In scientific-computing-solutions/badminton: Simulation of Continuous-Time Discrete-Space Markov Chains

Tutorial 3 -- Specifying the times at which hazard functions change

Throughout this package, 'calendar time' is defined to be the time since a clinical trial started and 'patient time' is defined to be the time for a subject since they were recruited onto the study. Therefore, if a subject was recruited at time r then, for this subject at calendar time = t, patient time =t+r

This package allows hazard functions to change a fixed time after the trial commenced (a calendar time switch) and also for the functions to change for each subject a fixed amount of time after they were recruited onto the trial (a patient time switch)

Calendar time switches could be useful, if, for example, a new drug is released part way through a trial. Patient time switches could be used to allow piecewise exponential (or Weibull -- see Tutorial 6) survival functions, perhaps modelling the lag time for treatment effects to kick in.

In this tutorial we describe how to set up the switch times at which the hazard functions will change. The switch times are stored in a Switches object. These objects are initialized using the following function.

library("badminton")
switches <-  InitializeStudySwitches()

In this case there are no calendar or patient switch points:

print(switches)

It is possible to initialize the object with a vector of calendar switch times:

switches <-  InitializeStudySwitches(c(10,30,50))
print(switches)

Finally, for each calendar switch time it is possible to insert a vector of patient switch times:

switches <-  InitializeStudySwitches(c(10,30,50))
#For calendar time 30->50 add a patient switch time at patient time 15
switches <- SetSubjectSwitchTimes.Switches(switches,30,15)
#For calendar time 50 -> Inf add patient switch times at patient times 10,20,30
switches <- SetSubjectSwitchTimes.Switches(switches,50,c(10,20,30))
#For calendar tie 0 -> 10 add a patient switch time at patient time 3
switches <- SetSubjectSwitchTimes.Switches(switches,0,3)
print(switches)

Reset Patient Time Switches

Suppose a study has the following transition graph:

crossOver <- c("control.progressing","active.progressed")
g <- SimpleStudyProgressionGraph(arms=c("control","active"),
                                 armProgression=c("progressing","progressed"),edge="death",crossOver=crossOver)
graph.par(list(nodes=list(fontsize=30)))
plot(g)

and that the treatment has a lag of 3 before it affects the survival function. In this case the following Switches object would be specified:

switches <-  InitializeStudySwitches()
switches <- SetSubjectSwitchTimes.Switches(switches,0,3)

For subjects starting in active.progressing, when patient time = 3, the hazard function will change and the treatment effect can kick in. However, for subjects starting in control.progressing, if they cross over into active.progressed we need the timer for patient switches to be reset so that the treatment effect will kick in 3 units after crossing over rather than three months after recruitment. The package allows this to be specified, setting the isResetEdge property to TRUE for all edges for which transitioning over them resets the patient switch timer.

DAG <- SetIsResetEdge.ProgressionGraph(DAG,from="control.progressing",to="active.progressed",isResetEdge=TRUE)

Note: The crossOver edges in SimpleStudyProgressionGraph automatically have their isResetEdge property set to TRUE

scientific-computing-solutions/badminton documentation built on May 29, 2019, 3:43 p.m.