GetSubTite: Gives the subgroup specific optimal dose vector.

Description Usage Arguments Value References Examples

View source: R/GetSubTite.R

Description

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

Usage

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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

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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

SubTite documentation built on Sept. 15, 2021, 9:07 a.m.

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