Description Usage Arguments Details Value References See Also Examples

View source: R/get.oc.obd.kb.R

Generate operating characteristics for optimal biological dose (OBD) finding

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | ```
get.oc.obd.kb(
toxicity.low,
toxicity.moderate,
toxicity.high,
efficacy.low,
efficacy.moderate,
efficacy.high,
target.toxicity,
target.efficacy,
ncohort = 10,
cohortsize = 3,
n.early = 100,
startdose = 1,
p.true,
q.true,
ntrial = 1000,
seed = 6,
p1 = 0.15,
p2 = 0.4,
q1 = 0.3,
q2 = 0.6,
cutoff.eli.toxicity = 0.95,
cutoff.eli.efficacy = 0.3,
w1.toxicity = 0.33,
w2.toxicity = 1.09,
indicator = target.toxicity
)
``` |

`toxicity.low` |
the upper boundary for low toxicity interval |

`toxicity.moderate` |
the upper boundary for moderate toxicity interval |

`toxicity.high` |
the upper boundary for high toxicity interval |

`efficacy.low` |
the upper boundary for low efficacy interval |

`efficacy.moderate` |
the upper boundary for moderate efficacy interval |

`efficacy.high` |
the upper boundary for high efficacy interval |

`target.toxicity` |
the target toxicity rate |

`target.efficacy` |
the target efficacy rate |

`ncohort` |
the total number of cohorts |

`cohortsize` |
the cohortsize |

`n.early` |
the early stopping parameter. If the number of patients treated at
the current dose reaches |

`startdose` |
the starting dose level |

`p.true` |
a vector containing the true toxicity probabilities of the investigational dose levels |

`q.true` |
a vector containing the true efficacy probabilities of the investigational dose levels |

`ntrial` |
the total number of trials to be simulated |

`seed` |
the random seed for simulation |

`p1` |
the cutoff lower limit for safety utility function 1, described in the Details section. |

`p2` |
the cutoff upper limit for safety utility function 1, described in the Details section. |

`q1` |
the cutoff lower limit for efficacy utility function 1, described in the Details section. |

`q2` |
the cutoff upper limit for efficacy utility function 1, described in the Details section. |

`cutoff.eli.toxicity` |
the cutoff to eliminate a dose with unacceptable high toxicity for safety.
We recommend the default value of ( |

`cutoff.eli.efficacy` |
the cutoff for the futility rule, the acceptable lowest efficacy.
The recommended default value of ( |

`w1.toxicity` |
the weight for toxicity utility function 2 and 3,described in the Details section. |

`w2.toxicity` |
the weight for toxicity utility function 3, described in the Details section. |

`indicator` |
the indicator cutoff for utility function 3, described in the Details section. |

Large trials are simulated to characterize the operating characteristics of the KEYBOARD design under the prespecified true toxicity probabilities and true efficacy probabilities of the investigational doses. Dose assignment rule follows the rule described in the function `get.decision.obd.kb()`

.

There are stopping rules built in the KEYBOARD design:

stop the trial if the lowest dose is eliminated from the trial due to high unacceptable toxicity.

stop the trial if the number of patients treated at current dose is exceeds

`n.earlystop`

.

`get.oc.obd.kb()`

returns the operating characteristics of the KEYBOARD design as a list, including:

selection percentage at each dose level using utility function 1 (

`$selpercent1`

),

selection percentage at each dose level using utility function 2 (

`$selpercent2`

),

selection percentage at each dose level using utility function 3 (

`$selpercent3`

),

the number of patients treated at each dose level (

`$npatients`

),

the number of dose limiting toxicities (DLTs) observed at each dose level (

`$ntox`

),

the number of responders observed at each dose level (

`$neff`

),

the average number of DLTs (

`$totaltox`

),

the average number of responders (

`$totaleff`

),

the average number of patients (

`$totaln`

),

the percentage of early stopping without selecting the OBD using utility function 1 (

`$percentstop1`

),

the percentage of early stopping without selecting the OBD using utility function 2 (

`$percentstop2`

),

the percentage of early stopping without selecting the OBD using utility function 3 (

`$percentstop3`

),

data.frame (

`$simu.setup`

) containing simulation parameters, such as target, p.true, etc.

Daniel H. Li, James B. Whitmore, Wentian Guo and Yuan Ji Toxicity and Efficacy Probability Interval Design for Phase I Adoptive Cell Therapy Dose-Finding Clinical Trials
*Clinical Cancer Research*. 2017; 23:13-20.
https://clincancerres.aacrjournals.org/content/23/1/13.long

Suyu Liu, Valen E. Johnson. A robust Bayesian dose-finding design for phase I/II clinical trials
*Biostatistics*. 2016; 17:249-263.
https://academic.oup.com/biostatistics/article/17/2/249/1744018

Yanhong Zhou, J. Jack Lee, Ying Yuan. A utility-based Bayesian optimal interval (U-BOIN) phase I/II design to identify the optimal biological dose for targeted and immune therapies
*Statistics in Medicine*. 2019; 38:S5299-5316.
https://onlinelibrary.wiley.com/doi/epdf/10.1002/sim.8361

Other single-agent phase I/II functions:
`get.decision.obd.kb()`

,
`get.decision.obd2.kb()`

,
`get.oc.obd2.kb()`

,
`select.obd.kb()`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | ```
toxicity.low <- 0.15
toxicity.moderate <- 0.25
toxicity.high <- 0.35
efficacy.low <- 0.25
efficacy.moderate <- 0.45
efficacy.high <- 0.65
p.true <-c(0.08,0.30,0.60,0.80)
q.true <- c(0.25,0.40,0.25,0.50)
oc.obd.kb <- get.oc.obd.kb(toxicity.low = toxicity.low,
toxicity.moderate= toxicity.moderate,
toxicity.high = toxicity.high,
efficacy.low = efficacy.low,
efficacy.moderate = efficacy.moderate,
efficacy.high = efficacy.high,
target.toxicity=target.toxicity,
target.efficacy= target.efficacy,
p.true= p.true, q.true= q.true)
oc.obd.kb
summary.kb(oc.obd.kb)
plot.kb(oc.obd.kb)
plot.kb(oc.obd.kb$selpercent1)
plot.kb(oc.obd.kb$selpercent2)
plot.kb(oc.obd.kb$selpercent3)
plot.kb(oc.obd.kb$npatients)
plot.kb(oc.obd.kb$ntox)
plot.kb(oc.obd.kb$neff)
``` |

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