CFOeff.next: Determination of the dose level for next cohort in the...
In CFO: CFO-Type Designs in Phase I/II Clinical Trials

CFOeff.next

R Documentation

Determination of the dose level for next cohort in the calibration-free odds (CFO) design for phase I/II trials

Description

In the CFO design for phase I/II trials, the function is used to determine the dose movement based on the toxicity outcomes and efficacy outcomes of the enrolled cohorts.

Usage

CFOeff.next(target, axs, ays, ans, currdose, 
                   prior.para=list(alp.prior = target, bet.prior = 1 - target, 
                   alp.prior.eff = 0.5, bet.prior.eff = 0.5),  
                   cutoff.eli=0.95, early.stop=0.95, effearly.stop = 0.9, mineff)

Arguments

`target`	the target DLT rate.
`axs`	the cumulative counts of efficacy outcomes at all dose levels.
`ays`	the cumulative counts of DLTs observed at all dose levels.
`ans`	the cumulative counts of patients treated at all dose levels.
`currdose`	the current dose level.
`prior.para`	the prior parameters for two beta distributions, where set as `list(alp.prior = target, bet.prior = 1 - target, alp.prior.eff = 0.5, bet.prior.eff = 0.5)` by default. `alp.prior` and `bet.prior` represent the parameters of the prior distribution for the true DLT rate at any dose level. This prior distribution is specified as Beta(`alpha.prior`, `beta.prior`). `alp.eff.prior` and `bet.eff.prior` represent 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`).
`cutoff.eli`	the cutoff to eliminate overly toxic doses for safety. We recommend the default value of `cutoff.eli = 0.95` for general use.
`early.stop`	the threshold value for early stopping due to overly toxic. The default value `early.stop = 0.95` generally works well.
`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`.
`mineff`	the lowest acceptable efficacy rate.

Details

The CFO design for phase I/II trials will determine admissible set A_n through the dose escalation rules for the MTD. The current dose is set as d_n. If the decision is to de-escalate the dose, the set A_n will be \{1,\dots,d_n-1\}. If the decision is to stay at the current dose, then the admissible set A_n will be \{1,\dots,d_n\}. If the decision is to escalate the dose, then A_n will be \{1,\dots,d_n+1\}. The dose level d_{n+1} for the next cohort will be selected from A_n by using the rule: d_{n+1} = argmax_{k\in A_n}Pr(q_k = max_{j\in A_n}\{q_j\}| D_n) where D_n and q_k are the current data and the efficacy probability for dose level k.

Value

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

target: the target DLT rate.
axs: the cumulative counts of efficacy outcomes at all dose levels.
ays: the cumulative counts of DLTs observed at all dose levels.
ans: the cumulative counts of patients treated at all dose levels.
decision: the decision in the CFO design, where de-escalation, stay, and escalation represent the movement directions of the dose level, stop_for_tox indicates stopping the experiment because the lowest dose level is overly toxic and stop_for_low_eff indicates that all dose level in the admissible set shows low efficacy.
currdose: the current dose level.
nextdose: the recommended dose level for the next cohort. nextdose = 99 indicates that the trial is terminated due to early stopping.
overtox: the situation regarding which positions experience over-toxicity. The dose level indicated by overtox and all the dose levels above experience over-toxicity. overtox = NA signifies that the occurrence of over-toxicity did not happen.
toxprob: the expected toxicity probability, Pr(p_k > \phi | x_k, m_k), for doses in admissible set, where p_k, x_k, and m_k are the dose-limiting toxicity (DLT) rate, the numbers of observed DLTs, and the numbers of patients at dose level k.
effprob: the empirical probability of Pr(q_k=max_{j\in A_n}\{q_j\}|D_n) for doses in admissible set, where q_k is efficacy probability at dose level k. A_n is the admissible set determined through the dose escalation rules for the MTD and D_n is the current cumulative dataset.
admset: the admissible set A_n. The dose level for the next cohort will be selected from A_n.
class: the phase of the trial.

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

axs = c(3, 1, 7, 11, 26); ays = c(0, 0, 0, 0, 6); ans = c(6, 3, 12, 17, 36)
target <- 0.4
decision <- CFOeff.next(target,axs,ays,ans,currdose = 3, mineff = 0.3)
summary(decision)
#early stop for overly toxic
axs = c(13, 11, 7, 11, 26); ays = c(25, 18, 12, 17, 26); ans = c(36, 23, 22, 27, 36)
target <- 0.4
decision <- CFOeff.next(target,axs,ays,ans,currdose = 1, mineff = 0.3)
summary(decision)

#early stop for low efficacy
axs = c(0, 0, 0, 0, 0); ays = c(2, 1, 1, 1, 6); ans = c(36, 23, 22, 27, 36)
target <- 0.4
decision <- CFOeff.next(target,axs,ays,ans,currdose = 1, mineff = 0.3)
summary(decision)

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