R: Gives the subgroup specific optimal dose vector.

GetSubTite

R Documentation

Gives the subgroup specific optimal dose vector.

Description

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

Usage

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
)

Arguments

`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

Value

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.

References

[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.

Examples

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