GetOptimalUT: Gives the dose to assign the next patient cohort using...

In UtilityFrailtyPH12: Implementing EFF-TOX and Monotone Utility Based Phase 12 Trials

Description

Gives the dose to assign the next patient cohort using the monotone utility based phase 12 trial using either adaptive randomization or fixed dose assignment. If the trial has been completed, AR equals FALSE will give the optimal dose level for the trial.

Usage

GetOptimalUT(YE, YT, Doses, DoseTried, AR, UT, CutE, CutT, AcceptE,
  AcceptT, HypermeansE, HypermeansT, Hypervars)

Arguments

YE	Vector of patient efficacy status.
YT	Vector of patient toxicity status.
Doses	Vector of patient dose assignment.
DoseTried	Vector containing 1s for doses tried and 0 otherwise.
AR	Logical stating whether or not to adaptively randomize the next cohort of patients. If the trial has been completed, AR equals FALSE will give the optimal dose level for the trial.
UT	Utility Matrix with entries U11, U22 elicited and U12 equals 100, U21 equals 0.
CutE	Cutoff for efficacy acceptability.
CutT	Cutoff for toxicity acceptability.
AcceptE	Probability threshold for efficacy acceptability.
AcceptT	Probability threshold for toxicity acceptability.
HypermeansE	Dose-specific hypermeans for efficacy.
HypermeansT	Dose-specific hypermeans for toxcity.
Hypervars	Length 3 vector of hypervariances. Hypervars[1] contains the Latent parameter variance for normal probability of efficacy and toxicity. Hypervars[2] contains the hypervariance on dose specific mean efficacy and toxicity parameters and Hypervars[3] contains the frailty variance parameter.

Value

A numerical value of the dose to assign the next patient cohort to. If the trial has been completed, this is the optimal dose. If a value of 0 is returned, no doses are acceptable and the trial should be stopped.

Examples

library(mvtnorm)
##Data Here
YE=rbinom(30,1,.8)
YT=rbinom(30,1,.3)
Doses=sample(1:3,30,replace=TRUE)
DoseTried=c(1,1,1,0,0)
##UTILITIES
UT = matrix(c(38.23529,100,0,61.76471),nrow=2,byrow=TRUE)
##Safety Parameters
CutE=.3
CutT=.4
AcceptE=.1
AcceptT=.1
##Hyperparameters for Utility
HypermeansE=c(-1.189, -0.357,  0.360,  0.546,  0.743)
HypermeansT=c(-2.325, -1.811, -1.464, -1.189, -0.740)
Hypervars=c(1,36,1)  
##Adaptively randomize or not?
AR=FALSE
GetOptimalUT( YE,YT, Doses,DoseTried,AR, UT, CutE, CutT,
AcceptE, AcceptT, HypermeansE, HypermeansT,Hypervars)

UtilityFrailtyPH12 documentation built on May 2, 2019, 6:03 a.m.