CFO (version 2.1.0)

CFOeff.selectobd: Select the optimal biological dose (OBD) for the real single-drug trials

Description

Select the optimal biological dose (OBD) when the real single-drug trials is completed

Usage

CFOeff.selectobd(target, txs, tys, tns, prior.para, mineff, effearly.stop)

Value

The CFOeff.selectobd() function returns a list object comprising the following elements:

• OBD: the selected OBD. OBD = 99 indicates that all tested doses are overly toxic or having low efficacy.

• MTD: MTD here is get by using function CFO.selectmtd. MTD is used as the upper bound of the admissible set.

• OBD.probs: the probability that each dose level would be selected as OBD. The probability indicates that \(q_k\) corresponds to dose level \(k\) being the highest in the admissible set. \(q_k\) is efficacy probability correspond to dose level k here.

Arguments

target

the target DLT rate.

txs

the cumulative counts of efficacy outcomes at all dose levels.

tys

the cumulative counts of DLTs observed at all dose levels.

tns

the cumulative counts of patients treated at all dose levels.

prior.para

the prior parameters for two beta distributions, where set as list(alp.prior.eff = 0.5, bet.prior.eff = 0.5) by default. alp.eff.prior and bet.eff.priorrepresent the parameters of the Jeffreys' prior distribution for the efficacy probability at any dose level.This prior distribution is specified as Beta(alpha.eff.prior, beta.eff.prior).

mineff

the lowest acceptable efficacy rate.

effearly.stop

the threshold value for early stopping due to low efficacy. The trial would be terminated early if \(Pr(q_k<\psi |y_k,m_k \ge 3)\) is smaller than the value of effearly.stop where \(q_k, y_k\) and \(m_k\) are the efficacy probability, the number of efficacy outcomes and the number of patients at dose level \(k\). \(\psi\) is the the lowest acceptable efficacy rate which is set by mineff here. By default, effearly.stop is set as 0.9.

Author

Jialu Fang, Ninghao Zhang, Wenliang Wang, and Guosheng Yin

References

Jin H, Yin G (2022). CFO: Calibration-free odds design for phase I/II clinical trials. Statistical Methods in Medical Research, 31(6), 1051-1066.

Examples

target <- 0.3; mineff<- 0.3
txs <- c(3, 1, 7, 11, 26); tys <- c(0, 0, 0, 0, 6); tns <- c(6, 3, 12, 17, 36)
prior.para = list(alp.prior.eff = 0.5, bet.prior.eff = 0.5)
effearly.stop <- 0.95
result <- CFOeff.selectobd(target, txs, tys, tns, prior.para, mineff, effearly.stop)
summary(result)
# \donttest{
##Low efficacy
target <- 0.3; mineff<- 0.3
txs = c(0, 0, 0, 0, 0); tys = c(2, 1, 1, 1, 6); tns = c(36, 23, 22, 27, 36)
prior.para = list(alp.prior.eff = 0.5, bet.prior.eff = 0.5)
effearly.stop <- 0.95
result <- CFOeff.selectobd(target, txs, tys, tns, prior.para, mineff, effearly.stop)
summary(result)
# }
# \donttest{
##High toxicity
target <- 0.3; mineff<- 0.3
txs = c(3, 1, 7, 11, 26); tys = c(36, 23, 22, 27, 36); tns = c(36, 23, 22, 27, 36)
prior.para = list(alp.prior.eff = 0.5, bet.prior.eff = 0.5)
effearly.stop <- 0.95
result <- CFOeff.selectobd(target, txs, tys, tns, prior.para, mineff, effearly.stop)
summary(result)
# }