R: Log-rank test simulation for two endpoints

lrsim2e {lrstat}

R Documentation

Log-rank test simulation for two endpoints

Description

Performs simulation for two-endpoint two-arm group sequential trials based on weighted log-rank test. The first kMaxe1 looks are driven by the total number of PFS events in two arms combined, and the subsequent looks are driven by the total number of OS events in two arms combined. Alternatively, the analyses can be planned to occur at specified calendar times.

Usage

lrsim2e(
  kMax = NA_integer_,
  kMaxe1 = NA_integer_,
  hazardRatioH0e1 = 1,
  hazardRatioH0e2 = 1,
  allocation1 = 1L,
  allocation2 = 1L,
  accrualTime = 0L,
  accrualIntensity = NA_real_,
  piecewiseSurvivalTime = 0L,
  stratumFraction = 1L,
  rho = 0,
  lambda1e1 = NA_real_,
  lambda2e1 = NA_real_,
  lambda1e2 = NA_real_,
  lambda2e2 = NA_real_,
  gamma1e1 = 0L,
  gamma2e1 = 0L,
  gamma1e2 = 0L,
  gamma2e2 = 0L,
  accrualDuration = NA_real_,
  followupTime = NA_real_,
  fixedFollowup = 0L,
  rho1 = 0,
  rho2 = 0,
  plannedEvents = NA_integer_,
  plannedTime = NA_real_,
  maxNumberOfIterations = 1000L,
  maxNumberOfRawDatasetsPerStage = 0L,
  seed = NA_integer_
)

Arguments

`kMax`	The maximum number of stages.
`kMaxe1`	Number of stages with timing determined by PFS events. Ranges from 0 (none) to `kMax`.
`hazardRatioH0e1`	Hazard ratio under the null hypothesis for the active treatment vs control for endpoint 1 (PFS). Defaults to 1 for superiority test.
`hazardRatioH0e2`	Hazard ratio under the null hypothesis for the active treatment vs control for endpoint 2 (OS). Defaults to 1 for superiority test.
`allocation1`	Number of subjects in the treatment group in a randomization block. Defaults to 1 for equal randomization.
`allocation2`	Number of subjects in the control group in a randomization block. Defaults to 1 for equal randomization.
`accrualTime`	A vector that specifies the starting time of piecewise Poisson enrollment time intervals. Must start with 0, e.g., `c(0, 3)` breaks the time axis into 2 accrual intervals: [0, 3) and [3, Inf).
`accrualIntensity`	A vector of accrual intensities. One for each accrual time interval.
`piecewiseSurvivalTime`	A vector that specifies the starting time of piecewise exponential survival time intervals. Must start with 0, e.g., `c(0, 6)` breaks the time axis into 2 event intervals: [0, 6) and [6, Inf). Defaults to 0 for exponential distribution.
`stratumFraction`	A vector of stratum fractions that sum to 1. Defaults to 1 for no stratification.
`rho`	The correlation coefficient for the standard bivariate normal random variables used to generate time to disease progression and time to death using the inverse CDF method.
`lambda1e1`	A vector of hazard rates for the event in each analysis time interval by stratum for the treatment group and endpoint 1 (PFS).
`lambda2e1`	A vector of hazard rates for the event in each analysis time interval by stratum for the control group and endpoint 1 (PFS).
`lambda1e2`	A vector of hazard rates for the event in each analysis time interval by stratum for the treatment group and endpoint 2 (OS).
`lambda2e2`	A vector of hazard rates for the event in each analysis time interval by stratum for the control group and endpoint 2 (OS).
`gamma1e1`	The hazard rate for exponential dropout, a vector of hazard rates for piecewise exponential dropout applicable for all strata, or a vector of hazard rates for dropout in each analysis time interval by stratum for the treatment group and endpoint 1 (PFS).
`gamma2e1`	The hazard rate for exponential dropout, a vector of hazard rates for piecewise exponential dropout applicable for all strata, or a vector of hazard rates for dropout in each analysis time interval by stratum for the control group and endpoint 1 (PFS).
`gamma1e2`	The hazard rate for exponential dropout, a vector of hazard rates for piecewise exponential dropout applicable for all strata, or a vector of hazard rates for dropout in each analysis time interval by stratum for the treatment group and endpoint 2 (OS).
`gamma2e2`	The hazard rate for exponential dropout, a vector of hazard rates for piecewise exponential dropout applicable for all strata, or a vector of hazard rates for dropout in each analysis time interval by stratum for the control group and endpoint 2 (OS).
`accrualDuration`	Duration of the enrollment period.
`followupTime`	Follow-up time for the last enrolled subject.
`fixedFollowup`	Whether a fixed follow-up design is used. Defaults to 0 for variable follow-up.
`rho1`	The first parameter of the Fleming-Harrington family of weighted log-rank test. Defaults to 0 for conventional log-rank test.
`rho2`	The second parameter of the Fleming-Harrington family of weighted log-rank test. Defaults to 0 for conventional log-rank test.
`plannedEvents`	The planned cumulative total number of PFS events at Look 1 to Look `kMaxe1` and the planned cumulative total number of OS events at Look `kMaxe1+1` to Look `kMax`.
`plannedTime`	The calendar times for the analyses. To use calendar time to plan the analyses, `plannedEvents` should be missing.
`maxNumberOfIterations`	The number of simulation iterations. Defaults to 1000.
`maxNumberOfRawDatasetsPerStage`	The number of raw datasets per stage to extract.
`seed`	The seed to reproduce the simulation results. The seed from the environment will be used if left unspecified,

Value

A list with 2 components:

sumdata: A data frame of summary data by iteration and stage:
- iterationNumber: The iteration number.
- eventsNotAchieved: Whether the target number of events is not achieved for the iteration.
- stageNumber: The stage number, covering all stages even if the trial stops at an interim look.
- analysisTime: The time for the stage since trial start.
- accruals1: The number of subjects enrolled at the stage for the treatment group.
- accruals2: The number of subjects enrolled at the stage for the control group.
- totalAccruals: The total number of subjects enrolled at the stage.
- endpoint: The endpoint (1 or 2) under consideration.
- events1: The number of events at the stage for the treatment group.
- events2: The number of events at the stage for the control group.
- totalEvents: The total number of events at the stage.
- dropouts1: The number of dropouts at the stage for the treatment group.
- dropouts2: The number of dropouts at the stage for the control group.
- totalDropouts: The total number of dropouts at the stage.
- logRankStatistic: The log-rank test Z-statistic for the endpoint.
rawdata (exists if maxNumberOfRawDatasetsPerStage is a positive integer): A data frame for subject-level data for selected replications, containing the following variables:
- iterationNumber: The iteration number.
- stageNumber: The stage under consideration.
- analysisTime: The time for the stage since trial start.
- subjectId: The subject ID.
- arrivalTime: The enrollment time for the subject.
- stratum: The stratum for the subject.
- treatmentGroup: The treatment group (1 or 2) for the subject.
- survivalTime1: The underlying survival time for event endpoint 1 for the subject.
- dropoutTime1: The underlying dropout time for event endpoint 1 for the subject.
- timeUnderObservation1: The time under observation since randomization for event endpoint 1 for the subject.
- event1: Whether the subject experienced event endpoint 1.
- dropoutEvent1: Whether the subject dropped out for endpoint 1.
- survivalTime2: The underlying survival time for event endpoint 2 for the subject.
- dropoutTime2: The underlying dropout time for event endpoint 2 for the subject.
- timeUnderObservation2: The time under observation since randomization for event endpoint 2 for the subject.
- event2: Whether the subject experienced event endpoint 2.
- dropoutEvent2: Whether the subject dropped out for endpoint 2.

Author(s)

Kaifeng Lu, kaifenglu@gmail.com

Examples


sim1 = lrsim2e(
  kMax = 3,
  kMaxe1 = 2,
  allocation1 = 2,
  allocation2 = 1,
  accrualTime = c(0, 8),
  accrualIntensity = c(10, 28),
  piecewiseSurvivalTime = 0,
  rho = 0,
  lambda1e1 = log(2)/12*0.60,
  lambda2e1 = log(2)/12,
  lambda1e2 = log(2)/30*0.65,
  lambda2e2 = log(2)/30,
  accrualDuration = 20.143,
  plannedEvents = c(186, 259, 183),
  maxNumberOfIterations = 1000,
  maxNumberOfRawDatasetsPerStage = 1,
  seed = 314159)

head(sim1$sumdata)
head(sim1$rawdata)

[Package lrstat version 0.2.9 Index]