Robust-Quasi-CRM design (Pan et al. 2014) using the gBOIN design (Mu et al. 2017)

Usage

next_QuasiBOIN(target, n, y, d, p.saf = 0.6 * target, p.tox = 1.4 * target,
               cutoff.eli = 0.95, extrasafe = FALSE, n.earlystop = 100)

Arguments

target

the target DLT rate

n

the number of patients enrolled at each dose level

y

the toxicity score at each dose level

d

the current dose level

p.saf

the lower bound. The default value is p.saf = 0.6 * target

p.tox

the upper bound. The default value is p.tox = 1.4 * target

cutoff.eli

the cutoff to eliminate an overly toxic dose for safety. The default value is cutoff.eli = 0.95

extrasafe

extrasafe set extrasafe = TRUE to impose a more stringent stopping . The default value is extrasafe = FALSE

n.earlystop

the early stopping parameter. The default value is n.earlystop = 100

Value

next_QuasiBOIN() returns recommended dose level for the next cohort as a numeric value under quasi-binary measure

Author(s)

Chia-Wei Hsu, Haitao Pan, Rongji Mu

References

Yuan, Z., R. Chappell, and H. Bailey. "The continual reassessment method for multiple toxicity grades: a Bayesian quasi-likelihood approach." Biometrics 63, no. 1 (2007): 173-179.

Pan, Haitao, Cailin Zhu, Feng Zhang, Ying Yuan, Shemin Zhang, Wenhong Zhang, Chanjuan Li, Ling Wang, and Jielai Xia. "The continual reassessment method for multiple toxicity grades: a Bayesian model selection approach." PloS one 9, no. 5 (2014): e98147.

Mu, Rongji, Ying Yuan, Jin Xu, Sumithra J. Mandrekar, and Jun Yin. "gBOIN: a unified model-assisted phase I trial design accounting for toxicity grades, and binary or continuous end points." Journal of the Royal Statistical Society. Series C: Applied Statistics 68, no. 2 (2019): 289-308.

Examples

target <- 0.47 / 1.5
n <- c(3, 3, 6, 3, 3, 0)
y <- c(0, 0, 1.333333, 0, 1, 0)
d <- 5
next_QuasiBOIN(target = target, n = n, y = y, d = d)