CFOeff.selectobd: Select the optimal biological dose (OBD) for the real...

In CFO: CFO-Type Designs in Phase I/II Clinical Trials

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)

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.

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.

Author(s)

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)

##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)


##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)

CFO documentation built on April 4, 2025, 2:34 a.m.