Description Usage Arguments Value References Examples

Returns a list containing the optimal doses to enroll each subgroup at and the subgroups that should have their accrual suspended temporarily.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | ```
GetSubTite(
Y,
I,
Doses,
Groups,
Include = rep(1, length(Y)),
ID,
cohort,
Conservative,
T1,
Target,
Upper,
Dose,
meanmu,
meanslope,
MeanInts,
MeanSlopes,
VarInt,
VarSlope,
phetero,
Borrow,
B
)
``` |

`Y` |
Vector containing observed event or censoring times. |

`I` |
Vector containing event indicators (1 if patient experiences an event for a patient). |

`Doses` |
Vector containing numerical doses assigned to patients in the trial. |

`Groups` |
Vector containing group assignment of patients, 1 is baseline group. |

`Include` |
Binary vector indicating whether each patient record should be included in the decision making process. |

`ID` |
Vector of patient IDs. Can be numeric or character valued. |

`cohort` |
Number of patients needed to be assigned at a dose level prior to escalation. |

`Conservative` |
Binary Indicator of Whether conservative escalation, i.e. not allowing escalation until cohort patients have been fully evaluated at the highest tried dose level. |

`T1` |
Reference time for toxicity. |

`Target` |
Target cumulative toxicity probability vector at time T1. |

`Upper` |
Cutoff values used to determine if accrual in a subgroup should be suspended. |

`Dose` |
Vector containing the standardized doses considered. |

`meanmu` |
Prior mean for baseline intercept. |

`meanslope` |
Prior mean for baseline slope. |

`MeanInts` |
Vector of prior means for the group specific intercept parameters. |

`MeanSlopes` |
Vector of prior means for the group specific slope parameters. |

`VarInt` |
Prior variance for the intercept parameters. |

`VarSlope` |
Prior variance for the slope parameters. |

`phetero` |
Prior probability of heterogeneous subgroups. |

`Borrow` |
Parameter to specify subgroup borrowing/clustering. 0=No borrowing, 1=Borrowing but no clustering, 2=Borrowing and clustering. |

`B` |
Number of Iterations to run for MCMC |

Returns a list with two objects, a vector of optimal doses for each subgroup and matrix of posterior toxicity probabilities at each dose level within each subgroup.

[1] Chapple and Thall (2017), Subgroup Specific Dose Finding in Phase I Clinical Trials Based on Time to Toxicity Within a Fixed Follow Up Period.

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 28 29 30 31 | ```
T1=28 ##Reference time for toxicity
Target=rep(.3,2) ##Target toxicity probability
Upper=rep(.95,2) ##Upper cutoffs for excessive toxicity
##How many patients in each subgroup have been assigned at each dose level?
cohort=3 ##Cohort size required for escalation
Conservative = 1 ##Conservative escalation
##Only can escalate with a fully evaluated cohort at the highest dose level.
##Matrix of umber of patients tried or fully evaluated at each dose level.
##Hyperparameters
meanmu=-0.4467184 ##Common Intercept hypermean
meanslope= 0.8861634 ##Common slope hypermean
MeanInts =c(0, -0.5205379) ##Group Intercept hypermeans
MeanSlopes = c(0, 0.1888923) ##Group slope hyperneabs
VarInt=5 #Prior Variance of the intercept betas
VarSlope=1 ##Prior Variance of slope betas
phetero=.9 ##Prior Probability of hetergeneity
Borrow=0 ##Borrowing specification, 0=none, 1=some, 2=clustering.
B=5000 ##Number of iterations
Borrow=2
Y=c(28,26,29,28,29,5,1)
RawDose=c(350,420,530,660,825)
Dose=(RawDose-mean(RawDose))/sd(RawDose)
I <- c(0,0,0,0,0,0,0)
Doses <- rep(2,7)
Groups <- c(0,1,1,0,0,1,1)
Include <- rep(1,7)
ID=1:length(Y)
Z=GetSubTite(Y, I,Doses, Groups, Include,ID,cohort, Conservative,
T1,Target, Upper, Dose, meanmu, meanslope,
MeanInts, MeanSlopes ,VarInt,VarSlope,phetero, Borrow,B)
Z
``` |

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