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f_design_plan_survival.R
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f_design_plan_survival.R
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## |
## | *Sample size and power survival*
## |
## | This file is part of the R package rpact:
## | Confirmatory Adaptive Clinical Trial Design and Analysis
## |
## | Author: Gernot Wassmer, PhD, and Friedrich Pahlke, PhD
## | Licensed under "GNU Lesser General Public License" version 3
## | License text can be found here: https://www.r-project.org/Licenses/LGPL-3
## |
## | RPACT company website: https://www.rpact.com
## | rpact package website: https://www.rpact.org
## |
## | Contact us for information about our services: info@rpact.com
## |
## | File version: $Revision: 7962 $
## | Last changed: $Date: 2024-05-31 13:41:37 +0200 (Fr, 31 Mai 2024) $
## | Last changed by: $Author: pahlke $
## |
#' @include f_core_utilities.R
NULL
.addStudyDurationToDesignPlan <- function(designPlan) {
if (!designPlan$accountForObservationTimes) {
return(invisible())
}
kMax <- designPlan$.design$kMax
if (kMax == 1) {
designPlan$studyDuration <- designPlan$analysisTime[1, ]
designPlan$.setParameterType("studyDuration", C_PARAM_GENERATED)
designPlan$maxStudyDuration <- designPlan$studyDuration
} else {
designPlan$maxStudyDuration <- designPlan$analysisTime[kMax, ]
designPlan$.setParameterType("maxStudyDuration", C_PARAM_GENERATED)
}
}
.getLambda <- function(..., groupNumber, lambda2, lambda1, hazardRatio, kappa) {
if (groupNumber == 1) {
if (!any(is.na(lambda1))) {
return(lambda1)
}
lambda2 <- lambda2 * hazardRatio^(1 / kappa)
}
return(lambda2)
}
.getEventProbabilityFunction <- function(..., time, piecewiseLambda, piecewiseSurvivalTime, phi, kappa) {
if (length(piecewiseLambda) == 1) {
if (kappa != 1 && phi > 0) {
stop(C_EXCEPTION_TYPE_ILLEGAL_ARGUMENT, "Weibull distribution cannot ",
"be used together with specified dropout rate (use simulation instead)",
call. = FALSE
)
}
return(piecewiseLambda / (piecewiseLambda + phi) *
pweibull(time, shape = kappa, scale = 1 / (piecewiseLambda + phi), lower.tail = TRUE, log.p = FALSE))
}
if (length(piecewiseSurvivalTime) != length(piecewiseLambda)) {
stop(
C_EXCEPTION_TYPE_ILLEGAL_ARGUMENT,
"length of 'piecewiseSurvivalTime' (", .arrayToString(piecewiseSurvivalTime),
") must be equal to length of 'piecewiseLambda' (", .arrayToString(piecewiseLambda), ")"
)
}
piecewiseSurvivalTime <- .getPiecewiseExpStartTimesWithoutLeadingZero(piecewiseSurvivalTime)
if (kappa != 1) {
stop(C_EXCEPTION_TYPE_ILLEGAL_ARGUMENT,
"Weibull distribution cannot be used for piecewise survival definition",
call. = FALSE
)
}
len <- length(piecewiseSurvivalTime)
for (i in 1:len) {
if (i == 1) {
if (time <= piecewiseSurvivalTime[1]) {
return(piecewiseLambda[1] / (piecewiseLambda[1] + phi) *
(1 - exp(-((piecewiseLambda[1] + phi) * time))))
}
} else if (i == 2) {
cdfPart <- piecewiseLambda[1] / (piecewiseLambda[1] + phi) *
(1 - exp(-((piecewiseLambda[1] + phi) * piecewiseSurvivalTime[1])))
if (time <= piecewiseSurvivalTime[2]) {
cdfFactor <- piecewiseLambda[1] * piecewiseSurvivalTime[1]
cdf <- cdfPart + piecewiseLambda[2] / (piecewiseLambda[2] + phi) * exp(-cdfFactor) * (
exp(-phi * piecewiseSurvivalTime[1]) - exp(-piecewiseLambda[2] *
(time - piecewiseSurvivalTime[1]) - phi * time))
return(cdf)
}
} else if (i == 3) {
cdfPart <- cdfPart + piecewiseLambda[2] / (piecewiseLambda[2] + phi) *
exp(-piecewiseLambda[1] * piecewiseSurvivalTime[1]) * (
exp(-phi * piecewiseSurvivalTime[1]) - exp(-piecewiseLambda[2] *
(piecewiseSurvivalTime[2] - piecewiseSurvivalTime[1]) - phi * piecewiseSurvivalTime[2]))
if (time <= piecewiseSurvivalTime[3]) {
cdfFactor <- piecewiseLambda[1] * piecewiseSurvivalTime[1] +
piecewiseLambda[2] * (piecewiseSurvivalTime[2] - piecewiseSurvivalTime[1])
cdf <- cdfPart + piecewiseLambda[3] / (piecewiseLambda[3] + phi) * exp(-cdfFactor) * (
exp(-phi * piecewiseSurvivalTime[2]) - exp(-piecewiseLambda[3] *
(time - piecewiseSurvivalTime[2]) - phi * time))
return(cdf)
}
} else if (i > 3) {
cdfFactor <- piecewiseLambda[1] * piecewiseSurvivalTime[1] +
sum(piecewiseLambda[2:(i - 2)] * (piecewiseSurvivalTime[2:(i - 2)] -
piecewiseSurvivalTime[1:(i - 3)]))
cdfPart <- cdfPart + piecewiseLambda[i - 1] / (piecewiseLambda[i - 1] + phi) * exp(-cdfFactor) * (
exp(-phi * piecewiseSurvivalTime[i - 2]) - exp(-piecewiseLambda[i - 1] *
(piecewiseSurvivalTime[i - 1] - piecewiseSurvivalTime[i - 2]) - phi * piecewiseSurvivalTime[i - 1]))
if (time <= piecewiseSurvivalTime[i]) {
cdfFactor <- piecewiseLambda[1] * piecewiseSurvivalTime[1] +
sum(piecewiseLambda[2:(i - 1)] * (piecewiseSurvivalTime[2:(i - 1)] - piecewiseSurvivalTime[1:(i - 2)]))
cdf <- cdfPart + piecewiseLambda[i] / (piecewiseLambda[i] + phi) * exp(-cdfFactor) * (
exp(-phi * piecewiseSurvivalTime[i - 1]) - exp(-piecewiseLambda[i] *
(time - piecewiseSurvivalTime[i - 1]) - phi * time))
return(cdf)
}
}
}
if (len == 1) {
cdfPart <- piecewiseLambda[1] / (piecewiseLambda[1] + phi) *
(1 - exp(-((piecewiseLambda[1] + phi) * piecewiseSurvivalTime[1])))
} else if (len == 2) {
cdfFactor <- piecewiseLambda[1] * piecewiseSurvivalTime[1]
cdfPart <- cdfPart + piecewiseLambda[len] / (piecewiseLambda[len] + phi) * exp(-cdfFactor) * (
exp(-phi * piecewiseSurvivalTime[len - 1]) - exp(-piecewiseLambda[len] *
(piecewiseSurvivalTime[len] - piecewiseSurvivalTime[len - 1]) - phi * piecewiseSurvivalTime[len]))
} else {
cdfFactor <- piecewiseLambda[1] * piecewiseSurvivalTime[1] +
sum(piecewiseLambda[2:(len - 1)] * (piecewiseSurvivalTime[2:(len - 1)] - piecewiseSurvivalTime[1:(len - 2)]))
cdfPart <- cdfPart + piecewiseLambda[len] / (piecewiseLambda[len] + phi) * exp(-cdfFactor) * (
exp(-phi * piecewiseSurvivalTime[len - 1]) - exp(-piecewiseLambda[len] *
(piecewiseSurvivalTime[len] - piecewiseSurvivalTime[len - 1]) - phi * piecewiseSurvivalTime[len]))
}
if (len == 1) {
cdfFactor <- piecewiseLambda[1] * piecewiseSurvivalTime[1]
} else {
cdfFactor <- cdfFactor + piecewiseLambda[len] * (piecewiseSurvivalTime[len] - piecewiseSurvivalTime[len - 1])
}
cdf <- cdfPart + piecewiseLambda[len + 1] / (piecewiseLambda[len + 1] + phi) * exp(-cdfFactor) * (
exp(-phi * piecewiseSurvivalTime[len]) - exp(-piecewiseLambda[len + 1] *
(time - piecewiseSurvivalTime[len]) - phi * time))
return(cdf)
}
.getEventProbabilityFunctionVec <- function(..., timeVector, piecewiseLambda, piecewiseSurvivalTime, phi, kappa) {
result <- c()
for (time in timeVector) {
result <- c(result, .getEventProbabilityFunction(
time = time, piecewiseLambda = piecewiseLambda,
piecewiseSurvivalTime = piecewiseSurvivalTime, phi = phi, kappa = kappa
))
}
return(result)
}
.getEventProbabilitiesGroupwise <- function(..., time, accrualTimeVector, accrualIntensity, lambda2,
lambda1, piecewiseSurvivalTime, phi, kappa, allocationRatioPlanned, hazardRatio) {
.assertIsSingleNumber(time, "time")
if (length(accrualTimeVector) > 1 && accrualTimeVector[1] == 0) {
accrualTimeVector <- accrualTimeVector[2:length(accrualTimeVector)]
}
accrualTimeVectorLength <- length(accrualTimeVector)
densityIntervals <- accrualTimeVector
if (accrualTimeVectorLength > 1) {
densityIntervals[2:accrualTimeVectorLength] <-
accrualTimeVector[2:accrualTimeVectorLength] -
accrualTimeVector[1:(accrualTimeVectorLength - 1)]
}
if (length(densityIntervals) > 1 && length(accrualIntensity) > 1 &&
length(densityIntervals) != length(accrualIntensity)) {
stop(
C_EXCEPTION_TYPE_ILLEGAL_ARGUMENT, "'densityIntervals' (", .arrayToString(densityIntervals),
") and 'accrualIntensity' (", .arrayToString(accrualIntensity), ") must have same length"
)
}
densityVector <- accrualIntensity / sum(densityIntervals * accrualIntensity)
eventProbs <- rep(NA_real_, 2)
for (k in 1:accrualTimeVectorLength) {
if (time <= accrualTimeVector[k]) {
for (groupNumber in c(1, 2)) { # two groups: 1 = treatment, 2 = control
lambdaTemp <- .getLambda(
groupNumber = groupNumber,
lambda2 = lambda2,
lambda1 = lambda1,
hazardRatio = hazardRatio,
kappa = kappa
)
inner <- function(x) {
.getEventProbabilityFunctionVec(
timeVector = x, piecewiseLambda = lambdaTemp,
piecewiseSurvivalTime = piecewiseSurvivalTime, phi = phi[groupNumber], kappa = kappa
)
}
timeValue1 <- 0
if (k > 1) {
timeValue1 <- time - accrualTimeVector[1]
}
eventProbs[groupNumber] <- densityVector[1] * stats::integrate(inner, timeValue1, time)$value
if (k > 2) {
for (j in 2:(k - 1)) {
eventProbs[groupNumber] <- eventProbs[groupNumber] +
densityVector[j] * stats::integrate(
inner, time - accrualTimeVector[j],
time - accrualTimeVector[j - 1]
)$value
}
}
if (k > 1) {
eventProbs[groupNumber] <- eventProbs[groupNumber] +
densityVector[k] * stats::integrate(inner, 0, time - accrualTimeVector[k - 1])$value
}
}
return(eventProbs)
}
}
for (groupNumber in c(1, 2)) {
lambdaTemp <- .getLambda(
groupNumber = groupNumber,
lambda2 = lambda2,
lambda1 = lambda1,
hazardRatio = hazardRatio,
kappa = kappa
)
inner <- function(x) {
.getEventProbabilityFunctionVec(
timeVector = x, piecewiseLambda = lambdaTemp,
piecewiseSurvivalTime = piecewiseSurvivalTime, phi = phi[groupNumber], kappa = kappa
)
}
eventProbs[groupNumber] <- densityVector[1] *
stats::integrate(inner, time - accrualTimeVector[1], time)$value
if (accrualTimeVectorLength > 1) {
for (j in (2:accrualTimeVectorLength)) {
eventProbs[groupNumber] <- eventProbs[groupNumber] +
densityVector[j] * stats::integrate(
inner, time - accrualTimeVector[j],
time - accrualTimeVector[j - 1]
)$value
}
}
}
return(eventProbs)
}
.getEventProbabilitiesOverall <- function(eventProbs, allocationRatioPlanned) {
return((allocationRatioPlanned * eventProbs[1] + eventProbs[2]) / (1 + allocationRatioPlanned))
}
.isUserDefinedMaxNumberOfSubjects <- function(designPlan) {
if (!is.null(designPlan) && length(designPlan$.getParameterType("maxNumberOfSubjects")) > 0) {
if (designPlan$.getParameterType("maxNumberOfSubjects") == C_PARAM_USER_DEFINED) {
return(TRUE)
}
}
return(!is.null(designPlan$maxNumberOfSubjects) && length(designPlan$maxNumberOfSubjects) == 1 &&
!is.na(designPlan$maxNumberOfSubjects) && designPlan$maxNumberOfSubjects > 0)
}
.getEventsFixed <- function(..., typeOfComputation = c("Schoenfeld", "Freedman", "HsiehFreedman"),
twoSidedPower, alpha, beta, sided, hazardRatio, thetaH0, allocationRatioPlanned) {
typeOfComputation <- match.arg(typeOfComputation)
if (typeOfComputation == "Schoenfeld") {
eventsFixed <- (.getOneMinusQNorm(alpha / sided) + .getOneMinusQNorm(beta))^2 /
(log(hazardRatio) - log(thetaH0))^2 *
(1 + allocationRatioPlanned)^2 / allocationRatioPlanned
if (twoSidedPower && (sided == 2)) {
up <- 2 * eventsFixed
eventsFixed <- .getOneDimensionalRoot(
function(n) {
return(stats::pnorm(.getOneMinusQNorm(alpha / 2) - sqrt(n) *
(log(hazardRatio) - log(thetaH0)) * sqrt(allocationRatioPlanned) /
(1 + allocationRatioPlanned)) -
stats::pnorm(-.getOneMinusQNorm(alpha / 2) - sqrt(n) *
(log(hazardRatio) - log(thetaH0)) * sqrt(allocationRatioPlanned) /
(1 + allocationRatioPlanned)) - beta)
},
lower = 0.001, upper = up, tolerance = 1e-04,
callingFunctionInformation = ".getEventsFixed"
)
}
return(eventsFixed)
}
if (typeOfComputation == "Freedman") {
eventsFixed <- (.getOneMinusQNorm(alpha / sided) + .getOneMinusQNorm(beta))^2 *
(1 + hazardRatio * allocationRatioPlanned)^2 / (1 - hazardRatio)^2 /
allocationRatioPlanned
if (twoSidedPower && (sided == 2)) {
up <- 2 * eventsFixed
eventsFixed <- .getOneDimensionalRoot(
function(n) {
return(stats::pnorm(.getOneMinusQNorm(alpha / 2) - sqrt(n) *
sqrt(allocationRatioPlanned) * (1 - hazardRatio) /
(1 + allocationRatioPlanned * hazardRatio)) -
stats::pnorm(-.getOneMinusQNorm(alpha / 2) - sqrt(n) *
sqrt(allocationRatioPlanned) * (1 - hazardRatio) /
(1 + allocationRatioPlanned * hazardRatio)) - beta)
},
lower = 0.001, upper = up, tolerance = 1e-04,
callingFunctionInformation = ".getEventsFixed"
)
}
return(eventsFixed)
}
if (typeOfComputation == "HsiehFreedman") {
eventsFixed <- (.getOneMinusQNorm(alpha / sided) + .getOneMinusQNorm(beta))^2 *
(1 + hazardRatio)^2 / (1 - hazardRatio)^2 *
(1 + allocationRatioPlanned)^2 / (4 * allocationRatioPlanned)
if (twoSidedPower && sided == 2) {
up <- 2 * eventsFixed
eventsFixed <- .getOneDimensionalRoot(
function(n) {
return(stats::pnorm(.getOneMinusQNorm(alpha / 2) - sqrt(n) *
2 * sqrt(allocationRatioPlanned) / (1 + allocationRatioPlanned) *
(1 - hazardRatio) / (1 + hazardRatio)) -
stats::pnorm(-.getOneMinusQNorm(alpha / 2) - sqrt(n) *
2 * sqrt(allocationRatioPlanned) / (1 + allocationRatioPlanned) *
(1 - hazardRatio) / (1 + hazardRatio)) - beta)
},
lower = 0.001, upper = up, tolerance = 1e-04,
callingFunctionInformation = ".getEventsFixed"
)
}
return(eventsFixed)
}
}
.getEventProbabilities <- function(..., time, accrualTimeVector, accrualIntensity, lambda2,
lambda1, piecewiseSurvivalTime, phi, kappa, allocationRatioPlanned, hazardRatio) {
eventProbs <- .getEventProbabilitiesGroupwise(
time = time, accrualTimeVector = accrualTimeVector,
accrualIntensity = accrualIntensity, lambda2 = lambda2,
lambda1 = lambda1, piecewiseSurvivalTime = piecewiseSurvivalTime, phi = phi,
kappa = kappa, allocationRatioPlanned = allocationRatioPlanned, hazardRatio = hazardRatio
)
return(.getEventProbabilitiesOverall(eventProbs, allocationRatioPlanned))
}
.getEffectScaleBoundaryDataSurvival <- function(designPlan) {
design <- designPlan$.design
thetaH0 <- designPlan$thetaH0
cumulativeEventsPerStage <- designPlan$cumulativeEventsPerStage
allocationRatioPlanned <- designPlan$allocationRatioPlanned
directionUpper <- designPlan$directionUpper
if (design$kMax == 1) {
nParameters <- length(cumulativeEventsPerStage)
} else {
nParameters <- ncol(cumulativeEventsPerStage)
}
directionUpper[is.na(directionUpper)] <- TRUE
if (length(allocationRatioPlanned) == 1) {
allocationRatioPlanned <- rep(allocationRatioPlanned, nParameters)
}
futilityBounds <- design$futilityBounds
futilityBounds[!is.na(futilityBounds) & futilityBounds <= C_FUTILITY_BOUNDS_DEFAULT] <- NA_real_
criticalValues <- design$criticalValues
criticalValuesEffectScaleUpper <- matrix(, nrow = design$kMax, ncol = nParameters)
criticalValuesEffectScaleLower <- matrix(, nrow = design$kMax, ncol = nParameters)
futilityBoundsEffectScaleUpper <- matrix(, nrow = design$kMax - 1, ncol = nParameters)
futilityBoundsEffectScaleLower <- matrix(, nrow = design$kMax - 1, ncol = nParameters)
for (j in (1:nParameters)) {
if (design$sided == 1) {
criticalValuesEffectScaleUpper[, j] <- thetaH0 * (exp((2 * directionUpper[j] - 1) * criticalValues *
(1 + allocationRatioPlanned[j]) / sqrt(allocationRatioPlanned[j] *
cumulativeEventsPerStage[, j])))
} else {
criticalValuesEffectScaleUpper[, j] <- thetaH0 * (exp((2 * directionUpper[j] - 1) * criticalValues *
(1 + allocationRatioPlanned[j]) / sqrt(allocationRatioPlanned[j] *
cumulativeEventsPerStage[, j])))
criticalValuesEffectScaleLower[, j] <- thetaH0 * (exp(-(2 * directionUpper[j] - 1) * criticalValues *
(1 + allocationRatioPlanned[j]) / sqrt(allocationRatioPlanned[j] *
cumulativeEventsPerStage[, j])))
}
if (!.isTrialDesignFisher(design) && !all(is.na(futilityBounds))) {
futilityBoundsEffectScaleUpper[, j] <- thetaH0 * (exp((2 * directionUpper[j] - 1) * futilityBounds *
(1 + allocationRatioPlanned[j]) / sqrt(allocationRatioPlanned[j] *
cumulativeEventsPerStage[1:(design$kMax - 1), j])))
}
if (!.isTrialDesignFisher(design) && design$sided == 2 && design$kMax > 1 &&
(design$typeOfDesign == C_TYPE_OF_DESIGN_PT || !is.null(design$typeBetaSpending) && design$typeBetaSpending != "none")) {
futilityBoundsEffectScaleLower[, j] <- thetaH0 * (exp(-(2 * directionUpper[j] - 1) * futilityBounds *
(1 + allocationRatioPlanned[j]) / sqrt(allocationRatioPlanned[j] *
cumulativeEventsPerStage[1:(design$kMax - 1), j])))
}
}
return(list(
criticalValuesEffectScaleUpper = matrix(criticalValuesEffectScaleUpper, nrow = design$kMax),
criticalValuesEffectScaleLower = matrix(criticalValuesEffectScaleLower, nrow = design$kMax),
futilityBoundsEffectScaleUpper = matrix(futilityBoundsEffectScaleUpper, nrow = design$kMax - 1),
futilityBoundsEffectScaleLower = matrix(futilityBoundsEffectScaleLower, nrow = design$kMax - 1)
))
}
.calculateSampleSizeSurvival <- function(designPlan) {
# Fixed
designPlan <- .getSampleSizeFixedSurvival(designPlan)
# Sequential
if (designPlan$.design$kMax > 1) {
designCharacteristics <- getDesignCharacteristics(designPlan$.design)
designPlan <- .getSampleSizeSequentialSurvival(designPlan, designCharacteristics)
}
if (designPlan$accountForObservationTimes && !any(is.na(designPlan$followUpTime)) &&
all(designPlan$followUpTime == C_FOLLOW_UP_TIME_DEFAULT)) {
designPlan$.setParameterType("followUpTime", C_PARAM_DEFAULT_VALUE)
}
.addEffectScaleBoundaryDataToDesignPlan(designPlan)
designPlan$singleEventsPerStage <- .getSingleEventsPerStage(designPlan$cumulativeEventsPerStage)
.addDeprecatedFieldValues(designPlan, "eventsPerStage", designPlan$cumulativeEventsPerStage)
paramName <- ifelse(designPlan$.design$kMax == 1, "nFixed", "maxNumberOfSubjects")
if (designPlan$.getParameterType(paramName) == C_PARAM_GENERATED &&
designPlan$.accrualTime$.getParameterType("maxNumberOfSubjects") != C_PARAM_GENERATED &&
all(designPlan$accrualIntensity < 1)) {
numberOfDefinedAccrualIntensities <- length(designPlan$accrualIntensity)
accrualTime <- designPlan$accrualTime
if (length(accrualTime) > 0 && accrualTime[1] != 0) {
accrualTime <- c(0, accrualTime)
}
if (any(designPlan$accrualIntensity < 0)) {
stop(
C_EXCEPTION_TYPE_ILLEGAL_ARGUMENT,
"'accrualIntensityRelative' (",
.arrayToString(designPlan$accrualIntensity), ") must be >= 0"
)
}
designPlan$accrualIntensityRelative <- designPlan$accrualIntensity
if (identical(designPlan$accrualIntensityRelative, C_ACCRUAL_INTENSITY_DEFAULT)) {
designPlan$.setParameterType("accrualIntensityRelative", C_PARAM_NOT_APPLICABLE)
} else {
designPlan$.setParameterType(
"accrualIntensityRelative",
designPlan$.getParameterType("accrualIntensity")
)
}
accrualIntensityAbsolute <- numeric()
for (maxNumberOfSubjects in designPlan[[paramName]]) {
accrualSetup <- getAccrualTime(
accrualTime = accrualTime,
accrualIntensity = designPlan$accrualIntensityRelative,
accrualIntensityType = "relative",
maxNumberOfSubjects = maxNumberOfSubjects
)
accrualIntensityAbsolute <- c(accrualIntensityAbsolute, accrualSetup$accrualIntensity)
}
designPlan$accrualIntensity <- accrualIntensityAbsolute
designPlan$.setParameterType("accrualIntensity", C_PARAM_GENERATED)
if (numberOfDefinedAccrualIntensities > 1) {
paramName <- NULL
if (designPlan$.getParameterType("pi1") == C_PARAM_USER_DEFINED ||
designPlan$.getParameterType("pi1") == C_PARAM_DEFAULT_VALUE ||
designPlan$.getParameterType("pi2") == C_PARAM_USER_DEFINED) {
paramName <- "pi1"
} else if (designPlan$.getParameterType("median1") == C_PARAM_USER_DEFINED ||
designPlan$.getParameterType("median2") == C_PARAM_USER_DEFINED) {
paramName <- "median1"
}
if (!is.null(paramName)) {
paramValue <- designPlan[[paramName]]
if (!is.null(paramValue) && length(paramValue) > 1) {
stop(
C_EXCEPTION_TYPE_ILLEGAL_ARGUMENT,
"the definition of relative accrual intensities ",
"(all 'accrualIntensity' values < 1) ",
"is only available for a single value ",
"(", paramName, " = ", .arrayToString(
paramValue,
vectorLookAndFeelEnabled = TRUE
), ")"
)
}
}
}
}
designPlan$maxNumberOfEvents <- designPlan$cumulativeEventsPerStage[designPlan$.design$kMax, ]
designPlan$.setParameterType("maxNumberOfEvents", C_PARAM_GENERATED)
if (!any(is.na(designPlan$followUpTime))) {
if (any(designPlan$followUpTime < -1e-02)) {
warning("Accrual duration longer than maximal study ",
"duration (time to maximal number of events); followUpTime = ",
.arrayToString(designPlan$followUpTime),
call. = FALSE
)
}
} else {
warning("Follow-up time could not be calculated for hazardRatio = ",
.arrayToString(designPlan$hazardRatio),
call. = FALSE
)
}
if (designPlan$.getParameterType("accountForObservationTimes") != C_PARAM_USER_DEFINED) {
designPlan$.setParameterType("accountForObservationTimes", C_PARAM_NOT_APPLICABLE)
}
designPlan$.setParameterType("chi", C_PARAM_NOT_APPLICABLE)
.addStudyDurationToDesignPlan(designPlan)
return(designPlan)
}
# Hidden parameter:
# @param accountForObservationTimes If \code{accountForObservationTimes = TRUE}, the number of
# subjects is calculated assuming specific accrual and follow-up time, default is \code{TRUE}
# (see details).
# If \code{accountForObservationTimes = FALSE}, only the event rates are used for the calculation
# of the maximum number of subjects.
# \code{accountForObservationTimes} can be selected as \code{FALSE}. In this case,
# the number of subjects is calculated from the event probabilities only.
# This kind of computation does not account for the specific accrual pattern and survival distribution.
.getSampleSizeSurvival <- function(...,
design = NULL,
typeOfComputation = c("Schoenfeld", "Freedman", "HsiehFreedman"),
thetaH0 = 1,
pi2 = NA_real_,
pi1 = NA_real_,
allocationRatioPlanned = NA_real_,
accountForObservationTimes = TRUE,
eventTime = C_EVENT_TIME_DEFAULT,
accrualTime = C_ACCRUAL_TIME_DEFAULT,
accrualIntensity = C_ACCRUAL_INTENSITY_DEFAULT,
accrualIntensityType = c("auto", "absolute", "relative"),
kappa = 1,
piecewiseSurvivalTime = NA_real_,
lambda2 = NA_real_,
lambda1 = NA_real_,
median1 = NA_real_,
median2 = NA_real_,
followUpTime = NA_real_,
maxNumberOfSubjects = NA_real_,
dropoutRate1 = 0,
dropoutRate2 = dropoutRate1,
dropoutTime = NA_real_,
hazardRatio = NA_real_,
userFunctionCallEnabled = TRUE) {
designPlan <- .createDesignPlanSurvival(
objectType = "sampleSize",
design = design,
typeOfComputation = typeOfComputation,
thetaH0 = thetaH0,
pi2 = pi2,
pi1 = pi1,
allocationRatioPlanned = allocationRatioPlanned,
accountForObservationTimes = accountForObservationTimes,
eventTime = eventTime,
accrualTime = accrualTime,
accrualIntensity = accrualIntensity,
accrualIntensityType = accrualIntensityType,
kappa = kappa,
piecewiseSurvivalTime = piecewiseSurvivalTime,
lambda2 = lambda2,
lambda1 = lambda1,
median1 = median1,
median2 = median2,
followUpTime = followUpTime,
maxNumberOfSubjects = maxNumberOfSubjects,
dropoutRate1 = dropoutRate1,
dropoutRate2 = dropoutRate2,
dropoutTime = dropoutTime,
hazardRatio = hazardRatio,
userFunctionCallEnabled = userFunctionCallEnabled
)
return(.calculateSampleSizeSurvival(designPlan))
}
.createDesignPlanSurvival <- function(..., objectType = c("sampleSize", "power"),
design,
typeOfComputation = c("Schoenfeld", "Freedman", "HsiehFreedman"),
thetaH0, pi2, pi1,
allocationRatioPlanned,
accountForObservationTimes,
eventTime,
accrualTime,
accrualIntensity,
accrualIntensityType,
kappa,
piecewiseSurvivalTime,
lambda2,
lambda1,
median1,
median2,
followUpTime = NA_real_,
directionUpper = NA,
maxNumberOfEvents = NA_real_,
maxNumberOfSubjects,
dropoutRate1,
dropoutRate2,
dropoutTime,
hazardRatio,
userFunctionCallEnabled = TRUE) {
objectType <- match.arg(objectType)
typeOfComputation <- .matchArgument(typeOfComputation, "Schoenfeld")
if (userFunctionCallEnabled) {
.assertIsTrialDesignInverseNormalOrGroupSequential(design)
.assertIsValidAlphaAndBeta(design$alpha, design$beta)
.assertIsValidSidedParameter(design$sided)
.assertIsSingleLogical(accountForObservationTimes, "accountForObservationTimes", naAllowed = TRUE)
.assertIsSingleNumber(thetaH0, "thetaH0")
.assertIsValidThetaH0(thetaH0, endpoint = "survival", groups = 2)
.assertIsValidKappa(kappa)
directionUpper <- .assertIsValidDirectionUpper(directionUpper,
design$sided, objectType,
userFunctionCallEnabled = TRUE
)
if (objectType == "power") {
.assertIsSingleNumber(maxNumberOfEvents, "maxNumberOfEvents")
.assertIsInClosedInterval(maxNumberOfEvents, "maxNumberOfEvents",
lower = 1, upper = maxNumberOfSubjects
)
}
if (!any(is.na(pi1)) && (any(pi1 <= 0) || any(pi1 >= 1))) {
stop(
C_EXCEPTION_TYPE_ARGUMENT_OUT_OF_BOUNDS,
"event rate 'pi1' (", .arrayToString(pi1), ") is out of bounds (0; 1)"
)
}
if (!any(is.na(pi2)) && (any(pi2 <= 0) || any(pi2 >= 1))) {
stop(
C_EXCEPTION_TYPE_ARGUMENT_OUT_OF_BOUNDS,
"event rate 'pi2' (", .arrayToString(pi2), ") is out of bounds (0; 1)"
)
}
if (design$sided == 2 && thetaH0 != 1) {
stop(
C_EXCEPTION_TYPE_ILLEGAL_ARGUMENT,
"two-sided case is implemented for superiority testing only (i.e., thetaH0 = 1)"
)
}
if (thetaH0 <= 0) {
stop(
C_EXCEPTION_TYPE_ILLEGAL_ARGUMENT,
"null hypothesis hazard ratio is not allowed be negative or zero"
)
}
if (!(typeOfComputation %in% c("Schoenfeld", "Freedman", "HsiehFreedman"))) {
stop(
C_EXCEPTION_TYPE_ILLEGAL_ARGUMENT,
"computation type ('", typeOfComputation, "') must be one of the following: ",
"'Schoenfeld', 'Freedman', or 'HsiehFreedman' "
)
}
if (typeOfComputation != "Schoenfeld" && thetaH0 != 1) {
stop(
C_EXCEPTION_TYPE_ILLEGAL_ARGUMENT,
"Freedman test calculation is possible only for superiority testing (thetaH0 != 1)"
)
}
}
if (is.numeric(accrualTime) && all(is.na(accrualTime))) {
accrualTime <- C_ACCRUAL_TIME_DEFAULT
}
if (all(is.na(accrualIntensity))) {
accrualIntensity <- C_ACCRUAL_INTENSITY_DEFAULT
}
accrualSetup <- getAccrualTime(
accrualTime = accrualTime,
accrualIntensity = accrualIntensity,
accrualIntensityType = accrualIntensityType,
maxNumberOfSubjects = maxNumberOfSubjects
)
accrualSetup$.validate()
if (is.na(allocationRatioPlanned)) {
allocationRatioPlanned <- C_ALLOCATION_RATIO_DEFAULT
}
if (userFunctionCallEnabled) {
.assertIsValidAllocationRatioPlannedSampleSize(allocationRatioPlanned, maxNumberOfSubjects)
}
designPlan <- TrialDesignPlanSurvival$new(
design = design,
typeOfComputation = typeOfComputation,
thetaH0 = thetaH0,
allocationRatioPlanned = allocationRatioPlanned,
accountForObservationTimes = accountForObservationTimes,
eventTime = eventTime,
accrualTime = accrualSetup$.getAccrualTimeWithoutLeadingZero(),
accrualIntensity = accrualSetup$accrualIntensity,
kappa = kappa,
followUpTime = followUpTime,
maxNumberOfSubjects = maxNumberOfSubjects,
dropoutRate1 = dropoutRate1,
dropoutRate2 = dropoutRate2,
dropoutTime = dropoutTime,
hazardRatio = hazardRatio
)
.setValueAndParameterType(
designPlan, "allocationRatioPlanned",
allocationRatioPlanned, C_ALLOCATION_RATIO_DEFAULT
)
.setValueAndParameterType(designPlan, "dropoutRate1", dropoutRate1, C_DROP_OUT_RATE_1_DEFAULT)
.setValueAndParameterType(designPlan, "dropoutRate2", dropoutRate2, C_DROP_OUT_RATE_2_DEFAULT)
.setValueAndParameterType(designPlan, "dropoutTime", dropoutTime, C_DROP_OUT_TIME_DEFAULT)
.setValueAndParameterType(designPlan, "kappa", kappa, 1)
designPlan$.setObjectType(objectType)
designPlan$criticalValuesPValueScale <- matrix(design$stageLevels, ncol = 1)
if (design$sided == 2) {
designPlan$criticalValuesPValueScale <- designPlan$criticalValuesPValueScale * 2
designPlan$.setParameterType("criticalValuesPValueScale", C_PARAM_GENERATED)
}
if (any(design$futilityBounds > C_FUTILITY_BOUNDS_DEFAULT)) {
designPlan$futilityBoundsPValueScale <- matrix(1 - stats::pnorm(design$futilityBounds), ncol = 1)
designPlan$.setParameterType("futilityBoundsPValueScale", C_PARAM_GENERATED)
}
designPlan$.accrualTime <- accrualSetup
designPlan$totalAccrualTime <- accrualSetup$accrualTime[length(accrualSetup$accrualTime)]
if (length(accrualSetup$accrualTime) > 2) {
designPlan$.setParameterType("totalAccrualTime", C_PARAM_GENERATED)
} else {
designPlan$.setParameterType("totalAccrualTime", C_PARAM_NOT_APPLICABLE)
}
if (is.na(maxNumberOfSubjects)) {
if (!is.na(accrualSetup$maxNumberOfSubjects)) {
designPlan$maxNumberOfSubjects <- accrualSetup$maxNumberOfSubjects
designPlan$.setParameterType(
"maxNumberOfSubjects",
accrualSetup$.getParameterType("maxNumberOfSubjects")
)
}
} else if (maxNumberOfSubjects == 0) {
designPlan$.setParameterType("maxNumberOfSubjects", C_PARAM_GENERATED)
} else {
designPlan$.setParameterType("maxNumberOfSubjects", C_PARAM_USER_DEFINED)
}
if (isTRUE(all.equal(accrualSetup$accrualTime, C_ACCRUAL_TIME_DEFAULT)) ||
isTRUE(all.equal(
as.integer(c(0L, accrualSetup$.getAccrualTimeWithoutLeadingZero())),
C_ACCRUAL_TIME_DEFAULT))
) {
designPlan$.setParameterType("accrualTime", C_PARAM_DEFAULT_VALUE)
} else {
designPlan$.setParameterType("accrualTime", accrualSetup$.getParameterType("accrualTime"))
}
if (length(designPlan$accrualIntensity) == 1 &&
designPlan$accrualIntensity == C_ACCRUAL_INTENSITY_DEFAULT) {
designPlan$.setParameterType("accrualIntensity", C_PARAM_DEFAULT_VALUE)
} else {
designPlan$.setParameterType(
"accrualIntensity",
accrualSetup$.getParameterType("accrualIntensity")
)
}
.assertIsSingleNumber(designPlan$eventTime, "eventTime")
.assertIsSingleNumber(designPlan$allocationRatioPlanned, "allocationRatioPlanned")
.assertIsSingleNumber(designPlan$kappa, "kappa")
if (objectType == "power") {
.assertIsValidMaxNumberOfSubjects(designPlan$maxNumberOfSubjects)
}
.assertIsSingleNumber(designPlan$dropoutRate1, "dropoutRate1")
.assertIsSingleNumber(designPlan$dropoutRate2, "dropoutRate2")
.assertIsSingleNumber(designPlan$dropoutTime, "dropoutTime")
if (objectType == "power") {
pi1Default <- C_PI_1_DEFAULT
} else {
pi1Default <- C_PI_1_SAMPLE_SIZE_DEFAULT
}
designPlan$.piecewiseSurvivalTime <- getPiecewiseSurvivalTime(
piecewiseSurvivalTime = piecewiseSurvivalTime, lambda2 = lambda2, lambda1 = lambda1,
median1 = median1, median2 = median2,
hazardRatio = hazardRatio, pi1 = pi1, pi2 = pi2, eventTime = eventTime, kappa = kappa,
.pi1Default = pi1Default
)
designPlan$.setParameterType("kappa", designPlan$.piecewiseSurvivalTime$.getParameterType("kappa"))
if (designPlan$.piecewiseSurvivalTime$.getParameterType("pi1") == C_PARAM_DEFAULT_VALUE &&
length(designPlan$.piecewiseSurvivalTime$pi1) > 1 &&
length(accrualSetup$accrualIntensity) > 1 && all(accrualSetup$accrualIntensity < 1)) {
designPlan$.piecewiseSurvivalTime$pi1 <- designPlan$.piecewiseSurvivalTime$pi1[1]
warning("Only the first default 'pi1' (", designPlan$.piecewiseSurvivalTime$pi1, ") was used ",
"because the accrual intensities (", .arrayToString(accrualSetup$accrualIntensity), ") ",
"were defined relative (all accrual intensities are < 1)",
call. = FALSE
)
}
.initDesignPlanSurvival(designPlan)
designPlan$.setParameterType("followUpTime", C_PARAM_NOT_APPLICABLE)
if (designPlan$accountForObservationTimes) {
.assertIsSingleNumber(dropoutRate1, "dropoutRate1")
.assertIsSingleNumber(dropoutRate2, "dropoutRate2")
.assertIsSingleNumber(dropoutTime, "dropoutTime")
if (!is.na(dropoutTime) && dropoutTime <= 0) {
stop(C_EXCEPTION_TYPE_ILLEGAL_ARGUMENT, "'dropoutTime' (", dropoutTime, ") must be > 0")
}
if (dropoutRate1 < 0 || dropoutRate1 >= 1) {
stop(
C_EXCEPTION_TYPE_ARGUMENT_OUT_OF_BOUNDS,
"'dropoutRate1' (", dropoutRate1, ") is out of bounds [0; 1)"
)
}
if (dropoutRate2 < 0 || dropoutRate2 >= 1) {
stop(
C_EXCEPTION_TYPE_ARGUMENT_OUT_OF_BOUNDS,
"'dropoutRate2' (", dropoutRate2, ") is out of bounds [0; 1)"
)
}
if (!is.na(eventTime) && eventTime <= 0) {
stop(C_EXCEPTION_TYPE_ILLEGAL_ARGUMENT, "'eventTime' (", eventTime, ") must be > 0")
}
.assertIsValidAccrualTime(accrualSetup$accrualTime)
.assertIsValidFollowUpTime(followUpTime)
.setValueAndParameterType(designPlan, "followUpTime", followUpTime, C_FOLLOW_UP_TIME_DEFAULT)
if (.isUserDefinedMaxNumberOfSubjects(designPlan) && !is.null(followUpTime) &&
length(followUpTime) == 1 && !is.na(followUpTime)) {
warning("Follow-up time will be calculated, value entered (",
followUpTime, ") is not taken into account",
call. = FALSE
)
} else if (is.na(followUpTime)) {
designPlan$followUpTime <- C_FOLLOW_UP_TIME_DEFAULT
designPlan$.setParameterType("followUpTime", C_PARAM_DEFAULT_VALUE)
}
if (objectType == "power") {
designPlan$followUpTime <- NA_real_
designPlan$.setParameterType("followUpTime", C_PARAM_NOT_APPLICABLE)
}
} else {
for (p in c(
"accrualTime", "accrualIntensity",
"eventTime", "dropoutRate1", "dropoutRate2", "dropoutTime", "followUpTime",
"analysisTime", "studyDuration"
)) {
designPlan$.setParameterType(p, C_PARAM_NOT_APPLICABLE)
}
if (designPlan$.getParameterType("accrualTime") == C_PARAM_USER_DEFINED ||
!isTRUE(all.equal(accrualTime, C_ACCRUAL_TIME_DEFAULT))) {
designPlan$.warnInCaseArgumentExists(accrualSetup$accrualTime, "accrualTime")
}
designPlan$.warnInCaseArgumentExists(dropoutRate1, "dropoutRate1")
designPlan$.warnInCaseArgumentExists(dropoutRate2, "dropoutRate2")
if (!identical(dropoutTime, C_DROP_OUT_TIME_DEFAULT)) {
designPlan$.warnInCaseArgumentExists(dropoutTime, "dropoutTime")
}
designPlan$.warnInCaseArgumentExists(maxNumberOfSubjects, "maxNumberOfSubjects")
if (!identical(followUpTime, C_FOLLOW_UP_TIME_DEFAULT)) {
designPlan$.warnInCaseArgumentExists(followUpTime, "followUpTime")
}
}
.setValueAndParameterType(designPlan, "directionUpper", directionUpper, TRUE)
if (objectType == "power") {
.setValueAndParameterType(designPlan, "maxNumberOfEvents", maxNumberOfEvents, NA_real_)
designPlan$.setParameterType("accountForObservationTimes", C_PARAM_NOT_APPLICABLE)
}
return(designPlan)
}
.initDesignPlanSurvivalByPiecewiseSurvivalTimeObject <- function(designPlan, pwstSetup) {
designPlan$pi1 <- pwstSetup$pi1
designPlan$.setParameterType("pi1", pwstSetup$.getParameterType("pi1"))
designPlan$pi2 <- pwstSetup$pi2
designPlan$.setParameterType("pi2", pwstSetup$.getParameterType("pi2"))
designPlan$hazardRatio <- pwstSetup$hazardRatio
designPlan$.setParameterType("hazardRatio", pwstSetup$.getParameterType("hazardRatio"))
designPlan$lambda1 <- pwstSetup$lambda1
designPlan$.setParameterType("lambda1", pwstSetup$.getParameterType("lambda1"))
designPlan$lambda2 <- pwstSetup$lambda2
designPlan$.setParameterType("lambda2", pwstSetup$.getParameterType("lambda2"))
designPlan$median1 <- pwstSetup$median1
designPlan$.setParameterType("median1", pwstSetup$.getParameterType("median1"))
designPlan$median2 <- pwstSetup$median2
designPlan$.setParameterType("median2", pwstSetup$.getParameterType("median2"))
designPlan$piecewiseSurvivalTime <- pwstSetup$piecewiseSurvivalTime
designPlan$.setParameterType(
"piecewiseSurvivalTime",
pwstSetup$.getParameterType("piecewiseSurvivalTime")
)
designPlan$eventTime <- pwstSetup$eventTime
designPlan$.setParameterType("eventTime", pwstSetup$.getParameterType("eventTime"))
if (pwstSetup$.isLambdaBased()) {
return(length(designPlan$hazardRatio))
}
return(length(designPlan$pi1))
}
.initDesignPlanSurvival <- function(designPlan) {
numberOfResults <- .initDesignPlanSurvivalByPiecewiseSurvivalTimeObject(
designPlan, designPlan$.piecewiseSurvivalTime
)
if (designPlan$.piecewiseSurvivalTime$.isLambdaBased()) {
if (length(designPlan$accountForObservationTimes) == 0 ||
is.na(designPlan$accountForObservationTimes) ||
!designPlan$accountForObservationTimes) {
designPlan$accountForObservationTimes <- TRUE
designPlan$.setParameterType("accountForObservationTimes", C_PARAM_DEFAULT_VALUE)
}
if (!designPlan$accountForObservationTimes) {
designPlan$accountForObservationTimes <- TRUE
warning("'accountForObservationTimes' was set to TRUE ",
"because piecewise exponential survival function is enabled",
call. = FALSE
)
}
} else {
if (.isUserDefinedMaxNumberOfSubjects(designPlan)) {
if (length(designPlan$accountForObservationTimes) != 0 &&
!is.na(designPlan$accountForObservationTimes) &&
!designPlan$accountForObservationTimes) {
stop(
C_EXCEPTION_TYPE_ILLEGAL_ARGUMENT,
"'accountForObservationTimes' must be TRUE because 'maxNumberOfSubjects' is > 0"
)
}
designPlan$.setParameterType("accountForObservationTimes", C_PARAM_GENERATED)
designPlan$accountForObservationTimes <- TRUE
} else {