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inst/shinyApp/app.R
In lrstat: Power and Sample Size Calculation for Non-Proportional Hazards and Beyond
library(shiny)
library(shinyMatrix)
library(shinyFeedback)
library(shinyjs)
library(dplyr)
library(tidyr)
library(prompter)
library(plotly)
library(lrstat)
# popover texts
followupTimeText = "Follow-up time for the last enrolled subject"
rho1Text = "First parameter of Fleming-Harrington weight"
rho2Text = "Second parameter of Fleming-Harrington weight"
informationRatesText = "Information rates in terms of event fractions"
informationRatesText = gsub(
"\\s+", " ", "Information rates in terms of variance of
logrank score statistic under the null hypothesis")
# palette for color-blinded
cbbPalette <- c("#000000", "#E69F00", "#56B4E9", "#009E73",
"#F0E442", "#0072B2", "#D55E00", "#CC79A7")
# number of time points for power curves
ntpts = 11
# Number of subintervals for approximating the numerator and denominator
# of the log-rank test statistic
numSubintervals = 300
# Bracket interval for root finding when the calculation target is
# accrual or follow-up duration
interval = c(0.001, 120)
# reduced style fileInput
fileInputNoExtra<-function(inputId, label, multiple = FALSE, accept = NULL,
width = NULL, buttonLabel = "Browse...",
placeholder = "No file selected"){
restoredValue <- restoreInput(id = inputId, default = NULL)
if (!is.null(restoredValue) && !is.data.frame(restoredValue)) {
warning("Restored value for ", inputId, " has incorrect format.")
restoredValue <- NULL
}
if (!is.null(restoredValue)) {
restoredValue <- toJSON(restoredValue, strict_atomic = FALSE)
}
inputTag <- tags$input(id = inputId, name = inputId, type = "file",
style = "display: none;",
`data-restore` = restoredValue)
if (multiple)
inputTag$attribs$multiple <- "multiple"
if (length(accept) > 0)
inputTag$attribs$accept <- paste(accept, collapse = ",")
tags$label(
class = "input-group-btn",
type="button",
style=if (!is.null(width))
paste0("width: ", validateCssUnit(width),";",
"padding-right: 5px; padding-bottom: 0px; display:inline-block;"),
span(class = "btn btn-default btn-file",type="button",
buttonLabel, inputTag,
style=if (!is.null(width))
paste0("width: ", validateCssUnit(width),";",
"border-radius: 4px; padding-bottom:5px;"))
)
}
# conditional panels for interim timing
f <- function(i) {
conditionalPanel(
condition = paste0("input.kMax == ", i),
shinyMatrix::matrixInput(
paste0("xIA_",i),
label = tags$span(
"Timing of interim analyses",
tags$span(icon(name = "question-circle")) %>%
add_prompt(message = informationRatesText, position = "right")
),
value = matrix(seq_len(i-1)/i,
ncol = 1,
dimnames = list(paste0("Look ", seq_len(i-1)),
"Information rate")),
inputClass = "numeric",
rows = list(names=TRUE, extend=FALSE),
cols = list(names=TRUE, extend=FALSE)),
fluidRow(
column(6, checkboxGroupInput(
paste0("xES_",i),
label = "Stop for efficacy",
choices = paste0("Look ", seq_len(i-1)),
selected = paste0("Look ", seq_len(i-1)))),
column(6, checkboxGroupInput(
paste0("xFS_",i),
label = "Stop for futility",
choices = paste0("Look ", seq_len(i-1)),
selected = paste0("Look ", seq_len(i-1)))),
),
)
}
# initial values for user-specified alpha spending
g <- function(i) {
conditionalPanel(
condition = paste0("input.kMax == ", i),
shinyMatrix::matrixInput(
paste0("xUA_",i),
value = matrix(0.0125*(1-exp(4*seq_len(i-1)/i))/(1-exp(4)),
ncol = 1,
dimnames = list(paste0("Look ", seq_len(i-1)),
c("Cumulative alpha"))),
inputClass = "numeric",
rows = list(names=TRUE, extend=FALSE),
cols = list(names=TRUE, extend=FALSE)
)
)
}
# design panel -------------------
designPanel <- tabPanel(
"Design",
radioButtons(
"target",
"Calculation target",
choices = c("Power" = "power",
"Accrual duration" = "accrualDuration",
"Follow-up duration" = "followupTime"),
selected = "accrualDuration",
inline = TRUE
),
fluidRow(
column(6, numericInput(
"alpha",
label = tags$span(
"alpha",
tags$span(icon(name = "question-circle")) %>%
add_prompt(message = "1-sided significance level",
position = "right")),
value = 0.025,
min = 0.0001, max = 0.4999, step = 0.0001)
),
column(6, numericInput(
"power",
"Power",
value = 0.9,
min = 0.001, max = 0.999, step = 0.001)
),
),
fluidRow(
column(6, numericInput(
"accrualDuration",
"Accrual duration",
value = 11.643,
min = 0.01, max = 120, step = 0.001)
),
column(6, numericInput(
"followupTime",
label = tags$span(
"Follow-up duration",
tags$span(icon(name = "question-circle")) %>%
add_prompt(message = followupTimeText, position = "right")
),
value = 18,
min = 0.01, max = 120, step = 0.001)
),
),
fluidRow(
column(6, numericInput(
"allocationRatioPlanned",
"Allocation ratio",
value=1, min=0.1, max=10, step=0.01),
),
column(6, checkboxInput(
"fixedFollowup",
"Fixed follow-up", value=FALSE)
),
),
fluidRow(
column(6, numericInput(
"rho1",
label = tags$span(
"rho1",
tags$span(icon(name = "question-circle")) %>%
add_prompt(message = rho1Text, position = "right")
),
value = 0,
min = 0, max = 2, step = 0.01)
),
column(6, numericInput(
"rho2",
label = tags$span(
"rho2",
tags$span(icon(name = "question-circle")) %>%
add_prompt(message = rho2Text, position = "right")
),
value = 0,
min = 0, max = 2, step = 0.01)
),
),
checkboxInput(
"rounding",
"Rounding up sample size and events", value=TRUE)
)
# test boundaries panel ----------------
boundariesPanel <- tabPanel(
"Boundaries",
lapply(2:6, f),
selectInput(
"asf", "Alpha spending",
choices = c(
"O'Brien-Fleming boundaries" = "OF",
"Pocock boundaries" = "P",
"Wang & Tsiatis boundaries" = "WT",
"O'Brien-Fleming type spending" = "sfOF",
"Pocock type spending" = "sfP",
"Kim & DeMets spending" = "sfKD",
"Hwang, Shi & DeCani spending" = "sfHSD",
"User defined spending" = "user",
"No early efficacy stopping" = "none"
),
selected = "sfOF"
),
conditionalPanel(
condition = "input.asf == 'WT'",
sliderInput(
"deltaAlpha",
"Delta for Wang & Tsiatis efficacy boundaries",
min=-0.3, max=0.5, value=0.25, step=0.01)
),
conditionalPanel(
condition = "input.asf == 'sfKD'",
sliderInput(
"rhoAlpha",
"rho for Kim & DeMets alpha spending",
min=0.4, max=8, value=1, step=0.01)
),
conditionalPanel(
condition = "input.asf == 'sfHSD'",
sliderInput(
"gammaAlpha",
"gamma for Hwang, Shi & DeCani alpha spending",
min=-10, max=5, value=1, step=0.01)
),
conditionalPanel(
condition = "input.asf == 'user'",
lapply(2:6, g),
),
selectInput(
"bsf", "Beta spending",
choices = c(
"O'Brien-Fleming type spending" = "sfOF",
"Pocock type spending" = "sfP",
"Kim & DeMets spending" = "sfKD",
"Hwang, Shi & DeCani spending" = "sfHSD",
"No early futility stopping" = "none"
),
selected = "none"
),
conditionalPanel(
condition = "input.bsf == 'sfKD'",
sliderInput(
"rhoBeta",
"rho for Kim & DeMets beta spending",
min=0.4, max=8, value=1, step=0.01)
),
conditionalPanel(
condition = "input.bsf == 'sfHSD'",
sliderInput(
"gammaBeta",
"gamma for Hwang, Shi & DeCani beta spending",
min=-10, max=5, value=1, step=0.01)
),
)
# settings panel -------------------
settingsPanel <- tabPanel(
"Settings",
shinyMatrix::matrixInput(
"survival",
"Piecewise exponential survival",
value = matrix(c(0, 0.0309, 0.0533),
nrow = 1,
dimnames = list(
NULL, c("Starting time",
"Treatment hazard rate",
"Control hazard rate"))
),
inputClass = "numeric",
rows = list(names=FALSE, extend=FALSE),
cols = list(names=TRUE, extend=FALSE)
),
actionButton("add_x", label=NULL, icon=icon("plus") ),
actionButton("del_x", label=NULL, icon=icon("minus")),
shinyMatrix::matrixInput(
"accrual",
"Piecewise constant accrual",
value = matrix(c(0, 20),
nrow=1,
dimnames = list(
NULL, c("Starting time",
"Accrual intensity"))
),
inputClass = "numeric",
rows = list(names=FALSE, extend=FALSE),
cols = list(names=TRUE, extend=FALSE)
),
actionButton("add_y", label=NULL, icon=icon("plus") ),
actionButton("del_y", label=NULL, icon=icon("minus")),
shinyMatrix::matrixInput(
"dropout",
"Exponential dropout",
value = matrix(c(0, 0),
nrow = 1,
dimnames = list(
NULL, c("Treatment hazard rate",
"Control hazard rate"))
),
inputClass = "numeric",
rows = list(names=FALSE, extend=FALSE),
cols = list(names=TRUE, extend=FALSE)
),
)
# summary panel -------------------
summaryPanel <- tabPanel(
"Summary",
htmlOutput("design"),
htmlOutput("text"),
conditionalPanel(
condition = "input.kMax > 1",
verbatimTextOutput("table"),
),
htmlOutput("text0"),
conditionalPanel(
condition = "input.kMax > 1",
verbatimTextOutput("table0"),
),
)
# plot panel -------------------
plotPanel <- tabPanel(
"Plot",
conditionalPanel(
condition = "input.kMax > 1",
selectInput(
"plottype",
"Plot type",
choices = c("Boundaries (Z)" = "boundaryZ",
"Boundaries (HR)" = "boundaryHR",
"Boundaries (p)" = "boundaryP",
"Error Spending" = "errorSpend",
"Sample Size / Events vs. Time" = "eventPred",
"Power vs. Follow-up Duration" = "powerVsTf",
"Power vs. Sample Size" = "powerVsN",
"Study Duration vs. Sample Size" = "TsVsN"),
selected = "boundaryZ"
),
),
conditionalPanel(
condition = "input.kMax == 1",
selectInput(
"plottype2",
"Plot type",
choices = c("Sample Size / Events vs. Time" = "eventPred",
"Power vs. Follow-up Duration" = "powerVsTf",
"Power vs. Sample Size" = "powerVsN",
"Study Duration vs. Sample Size" = "TsVsN"),
selected = "boundaryZ"
),
),
plotlyOutput("plot"),
)
# simulation panel -------------------
simulationPanel <- tabPanel(
"Simulation",
shinyMatrix::matrixInput(
"boundaries",
label = tags$span(
"Analysis timing and boundaries",
tags$span(icon(name = "question-circle")) %>%
add_prompt(message = informationRatesText, position = "right")
),
value = matrix(),
inputClass = "numeric",
rows = list(names = TRUE, extend = FALSE),
cols = list(names = TRUE, extend = FALSE)
),
fluidRow(
column(3, numericInput(
"nIterations",
label = "# simulations",
value = 1000,
min = 200, max = 10000, step = 1)
),
column(3, numericInput(
"nRawDatasets",
label = tags$span(
"Raw datasets",
tags$span(icon(name = "question-circle")) %>%
add_prompt(message = "# raw datasets to extract per stage",
position = "right")),
value = 1,
min = 0, max = 100, step = 1)
),
column(3, numericInput(
"seed",
label = "Seed",
value = 100,
min = 0, max = 100000, step = 1
)),
column(3, style = "margin-top: 25px;", actionButton(
"sim", "Simulate",
style="color: #fff; background-color: #337ab7; border-color: #2e6da4"
)),
),
htmlOutput("simtext"),
conditionalPanel(
condition = "input.kMax > 1",
verbatimTextOutput("simtable"),
),
conditionalPanel(
condition = "input.sim > 0",
fluidRow(
column(6, downloadButton(
"downloadSumdata", "Download summary data under H1")),
conditionalPanel(
condition = "input.nRawDatasets > 0",
column(6, downloadButton(
"downloadRawdata", "Download raw data under H1")),
),
),
),
htmlOutput("simtext0"),
conditionalPanel(
condition = "input.kMax > 1",
verbatimTextOutput("simtable0"),
),
conditionalPanel(
condition = "input.sim > 0",
fluidRow(
column(6, downloadButton(
"downloadSumdata0", "Download summary data under H0")),
conditionalPanel(
condition = "input.nRawDatasets > 0",
column(6, downloadButton(
"downloadRawdata0", "Download raw data under H0")),
),
),
),
)
# code panel -------------------
codePanel <- tabPanel(
"Code",
helpText('library(lrstat)'),
fluidRow(
column(6, htmlOutput("lrp")),
column(6, htmlOutput("lrs")),
),
)
# user interface ----------------
ui <- fluidPage(
shinyFeedback::useShinyFeedback(),
shinyjs::useShinyjs(),
prompter::use_prompt(),
titlePanel(tagList(
span(HTML(paste(tags$span(style="font-size:14pt",
paste("Power and Sample Size Calculation",
"for Non-Proportional Hazards")))),
span(downloadButton("saveInputs", "Save inputs"),
fileInputNoExtra("loadInputs", label=NULL, accept=".rds",
buttonLabel=list(icon("upload"),
"Load inputs"),
width="116px"),
style="position:absolute;right:0.5em;",
tags$style(type='text/css', "#saveInputs{margin-top: -5px;}")
))),
windowTitle = paste("Power and Sample Size Calculation",
"for Non-Proportional Hazards")
),
sidebarLayout(
sidebarPanel(
fluidRow(
column(7, selectInput(
"kMax", "Number of stages",
choices = seq_len(6), selected = 2),
),
column(5, style = "margin-top: 25px;", actionButton(
"calc", "Calculate",
style="color: #fff; background-color: #337ab7; border-color: #2e6da4"
),
),
),
tabsetPanel(
id = "Home",
designPanel,
boundariesPanel,
settingsPanel,
),
),
mainPanel(
tabsetPanel(
id = "Results",
summaryPanel,
plotPanel,
simulationPanel,
codePanel,
),
)
)
)
# server function -------------
server <- function(input, output, session) {
session$onSessionEnded(function() {
stopApp()
})
kMax <- reactive(as.numeric(input$kMax))
observeEvent(input$kMax, {
if (input$kMax > 1) {
showTab(inputId = "Home", target = "Boundaries")
} else {
hideTab(inputId = "Home", target = "Boundaries")
}
})
observeEvent(input$target, {
shinyjs::toggleState("power",
input$target != "power")
shinyjs::toggleState("accrualDuration",
input$target != "accrualDuration")
shinyjs::toggleState("followupTime",
input$target != "followupTime")
})
observe({
shinyjs::toggleState("saveInputs", input$calc > 0)
shinyjs::toggle(paste0("xES_", kMax()),
condition = {input$asf != 'none'})
shinyjs::toggle(paste0("xFS_", kMax()),
condition = {input$bsf != 'none'})
})
# edit check for alpha
alpha <- reactive({
req(input$alpha)
valid <- (input$alpha >= 0.00001) && (input$alpha < 0.5)
shinyFeedback::feedbackWarning(
"alpha", !valid,
"alpha is out of bounds [0.00001, 0.5)")
req(valid)
as.numeric(input$alpha)
})
# edit check for power
beta <- reactive({
if (input$target != "power") {
req(input$power)
valid <- (input$power <= 0.9999) &&
(input$power > input$alpha)
shinyFeedback::feedbackWarning(
"power", !valid,
"Power is out of bounds (alpha, 0.9999]")
req(valid)
1 - as.numeric(input$power)
}
})
# edit check for accrual duration
accrualDuration <- reactive({
if (input$target != "accrualDuration") {
req(input$accrualDuration)
valid <- (input$accrualDuration > 0)
shinyFeedback::feedbackWarning(
"accrualDuration", !valid,
"Accrual duration must be positive")
req(valid)
as.numeric(input$accrualDuration)
}
})
# edit check for follow-up duration
followupTime <- reactive({
if (input$target != 'followupTime') {
req(input$followupTime)
if (input$fixedFollowup) {
valid <- (input$followupTime > 0)
shinyFeedback::feedbackWarning(
"followupTime", !valid,
"Follow-up duration must be positive for fixed follow-up")
} else {
valid <- (input$followupTime >= 0)
shinyFeedback::feedbackWarning(
"followupTime", !valid,
"Follow-up duration must be nonnegative for variable follow-up")
}
req(valid)
as.numeric(input$followupTime)
}
})
# edit check for allocation ratio
allocationRatioPlanned <- reactive({
req(input$allocationRatioPlanned)
valid <- (input$allocationRatioPlanned > 0)
shinyFeedback::feedbackWarning(
"allocationRatioPlanned", !valid,
"Allocation ratio must be positive")
req(valid)
as.numeric(input$allocationRatioPlanned)
})
# edit check for rho1
rho1 <- reactive({
req(input$rho1)
valid <- (input$rho1 >= 0)
shinyFeedback::feedbackWarning(
"rho1", !valid,
"rho1 must be nonnegative")
req(valid)
as.numeric(input$rho1)
})
# edit check for rho2
rho2 <- reactive({
req(input$rho2)
valid <- (input$rho2 >= 0)
shinyFeedback::feedbackWarning(
"rho2", !valid,
"rho2 must be nonnegative")
req(valid)
as.numeric(input$rho2)
})
# edit check for interim timing
informationRates <- eventReactive(input$calc, {
if (kMax()>1) {
d = input[[paste0("xIA_", kMax())]]
t = c(0, as.vector(d[,1], "numeric"), 1)
valid = all(diff(t) > 0)
if (!valid) {
showNotification(
paste0("Information rates must be strictly ",
"increasing and lie between 0 and 1")
)
}
req(valid)
t[-1]
} else {
1
}
})
efficacyStopping <- eventReactive(input$calc, {
if (kMax()>1) {
d = input[[paste0("xES_", kMax())]]
checked = c(d, paste0("Look ", kMax()))
t = rep(0, kMax())
for (i in 1:kMax()) {
if (paste0("Look ", i) %in% checked) t[i] = 1
}
t
} else {
1
}
})
futilityStopping <- eventReactive(input$calc, {
if (kMax()>1) {
d = input[[paste0("xFS_", kMax())]]
checked = c(d, paste0("Look ", kMax()))
t = rep(0, kMax())
for (i in 1:kMax()) {
if (paste0("Look ", i) %in% checked) t[i] = 1
}
t
} else {
1
}
})
# alpha spending
typeAlphaSpending <- reactive({
if (kMax()>1) {
input$asf
} else {
"none"
}
})
parameterAlphaSpending <- reactive({
if (kMax()>1) {
if (input$asf == "WT") {
as.numeric(input$deltaAlpha)
} else if (input$asf == "sfKD") {
as.numeric(input$rhoAlpha)
} else if (input$asf == "sfHSD") {
as.numeric(input$gammaAlpha)
} else {
NA_real_
}
} else {
NA_real_
}
})
# edit check for user-specified alpha spending
userAlphaSpending = eventReactive(input$calc, {
if (kMax() > 1) {
d = input[[paste0("xUA_", kMax())]]
t = c(0, as.vector(d[,1], "numeric"), alpha())
valid = all(diff(t) >= 0)
if (!valid) {
showNotification(
"Cumulative alpha must be non-decreasing in [0, alpha]"
)
}
req(valid)
t[-1]
} else {
alpha()
}
})
# beta-spending
typeBetaSpending <- reactive({
if (kMax()>1) {
input$bsf
} else {
"none"
}
})
parameterBetaSpending <- reactive({
if (kMax()>1) {
if (input$bsf == "sfKD") {
as.numeric(input$rhoBeta)
} else if (input$bsf == "sfHSD") {
as.numeric(input$gammaBeta)
} else {
NA_real_
}
} else {
NA_real_
}
})
# survival information
observeEvent(input$add_x, {
a = matrix(as.numeric(input$survival),
ncol=ncol(input$survival))
b = matrix(a[nrow(a),], nrow=1)
b[,1] = b[,1] + 1
c = rbind(a, b)
colnames(c) = colnames(input$survival)
updateMatrixInput(session, "survival", c)
})
observeEvent(input$del_x, {
if (nrow(input$survival) >= 2) {
a = matrix(as.numeric(input$survival),
ncol=ncol(input$survival))
b = matrix(a[-nrow(a),], ncol=ncol(a))
colnames(b) = colnames(input$survival)
updateMatrixInput(session, "survival", b)
}
})
piecewiseSurvivalTime <- reactive({
t = as.vector(input$survival[,1], "numeric")
valid = all(diff(t) > 0) && (t[1]==0)
if (!valid) {
showNotification(
"Starting time should be increasing and start at zero"
)
}
req(valid)
t
})
lambda1 <- reactive({
lam1 = as.vector(input$survival[,2], "numeric")
valid = all(lam1 >= 0)
if (!valid) {
showNotification(
"Treatment hazard rate must be non-negative")
}
req(valid)
lam1
})
lambda2 <- reactive({
lam2 = as.vector(input$survival[,3], "numeric")
valid = all(lam2 >= 0)
if (!valid) {
showNotification(
"Control hazard rate must be non-negative")
}
req(valid)
lam2
})
# edit check for dropout
gamma1 <- reactive({
gam1 = as.numeric(input$dropout[,1])
valid = (gam1 >= 0)
if (!valid) {
showNotification(
"Treatment hazard rate must be non-negative")
}
req(valid)
gam1
})
gamma2 <- reactive({
gam2 = as.numeric(input$dropout[,2])
valid = (gam2 >= 0)
if (!valid) {
showNotification(
"Control hazard rate must be non-negative")
}
req(valid)
gam2
})
# accrual information
observeEvent(input$add_y, {
a = matrix(as.numeric(input$accrual),
ncol=ncol(input$accrual))
b = matrix(a[nrow(a),], nrow=1)
b[,1] = b[,1] + 1
c = rbind(a, b)
colnames(c) = colnames(input$accrual)
updateMatrixInput(session, "accrual", c)
})
observeEvent(input$del_y, {
if (nrow(input$accrual) >= 2) {
a = matrix(as.numeric(input$accrual),
ncol=ncol(input$accrual))
b = matrix(a[-nrow(a),], ncol=ncol(a))
colnames(b) = colnames(input$accrual)
updateMatrixInput(session, "accrual", b)
}
})
accrualTime <- reactive({
t = as.vector(input$accrual[,1], "numeric")
valid = all(diff(t) > 0) && (t[1]==0)
if (!valid) {
showNotification(
"Starting time should be increasing and start at zero"
)
}
req(valid)
t
})
accrualIntensity <- reactive({
a = as.vector(input$accrual[,2], "numeric")
valid = all(a >= 0)
if (!valid) {
showNotification(
"Accrual intensity must be non-negative")
}
req(valid)
a
})
typeOfComputation <- reactive({
hr = lambda1()/lambda2()
ph = all(abs(hr - hr[1]) <= 1e-8)
ifelse(rho1() == 0 && rho2() == 0 && ph, "schoenfeld", "direct")
})
lr <- eventReactive(input$calc, {
if (input$target == "power") {
tryCatch({
l = lrpower(
kMax = kMax(),
informationRates = informationRates(),
efficacyStopping = efficacyStopping(),
futilityStopping = futilityStopping(),
alpha = alpha(),
typeAlphaSpending = typeAlphaSpending(),
parameterAlphaSpending = parameterAlphaSpending(),
userAlphaSpending = userAlphaSpending(),
typeBetaSpending = typeBetaSpending(),
parameterBetaSpending = parameterBetaSpending(),
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = accrualDuration(),
followupTime = followupTime(),
fixedFollowup = input$fixedFollowup,
rho1 = rho1(),
rho2 = rho2(),
numSubintervals = numSubintervals,
typeOfComputation = typeOfComputation())
}, error = function(e) {
shiny:::reactiveStop(conditionMessage(e))
})
updateNumericInput(
session, "power",
value = round(l$overallResults$overallReject, 3)
)
} else if (input$target == "accrualDuration") {
tryCatch({
l = lrsamplesize(
beta = beta(),
kMax = kMax(),
informationRates = informationRates(),
efficacyStopping = efficacyStopping(),
futilityStopping = futilityStopping(),
alpha = alpha(),
typeAlphaSpending = typeAlphaSpending(),
parameterAlphaSpending = parameterAlphaSpending(),
userAlphaSpending = userAlphaSpending(),
typeBetaSpending = typeBetaSpending(),
parameterBetaSpending = parameterBetaSpending(),
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = NA,
followupTime = followupTime(),
fixedFollowup = input$fixedFollowup,
rho1 = rho1(),
rho2 = rho2(),
numSubintervals = numSubintervals,
typeOfComputation = typeOfComputation(),
interval = interval,
rounding = input$rounding)
}, error = function(e) {
shiny:::reactiveStop(conditionMessage(e))
})
updateNumericInput(
session, "accrualDuration",
value = round(l$resultsUnderH1$overallResults$accrualDuration, 3)
)
} else if (input$target == "followupTime") {
tryCatch({
l = lrsamplesize(
beta = beta(),
kMax = kMax(),
informationRates = informationRates(),
efficacyStopping = efficacyStopping(),
futilityStopping = futilityStopping(),
alpha = alpha(),
typeAlphaSpending = typeAlphaSpending(),
parameterAlphaSpending = parameterAlphaSpending(),
userAlphaSpending = userAlphaSpending(),
typeBetaSpending = typeBetaSpending(),
parameterBetaSpending = parameterBetaSpending(),
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = accrualDuration(),
followupTime = NA,
fixedFollowup = input$fixedFollowup,
rho1 = rho1(),
rho2 = rho2(),
numSubintervals = numSubintervals,
typeOfComputation = typeOfComputation(),
interval = interval,
rounding = input$rounding)
}, error = function(e) {
shiny:::reactiveStop(conditionMessage(e))
})
updateNumericInput(
session, "followupTime",
value = round(l$resultsUnderH1$overallResults$followupTime, 3)
)
}
l
})
# power vs. Tf
tmin1 <- eventReactive(input$calc, {
a <- lr()$resultsUnderH1$overallResults
if (rho1() == 0 && rho2() == 0) {
criticalValues = lr()$resultsUnderH1$byStageResults$efficacyBounds
} else {
criticalValues = NA
}
if (a$fixedFollowup) {
tmin <- lrsamplesize(
beta = 0.8,
kMax = kMax(),
informationRates = informationRates(),
efficacyStopping = efficacyStopping(),
futilityStopping = futilityStopping(),
criticalValues = criticalValues,
alpha = alpha(),
typeAlphaSpending = typeAlphaSpending(),
parameterAlphaSpending = parameterAlphaSpending(),
userAlphaSpending = userAlphaSpending(),
typeBetaSpending = typeBetaSpending(),
parameterBetaSpending = parameterBetaSpending(),
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = a$accrualDuration,
followupTime = NA,
fixedFollowup = a$fixedFollowup,
rho1 = a$rho1,
rho2 = a$rho2,
numSubintervals = numSubintervals,
estimateHazardRatio = 0,
typeOfComputation = typeOfComputation(),
interval = interval,
rounding = input$rounding
)$resultsUnderH1$overallResults$followupTime
} else {
tmin = 0
}
tmin
})
powerVsTf <- eventReactive(input$calc, {
if (kMax()>1) {
a = lr()$resultsUnderH1$overallResults
if (rho1() == 0 && rho2() == 0) {
criticalValues = lr()$resultsUnderH1$byStageResults$efficacyBounds
} else {
criticalValues = NA
}
time = seq(tmin1(), a$followupTime, length.out=ntpts)
power = rep(0, ntpts)
for (i in 1:ntpts) {
power[i] <- lrpower(
kMax = kMax(),
informationRates = informationRates(),
efficacyStopping = efficacyStopping(),
futilityStopping = futilityStopping(),
criticalValues = criticalValues,
alpha = alpha(),
typeAlphaSpending = typeAlphaSpending(),
parameterAlphaSpending = parameterAlphaSpending(),
userAlphaSpending = userAlphaSpending(),
typeBetaSpending = typeBetaSpending(),
parameterBetaSpending = parameterBetaSpending(),
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = a$accrualDuration,
followupTime = time[i],
fixedFollowup = a$fixedFollowup,
rho1 = a$rho1,
rho2 = a$rho2,
numSubintervals = numSubintervals,
estimateHazardRatio = 0,
typeOfComputation = typeOfComputation()
)$overallResults$overallReject
}
data.frame(time, power)
}
})
powerVsTf2 <- eventReactive(input$calc, {
if (kMax()==1) {
a = lr()$resultsUnderH1$overallResults
time = seq(tmin1(), a$followupTime, length.out=ntpts)
power = rep(0, ntpts)
for (i in 1:ntpts) {
power[i] <- lrpower(
kMax = kMax(),
alpha = alpha(),
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = a$accrualDuration,
followupTime = time[i],
fixedFollowup = a$fixedFollowup,
rho1 = a$rho1,
rho2 = a$rho2,
numSubintervals = numSubintervals,
estimateHazardRatio = 0,
typeOfComputation = typeOfComputation()
)$overallResults$overallReject
}
data.frame(time, power)
}
})
# power vs. N
tmin2 <- eventReactive(input$calc, {
a <- lr()$resultsUnderH1$overallResults
if (rho1() == 0 && rho2() == 0) {
criticalValues = lr()$resultsUnderH1$byStageResults$efficacyBounds
} else {
criticalValues = NA
}
lrsamplesize(
beta = 0.8,
kMax = kMax(),
informationRates = informationRates(),
efficacyStopping = efficacyStopping(),
futilityStopping = futilityStopping(),
criticalValues = criticalValues,
alpha = alpha(),
typeAlphaSpending = typeAlphaSpending(),
parameterAlphaSpending = parameterAlphaSpending(),
userAlphaSpending = userAlphaSpending(),
typeBetaSpending = typeBetaSpending(),
parameterBetaSpending = parameterBetaSpending(),
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = NA,
followupTime = a$followupTime,
fixedFollowup = a$fixedFollowup,
rho1 = a$rho1,
rho2 = a$rho2,
numSubintervals = numSubintervals,
estimateHazardRatio = 0,
typeOfComputation = typeOfComputation(),
interval = interval,
rounding = input$rounding
)$resultsUnderH1$overallResults$accrualDuration
})
powerVsN <- eventReactive(input$calc, {
if (kMax()>1) {
a = lr()$resultsUnderH1$overallResults
if (rho1() == 0 && rho2() == 0) {
criticalValues = lr()$resultsUnderH1$byStageResults$efficacyBounds
} else {
criticalValues = NA
}
time = seq(tmin2(), a$accrualDuration, length.out=ntpts)
N = rep(0, ntpts)
power = rep(0, ntpts)
for (i in 1:ntpts) {
lrx <- lrpower(
kMax = kMax(),
informationRates = informationRates(),
efficacyStopping = efficacyStopping(),
futilityStopping = futilityStopping(),
criticalValues = criticalValues,
alpha = alpha(),
typeAlphaSpending = typeAlphaSpending(),
parameterAlphaSpending = parameterAlphaSpending(),
userAlphaSpending = userAlphaSpending(),
typeBetaSpending = typeBetaSpending(),
parameterBetaSpending = parameterBetaSpending(),
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = time[i],
followupTime = a$followupTime,
fixedFollowup = a$fixedFollowup,
rho1 = a$rho1,
rho2 = a$rho2,
numSubintervals = numSubintervals,
estimateHazardRatio = 0,
typeOfComputation = typeOfComputation())
N[i] = lrx$overallResults$numberOfSubjects
power[i] = lrx$overallResults$overallReject
}
data.frame(N, power)
}
})
powerVsN2 <- eventReactive(input$calc, {
if (kMax()==1) {
a = lr()$resultsUnderH1$overallResults
time = seq(tmin2(), a$accrualDuration, length.out=ntpts)
N = rep(0, ntpts)
power = rep(0, ntpts)
for (i in 1:ntpts) {
lrx <- lrpower(
kMax = kMax(),
alpha = alpha(),
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = time[i],
followupTime = a$followupTime,
fixedFollowup = a$fixedFollowup,
rho1 = a$rho1,
rho2 = a$rho2,
numSubintervals = numSubintervals,
estimateHazardRatio = 0,
typeOfComputation = typeOfComputation()
)
N[i] = lrx$overallResults$numberOfSubjects
power[i] = lrx$overallResults$overallReject
}
data.frame(N, power)
}
})
# Ts vs. N
tmin3 <- eventReactive(input$calc, {
a <- lr()$resultsUnderH1$overallResults
if (rho1() == 0 && rho2() == 0) {
criticalValues = lr()$resultsUnderH1$byStageResults$efficacyBounds
} else {
criticalValues = NA
}
lrsamplesize(
beta = 1-a$overallReject,
kMax = kMax(),
informationRates = informationRates(),
efficacyStopping = efficacyStopping(),
futilityStopping = futilityStopping(),
criticalValues = criticalValues,
alpha = alpha(),
typeAlphaSpending = typeAlphaSpending(),
parameterAlphaSpending = parameterAlphaSpending(),
userAlphaSpending = userAlphaSpending(),
typeBetaSpending = typeBetaSpending(),
parameterBetaSpending = parameterBetaSpending(),
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = NA,
followupTime = 60,
fixedFollowup = a$fixedFollowup,
rho1 = a$rho1,
rho2 = a$rho2,
numSubintervals = numSubintervals,
estimateHazardRatio = 0,
typeOfComputation = typeOfComputation(),
interval = interval,
rounding = input$rounding
)$resultsUnderH1$overallResults$accrualDuration
})
TsVsN <- eventReactive(input$calc, {
if (kMax()>1) {
a = lr()$resultsUnderH1$overallResults
time = seq(tmin3(), a$accrualDuration, length.out=ntpts)
N = rep(0, ntpts)
Ts = rep(0, ntpts)
for (i in 1:ntpts) {
if (typeOfComputation() == "schoenfeld") {
N[i] = accrual(
time = time[i],
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
accrualDuration = time[i])
Ts[i] = caltime(
nevents = a$numberOfEvents,
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = time[i],
followupTime = 1200,
fixedFollowup = a$fixedFollowup)
} else {
lrx <- lrsamplesize(
beta = 1-a$overallReject,
kMax = kMax(),
informationRates = informationRates(),
efficacyStopping = efficacyStopping(),
futilityStopping = futilityStopping(),
alpha = alpha(),
typeAlphaSpending = typeAlphaSpending(),
parameterAlphaSpending = parameterAlphaSpending(),
userAlphaSpending = userAlphaSpending(),
typeBetaSpending = typeBetaSpending(),
parameterBetaSpending = parameterBetaSpending(),
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = time[i],
followupTime = NA,
fixedFollowup = a$fixedFollowup,
rho1 = a$rho1,
rho2 = a$rho2,
numSubintervals = numSubintervals,
estimateHazardRatio = 0,
typeOfComputation = typeOfComputation(),
interval = interval,
rounding = input$rounding)$resultsUnderH1
N[i] = lrx$overallResults$numberOfSubjects
Ts[i] = lrx$overallResults$studyDuration
}
}
data.frame(N, Ts)
}
})
TsVsN2 <- eventReactive(input$calc, {
if (kMax()==1) {
a = lr()$resultsUnderH1$overallResults
time = seq(tmin3(), a$accrualDuration, length.out=ntpts)
N = rep(0, ntpts)
Ts = rep(0, ntpts)
for (i in 1:ntpts) {
if (rho1() == 0 && rho2() == 0) {
N[i] = accrual(
time = time[i],
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
accrualDuration = time[i])
Ts[i] = caltime(
nevents = a$numberOfEvents,
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = time[i],
followupTime = 1200,
fixedFollowup = a$fixedFollowup)
} else {
lrx <- lrsamplesize(
beta = 1 - a$overallReject,
kMax = kMax(),
alpha = alpha(),
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = time[i],
followupTime = NA,
fixedFollowup = a$fixedFollowup,
rho1 = a$rho1,
rho2 = a$rho2,
numSubintervals = numSubintervals,
estimateHazardRatio = 0,
typeOfComputation = typeOfComputation(),
interval = interval,
rounding = input$rounding)$resultsUnderH1
N[i] = lrx$overallResults$numberOfSubjects
Ts[i] = lrx$overallResults$studyDuration
}
}
data.frame(N, Ts)
}
})
output$design <- renderText({
if (kMax()>1) {
str1 <- paste0("Group-sequential trial with ",
kMax(), " stages")
} else {
str1 <- "Fixed design"
}
str2 <- paste0("Fleming-Harrington weight FH(",
rho1(), ", ", rho2(), ")")
if (rho1() != 0 || rho2() != 0) {
HTML(paste(tags$h4(str1), tags$h4(str2)))
} else {
HTML(paste(tags$h4(str1)))
}
})
output$text <- renderText({
a <- lr()$resultsUnderH1$overallResults
req(a$kMax == kMax())
str1 <- paste0("Results under H1 (alternative hypothesis)")
str2 <- paste0("Overall power: ",
round(a$overallReject, 3), ", ",
"overall significance level (1-sided): ",
round(a$alpha, 4))
if (kMax()>1) {
str3 <- paste0("Maximum # events: ",
round(a$numberOfEvents, 1), ", ",
"expected # events: ",
round(a$expectedNumberOfEvents, 1))
str4 <- paste0("Maximum # dropouts: ",
round(a$numberOfDropouts, 1), ", ",
"expected # dropouts: ",
round(a$expectedNumberOfDropouts, 1))
str5 <- paste0("Maximum # subjects: ",
round(a$numberOfSubjects, 1), ", ",
"expected # subjects: ",
round(a$expectedNumberOfSubjects, 1))
str6 <- paste0("Total study duration: ",
round(a$studyDuration, 1), ", ",
"expected study duration: ",
round(a$expectedStudyDuration, 1))
} else {
str3 <- paste0("Number of events: ",
round(a$numberOfEvents, 1))
str4 <- paste0("Number of dropouts: ",
round(a$numberOfDropouts, 1))
str5 <- paste0("Number of subjects: ",
round(a$numberOfSubjects, 1))
str6 <- paste0("Study duration: ",
round(a$studyDuration, 1))
}
str7 <- paste0("Accrual duration: ",
round(a$accrualDuration, 1), ", ",
"follow-up duration: ",
round(a$followupTime, 1), ", ",
"fixed follow-up: ", a$fixedFollowup)
paste(paste("<b>", str1, "</b>", "<br>"),
paste(str2, str3, str4, str5, str6, str7, sep='<br/>'))
})
output$text0 <- renderText({
a <- lr()$resultsUnderH0$overallResults
req(a$kMax == kMax())
str1 <- paste0("Results under H0 (null hypothesis)")
str2 <- paste0("Overall type I error: ",
round(a$overallReject, 3), ", ",
"overall significance level (1-sided): ",
round(a$alpha, 4))
if (kMax()>1) {
str3 <- paste0("Maximum # events: ",
round(a$numberOfEvents, 1), ", ",
"expected # events: ",
round(a$expectedNumberOfEvents, 1))
str4 <- paste0("Maximum # dropouts: ",
round(a$numberOfDropouts, 1), ", ",
"expected # dropouts: ",
round(a$expectedNumberOfDropouts, 1))
str5 <- paste0("Maximum # subjects: ",
round(a$numberOfSubjects, 1), ", ",
"expected # subjects: ",
round(a$expectedNumberOfSubjects, 1))
str6 <- paste0("Total study duration: ",
round(a$studyDuration, 1), ", ",
"expected study duration: ",
round(a$expectedStudyDuration, 1))
} else {
str3 <- paste0("Number of events: ",
round(a$numberOfEvents, 1))
str4 <- paste0("Number of dropouts: ",
round(a$numberOfDropouts, 1))
str5 <- paste0("Number of subjects: ",
round(a$numberOfSubjects, 1))
str6 <- paste0("Study duration: ",
round(a$studyDuration, 1))
}
str7 <- paste0("Accrual duration: ",
round(a$accrualDuration, 1), ", ",
"follow-up duration: ",
round(a$followupTime, 1), ", ",
"fixed follow-up: ", a$fixedFollowup)
paste(paste("<b>", str1, "</b>", "<br>"),
paste(str2, str3, str4, str5, str6, str7, sep='<br/>'))
})
output$table <- renderPrint({
a <- lr()$resultsUnderH1$overallResults
req(a$kMax == kMax())
if (kMax()>1) {
b <- lr()$resultsUnderH1$byStageResults %>%
mutate(efficacyBounds = ifelse(efficacyStopping, efficacyBounds, NA),
futilityBounds = ifelse(futilityStopping, futilityBounds, NA),
efficacyHR = ifelse(efficacyStopping, efficacyHR, NA),
futilityHR = ifelse(futilityStopping, futilityHR, NA),
efficacyP = ifelse(efficacyStopping, efficacyP, NA),
futilityP = ifelse(futilityStopping, futilityP, NA))
# only keep necessary variables
b <- b[, c("informationRates", "efficacyBounds", "futilityBounds",
"cumulativeRejection", "cumulativeFutility",
"cumulativeAlphaSpent",
"numberOfEvents", "numberOfDropouts", "numberOfSubjects",
"analysisTime", "efficacyHR", "futilityHR",
"efficacyP", "futilityP", "information", "HR")]
# format number of digits after decimal for each column
j1 <- c(7,8,9,10)
j2 <- 15
j3 <- c(1,2,3,4,5,11,12,16)
j4 <- c(6,13,14)
b[j1] <- lapply(b[j1], formatC, format = "f", digits = 1)
b[j2] <- lapply(b[j2], formatC, format = "f", digits = 2)
b[j3] <- lapply(b[j3], formatC, format = "f", digits = 3)
b[j4] <- lapply(b[j4], formatC, format = "f", digits = 4)
if (input$bsf != 'none') {
df = t(b)
rownames(df) = c("Information rate",
"Efficacy boundary (Z-scale)",
"Futility boundary (Z-scale)",
"Cumulative rejection",
"Cumulative futility",
"Cumulative alpha spent",
"Number of events",
"Number of dropouts",
"Number of subjects",
"Analysis time",
"Efficacy boundary (HR-scale)",
"Futility boundary (HR-scale)",
"Efficacy boundary (p-scale)",
"Futility boundary (p-scale)",
"Information",
"HR")
} else {
df = t(b[,c(1,2,4,6,7,8,9,10,11,13,15,16)])
rownames(df) = c("Information rate",
"Efficacy boundary (Z-scale)",
"Cumulative rejection",
"Cumulative alpha spent",
"Number of events",
"Number of dropouts",
"Number of subjects",
"Analysis time",
"Efficacy boundary (HR-scale)",
"Efficacy boundary (p-scale)",
"Information",
"HR")
}
colnames(df) <- paste("Stage", seq_len(ncol(df)), sep=" ")
print(df, quote=FALSE)
}
})
output$table0 <- renderPrint({
a <- lr()$resultsUnderH0$overallResults
req(a$kMax == kMax())
if (kMax()>1) {
b <- lr()$resultsUnderH0$byStageResults %>%
mutate(efficacyBounds = ifelse(efficacyStopping, efficacyBounds, NA),
futilityBounds = ifelse(futilityStopping, futilityBounds, NA),
efficacyP = ifelse(efficacyStopping, efficacyP, NA),
futilityP = ifelse(futilityStopping, futilityP, NA))
# only keep necessary variables
b <- b[, c("informationRates", "efficacyBounds", "futilityBounds",
"cumulativeRejection", "cumulativeFutility",
"cumulativeAlphaSpent", "numberOfEvents",
"numberOfDropouts", "numberOfSubjects", "analysisTime",
"efficacyP", "futilityP", "information")]
# format number of digits after decimal for each column
j1 <- c(7,8,9,10)
j2 <- 13
j3 <- c(1,2,3,4,5)
j4 <- c(6,11,12)
b[j1] <- lapply(b[j1], formatC, format = "f", digits = 1)
b[j2] <- lapply(b[j2], formatC, format = "f", digits = 2)
b[j3] <- lapply(b[j3], formatC, format = "f", digits = 3)
b[j4] <- lapply(b[j4], formatC, format = "f", digits = 4)
if (input$bsf != 'none') {
df = t(b[,c(4,5,7,8,9,10,13)])
rownames(df) = c("Cumulative rejection",
"Cumulative futility",
"Number of events",
"Number of dropouts",
"Number of subjects",
"Analysis time",
"Information"
)
} else {
df = t(b[,c(4,7,8,9,10,13)])
rownames(df) = c("Cumulative rejection",
"Number of events",
"Number of dropouts",
"Number of subjects",
"Analysis time",
"Information"
)
}
colnames(df) <- paste("Stage", seq_len(ncol(df)), sep=" ")
print(df, quote=FALSE)
}
})
output$plot <- renderPlotly({
a <- lr()$resultsUnderH1$overallResults
req(a$kMax == kMax())
kMax <- a$kMax
if (lr()$resultsUnderH1$settings$typeAlphaSpending == "none") {
b <- lr()$resultsUnderH1$byStageResults
b[-nrow(b), "efficacyStopping"] = FALSE
b <- b %>%
mutate(efficacyBounds = ifelse(efficacyStopping, efficacyBounds, NA),
cumulativeRejection = ifelse(efficacyStopping,
cumulativeRejection, NA),
efficacyHR = ifelse(efficacyStopping, efficacyHR, NA),
efficacyP = ifelse(efficacyStopping, efficacyP, NA))
} else {
b <- lr()$resultsUnderH1$byStageResults %>%
mutate(efficacyBounds = ifelse(efficacyStopping, efficacyBounds, NA),
efficacyHR = ifelse(efficacyStopping, efficacyHR, NA),
efficacyP = ifelse(efficacyStopping, efficacyP, NA))
}
if (lr()$resultsUnderH1$settings$typeBetaSpending == "none") {
b <- b %>%
mutate(futilityStopping = FALSE,
futilityBounds = ifelse(futilityStopping, futilityBounds, NA),
cumulativeFutility = ifelse(futilityStopping,
cumulativeFutility, NA),
futilityHR = ifelse(futilityStopping, futilityHR, NA),
futilityP = ifelse(futilityStopping, futilityP, NA))
} else {
b <- b %>%
mutate(futilityBounds = ifelse(futilityStopping, futilityBounds, NA),
futilityHR = ifelse(futilityStopping, futilityHR, NA),
futilityP = ifelse(futilityStopping, futilityP, NA))
}
if (kMax > 1) {
if (input$plottype == "boundaryZ") {
af <- b %>%
pivot_longer(cols = c("efficacyBounds", "futilityBounds"),
names_to = "type",
values_to = "bounds") %>%
mutate(type = gsub("Bounds", "", type)) %>%
filter(!is.na(bounds))
plotly::plot_ly(af, x=~numberOfEvents, y=~bounds,
type="scatter", mode="markers+lines",
linetype=~type) %>%
plotly::layout(xaxis = list(title = "Events"),
yaxis = list(title = "Boundaries (Z)"))
} else if (input$plottype == "boundaryHR") {
af <- b %>%
pivot_longer(cols = c("efficacyHR", "futilityHR"),
names_to = "type",
values_to = "bounds") %>%
mutate(type = gsub("HR", "", type)) %>%
filter(!is.na(bounds))
plotly::plot_ly(af, x=~numberOfEvents, y=~bounds,
type="scatter", mode="markers+lines",
linetype=~type) %>%
plotly::layout(xaxis = list(title = "Events"),
yaxis = list(title = "Boundaries (HR)"))
} else if (input$plottype == "boundaryP") {
af <- b %>%
pivot_longer(cols = c("efficacyP", "futilityP"),
names_to = "type",
values_to = "bounds") %>%
mutate(type = gsub("P", "", type)) %>%
filter(!is.na(bounds))
plotly::plot_ly(af, x=~numberOfEvents, y=~bounds,
type="scatter", mode="markers+lines",
linetype=~type) %>%
plotly::layout(xaxis = list(title = "Events"),
yaxis = list(title = "Boundaries (p)",
zeroline = FALSE))
} else if (input$plottype == "errorSpend") {
af <- b %>%
pivot_longer(cols = c("cumulativeAlphaSpent", "cumulativeFutility"),
names_to = "type",
values_to = "bounds") %>%
mutate(type = ifelse(type=="cumulativeAlphaSpent",
"alpha", "beta")) %>%
filter(!is.na(bounds))
plotly::plot_ly(af, x=~numberOfEvents, y=~bounds,
type="scatter", mode="markers+lines",
linetype=~type) %>%
plotly::layout(xaxis = list(title = "Events"),
yaxis = list(title = "Cumulative error spent",
zeroline = FALSE))
} else if (input$plottype == "eventPred") {
time <- seq(0, a$studyDuration, length.out=100)
df <- lrstat(time,
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = a$accrualDuration,
followupTime = a$followupTime,
fixedFollowup = a$fixedFollowup,
rho1 = a$rho1,
rho2 = a$rho2,
numSubintervals = numSubintervals,
predictTarget = 1)
af <- df %>%
pivot_longer(cols = c("subjects", "nevents"),
names_to = "type",
values_to = "n") %>%
mutate(type = ifelse(type=="subjects", "subjects", "events"))
plotly::plot_ly(af, x=~time, y=~n, linetype=~type,
type="scatter", mode="lines") %>%
plotly::layout(xaxis = list(title = "Time", zeroline = FALSE),
yaxis = list(zeroline=FALSE),
legend = list(x=0, y=1.1, orientation="h"))
} else if (input$plottype == "powerVsTf") {
plotly::plot_ly(powerVsTf(), x=~time, y=~power,
type="scatter", mode="lines") %>%
plotly::layout(
xaxis = list(title = "Follow-up duration", zeroline = FALSE),
yaxis = list(title = "Power"),
title = list(text = paste0(
"For ", round(a$numberOfSubjects), " subjects",
" enrolled over ", round(a$accrualDuration, 1),
" time units"), x = 0, xref='paper')
)
} else if (input$plottype == "powerVsN") {
plotly::plot_ly(powerVsN(), x=~N, y=~power,
type="scatter", mode="lines") %>%
plotly::layout(
xaxis = list(title = "Sample size", zeroline = FALSE),
yaxis = list(title = "Power"),
title = list(text = paste0(
"For follow-up duration of ", round(a$followupTime, 1),
" time units"), x = 0, xref='paper')
)
} else if (input$plottype == "TsVsN") {
plotly::plot_ly(TsVsN(), x=~N, y=~Ts,
type="scatter", mode="lines") %>%
plotly::layout(
xaxis = list(title = "Sample size", zeroline = FALSE),
yaxis = list(title = "Study duration"),
title = list(text = paste0(
"For power of ", round(a$overallReject, 3)),
x = 0, xref='paper')
)
}
} else {
if (input$plottype2 == "eventPred") {
time <- seq(0, a$studyDuration, length.out=100)
df <- lrstat(time,
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = a$accrualDuration,
followupTime = a$followupTime,
fixedFollowup = a$fixedFollowup,
rho1 = a$rho1,
rho2 = a$rho2,
numSubintervals = numSubintervals,
predictTarget = 1)
af <- df %>%
pivot_longer(cols = c("subjects", "nevents"),
names_to = "type",
values_to = "n") %>%
mutate(type = ifelse(type=="subjects", "subjects", "events"))
plotly::plot_ly(af, x=~time, y=~n, linetype=~type,
type="scatter", mode="lines") %>%
plotly::layout(xaxis = list(title = "Time", zeroline = FALSE),
yaxis = list(zeroline=FALSE),
legend = list(x=0, y=1.1, orientation="h"))
} else if (input$plottype2 == "powerVsTf") {
plotly::plot_ly(powerVsTf2(), x=~time, y=~power,
type="scatter", mode="lines") %>%
plotly::layout(
xaxis = list(title = "Follow-up duration", zeroline = FALSE),
yaxis = list(title = "Power"),
title = list(text = paste0(
"For ", round(a$numberOfSubjects), " subjects",
" enrolled over ", round(a$accrualDuration, 1),
" time units"), x = 0, xref='paper')
)
} else if (input$plottype2 == "powerVsN") {
plotly::plot_ly(powerVsN2(), x=~N, y=~power,
type="scatter", mode="lines") %>%
plotly::layout(
xaxis = list(title = "Sample size", zeroline = FALSE),
yaxis = list(title = "Power"),
title = list(text = paste0(
"For follow-up duration of ", round(a$followupTime, 1),
" time units"), x = 0, xref='paper')
)
} else if (input$plottype2 == "TsVsN") {
plotly::plot_ly(TsVsN2(), x=~N, y=~Ts,
type="scatter", mode="lines") %>%
plotly::layout(
xaxis = list(title = "Sample size", zeroline = FALSE),
yaxis = list(title = "Study duration"),
title = list(text = paste0(
"For power of ", round(a$overallReject, 3)),
x = 0, xref='paper')
)
}
}
})
# simulation
observe({
freezeReactiveValue(input, "boundaries")
b <- lr()$resultsUnderH1$byStageResults
b0 <- lr()$resultsUnderH0$byStageResults
kMax <- nrow(b)
updateMatrixInput(
session,
inputId = "boundaries",
value = matrix(c(round(b0$information/b0$information[kMax], 4),
round(b$numberOfEvents),
round(b$efficacyBounds, 3),
round(b$futilityBounds, 3)),
ncol = 4,
dimnames = list(paste0("Look ", seq_len(kMax)),
c("Information rates",
"Planned events",
"Efficacy boundary",
"Futility boundary"))))
})
# edit check for number of replications
nIterations <- reactive({
req(input$nIterations)
valid <- (input$nIterations >= 1)
shinyFeedback::feedbackWarning(
"nIterations", !valid,
"Number of replications must be positive integers")
req(valid)
round(as.numeric(input$nIterations))
})
# edit check for number of replications
nRawDatasets <- reactive({
req(input$nRawDatasets, input$nIterations)
valid <- (input$nRawDatasets >= 0) &&
(input$nRawDatasets <= input$nIterations)
shinyFeedback::feedbackWarning(
"nRawDatasets", !valid,
paste0("Number of raw datasets per stage must be nonnegative integers",
" and less than or equal to the number of replications"))
req(valid)
round(as.numeric(input$nRawDatasets))
})
sim <- eventReactive(input$sim, {
req(nrow(input$boundaries)==as.numeric(input$kMax))
r <- as.numeric(input$allocationRatioPlanned)
if (r!= round(r)) {
allocation <- as.vector(unlist(strsplit(attr(
fractions(r), "fracs"), "/")), "numeric")
} else {
allocation <- c(r, 1)
}
l <- lrsim(
kMax = as.numeric(input$kMax),
informationRates = as.vector(input$boundaries[,1], "numeric"),
criticalValues = as.vector(input$boundaries[,3], "numeric"),
futilityBounds = as.vector(input$boundaries[,4], "numeric"),
allocation1 = allocation[1],
allocation2 = allocation[2],
accrualTime = as.vector(input$accrual[,1], "numeric"),
accrualIntensity = as.vector(input$accrual[,2], "numeric"),
piecewiseSurvivalTime = as.vector(input$survival[,1], "numeric"),
lambda1 = as.vector(input$survival[,2], "numeric"),
lambda2 = as.vector(input$survival[,3], "numeric"),
gamma1 = as.vector(input$dropout[,1], "numeric"),
gamma2 = as.vector(input$dropout[,2], "numeric"),
accrualDuration = input$accrualDuration,
followupTime = input$followupTime,
fixedFollowup = input$fixedFollowup,
rho1 = input$rho1,
rho2 = input$rho2,
plannedEvents = as.vector(input$boundaries[,2], "numeric"),
maxNumberOfIterations = input$nIterations,
maxNumberOfRawDatasetsPerStage = input$nRawDatasets,
seed = input$seed
)
l
})
sim0 <- eventReactive(input$sim, {
req(nrow(input$boundaries)==as.numeric(input$kMax))
r <- as.numeric(input$allocationRatioPlanned)
if (r!= round(r)) {
allocation <- as.vector(unlist(strsplit(attr(
fractions(r), "fracs"), "/")), "numeric")
} else {
allocation <- c(r, 1)
}
l <- lrsim(
kMax = as.numeric(input$kMax),
informationRates = as.vector(input$boundaries[,1], "numeric"),
criticalValues = as.vector(input$boundaries[,3], "numeric"),
futilityBounds = as.vector(input$boundaries[,4], "numeric"),
allocation1 = allocation[1],
allocation2 = allocation[2],
accrualTime = as.vector(input$accrual[,1], "numeric"),
accrualIntensity = as.vector(input$accrual[,2], "numeric"),
piecewiseSurvivalTime = as.vector(input$survival[,1], "numeric"),
lambda1 = as.vector(input$survival[,3], "numeric"),
lambda2 = as.vector(input$survival[,3], "numeric"),
gamma1 = as.vector(input$dropout[,1], "numeric"),
gamma2 = as.vector(input$dropout[,2], "numeric"),
accrualDuration = input$accrualDuration,
followupTime = input$followupTime,
fixedFollowup = input$fixedFollowup,
rho1 = input$rho1,
rho2 = input$rho2,
plannedEvents = as.vector(input$boundaries[,2], "numeric"),
maxNumberOfIterations = input$nIterations,
maxNumberOfRawDatasetsPerStage = input$nRawDatasets,
seed = input$seed
)
l
})
output$simtext <- renderText({
req(nrow(input$boundaries)==sim()$overview$kMax)
a <- sim()$overview
str1 <- "Simulation results under H1"
str2 <- paste0("Overall rejection, ",
round(a$overallReject,3), ", ",
"expected # events: ",
round(a$expectedNumberOfEvents, 1), ", ",
"expected # dropouts: ",
round(a$expectedNumberOfDropouts, 1), ", ",
"# subjects: ",
round(a$expectedNumberOfSubjects, 1), ", ",
"study duration: ",
round(a$expectedStudyDuration, 1))
paste(paste("<b>", str1, "</b>"),
str2, sep = '<br/>')
})
output$simtable <- renderPrint({
req(nrow(input$boundaries)==sim()$overview$kMax)
if (kMax()>1) {
a <- sim()$overview
b <- data.frame(a$cumulativeRejection,
a$cumulativeFutility,
a$numberOfEvents,
a$numberOfDropouts,
a$numberOfSubjects,
a$analysisTime)
j1 <- c(3,4,5,6)
j3 <- c(1,2)
b[j1] <- lapply(b[j1], formatC, format = "f", digits = 1)
b[j3] <- lapply(b[j3], formatC, format = "f", digits = 3)
df = t(b)
rownames(df) = c("Cumulative rejection",
"Cumulative futility",
"Number of events",
"Number of dropouts",
"Number of subjects",
"Analysis time")
colnames(df) <- paste("Stage", seq_len(ncol(df)), sep=" ")
print(df, quote=FALSE)
}
})
output$downloadSumdata <- downloadHandler(
filename = function() {
paste0("sim-sumdata-h1-", Sys.Date(), ".csv")
},
content = function(file) {
write.csv(sim()$sumdata, file, row.names=FALSE)
}
)
output$downloadRawdata <- downloadHandler(
filename = function() {
paste0("sim-rawdata-h1-", Sys.Date(), ".csv")
},
content = function(file) {
write.csv(sim()$rawdata, file, row.names=FALSE)
}
)
output$simtext0 <- renderText({
req(nrow(input$boundaries)==sim0()$overview$kMax)
a <- sim0()$overview
str1 <- "Simulation results under H0"
str2 <- paste0("Overall rejection: ",
round(a$overallReject,3), ", ",
"expected # events: ",
round(a$expectedNumberOfEvents), ", ",
"expected # dropouts: ",
round(a$expectedNumberOfDropouts, 1), ", ",
"# subjects: ",
round(a$expectedNumberOfSubjects), ", ",
"study duration: ",
round(a$expectedStudyDuration, 1))
paste(paste("<b>", str1, "</b>"),
str2, sep = '<br/>')
})
output$simtable0 <- renderPrint({
req(nrow(input$boundaries)==sim0()$overview$kMax)
if (kMax()>1) {
a <- sim0()$overview
b <- data.frame(a$cumulativeRejection,
a$cumulativeFutility,
a$numberOfEvents,
a$numberOfDropouts,
a$numberOfSubjects,
a$analysisTime)
j1 <- c(3,4,5,6)
j3 <- c(1,2)
b[j1] <- lapply(b[j1], formatC, format = "f", digits = 1)
b[j3] <- lapply(b[j3], formatC, format = "f", digits = 3)
df = t(b)
rownames(df) = c("Cumulative rejection",
"Cumulative futility",
"Number of events",
"Number of dropouts",
"Number of subjects",
"Analysis time")
colnames(df) <- paste("Stage", seq_len(ncol(df)), sep=" ")
print(df, quote=FALSE)
}
})
output$downloadSumdata0 <- downloadHandler(
filename = function() {
paste0("sim-sumdata-h0-", Sys.Date(), ".csv")
},
content = function(file) {
write.csv(sim0()$sumdata, file, row.names=FALSE)
}
)
output$downloadRawdata0 <- downloadHandler(
filename = function() {
paste0("sim-rawdata-h0-", Sys.Date(), ".csv")
},
content = function(file) {
write.csv(sim0()$rawdata, file, row.names=FALSE)
}
)
output$lrp <- renderText({
a <- lr()$resultsUnderH1$overallResults
req(a$kMax == kMax())
b <- lr()$resultsUnderH1$byStageResults
s <- lr()$resultsUnderH1$settings
str2 <- paste0("kMax = ", a$kMax, ",")
if (a$kMax > 1) {
str3 <- paste0("informationRates = c(",
paste(b$informationRates, collapse=", "), "),")
if (s$typeAlphaSpending != "none") {
str3 <- paste(str3,
paste0("efficacyStopping = c(",
paste(as.vector(b$efficacyStopping, "numeric"),
collapse=", "), "),"), sep="<br/>")
}
if (s$typeBetaSpending != "none") {
str3 <- paste(str3,
paste0("futilityStopping = c(",
paste(as.vector(b$futilityStopping, "numeric"),
collapse=", "), "),"), sep="<br/>")
}
str7 <- paste0("typeAlphaSpending = '", s$typeAlphaSpending, "',")
if (s$typeAlphaSpending %in% c("WT", "sfKD", "sfHSD")) {
str7 <- paste(str7, paste0("parameterAlphaSpending = ",
s$parameterAlphaSpending, ","), sep="<br/>")
}
if (s$typeAlphaSpending == "user") {
str7 <- paste(str7, paste0("userAlphaSpending = c(",
paste(s$userAlphaSpending, collapse=", "),
","), sep="<br/>")
}
str8 <- paste0("typeBetaSpending = '", s$typeBetaSpending, "',")
if (s$typeBetaSpending %in% c("sfKD", "sfHSD")) {
str8 <- paste(str8, paste0("parameterBetaSpending = ",
s$parameterBetaSpending, ","), sep="<br/>")
}
}
str6 <- paste0("alpha = ", round(a$alpha, 5), ",")
str9 <- paste0("allocationRatioPlanned = ", a$allocationRatioPlanned, ",")
if (length(s$accrualTime) == 1) {
str10 <- paste0("accrualTime = ", s$accrualTime, ",")
str10 <- paste(str10, paste0("accrualIntensity = ",
s$accrualIntensity, ","), sep="<br/>")
} else {
str10 <- paste0("accrualTime = c(",
paste(s$accrualTime, collapse=", "), "),")
str10 <- paste(str10, paste0("accrualIntensity = c(",
paste(s$accrualIntensity, collapse=", "),
"),"), sep="<br/>")
}
if (length(s$piecewiseSurvivalTime) == 1) {
str11 <- paste0("piecewiseSurvivalTime = ", s$piecewiseSurvivalTime, ",")
str11 <- paste(str11, paste0("lambda1 = ", s$lambda1, ","), sep="<br/>")
str11 <- paste(str11, paste0("lambda2 = ", s$lambda2, ","), sep="<br/>")
} else {
str11 <- paste0("piecewiseSurvivalTime = c(",
paste(s$piecewiseSurvivalTime, collapse=", "), "),")
str11 <- paste(str11, paste0("lambda1 = c(",
paste(s$lambda1, collapse=", "),
"),"), sep="<br/>")
str11 <- paste(str11, paste0("lambda2 = c(",
paste(s$lambda2, collapse=", "),
"),"), sep="<br/>")
}
str12 <- paste0("gamma1 = ", s$gamma1, ",")
str12 <- paste(str12, paste0("gamma2 = ", s$gamma2, ","), sep="<br/>")
str15 <- paste0("fixedFollowup = ", input$fixedFollowup, ",")
str16 <- paste0("rho1 = ", a$rho1, ",")
str16 <- paste(str16, paste0("rho2 = ", a$rho2, ","), sep="<br/>")
if (input$target == 'power') {
str1 <- paste0("(lr <- lrpower(")
str13 <- paste0("accrualDuration = ", a$accrualDuration, ",")
str14 <- paste0("followupTime = ", a$followupTime, ",")
str17 <- paste0("numSubintervals = ", numSubintervals, ",")
str17 <- paste(str17, paste0(
"typeOfComputation = '", typeOfComputation(), "'))"), sep="<br/>")
if (a$kMax == 1) {
paste(str1, str2, str6, str9, str10,
str11, str12, str13, str14, str15, str16, str17, sep = '<br/>')
} else {
paste(str1, str2, str3, str6, str7, str8, str9, str10,
str11, str12, str13, str14, str15, str16, str17, sep = '<br/>')
}
} else if (input$target == 'accrualDuration') {
str0 <- paste0("(lr <- lrsamplesize(")
str1 <- paste0("beta = ", round(1-a$overallReject, 4), ",")
str13 <- paste0("accrualDuration = NA,")
str14 <- paste0("followupTime = ", a$followupTime, ",")
str17 <- paste0("numSubintervals = ", numSubintervals, ",")
str17 <- paste(str17, paste0(
"typeOfComputation = '", typeOfComputation(), "',"), sep="<br/>")
str18 <- paste0("interval = c(", paste(interval, collapse=", "), ")))")
if (a$kMax == 1) {
paste(str0, str1, str2, str6, str9, str10,
str11, str12, str13, str14, str15, str16, str17,
str18, sep = '<br/>')
} else {
paste(str0, str1, str2, str3, str6, str7, str8, str9, str10,
str11, str12, str13, str14, str15, str16, str17,
str18, sep = '<br/>')
}
} else if (input$target == 'followupTime') {
str0 <- paste0("(lr <- lrsamplesize(")
str1 <- paste0("beta = ", round(1-a$overallReject, 4), ",")
str13 <- paste0("accrualDuration = ", a$accrualDuration, ",")
str14 <- paste0("followupTime = NA,")
str17 <- paste0("numSubintervals = ", numSubintervals, ",")
str17 <- paste(str17, paste0(
"typeOfComputation = '", typeOfComputation(), "',"), sep="<br/>")
str18 <- paste0("interval = c(", paste(interval, collapse=", "), ")),")
str19 <- paste("rounding = ", input$rounding, "))")
if (a$kMax == 1) {
paste(str0, str1, str2, str6, str9, str10,
str11, str12, str13, str14, str15, str16, str17,
str18, str19, sep = '<br/>')
} else {
paste(str0, str1, str2, str3, str6, str7, str8, str9, str10,
str11, str12, str13, str14, str15, str16, str17,
str18, str19, sep = '<br/>')
}
}
})
output$lrs <- renderText({
a <- lr()$resultsUnderH1$overallResults
req(a$kMax == kMax())
s <- lr()$resultsUnderH1$settings
str1 <- paste0("(sim <- lrsim(")
str2 <- paste0("kMax = ", a$kMax, ",")
if (a$kMax > 1) {
str3 <- paste0("informationRates = c(",
paste(as.vector(input$boundaries[,1], "numeric"),
collapse=", "), "),")
str4 <- paste0("criticalValues = c(",
paste(as.vector(input$boundaries[,3], "numeric"),
collapse=", "), "),")
str5 <- paste0("futilityBounds = c(",
paste(as.vector(input$boundaries[,4], "numeric"),
collapse=", "), "),")
} else {
str4 <- paste0("criticalValues = ", input$boundaries[,3], ",")
}
r <- lr()$resultsUnderH1$settings$allocationRatioPlanned
if (r!= round(r)) {
allocation <- as.vector(unlist(strsplit(attr(
fractions(r), "fracs"), "/")), "numeric")
} else {
allocation <- c(r, 1)
}
str6 <- paste0("allocation1 = ", allocation[1], ",")
str6 <- paste(str6, paste0("allocation2 = ",
allocation[2], ","), sep='<br/>')
if (length(s$accrualTime) == 1) {
str7 <- paste0("accrualTime = ", s$accrualTime, ",")
str7 <- paste(str7, paste0("accrualIntensity = ",
s$accrualIntensity, ","), sep="<br/>")
} else {
str7 <- paste0("accrualTime = c(", paste(s$accrualTime,
collapse=", "), "),")
str7 <- paste(str7, paste0("accrualIntensity = c(",
paste(s$accrualIntensity, collapse=", "),
"),"), sep="<br/>")
}
if (length(s$piecewiseSurvivalTime) == 1) {
str8 <- paste0("piecewiseSurvivalTime = ", s$piecewiseSurvivalTime, ",")
str8 <- paste(str8, paste0("lambda1 = ", s$lambda1, ","), sep="<br/>")
str8 <- paste(str8, paste0("lambda2 = ", s$lambda2, ","), sep="<br/>")
} else {
str8 <- paste0("piecewiseSurvivalTime = c(",
paste(s$piecewiseSurvivalTime, collapse=", "), "),")
str8 <- paste(str8, paste0("lambda1 = c(",
paste(s$lambda1, collapse=", "),
"),"), sep="<br/>")
str8 <- paste(str8, paste0("lambda2 = c(",
paste(s$lambda2, collapse=", "),
"),"), sep="<br/>")
}
str9 <- paste0("gamma1 = ", s$gamma1, ",")
str9 <- paste(str9, paste0("gamma2 = ", s$gamma2, ","), sep="<br/>")
str10 <- paste0("accrualDuration = ", round(a$accrualDuration, 2), ",")
str11 <- paste0("followupTime = ", round(a$followupTime, 2), ",")
str12 <- paste0("fixedFollowup = ", a$fixedFollowup, ",")
str13 <- paste0("rho1 = ", a$rho1, ",")
str13 <- paste(str13, paste0("rho2 = ", a$rho2, ","), sep="<br/>")
if (a$kMax == 1) {
str14 <- paste("plannedEvents = ", input$bounardies[,2], ",")
} else {
str14 <- paste0("plannedEvents = c(",
paste(as.vector(input$boundaries[,2], "numeric"),
collapse=", "), "),")
}
str15 <- paste0("maxNumberOfIterations = ", input$nIterations, ",")
str16 <- paste0("maxNumberOfRawDatasetsPerStage = ",
input$nRawDatasets, ",")
str17 <- paste0("seed = ", input$seed, "))")
if (a$kMax == 1) {
paste(str1, str2, str4, str6, str7, str8, str9, str10,
str11, str12, str13, str14, str15, str16, str17, sep = '<br/>')
} else {
paste(str1, str2, str3, str4, str5, str6, str7, str8, str9, str10,
str11, str12, str13, str14, str15, str16, str17, sep = '<br/>')
}
})
# save inputs
output$saveInputs <- downloadHandler(
filename = function() {
paste0("inputs-", Sys.Date(), ".rds")
},
content = function(file) {
x <- list(
kMax = kMax(),
target = input$target,
alpha = alpha(),
power = 1-beta(),
accrualDuration = accrualDuration(),
followupTime = followupTime(),
allocationRatioPlanned = allocationRatioPlanned(),
fixedFollowup = input$fixedFollowup,
rho1 = rho1(),
rho2 = rho2(),
rounding = input$rounding,
xIA = matrix(informationRates(), ncol=1,
dimnames = list(paste0("Look ", seq_len(kMax())),
c("Information rate"))
),
xES = efficacyStopping(),
xFS = futilityStopping(),
xUA = matrix(userAlphaSpending(), ncol=1,
dimnames = list(paste0("Look ", seq_len(kMax())),
c("Cumulative alpha"))
),
asf = typeAlphaSpending(),
deltaAlpha = input$deltaAlpha,
rhoAlpha = input$rhoAlpha,
gammaAlpha = input$gammaAlpha,
bsf = typeBetaSpending(),
rhoBeta = input$rhoBeta,
gammaBeta = input$gammaBeta,
survival = matrix(as.numeric(input$survival),
ncol=ncol(input$survival),
dimnames = list(
NULL, c("Starting time",
"Treatment hazard rate",
"Control hazard rate"))
),
accrual = matrix(as.numeric(input$accrual),
ncol=ncol(input$accrual),
dimnames = list(
NULL, c("Starting time",
"Accrual intensity"))
),
dropout = matrix(as.numeric(input$dropout),
ncol=ncol(input$dropout),
dimnames = list(
NULL, c("Treatment hazard rate",
"Control hazard rate"))
),
plottype = input$plottype,
plottype2 = input$plottype2,
boundaries = matrix(
as.numeric(input$boundaries),
ncol=ncol(input$boundaries),
dimnames = list(paste0("Look ", seq_len(kMax())),
c("Information rates",
"Planned events",
"Efficacy boundary",
"Futility boundary"))),
nIterations = nIterations(),
nRawDatasets = nRawDatasets(),
seed = input$seed
)
save(x, file = file)
}
)
# load inputs
observeEvent(input$loadInputs, {
file <- input$loadInputs
ext <- tools::file_ext(file$datapath)
req(file)
valid <- (ext == "rds")
if (!valid) showNotification("Please upload an rds file")
req(valid)
load(file=file$datapath)
updateSelectInput(session, "kMax", selected=x$kMax)
updateRadioButtons(session, "target", selected=x$target)
updateNumericInput(session, "alpha", value=x$alpha)
if (x$target != "power") {
updateNumericInput(session, "power", value=x$power)
}
if (x$target != "accrualDuration") {
updateNumericInput(session, "accrualDuration", value=x$accrualDuration)
}
if (x$target != "followupTime") {
updateNumericInput(session, "followupTime", value=x$followupTime)
}
updateNumericInput(session, "allocationRatioPlanned",
value=x$allocationRatioPlanned)
updateCheckboxInput(session, "fixedFollowup", value=x$fixedFollowup)
updateNumericInput(session, "rho1", value=x$rho1)
updateNumericInput(session, "rho2", value=x$rho2)
updateCheckboxInput(session, "rounding", value=x$rounding)
if (x$kMax > 1) {
updateMatrixInput(
session, paste0("xIA_", x$kMax),
value=matrix(x$xIA[-x$kMax,], ncol = 1,
dimnames = list(paste0("Look ", seq_len(x$kMax-1)),
c("Information rate"))))
updateCheckboxGroupInput(
session, paste0("xES_", x$kMax),
selected=paste0("Look ", which(x$xES[-x$kMax]==1)))
updateCheckboxGroupInput(
session, paste0("xFS_", x$kMax),
selected=paste0("Look ", which(x$xFS[-x$kMax]==1)))
}
if (x$kMax >1 && x$asf=="user") {
updateMatrixInput(
session, paste0("xUA_", x$kMax),
value=matrix(x$xUA[-x$kMax,], ncol=1,
dimnames = list(paste0("Look ", seq_len(x$kMax-1)),
c("Cumulative alpha"))))
}
updateSelectInput(session, "asf", selected=x$asf)
updateNumericInput(session, "deltaAlpha", value=x$deltaAlpha)
updateNumericInput(session, "gammaAlpha", value=x$gammaAlpha)
updateSelectInput(session, "bsf", selected=x$bsf)
updateNumericInput(session, "deltaBeta", value=x$deltaBeta)
updateNumericInput(session, "gammaBeta", value=x$gammaBeta)
updateMatrixInput(session, "survival", value=x$survival)
updateMatrixInput(session, "accrual", value=x$accrual)
updateMatrixInput(session, "dropout", value=x$dropout)
updateSelectInput(session, "plottype", selected=x$plottype)
updateSelectInput(session, "plottype2", selected=x$plottype2)
updateMatrixInput(session, "boundaries", value=x$boundaries)
updateNumericInput(session, "nIterations", value=x$nIterations)
updateNumericInput(session, "nRawDatasets", value=x$nRawDatasets)
updateNumericInput(session, "seed", value=x$seed)
})
}
# Run the application
shinyApp(ui = ui, server = server)
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library(shiny)
library(shinyMatrix)
library(shinyFeedback)
library(shinyjs)
library(dplyr)
library(tidyr)
library(prompter)
library(plotly)
library(lrstat)
# popover texts
followupTimeText = "Follow-up time for the last enrolled subject"
rho1Text = "First parameter of Fleming-Harrington weight"
rho2Text = "Second parameter of Fleming-Harrington weight"
informationRatesText = "Information rates in terms of event fractions"
informationRatesText = gsub(
"\\s+", " ", "Information rates in terms of variance of
logrank score statistic under the null hypothesis")
# palette for color-blinded
cbbPalette <- c("#000000", "#E69F00", "#56B4E9", "#009E73",
"#F0E442", "#0072B2", "#D55E00", "#CC79A7")
# number of time points for power curves
ntpts = 11
# Number of subintervals for approximating the numerator and denominator
# of the log-rank test statistic
numSubintervals = 300
# Bracket interval for root finding when the calculation target is
# accrual or follow-up duration
interval = c(0.001, 120)
# reduced style fileInput
fileInputNoExtra<-function(inputId, label, multiple = FALSE, accept = NULL,
width = NULL, buttonLabel = "Browse...",
placeholder = "No file selected"){
restoredValue <- restoreInput(id = inputId, default = NULL)
if (!is.null(restoredValue) && !is.data.frame(restoredValue)) {
warning("Restored value for ", inputId, " has incorrect format.")
restoredValue <- NULL
}
if (!is.null(restoredValue)) {
restoredValue <- toJSON(restoredValue, strict_atomic = FALSE)
}
inputTag <- tags$input(id = inputId, name = inputId, type = "file",
style = "display: none;",
`data-restore` = restoredValue)
if (multiple)
inputTag$attribs$multiple <- "multiple"
if (length(accept) > 0)
inputTag$attribs$accept <- paste(accept, collapse = ",")
tags$label(
class = "input-group-btn",
type="button",
style=if (!is.null(width))
paste0("width: ", validateCssUnit(width),";",
"padding-right: 5px; padding-bottom: 0px; display:inline-block;"),
span(class = "btn btn-default btn-file",type="button",
buttonLabel, inputTag,
style=if (!is.null(width))
paste0("width: ", validateCssUnit(width),";",
"border-radius: 4px; padding-bottom:5px;"))
)
}
# conditional panels for interim timing
f <- function(i) {
conditionalPanel(
condition = paste0("input.kMax == ", i),
shinyMatrix::matrixInput(
paste0("xIA_",i),
label = tags$span(
"Timing of interim analyses",
tags$span(icon(name = "question-circle")) %>%
add_prompt(message = informationRatesText, position = "right")
),
value = matrix(seq_len(i-1)/i,
ncol = 1,
dimnames = list(paste0("Look ", seq_len(i-1)),
"Information rate")),
inputClass = "numeric",
rows = list(names=TRUE, extend=FALSE),
cols = list(names=TRUE, extend=FALSE)),
fluidRow(
column(6, checkboxGroupInput(
paste0("xES_",i),
label = "Stop for efficacy",
choices = paste0("Look ", seq_len(i-1)),
selected = paste0("Look ", seq_len(i-1)))),
column(6, checkboxGroupInput(
paste0("xFS_",i),
label = "Stop for futility",
choices = paste0("Look ", seq_len(i-1)),
selected = paste0("Look ", seq_len(i-1)))),
),
)
}
# initial values for user-specified alpha spending
g <- function(i) {
conditionalPanel(
condition = paste0("input.kMax == ", i),
shinyMatrix::matrixInput(
paste0("xUA_",i),
value = matrix(0.0125*(1-exp(4*seq_len(i-1)/i))/(1-exp(4)),
ncol = 1,
dimnames = list(paste0("Look ", seq_len(i-1)),
c("Cumulative alpha"))),
inputClass = "numeric",
rows = list(names=TRUE, extend=FALSE),
cols = list(names=TRUE, extend=FALSE)
)
)
}
# design panel -------------------
designPanel <- tabPanel(
"Design",
radioButtons(
"target",
"Calculation target",
choices = c("Power" = "power",
"Accrual duration" = "accrualDuration",
"Follow-up duration" = "followupTime"),
selected = "accrualDuration",
inline = TRUE
),
fluidRow(
column(6, numericInput(
"alpha",
label = tags$span(
"alpha",
tags$span(icon(name = "question-circle")) %>%
add_prompt(message = "1-sided significance level",
position = "right")),
value = 0.025,
min = 0.0001, max = 0.4999, step = 0.0001)
),
column(6, numericInput(
"power",
"Power",
value = 0.9,
min = 0.001, max = 0.999, step = 0.001)
),
),
fluidRow(
column(6, numericInput(
"accrualDuration",
"Accrual duration",
value = 11.643,
min = 0.01, max = 120, step = 0.001)
),
column(6, numericInput(
"followupTime",
label = tags$span(
"Follow-up duration",
tags$span(icon(name = "question-circle")) %>%
add_prompt(message = followupTimeText, position = "right")
),
value = 18,
min = 0.01, max = 120, step = 0.001)
),
),
fluidRow(
column(6, numericInput(
"allocationRatioPlanned",
"Allocation ratio",
value=1, min=0.1, max=10, step=0.01),
),
column(6, checkboxInput(
"fixedFollowup",
"Fixed follow-up", value=FALSE)
),
),
fluidRow(
column(6, numericInput(
"rho1",
label = tags$span(
"rho1",
tags$span(icon(name = "question-circle")) %>%
add_prompt(message = rho1Text, position = "right")
),
value = 0,
min = 0, max = 2, step = 0.01)
),
column(6, numericInput(
"rho2",
label = tags$span(
"rho2",
tags$span(icon(name = "question-circle")) %>%
add_prompt(message = rho2Text, position = "right")
),
value = 0,
min = 0, max = 2, step = 0.01)
),
),
checkboxInput(
"rounding",
"Rounding up sample size and events", value=TRUE)
)
# test boundaries panel ----------------
boundariesPanel <- tabPanel(
"Boundaries",
lapply(2:6, f),
selectInput(
"asf", "Alpha spending",
choices = c(
"O'Brien-Fleming boundaries" = "OF",
"Pocock boundaries" = "P",
"Wang & Tsiatis boundaries" = "WT",
"O'Brien-Fleming type spending" = "sfOF",
"Pocock type spending" = "sfP",
"Kim & DeMets spending" = "sfKD",
"Hwang, Shi & DeCani spending" = "sfHSD",
"User defined spending" = "user",
"No early efficacy stopping" = "none"
),
selected = "sfOF"
),
conditionalPanel(
condition = "input.asf == 'WT'",
sliderInput(
"deltaAlpha",
"Delta for Wang & Tsiatis efficacy boundaries",
min=-0.3, max=0.5, value=0.25, step=0.01)
),
conditionalPanel(
condition = "input.asf == 'sfKD'",
sliderInput(
"rhoAlpha",
"rho for Kim & DeMets alpha spending",
min=0.4, max=8, value=1, step=0.01)
),
conditionalPanel(
condition = "input.asf == 'sfHSD'",
sliderInput(
"gammaAlpha",
"gamma for Hwang, Shi & DeCani alpha spending",
min=-10, max=5, value=1, step=0.01)
),
conditionalPanel(
condition = "input.asf == 'user'",
lapply(2:6, g),
),
selectInput(
"bsf", "Beta spending",
choices = c(
"O'Brien-Fleming type spending" = "sfOF",
"Pocock type spending" = "sfP",
"Kim & DeMets spending" = "sfKD",
"Hwang, Shi & DeCani spending" = "sfHSD",
"No early futility stopping" = "none"
),
selected = "none"
),
conditionalPanel(
condition = "input.bsf == 'sfKD'",
sliderInput(
"rhoBeta",
"rho for Kim & DeMets beta spending",
min=0.4, max=8, value=1, step=0.01)
),
conditionalPanel(
condition = "input.bsf == 'sfHSD'",
sliderInput(
"gammaBeta",
"gamma for Hwang, Shi & DeCani beta spending",
min=-10, max=5, value=1, step=0.01)
),
)
# settings panel -------------------
settingsPanel <- tabPanel(
"Settings",
shinyMatrix::matrixInput(
"survival",
"Piecewise exponential survival",
value = matrix(c(0, 0.0309, 0.0533),
nrow = 1,
dimnames = list(
NULL, c("Starting time",
"Treatment hazard rate",
"Control hazard rate"))
),
inputClass = "numeric",
rows = list(names=FALSE, extend=FALSE),
cols = list(names=TRUE, extend=FALSE)
),
actionButton("add_x", label=NULL, icon=icon("plus") ),
actionButton("del_x", label=NULL, icon=icon("minus")),
shinyMatrix::matrixInput(
"accrual",
"Piecewise constant accrual",
value = matrix(c(0, 20),
nrow=1,
dimnames = list(
NULL, c("Starting time",
"Accrual intensity"))
),
inputClass = "numeric",
rows = list(names=FALSE, extend=FALSE),
cols = list(names=TRUE, extend=FALSE)
),
actionButton("add_y", label=NULL, icon=icon("plus") ),
actionButton("del_y", label=NULL, icon=icon("minus")),
shinyMatrix::matrixInput(
"dropout",
"Exponential dropout",
value = matrix(c(0, 0),
nrow = 1,
dimnames = list(
NULL, c("Treatment hazard rate",
"Control hazard rate"))
),
inputClass = "numeric",
rows = list(names=FALSE, extend=FALSE),
cols = list(names=TRUE, extend=FALSE)
),
)
# summary panel -------------------
summaryPanel <- tabPanel(
"Summary",
htmlOutput("design"),
htmlOutput("text"),
conditionalPanel(
condition = "input.kMax > 1",
verbatimTextOutput("table"),
),
htmlOutput("text0"),
conditionalPanel(
condition = "input.kMax > 1",
verbatimTextOutput("table0"),
),
)
# plot panel -------------------
plotPanel <- tabPanel(
"Plot",
conditionalPanel(
condition = "input.kMax > 1",
selectInput(
"plottype",
"Plot type",
choices = c("Boundaries (Z)" = "boundaryZ",
"Boundaries (HR)" = "boundaryHR",
"Boundaries (p)" = "boundaryP",
"Error Spending" = "errorSpend",
"Sample Size / Events vs. Time" = "eventPred",
"Power vs. Follow-up Duration" = "powerVsTf",
"Power vs. Sample Size" = "powerVsN",
"Study Duration vs. Sample Size" = "TsVsN"),
selected = "boundaryZ"
),
),
conditionalPanel(
condition = "input.kMax == 1",
selectInput(
"plottype2",
"Plot type",
choices = c("Sample Size / Events vs. Time" = "eventPred",
"Power vs. Follow-up Duration" = "powerVsTf",
"Power vs. Sample Size" = "powerVsN",
"Study Duration vs. Sample Size" = "TsVsN"),
selected = "boundaryZ"
),
),
plotlyOutput("plot"),
)
# simulation panel -------------------
simulationPanel <- tabPanel(
"Simulation",
shinyMatrix::matrixInput(
"boundaries",
label = tags$span(
"Analysis timing and boundaries",
tags$span(icon(name = "question-circle")) %>%
add_prompt(message = informationRatesText, position = "right")
),
value = matrix(),
inputClass = "numeric",
rows = list(names = TRUE, extend = FALSE),
cols = list(names = TRUE, extend = FALSE)
),
fluidRow(
column(3, numericInput(
"nIterations",
label = "# simulations",
value = 1000,
min = 200, max = 10000, step = 1)
),
column(3, numericInput(
"nRawDatasets",
label = tags$span(
"Raw datasets",
tags$span(icon(name = "question-circle")) %>%
add_prompt(message = "# raw datasets to extract per stage",
position = "right")),
value = 1,
min = 0, max = 100, step = 1)
),
column(3, numericInput(
"seed",
label = "Seed",
value = 100,
min = 0, max = 100000, step = 1
)),
column(3, style = "margin-top: 25px;", actionButton(
"sim", "Simulate",
style="color: #fff; background-color: #337ab7; border-color: #2e6da4"
)),
),
htmlOutput("simtext"),
conditionalPanel(
condition = "input.kMax > 1",
verbatimTextOutput("simtable"),
),
conditionalPanel(
condition = "input.sim > 0",
fluidRow(
column(6, downloadButton(
"downloadSumdata", "Download summary data under H1")),
conditionalPanel(
condition = "input.nRawDatasets > 0",
column(6, downloadButton(
"downloadRawdata", "Download raw data under H1")),
),
),
),
htmlOutput("simtext0"),
conditionalPanel(
condition = "input.kMax > 1",
verbatimTextOutput("simtable0"),
),
conditionalPanel(
condition = "input.sim > 0",
fluidRow(
column(6, downloadButton(
"downloadSumdata0", "Download summary data under H0")),
conditionalPanel(
condition = "input.nRawDatasets > 0",
column(6, downloadButton(
"downloadRawdata0", "Download raw data under H0")),
),
),
),
)
# code panel -------------------
codePanel <- tabPanel(
"Code",
helpText('library(lrstat)'),
fluidRow(
column(6, htmlOutput("lrp")),
column(6, htmlOutput("lrs")),
),
)
# user interface ----------------
ui <- fluidPage(
shinyFeedback::useShinyFeedback(),
shinyjs::useShinyjs(),
prompter::use_prompt(),
titlePanel(tagList(
span(HTML(paste(tags$span(style="font-size:14pt",
paste("Power and Sample Size Calculation",
"for Non-Proportional Hazards")))),
span(downloadButton("saveInputs", "Save inputs"),
fileInputNoExtra("loadInputs", label=NULL, accept=".rds",
buttonLabel=list(icon("upload"),
"Load inputs"),
width="116px"),
style="position:absolute;right:0.5em;",
tags$style(type='text/css', "#saveInputs{margin-top: -5px;}")
))),
windowTitle = paste("Power and Sample Size Calculation",
"for Non-Proportional Hazards")
),
sidebarLayout(
sidebarPanel(
fluidRow(
column(7, selectInput(
"kMax", "Number of stages",
choices = seq_len(6), selected = 2),
),
column(5, style = "margin-top: 25px;", actionButton(
"calc", "Calculate",
style="color: #fff; background-color: #337ab7; border-color: #2e6da4"
),
),
),
tabsetPanel(
id = "Home",
designPanel,
boundariesPanel,
settingsPanel,
),
),
mainPanel(
tabsetPanel(
id = "Results",
summaryPanel,
plotPanel,
simulationPanel,
codePanel,
),
)
)
)
# server function -------------
server <- function(input, output, session) {
session$onSessionEnded(function() {
stopApp()
})
kMax <- reactive(as.numeric(input$kMax))
observeEvent(input$kMax, {
if (input$kMax > 1) {
showTab(inputId = "Home", target = "Boundaries")
} else {
hideTab(inputId = "Home", target = "Boundaries")
}
})
observeEvent(input$target, {
shinyjs::toggleState("power",
input$target != "power")
shinyjs::toggleState("accrualDuration",
input$target != "accrualDuration")
shinyjs::toggleState("followupTime",
input$target != "followupTime")
})
observe({
shinyjs::toggleState("saveInputs", input$calc > 0)
shinyjs::toggle(paste0("xES_", kMax()),
condition = {input$asf != 'none'})
shinyjs::toggle(paste0("xFS_", kMax()),
condition = {input$bsf != 'none'})
})
# edit check for alpha
alpha <- reactive({
req(input$alpha)
valid <- (input$alpha >= 0.00001) && (input$alpha < 0.5)
shinyFeedback::feedbackWarning(
"alpha", !valid,
"alpha is out of bounds [0.00001, 0.5)")
req(valid)
as.numeric(input$alpha)
})
# edit check for power
beta <- reactive({
if (input$target != "power") {
req(input$power)
valid <- (input$power <= 0.9999) &&
(input$power > input$alpha)
shinyFeedback::feedbackWarning(
"power", !valid,
"Power is out of bounds (alpha, 0.9999]")
req(valid)
1 - as.numeric(input$power)
}
})
# edit check for accrual duration
accrualDuration <- reactive({
if (input$target != "accrualDuration") {
req(input$accrualDuration)
valid <- (input$accrualDuration > 0)
shinyFeedback::feedbackWarning(
"accrualDuration", !valid,
"Accrual duration must be positive")
req(valid)
as.numeric(input$accrualDuration)
}
})
# edit check for follow-up duration
followupTime <- reactive({
if (input$target != 'followupTime') {
req(input$followupTime)
if (input$fixedFollowup) {
valid <- (input$followupTime > 0)
shinyFeedback::feedbackWarning(
"followupTime", !valid,
"Follow-up duration must be positive for fixed follow-up")
} else {
valid <- (input$followupTime >= 0)
shinyFeedback::feedbackWarning(
"followupTime", !valid,
"Follow-up duration must be nonnegative for variable follow-up")
}
req(valid)
as.numeric(input$followupTime)
}
})
# edit check for allocation ratio
allocationRatioPlanned <- reactive({
req(input$allocationRatioPlanned)
valid <- (input$allocationRatioPlanned > 0)
shinyFeedback::feedbackWarning(
"allocationRatioPlanned", !valid,
"Allocation ratio must be positive")
req(valid)
as.numeric(input$allocationRatioPlanned)
})
# edit check for rho1
rho1 <- reactive({
req(input$rho1)
valid <- (input$rho1 >= 0)
shinyFeedback::feedbackWarning(
"rho1", !valid,
"rho1 must be nonnegative")
req(valid)
as.numeric(input$rho1)
})
# edit check for rho2
rho2 <- reactive({
req(input$rho2)
valid <- (input$rho2 >= 0)
shinyFeedback::feedbackWarning(
"rho2", !valid,
"rho2 must be nonnegative")
req(valid)
as.numeric(input$rho2)
})
# edit check for interim timing
informationRates <- eventReactive(input$calc, {
if (kMax()>1) {
d = input[[paste0("xIA_", kMax())]]
t = c(0, as.vector(d[,1], "numeric"), 1)
valid = all(diff(t) > 0)
if (!valid) {
showNotification(
paste0("Information rates must be strictly ",
"increasing and lie between 0 and 1")
)
}
req(valid)
t[-1]
} else {
1
}
})
efficacyStopping <- eventReactive(input$calc, {
if (kMax()>1) {
d = input[[paste0("xES_", kMax())]]
checked = c(d, paste0("Look ", kMax()))
t = rep(0, kMax())
for (i in 1:kMax()) {
if (paste0("Look ", i) %in% checked) t[i] = 1
}
t
} else {
1
}
})
futilityStopping <- eventReactive(input$calc, {
if (kMax()>1) {
d = input[[paste0("xFS_", kMax())]]
checked = c(d, paste0("Look ", kMax()))
t = rep(0, kMax())
for (i in 1:kMax()) {
if (paste0("Look ", i) %in% checked) t[i] = 1
}
t
} else {
1
}
})
# alpha spending
typeAlphaSpending <- reactive({
if (kMax()>1) {
input$asf
} else {
"none"
}
})
parameterAlphaSpending <- reactive({
if (kMax()>1) {
if (input$asf == "WT") {
as.numeric(input$deltaAlpha)
} else if (input$asf == "sfKD") {
as.numeric(input$rhoAlpha)
} else if (input$asf == "sfHSD") {
as.numeric(input$gammaAlpha)
} else {
NA_real_
}
} else {
NA_real_
}
})
# edit check for user-specified alpha spending
userAlphaSpending = eventReactive(input$calc, {
if (kMax() > 1) {
d = input[[paste0("xUA_", kMax())]]
t = c(0, as.vector(d[,1], "numeric"), alpha())
valid = all(diff(t) >= 0)
if (!valid) {
showNotification(
"Cumulative alpha must be non-decreasing in [0, alpha]"
)
}
req(valid)
t[-1]
} else {
alpha()
}
})
# beta-spending
typeBetaSpending <- reactive({
if (kMax()>1) {
input$bsf
} else {
"none"
}
})
parameterBetaSpending <- reactive({
if (kMax()>1) {
if (input$bsf == "sfKD") {
as.numeric(input$rhoBeta)
} else if (input$bsf == "sfHSD") {
as.numeric(input$gammaBeta)
} else {
NA_real_
}
} else {
NA_real_
}
})
# survival information
observeEvent(input$add_x, {
a = matrix(as.numeric(input$survival),
ncol=ncol(input$survival))
b = matrix(a[nrow(a),], nrow=1)
b[,1] = b[,1] + 1
c = rbind(a, b)
colnames(c) = colnames(input$survival)
updateMatrixInput(session, "survival", c)
})
observeEvent(input$del_x, {
if (nrow(input$survival) >= 2) {
a = matrix(as.numeric(input$survival),
ncol=ncol(input$survival))
b = matrix(a[-nrow(a),], ncol=ncol(a))
colnames(b) = colnames(input$survival)
updateMatrixInput(session, "survival", b)
}
})
piecewiseSurvivalTime <- reactive({
t = as.vector(input$survival[,1], "numeric")
valid = all(diff(t) > 0) && (t[1]==0)
if (!valid) {
showNotification(
"Starting time should be increasing and start at zero"
)
}
req(valid)
t
})
lambda1 <- reactive({
lam1 = as.vector(input$survival[,2], "numeric")
valid = all(lam1 >= 0)
if (!valid) {
showNotification(
"Treatment hazard rate must be non-negative")
}
req(valid)
lam1
})
lambda2 <- reactive({
lam2 = as.vector(input$survival[,3], "numeric")
valid = all(lam2 >= 0)
if (!valid) {
showNotification(
"Control hazard rate must be non-negative")
}
req(valid)
lam2
})
# edit check for dropout
gamma1 <- reactive({
gam1 = as.numeric(input$dropout[,1])
valid = (gam1 >= 0)
if (!valid) {
showNotification(
"Treatment hazard rate must be non-negative")
}
req(valid)
gam1
})
gamma2 <- reactive({
gam2 = as.numeric(input$dropout[,2])
valid = (gam2 >= 0)
if (!valid) {
showNotification(
"Control hazard rate must be non-negative")
}
req(valid)
gam2
})
# accrual information
observeEvent(input$add_y, {
a = matrix(as.numeric(input$accrual),
ncol=ncol(input$accrual))
b = matrix(a[nrow(a),], nrow=1)
b[,1] = b[,1] + 1
c = rbind(a, b)
colnames(c) = colnames(input$accrual)
updateMatrixInput(session, "accrual", c)
})
observeEvent(input$del_y, {
if (nrow(input$accrual) >= 2) {
a = matrix(as.numeric(input$accrual),
ncol=ncol(input$accrual))
b = matrix(a[-nrow(a),], ncol=ncol(a))
colnames(b) = colnames(input$accrual)
updateMatrixInput(session, "accrual", b)
}
})
accrualTime <- reactive({
t = as.vector(input$accrual[,1], "numeric")
valid = all(diff(t) > 0) && (t[1]==0)
if (!valid) {
showNotification(
"Starting time should be increasing and start at zero"
)
}
req(valid)
t
})
accrualIntensity <- reactive({
a = as.vector(input$accrual[,2], "numeric")
valid = all(a >= 0)
if (!valid) {
showNotification(
"Accrual intensity must be non-negative")
}
req(valid)
a
})
typeOfComputation <- reactive({
hr = lambda1()/lambda2()
ph = all(abs(hr - hr[1]) <= 1e-8)
ifelse(rho1() == 0 && rho2() == 0 && ph, "schoenfeld", "direct")
})
lr <- eventReactive(input$calc, {
if (input$target == "power") {
tryCatch({
l = lrpower(
kMax = kMax(),
informationRates = informationRates(),
efficacyStopping = efficacyStopping(),
futilityStopping = futilityStopping(),
alpha = alpha(),
typeAlphaSpending = typeAlphaSpending(),
parameterAlphaSpending = parameterAlphaSpending(),
userAlphaSpending = userAlphaSpending(),
typeBetaSpending = typeBetaSpending(),
parameterBetaSpending = parameterBetaSpending(),
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = accrualDuration(),
followupTime = followupTime(),
fixedFollowup = input$fixedFollowup,
rho1 = rho1(),
rho2 = rho2(),
numSubintervals = numSubintervals,
typeOfComputation = typeOfComputation())
}, error = function(e) {
shiny:::reactiveStop(conditionMessage(e))
})
updateNumericInput(
session, "power",
value = round(l$overallResults$overallReject, 3)
)
} else if (input$target == "accrualDuration") {
tryCatch({
l = lrsamplesize(
beta = beta(),
kMax = kMax(),
informationRates = informationRates(),
efficacyStopping = efficacyStopping(),
futilityStopping = futilityStopping(),
alpha = alpha(),
typeAlphaSpending = typeAlphaSpending(),
parameterAlphaSpending = parameterAlphaSpending(),
userAlphaSpending = userAlphaSpending(),
typeBetaSpending = typeBetaSpending(),
parameterBetaSpending = parameterBetaSpending(),
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = NA,
followupTime = followupTime(),
fixedFollowup = input$fixedFollowup,
rho1 = rho1(),
rho2 = rho2(),
numSubintervals = numSubintervals,
typeOfComputation = typeOfComputation(),
interval = interval,
rounding = input$rounding)
}, error = function(e) {
shiny:::reactiveStop(conditionMessage(e))
})
updateNumericInput(
session, "accrualDuration",
value = round(l$resultsUnderH1$overallResults$accrualDuration, 3)
)
} else if (input$target == "followupTime") {
tryCatch({
l = lrsamplesize(
beta = beta(),
kMax = kMax(),
informationRates = informationRates(),
efficacyStopping = efficacyStopping(),
futilityStopping = futilityStopping(),
alpha = alpha(),
typeAlphaSpending = typeAlphaSpending(),
parameterAlphaSpending = parameterAlphaSpending(),
userAlphaSpending = userAlphaSpending(),
typeBetaSpending = typeBetaSpending(),
parameterBetaSpending = parameterBetaSpending(),
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = accrualDuration(),
followupTime = NA,
fixedFollowup = input$fixedFollowup,
rho1 = rho1(),
rho2 = rho2(),
numSubintervals = numSubintervals,
typeOfComputation = typeOfComputation(),
interval = interval,
rounding = input$rounding)
}, error = function(e) {
shiny:::reactiveStop(conditionMessage(e))
})
updateNumericInput(
session, "followupTime",
value = round(l$resultsUnderH1$overallResults$followupTime, 3)
)
}
l
})
# power vs. Tf
tmin1 <- eventReactive(input$calc, {
a <- lr()$resultsUnderH1$overallResults
if (rho1() == 0 && rho2() == 0) {
criticalValues = lr()$resultsUnderH1$byStageResults$efficacyBounds
} else {
criticalValues = NA
}
if (a$fixedFollowup) {
tmin <- lrsamplesize(
beta = 0.8,
kMax = kMax(),
informationRates = informationRates(),
efficacyStopping = efficacyStopping(),
futilityStopping = futilityStopping(),
criticalValues = criticalValues,
alpha = alpha(),
typeAlphaSpending = typeAlphaSpending(),
parameterAlphaSpending = parameterAlphaSpending(),
userAlphaSpending = userAlphaSpending(),
typeBetaSpending = typeBetaSpending(),
parameterBetaSpending = parameterBetaSpending(),
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = a$accrualDuration,
followupTime = NA,
fixedFollowup = a$fixedFollowup,
rho1 = a$rho1,
rho2 = a$rho2,
numSubintervals = numSubintervals,
estimateHazardRatio = 0,
typeOfComputation = typeOfComputation(),
interval = interval,
rounding = input$rounding
)$resultsUnderH1$overallResults$followupTime
} else {
tmin = 0
}
tmin
})
powerVsTf <- eventReactive(input$calc, {
if (kMax()>1) {
a = lr()$resultsUnderH1$overallResults
if (rho1() == 0 && rho2() == 0) {
criticalValues = lr()$resultsUnderH1$byStageResults$efficacyBounds
} else {
criticalValues = NA
}
time = seq(tmin1(), a$followupTime, length.out=ntpts)
power = rep(0, ntpts)
for (i in 1:ntpts) {
power[i] <- lrpower(
kMax = kMax(),
informationRates = informationRates(),
efficacyStopping = efficacyStopping(),
futilityStopping = futilityStopping(),
criticalValues = criticalValues,
alpha = alpha(),
typeAlphaSpending = typeAlphaSpending(),
parameterAlphaSpending = parameterAlphaSpending(),
userAlphaSpending = userAlphaSpending(),
typeBetaSpending = typeBetaSpending(),
parameterBetaSpending = parameterBetaSpending(),
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = a$accrualDuration,
followupTime = time[i],
fixedFollowup = a$fixedFollowup,
rho1 = a$rho1,
rho2 = a$rho2,
numSubintervals = numSubintervals,
estimateHazardRatio = 0,
typeOfComputation = typeOfComputation()
)$overallResults$overallReject
}
data.frame(time, power)
}
})
powerVsTf2 <- eventReactive(input$calc, {
if (kMax()==1) {
a = lr()$resultsUnderH1$overallResults
time = seq(tmin1(), a$followupTime, length.out=ntpts)
power = rep(0, ntpts)
for (i in 1:ntpts) {
power[i] <- lrpower(
kMax = kMax(),
alpha = alpha(),
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = a$accrualDuration,
followupTime = time[i],
fixedFollowup = a$fixedFollowup,
rho1 = a$rho1,
rho2 = a$rho2,
numSubintervals = numSubintervals,
estimateHazardRatio = 0,
typeOfComputation = typeOfComputation()
)$overallResults$overallReject
}
data.frame(time, power)
}
})
# power vs. N
tmin2 <- eventReactive(input$calc, {
a <- lr()$resultsUnderH1$overallResults
if (rho1() == 0 && rho2() == 0) {
criticalValues = lr()$resultsUnderH1$byStageResults$efficacyBounds
} else {
criticalValues = NA
}
lrsamplesize(
beta = 0.8,
kMax = kMax(),
informationRates = informationRates(),
efficacyStopping = efficacyStopping(),
futilityStopping = futilityStopping(),
criticalValues = criticalValues,
alpha = alpha(),
typeAlphaSpending = typeAlphaSpending(),
parameterAlphaSpending = parameterAlphaSpending(),
userAlphaSpending = userAlphaSpending(),
typeBetaSpending = typeBetaSpending(),
parameterBetaSpending = parameterBetaSpending(),
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = NA,
followupTime = a$followupTime,
fixedFollowup = a$fixedFollowup,
rho1 = a$rho1,
rho2 = a$rho2,
numSubintervals = numSubintervals,
estimateHazardRatio = 0,
typeOfComputation = typeOfComputation(),
interval = interval,
rounding = input$rounding
)$resultsUnderH1$overallResults$accrualDuration
})
powerVsN <- eventReactive(input$calc, {
if (kMax()>1) {
a = lr()$resultsUnderH1$overallResults
if (rho1() == 0 && rho2() == 0) {
criticalValues = lr()$resultsUnderH1$byStageResults$efficacyBounds
} else {
criticalValues = NA
}
time = seq(tmin2(), a$accrualDuration, length.out=ntpts)
N = rep(0, ntpts)
power = rep(0, ntpts)
for (i in 1:ntpts) {
lrx <- lrpower(
kMax = kMax(),
informationRates = informationRates(),
efficacyStopping = efficacyStopping(),
futilityStopping = futilityStopping(),
criticalValues = criticalValues,
alpha = alpha(),
typeAlphaSpending = typeAlphaSpending(),
parameterAlphaSpending = parameterAlphaSpending(),
userAlphaSpending = userAlphaSpending(),
typeBetaSpending = typeBetaSpending(),
parameterBetaSpending = parameterBetaSpending(),
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = time[i],
followupTime = a$followupTime,
fixedFollowup = a$fixedFollowup,
rho1 = a$rho1,
rho2 = a$rho2,
numSubintervals = numSubintervals,
estimateHazardRatio = 0,
typeOfComputation = typeOfComputation())
N[i] = lrx$overallResults$numberOfSubjects
power[i] = lrx$overallResults$overallReject
}
data.frame(N, power)
}
})
powerVsN2 <- eventReactive(input$calc, {
if (kMax()==1) {
a = lr()$resultsUnderH1$overallResults
time = seq(tmin2(), a$accrualDuration, length.out=ntpts)
N = rep(0, ntpts)
power = rep(0, ntpts)
for (i in 1:ntpts) {
lrx <- lrpower(
kMax = kMax(),
alpha = alpha(),
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = time[i],
followupTime = a$followupTime,
fixedFollowup = a$fixedFollowup,
rho1 = a$rho1,
rho2 = a$rho2,
numSubintervals = numSubintervals,
estimateHazardRatio = 0,
typeOfComputation = typeOfComputation()
)
N[i] = lrx$overallResults$numberOfSubjects
power[i] = lrx$overallResults$overallReject
}
data.frame(N, power)
}
})
# Ts vs. N
tmin3 <- eventReactive(input$calc, {
a <- lr()$resultsUnderH1$overallResults
if (rho1() == 0 && rho2() == 0) {
criticalValues = lr()$resultsUnderH1$byStageResults$efficacyBounds
} else {
criticalValues = NA
}
lrsamplesize(
beta = 1-a$overallReject,
kMax = kMax(),
informationRates = informationRates(),
efficacyStopping = efficacyStopping(),
futilityStopping = futilityStopping(),
criticalValues = criticalValues,
alpha = alpha(),
typeAlphaSpending = typeAlphaSpending(),
parameterAlphaSpending = parameterAlphaSpending(),
userAlphaSpending = userAlphaSpending(),
typeBetaSpending = typeBetaSpending(),
parameterBetaSpending = parameterBetaSpending(),
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = NA,
followupTime = 60,
fixedFollowup = a$fixedFollowup,
rho1 = a$rho1,
rho2 = a$rho2,
numSubintervals = numSubintervals,
estimateHazardRatio = 0,
typeOfComputation = typeOfComputation(),
interval = interval,
rounding = input$rounding
)$resultsUnderH1$overallResults$accrualDuration
})
TsVsN <- eventReactive(input$calc, {
if (kMax()>1) {
a = lr()$resultsUnderH1$overallResults
time = seq(tmin3(), a$accrualDuration, length.out=ntpts)
N = rep(0, ntpts)
Ts = rep(0, ntpts)
for (i in 1:ntpts) {
if (typeOfComputation() == "schoenfeld") {
N[i] = accrual(
time = time[i],
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
accrualDuration = time[i])
Ts[i] = caltime(
nevents = a$numberOfEvents,
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = time[i],
followupTime = 1200,
fixedFollowup = a$fixedFollowup)
} else {
lrx <- lrsamplesize(
beta = 1-a$overallReject,
kMax = kMax(),
informationRates = informationRates(),
efficacyStopping = efficacyStopping(),
futilityStopping = futilityStopping(),
alpha = alpha(),
typeAlphaSpending = typeAlphaSpending(),
parameterAlphaSpending = parameterAlphaSpending(),
userAlphaSpending = userAlphaSpending(),
typeBetaSpending = typeBetaSpending(),
parameterBetaSpending = parameterBetaSpending(),
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = time[i],
followupTime = NA,
fixedFollowup = a$fixedFollowup,
rho1 = a$rho1,
rho2 = a$rho2,
numSubintervals = numSubintervals,
estimateHazardRatio = 0,
typeOfComputation = typeOfComputation(),
interval = interval,
rounding = input$rounding)$resultsUnderH1
N[i] = lrx$overallResults$numberOfSubjects
Ts[i] = lrx$overallResults$studyDuration
}
}
data.frame(N, Ts)
}
})
TsVsN2 <- eventReactive(input$calc, {
if (kMax()==1) {
a = lr()$resultsUnderH1$overallResults
time = seq(tmin3(), a$accrualDuration, length.out=ntpts)
N = rep(0, ntpts)
Ts = rep(0, ntpts)
for (i in 1:ntpts) {
if (rho1() == 0 && rho2() == 0) {
N[i] = accrual(
time = time[i],
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
accrualDuration = time[i])
Ts[i] = caltime(
nevents = a$numberOfEvents,
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = time[i],
followupTime = 1200,
fixedFollowup = a$fixedFollowup)
} else {
lrx <- lrsamplesize(
beta = 1 - a$overallReject,
kMax = kMax(),
alpha = alpha(),
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = time[i],
followupTime = NA,
fixedFollowup = a$fixedFollowup,
rho1 = a$rho1,
rho2 = a$rho2,
numSubintervals = numSubintervals,
estimateHazardRatio = 0,
typeOfComputation = typeOfComputation(),
interval = interval,
rounding = input$rounding)$resultsUnderH1
N[i] = lrx$overallResults$numberOfSubjects
Ts[i] = lrx$overallResults$studyDuration
}
}
data.frame(N, Ts)
}
})
output$design <- renderText({
if (kMax()>1) {
str1 <- paste0("Group-sequential trial with ",
kMax(), " stages")
} else {
str1 <- "Fixed design"
}
str2 <- paste0("Fleming-Harrington weight FH(",
rho1(), ", ", rho2(), ")")
if (rho1() != 0 || rho2() != 0) {
HTML(paste(tags$h4(str1), tags$h4(str2)))
} else {
HTML(paste(tags$h4(str1)))
}
})
output$text <- renderText({
a <- lr()$resultsUnderH1$overallResults
req(a$kMax == kMax())
str1 <- paste0("Results under H1 (alternative hypothesis)")
str2 <- paste0("Overall power: ",
round(a$overallReject, 3), ", ",
"overall significance level (1-sided): ",
round(a$alpha, 4))
if (kMax()>1) {
str3 <- paste0("Maximum # events: ",
round(a$numberOfEvents, 1), ", ",
"expected # events: ",
round(a$expectedNumberOfEvents, 1))
str4 <- paste0("Maximum # dropouts: ",
round(a$numberOfDropouts, 1), ", ",
"expected # dropouts: ",
round(a$expectedNumberOfDropouts, 1))
str5 <- paste0("Maximum # subjects: ",
round(a$numberOfSubjects, 1), ", ",
"expected # subjects: ",
round(a$expectedNumberOfSubjects, 1))
str6 <- paste0("Total study duration: ",
round(a$studyDuration, 1), ", ",
"expected study duration: ",
round(a$expectedStudyDuration, 1))
} else {
str3 <- paste0("Number of events: ",
round(a$numberOfEvents, 1))
str4 <- paste0("Number of dropouts: ",
round(a$numberOfDropouts, 1))
str5 <- paste0("Number of subjects: ",
round(a$numberOfSubjects, 1))
str6 <- paste0("Study duration: ",
round(a$studyDuration, 1))
}
str7 <- paste0("Accrual duration: ",
round(a$accrualDuration, 1), ", ",
"follow-up duration: ",
round(a$followupTime, 1), ", ",
"fixed follow-up: ", a$fixedFollowup)
paste(paste("<b>", str1, "</b>", "<br>"),
paste(str2, str3, str4, str5, str6, str7, sep='<br/>'))
})
output$text0 <- renderText({
a <- lr()$resultsUnderH0$overallResults
req(a$kMax == kMax())
str1 <- paste0("Results under H0 (null hypothesis)")
str2 <- paste0("Overall type I error: ",
round(a$overallReject, 3), ", ",
"overall significance level (1-sided): ",
round(a$alpha, 4))
if (kMax()>1) {
str3 <- paste0("Maximum # events: ",
round(a$numberOfEvents, 1), ", ",
"expected # events: ",
round(a$expectedNumberOfEvents, 1))
str4 <- paste0("Maximum # dropouts: ",
round(a$numberOfDropouts, 1), ", ",
"expected # dropouts: ",
round(a$expectedNumberOfDropouts, 1))
str5 <- paste0("Maximum # subjects: ",
round(a$numberOfSubjects, 1), ", ",
"expected # subjects: ",
round(a$expectedNumberOfSubjects, 1))
str6 <- paste0("Total study duration: ",
round(a$studyDuration, 1), ", ",
"expected study duration: ",
round(a$expectedStudyDuration, 1))
} else {
str3 <- paste0("Number of events: ",
round(a$numberOfEvents, 1))
str4 <- paste0("Number of dropouts: ",
round(a$numberOfDropouts, 1))
str5 <- paste0("Number of subjects: ",
round(a$numberOfSubjects, 1))
str6 <- paste0("Study duration: ",
round(a$studyDuration, 1))
}
str7 <- paste0("Accrual duration: ",
round(a$accrualDuration, 1), ", ",
"follow-up duration: ",
round(a$followupTime, 1), ", ",
"fixed follow-up: ", a$fixedFollowup)
paste(paste("<b>", str1, "</b>", "<br>"),
paste(str2, str3, str4, str5, str6, str7, sep='<br/>'))
})
output$table <- renderPrint({
a <- lr()$resultsUnderH1$overallResults
req(a$kMax == kMax())
if (kMax()>1) {
b <- lr()$resultsUnderH1$byStageResults %>%
mutate(efficacyBounds = ifelse(efficacyStopping, efficacyBounds, NA),
futilityBounds = ifelse(futilityStopping, futilityBounds, NA),
efficacyHR = ifelse(efficacyStopping, efficacyHR, NA),
futilityHR = ifelse(futilityStopping, futilityHR, NA),
efficacyP = ifelse(efficacyStopping, efficacyP, NA),
futilityP = ifelse(futilityStopping, futilityP, NA))
# only keep necessary variables
b <- b[, c("informationRates", "efficacyBounds", "futilityBounds",
"cumulativeRejection", "cumulativeFutility",
"cumulativeAlphaSpent",
"numberOfEvents", "numberOfDropouts", "numberOfSubjects",
"analysisTime", "efficacyHR", "futilityHR",
"efficacyP", "futilityP", "information", "HR")]
# format number of digits after decimal for each column
j1 <- c(7,8,9,10)
j2 <- 15
j3 <- c(1,2,3,4,5,11,12,16)
j4 <- c(6,13,14)
b[j1] <- lapply(b[j1], formatC, format = "f", digits = 1)
b[j2] <- lapply(b[j2], formatC, format = "f", digits = 2)
b[j3] <- lapply(b[j3], formatC, format = "f", digits = 3)
b[j4] <- lapply(b[j4], formatC, format = "f", digits = 4)
if (input$bsf != 'none') {
df = t(b)
rownames(df) = c("Information rate",
"Efficacy boundary (Z-scale)",
"Futility boundary (Z-scale)",
"Cumulative rejection",
"Cumulative futility",
"Cumulative alpha spent",
"Number of events",
"Number of dropouts",
"Number of subjects",
"Analysis time",
"Efficacy boundary (HR-scale)",
"Futility boundary (HR-scale)",
"Efficacy boundary (p-scale)",
"Futility boundary (p-scale)",
"Information",
"HR")
} else {
df = t(b[,c(1,2,4,6,7,8,9,10,11,13,15,16)])
rownames(df) = c("Information rate",
"Efficacy boundary (Z-scale)",
"Cumulative rejection",
"Cumulative alpha spent",
"Number of events",
"Number of dropouts",
"Number of subjects",
"Analysis time",
"Efficacy boundary (HR-scale)",
"Efficacy boundary (p-scale)",
"Information",
"HR")
}
colnames(df) <- paste("Stage", seq_len(ncol(df)), sep=" ")
print(df, quote=FALSE)
}
})
output$table0 <- renderPrint({
a <- lr()$resultsUnderH0$overallResults
req(a$kMax == kMax())
if (kMax()>1) {
b <- lr()$resultsUnderH0$byStageResults %>%
mutate(efficacyBounds = ifelse(efficacyStopping, efficacyBounds, NA),
futilityBounds = ifelse(futilityStopping, futilityBounds, NA),
efficacyP = ifelse(efficacyStopping, efficacyP, NA),
futilityP = ifelse(futilityStopping, futilityP, NA))
# only keep necessary variables
b <- b[, c("informationRates", "efficacyBounds", "futilityBounds",
"cumulativeRejection", "cumulativeFutility",
"cumulativeAlphaSpent", "numberOfEvents",
"numberOfDropouts", "numberOfSubjects", "analysisTime",
"efficacyP", "futilityP", "information")]
# format number of digits after decimal for each column
j1 <- c(7,8,9,10)
j2 <- 13
j3 <- c(1,2,3,4,5)
j4 <- c(6,11,12)
b[j1] <- lapply(b[j1], formatC, format = "f", digits = 1)
b[j2] <- lapply(b[j2], formatC, format = "f", digits = 2)
b[j3] <- lapply(b[j3], formatC, format = "f", digits = 3)
b[j4] <- lapply(b[j4], formatC, format = "f", digits = 4)
if (input$bsf != 'none') {
df = t(b[,c(4,5,7,8,9,10,13)])
rownames(df) = c("Cumulative rejection",
"Cumulative futility",
"Number of events",
"Number of dropouts",
"Number of subjects",
"Analysis time",
"Information"
)
} else {
df = t(b[,c(4,7,8,9,10,13)])
rownames(df) = c("Cumulative rejection",
"Number of events",
"Number of dropouts",
"Number of subjects",
"Analysis time",
"Information"
)
}
colnames(df) <- paste("Stage", seq_len(ncol(df)), sep=" ")
print(df, quote=FALSE)
}
})
output$plot <- renderPlotly({
a <- lr()$resultsUnderH1$overallResults
req(a$kMax == kMax())
kMax <- a$kMax
if (lr()$resultsUnderH1$settings$typeAlphaSpending == "none") {
b <- lr()$resultsUnderH1$byStageResults
b[-nrow(b), "efficacyStopping"] = FALSE
b <- b %>%
mutate(efficacyBounds = ifelse(efficacyStopping, efficacyBounds, NA),
cumulativeRejection = ifelse(efficacyStopping,
cumulativeRejection, NA),
efficacyHR = ifelse(efficacyStopping, efficacyHR, NA),
efficacyP = ifelse(efficacyStopping, efficacyP, NA))
} else {
b <- lr()$resultsUnderH1$byStageResults %>%
mutate(efficacyBounds = ifelse(efficacyStopping, efficacyBounds, NA),
efficacyHR = ifelse(efficacyStopping, efficacyHR, NA),
efficacyP = ifelse(efficacyStopping, efficacyP, NA))
}
if (lr()$resultsUnderH1$settings$typeBetaSpending == "none") {
b <- b %>%
mutate(futilityStopping = FALSE,
futilityBounds = ifelse(futilityStopping, futilityBounds, NA),
cumulativeFutility = ifelse(futilityStopping,
cumulativeFutility, NA),
futilityHR = ifelse(futilityStopping, futilityHR, NA),
futilityP = ifelse(futilityStopping, futilityP, NA))
} else {
b <- b %>%
mutate(futilityBounds = ifelse(futilityStopping, futilityBounds, NA),
futilityHR = ifelse(futilityStopping, futilityHR, NA),
futilityP = ifelse(futilityStopping, futilityP, NA))
}
if (kMax > 1) {
if (input$plottype == "boundaryZ") {
af <- b %>%
pivot_longer(cols = c("efficacyBounds", "futilityBounds"),
names_to = "type",
values_to = "bounds") %>%
mutate(type = gsub("Bounds", "", type)) %>%
filter(!is.na(bounds))
plotly::plot_ly(af, x=~numberOfEvents, y=~bounds,
type="scatter", mode="markers+lines",
linetype=~type) %>%
plotly::layout(xaxis = list(title = "Events"),
yaxis = list(title = "Boundaries (Z)"))
} else if (input$plottype == "boundaryHR") {
af <- b %>%
pivot_longer(cols = c("efficacyHR", "futilityHR"),
names_to = "type",
values_to = "bounds") %>%
mutate(type = gsub("HR", "", type)) %>%
filter(!is.na(bounds))
plotly::plot_ly(af, x=~numberOfEvents, y=~bounds,
type="scatter", mode="markers+lines",
linetype=~type) %>%
plotly::layout(xaxis = list(title = "Events"),
yaxis = list(title = "Boundaries (HR)"))
} else if (input$plottype == "boundaryP") {
af <- b %>%
pivot_longer(cols = c("efficacyP", "futilityP"),
names_to = "type",
values_to = "bounds") %>%
mutate(type = gsub("P", "", type)) %>%
filter(!is.na(bounds))
plotly::plot_ly(af, x=~numberOfEvents, y=~bounds,
type="scatter", mode="markers+lines",
linetype=~type) %>%
plotly::layout(xaxis = list(title = "Events"),
yaxis = list(title = "Boundaries (p)",
zeroline = FALSE))
} else if (input$plottype == "errorSpend") {
af <- b %>%
pivot_longer(cols = c("cumulativeAlphaSpent", "cumulativeFutility"),
names_to = "type",
values_to = "bounds") %>%
mutate(type = ifelse(type=="cumulativeAlphaSpent",
"alpha", "beta")) %>%
filter(!is.na(bounds))
plotly::plot_ly(af, x=~numberOfEvents, y=~bounds,
type="scatter", mode="markers+lines",
linetype=~type) %>%
plotly::layout(xaxis = list(title = "Events"),
yaxis = list(title = "Cumulative error spent",
zeroline = FALSE))
} else if (input$plottype == "eventPred") {
time <- seq(0, a$studyDuration, length.out=100)
df <- lrstat(time,
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = a$accrualDuration,
followupTime = a$followupTime,
fixedFollowup = a$fixedFollowup,
rho1 = a$rho1,
rho2 = a$rho2,
numSubintervals = numSubintervals,
predictTarget = 1)
af <- df %>%
pivot_longer(cols = c("subjects", "nevents"),
names_to = "type",
values_to = "n") %>%
mutate(type = ifelse(type=="subjects", "subjects", "events"))
plotly::plot_ly(af, x=~time, y=~n, linetype=~type,
type="scatter", mode="lines") %>%
plotly::layout(xaxis = list(title = "Time", zeroline = FALSE),
yaxis = list(zeroline=FALSE),
legend = list(x=0, y=1.1, orientation="h"))
} else if (input$plottype == "powerVsTf") {
plotly::plot_ly(powerVsTf(), x=~time, y=~power,
type="scatter", mode="lines") %>%
plotly::layout(
xaxis = list(title = "Follow-up duration", zeroline = FALSE),
yaxis = list(title = "Power"),
title = list(text = paste0(
"For ", round(a$numberOfSubjects), " subjects",
" enrolled over ", round(a$accrualDuration, 1),
" time units"), x = 0, xref='paper')
)
} else if (input$plottype == "powerVsN") {
plotly::plot_ly(powerVsN(), x=~N, y=~power,
type="scatter", mode="lines") %>%
plotly::layout(
xaxis = list(title = "Sample size", zeroline = FALSE),
yaxis = list(title = "Power"),
title = list(text = paste0(
"For follow-up duration of ", round(a$followupTime, 1),
" time units"), x = 0, xref='paper')
)
} else if (input$plottype == "TsVsN") {
plotly::plot_ly(TsVsN(), x=~N, y=~Ts,
type="scatter", mode="lines") %>%
plotly::layout(
xaxis = list(title = "Sample size", zeroline = FALSE),
yaxis = list(title = "Study duration"),
title = list(text = paste0(
"For power of ", round(a$overallReject, 3)),
x = 0, xref='paper')
)
}
} else {
if (input$plottype2 == "eventPred") {
time <- seq(0, a$studyDuration, length.out=100)
df <- lrstat(time,
allocationRatioPlanned = allocationRatioPlanned(),
accrualTime = accrualTime(),
accrualIntensity = accrualIntensity(),
piecewiseSurvivalTime = piecewiseSurvivalTime(),
lambda1 = lambda1(),
lambda2 = lambda2(),
gamma1 = gamma1(),
gamma2 = gamma2(),
accrualDuration = a$accrualDuration,
followupTime = a$followupTime,
fixedFollowup = a$fixedFollowup,
rho1 = a$rho1,
rho2 = a$rho2,
numSubintervals = numSubintervals,
predictTarget = 1)
af <- df %>%
pivot_longer(cols = c("subjects", "nevents"),
names_to = "type",
values_to = "n") %>%
mutate(type = ifelse(type=="subjects", "subjects", "events"))
plotly::plot_ly(af, x=~time, y=~n, linetype=~type,
type="scatter", mode="lines") %>%
plotly::layout(xaxis = list(title = "Time", zeroline = FALSE),
yaxis = list(zeroline=FALSE),
legend = list(x=0, y=1.1, orientation="h"))
} else if (input$plottype2 == "powerVsTf") {
plotly::plot_ly(powerVsTf2(), x=~time, y=~power,
type="scatter", mode="lines") %>%
plotly::layout(
xaxis = list(title = "Follow-up duration", zeroline = FALSE),
yaxis = list(title = "Power"),
title = list(text = paste0(
"For ", round(a$numberOfSubjects), " subjects",
" enrolled over ", round(a$accrualDuration, 1),
" time units"), x = 0, xref='paper')
)
} else if (input$plottype2 == "powerVsN") {
plotly::plot_ly(powerVsN2(), x=~N, y=~power,
type="scatter", mode="lines") %>%
plotly::layout(
xaxis = list(title = "Sample size", zeroline = FALSE),
yaxis = list(title = "Power"),
title = list(text = paste0(
"For follow-up duration of ", round(a$followupTime, 1),
" time units"), x = 0, xref='paper')
)
} else if (input$plottype2 == "TsVsN") {
plotly::plot_ly(TsVsN2(), x=~N, y=~Ts,
type="scatter", mode="lines") %>%
plotly::layout(
xaxis = list(title = "Sample size", zeroline = FALSE),
yaxis = list(title = "Study duration"),
title = list(text = paste0(
"For power of ", round(a$overallReject, 3)),
x = 0, xref='paper')
)
}
}
})
# simulation
observe({
freezeReactiveValue(input, "boundaries")
b <- lr()$resultsUnderH1$byStageResults
b0 <- lr()$resultsUnderH0$byStageResults
kMax <- nrow(b)
updateMatrixInput(
session,
inputId = "boundaries",
value = matrix(c(round(b0$information/b0$information[kMax], 4),
round(b$numberOfEvents),
round(b$efficacyBounds, 3),
round(b$futilityBounds, 3)),
ncol = 4,
dimnames = list(paste0("Look ", seq_len(kMax)),
c("Information rates",
"Planned events",
"Efficacy boundary",
"Futility boundary"))))
})
# edit check for number of replications
nIterations <- reactive({
req(input$nIterations)
valid <- (input$nIterations >= 1)
shinyFeedback::feedbackWarning(
"nIterations", !valid,
"Number of replications must be positive integers")
req(valid)
round(as.numeric(input$nIterations))
})
# edit check for number of replications
nRawDatasets <- reactive({
req(input$nRawDatasets, input$nIterations)
valid <- (input$nRawDatasets >= 0) &&
(input$nRawDatasets <= input$nIterations)
shinyFeedback::feedbackWarning(
"nRawDatasets", !valid,
paste0("Number of raw datasets per stage must be nonnegative integers",
" and less than or equal to the number of replications"))
req(valid)
round(as.numeric(input$nRawDatasets))
})
sim <- eventReactive(input$sim, {
req(nrow(input$boundaries)==as.numeric(input$kMax))
r <- as.numeric(input$allocationRatioPlanned)
if (r!= round(r)) {
allocation <- as.vector(unlist(strsplit(attr(
fractions(r), "fracs"), "/")), "numeric")
} else {
allocation <- c(r, 1)
}
l <- lrsim(
kMax = as.numeric(input$kMax),
informationRates = as.vector(input$boundaries[,1], "numeric"),
criticalValues = as.vector(input$boundaries[,3], "numeric"),
futilityBounds = as.vector(input$boundaries[,4], "numeric"),
allocation1 = allocation[1],
allocation2 = allocation[2],
accrualTime = as.vector(input$accrual[,1], "numeric"),
accrualIntensity = as.vector(input$accrual[,2], "numeric"),
piecewiseSurvivalTime = as.vector(input$survival[,1], "numeric"),
lambda1 = as.vector(input$survival[,2], "numeric"),
lambda2 = as.vector(input$survival[,3], "numeric"),
gamma1 = as.vector(input$dropout[,1], "numeric"),
gamma2 = as.vector(input$dropout[,2], "numeric"),
accrualDuration = input$accrualDuration,
followupTime = input$followupTime,
fixedFollowup = input$fixedFollowup,
rho1 = input$rho1,
rho2 = input$rho2,
plannedEvents = as.vector(input$boundaries[,2], "numeric"),
maxNumberOfIterations = input$nIterations,
maxNumberOfRawDatasetsPerStage = input$nRawDatasets,
seed = input$seed
)
l
})
sim0 <- eventReactive(input$sim, {
req(nrow(input$boundaries)==as.numeric(input$kMax))
r <- as.numeric(input$allocationRatioPlanned)
if (r!= round(r)) {
allocation <- as.vector(unlist(strsplit(attr(
fractions(r), "fracs"), "/")), "numeric")
} else {
allocation <- c(r, 1)
}
l <- lrsim(
kMax = as.numeric(input$kMax),
informationRates = as.vector(input$boundaries[,1], "numeric"),
criticalValues = as.vector(input$boundaries[,3], "numeric"),
futilityBounds = as.vector(input$boundaries[,4], "numeric"),
allocation1 = allocation[1],
allocation2 = allocation[2],
accrualTime = as.vector(input$accrual[,1], "numeric"),
accrualIntensity = as.vector(input$accrual[,2], "numeric"),
piecewiseSurvivalTime = as.vector(input$survival[,1], "numeric"),
lambda1 = as.vector(input$survival[,3], "numeric"),
lambda2 = as.vector(input$survival[,3], "numeric"),
gamma1 = as.vector(input$dropout[,1], "numeric"),
gamma2 = as.vector(input$dropout[,2], "numeric"),
accrualDuration = input$accrualDuration,
followupTime = input$followupTime,
fixedFollowup = input$fixedFollowup,
rho1 = input$rho1,
rho2 = input$rho2,
plannedEvents = as.vector(input$boundaries[,2], "numeric"),
maxNumberOfIterations = input$nIterations,
maxNumberOfRawDatasetsPerStage = input$nRawDatasets,
seed = input$seed
)
l
})
output$simtext <- renderText({
req(nrow(input$boundaries)==sim()$overview$kMax)
a <- sim()$overview
str1 <- "Simulation results under H1"
str2 <- paste0("Overall rejection, ",
round(a$overallReject,3), ", ",
"expected # events: ",
round(a$expectedNumberOfEvents, 1), ", ",
"expected # dropouts: ",
round(a$expectedNumberOfDropouts, 1), ", ",
"# subjects: ",
round(a$expectedNumberOfSubjects, 1), ", ",
"study duration: ",
round(a$expectedStudyDuration, 1))
paste(paste("<b>", str1, "</b>"),
str2, sep = '<br/>')
})
output$simtable <- renderPrint({
req(nrow(input$boundaries)==sim()$overview$kMax)
if (kMax()>1) {
a <- sim()$overview
b <- data.frame(a$cumulativeRejection,
a$cumulativeFutility,
a$numberOfEvents,
a$numberOfDropouts,
a$numberOfSubjects,
a$analysisTime)
j1 <- c(3,4,5,6)
j3 <- c(1,2)
b[j1] <- lapply(b[j1], formatC, format = "f", digits = 1)
b[j3] <- lapply(b[j3], formatC, format = "f", digits = 3)
df = t(b)
rownames(df) = c("Cumulative rejection",
"Cumulative futility",
"Number of events",
"Number of dropouts",
"Number of subjects",
"Analysis time")
colnames(df) <- paste("Stage", seq_len(ncol(df)), sep=" ")
print(df, quote=FALSE)
}
})
output$downloadSumdata <- downloadHandler(
filename = function() {
paste0("sim-sumdata-h1-", Sys.Date(), ".csv")
},
content = function(file) {
write.csv(sim()$sumdata, file, row.names=FALSE)
}
)
output$downloadRawdata <- downloadHandler(
filename = function() {
paste0("sim-rawdata-h1-", Sys.Date(), ".csv")
},
content = function(file) {
write.csv(sim()$rawdata, file, row.names=FALSE)
}
)
output$simtext0 <- renderText({
req(nrow(input$boundaries)==sim0()$overview$kMax)
a <- sim0()$overview
str1 <- "Simulation results under H0"
str2 <- paste0("Overall rejection: ",
round(a$overallReject,3), ", ",
"expected # events: ",
round(a$expectedNumberOfEvents), ", ",
"expected # dropouts: ",
round(a$expectedNumberOfDropouts, 1), ", ",
"# subjects: ",
round(a$expectedNumberOfSubjects), ", ",
"study duration: ",
round(a$expectedStudyDuration, 1))
paste(paste("<b>", str1, "</b>"),
str2, sep = '<br/>')
})
output$simtable0 <- renderPrint({
req(nrow(input$boundaries)==sim0()$overview$kMax)
if (kMax()>1) {
a <- sim0()$overview
b <- data.frame(a$cumulativeRejection,
a$cumulativeFutility,
a$numberOfEvents,
a$numberOfDropouts,
a$numberOfSubjects,
a$analysisTime)
j1 <- c(3,4,5,6)
j3 <- c(1,2)
b[j1] <- lapply(b[j1], formatC, format = "f", digits = 1)
b[j3] <- lapply(b[j3], formatC, format = "f", digits = 3)
df = t(b)
rownames(df) = c("Cumulative rejection",
"Cumulative futility",
"Number of events",
"Number of dropouts",
"Number of subjects",
"Analysis time")
colnames(df) <- paste("Stage", seq_len(ncol(df)), sep=" ")
print(df, quote=FALSE)
}
})
output$downloadSumdata0 <- downloadHandler(
filename = function() {
paste0("sim-sumdata-h0-", Sys.Date(), ".csv")
},
content = function(file) {
write.csv(sim0()$sumdata, file, row.names=FALSE)
}
)
output$downloadRawdata0 <- downloadHandler(
filename = function() {
paste0("sim-rawdata-h0-", Sys.Date(), ".csv")
},
content = function(file) {
write.csv(sim0()$rawdata, file, row.names=FALSE)
}
)
output$lrp <- renderText({
a <- lr()$resultsUnderH1$overallResults
req(a$kMax == kMax())
b <- lr()$resultsUnderH1$byStageResults
s <- lr()$resultsUnderH1$settings
str2 <- paste0("kMax = ", a$kMax, ",")
if (a$kMax > 1) {
str3 <- paste0("informationRates = c(",
paste(b$informationRates, collapse=", "), "),")
if (s$typeAlphaSpending != "none") {
str3 <- paste(str3,
paste0("efficacyStopping = c(",
paste(as.vector(b$efficacyStopping, "numeric"),
collapse=", "), "),"), sep="<br/>")
}
if (s$typeBetaSpending != "none") {
str3 <- paste(str3,
paste0("futilityStopping = c(",
paste(as.vector(b$futilityStopping, "numeric"),
collapse=", "), "),"), sep="<br/>")
}
str7 <- paste0("typeAlphaSpending = '", s$typeAlphaSpending, "',")
if (s$typeAlphaSpending %in% c("WT", "sfKD", "sfHSD")) {
str7 <- paste(str7, paste0("parameterAlphaSpending = ",
s$parameterAlphaSpending, ","), sep="<br/>")
}
if (s$typeAlphaSpending == "user") {
str7 <- paste(str7, paste0("userAlphaSpending = c(",
paste(s$userAlphaSpending, collapse=", "),
","), sep="<br/>")
}
str8 <- paste0("typeBetaSpending = '", s$typeBetaSpending, "',")
if (s$typeBetaSpending %in% c("sfKD", "sfHSD")) {
str8 <- paste(str8, paste0("parameterBetaSpending = ",
s$parameterBetaSpending, ","), sep="<br/>")
}
}
str6 <- paste0("alpha = ", round(a$alpha, 5), ",")
str9 <- paste0("allocationRatioPlanned = ", a$allocationRatioPlanned, ",")
if (length(s$accrualTime) == 1) {
str10 <- paste0("accrualTime = ", s$accrualTime, ",")
str10 <- paste(str10, paste0("accrualIntensity = ",
s$accrualIntensity, ","), sep="<br/>")
} else {
str10 <- paste0("accrualTime = c(",
paste(s$accrualTime, collapse=", "), "),")
str10 <- paste(str10, paste0("accrualIntensity = c(",
paste(s$accrualIntensity, collapse=", "),
"),"), sep="<br/>")
}
if (length(s$piecewiseSurvivalTime) == 1) {
str11 <- paste0("piecewiseSurvivalTime = ", s$piecewiseSurvivalTime, ",")
str11 <- paste(str11, paste0("lambda1 = ", s$lambda1, ","), sep="<br/>")
str11 <- paste(str11, paste0("lambda2 = ", s$lambda2, ","), sep="<br/>")
} else {
str11 <- paste0("piecewiseSurvivalTime = c(",
paste(s$piecewiseSurvivalTime, collapse=", "), "),")
str11 <- paste(str11, paste0("lambda1 = c(",
paste(s$lambda1, collapse=", "),
"),"), sep="<br/>")
str11 <- paste(str11, paste0("lambda2 = c(",
paste(s$lambda2, collapse=", "),
"),"), sep="<br/>")
}
str12 <- paste0("gamma1 = ", s$gamma1, ",")
str12 <- paste(str12, paste0("gamma2 = ", s$gamma2, ","), sep="<br/>")
str15 <- paste0("fixedFollowup = ", input$fixedFollowup, ",")
str16 <- paste0("rho1 = ", a$rho1, ",")
str16 <- paste(str16, paste0("rho2 = ", a$rho2, ","), sep="<br/>")
if (input$target == 'power') {
str1 <- paste0("(lr <- lrpower(")
str13 <- paste0("accrualDuration = ", a$accrualDuration, ",")
str14 <- paste0("followupTime = ", a$followupTime, ",")
str17 <- paste0("numSubintervals = ", numSubintervals, ",")
str17 <- paste(str17, paste0(
"typeOfComputation = '", typeOfComputation(), "'))"), sep="<br/>")
if (a$kMax == 1) {
paste(str1, str2, str6, str9, str10,
str11, str12, str13, str14, str15, str16, str17, sep = '<br/>')
} else {
paste(str1, str2, str3, str6, str7, str8, str9, str10,
str11, str12, str13, str14, str15, str16, str17, sep = '<br/>')
}
} else if (input$target == 'accrualDuration') {
str0 <- paste0("(lr <- lrsamplesize(")
str1 <- paste0("beta = ", round(1-a$overallReject, 4), ",")
str13 <- paste0("accrualDuration = NA,")
str14 <- paste0("followupTime = ", a$followupTime, ",")
str17 <- paste0("numSubintervals = ", numSubintervals, ",")
str17 <- paste(str17, paste0(
"typeOfComputation = '", typeOfComputation(), "',"), sep="<br/>")
str18 <- paste0("interval = c(", paste(interval, collapse=", "), ")))")
if (a$kMax == 1) {
paste(str0, str1, str2, str6, str9, str10,
str11, str12, str13, str14, str15, str16, str17,
str18, sep = '<br/>')
} else {
paste(str0, str1, str2, str3, str6, str7, str8, str9, str10,
str11, str12, str13, str14, str15, str16, str17,
str18, sep = '<br/>')
}
} else if (input$target == 'followupTime') {
str0 <- paste0("(lr <- lrsamplesize(")
str1 <- paste0("beta = ", round(1-a$overallReject, 4), ",")
str13 <- paste0("accrualDuration = ", a$accrualDuration, ",")
str14 <- paste0("followupTime = NA,")
str17 <- paste0("numSubintervals = ", numSubintervals, ",")
str17 <- paste(str17, paste0(
"typeOfComputation = '", typeOfComputation(), "',"), sep="<br/>")
str18 <- paste0("interval = c(", paste(interval, collapse=", "), ")),")
str19 <- paste("rounding = ", input$rounding, "))")
if (a$kMax == 1) {
paste(str0, str1, str2, str6, str9, str10,
str11, str12, str13, str14, str15, str16, str17,
str18, str19, sep = '<br/>')
} else {
paste(str0, str1, str2, str3, str6, str7, str8, str9, str10,
str11, str12, str13, str14, str15, str16, str17,
str18, str19, sep = '<br/>')
}
}
})
output$lrs <- renderText({
a <- lr()$resultsUnderH1$overallResults
req(a$kMax == kMax())
s <- lr()$resultsUnderH1$settings
str1 <- paste0("(sim <- lrsim(")
str2 <- paste0("kMax = ", a$kMax, ",")
if (a$kMax > 1) {
str3 <- paste0("informationRates = c(",
paste(as.vector(input$boundaries[,1], "numeric"),
collapse=", "), "),")
str4 <- paste0("criticalValues = c(",
paste(as.vector(input$boundaries[,3], "numeric"),
collapse=", "), "),")
str5 <- paste0("futilityBounds = c(",
paste(as.vector(input$boundaries[,4], "numeric"),
collapse=", "), "),")
} else {
str4 <- paste0("criticalValues = ", input$boundaries[,3], ",")
}
r <- lr()$resultsUnderH1$settings$allocationRatioPlanned
if (r!= round(r)) {
allocation <- as.vector(unlist(strsplit(attr(
fractions(r), "fracs"), "/")), "numeric")
} else {
allocation <- c(r, 1)
}
str6 <- paste0("allocation1 = ", allocation[1], ",")
str6 <- paste(str6, paste0("allocation2 = ",
allocation[2], ","), sep='<br/>')
if (length(s$accrualTime) == 1) {
str7 <- paste0("accrualTime = ", s$accrualTime, ",")
str7 <- paste(str7, paste0("accrualIntensity = ",
s$accrualIntensity, ","), sep="<br/>")
} else {
str7 <- paste0("accrualTime = c(", paste(s$accrualTime,
collapse=", "), "),")
str7 <- paste(str7, paste0("accrualIntensity = c(",
paste(s$accrualIntensity, collapse=", "),
"),"), sep="<br/>")
}
if (length(s$piecewiseSurvivalTime) == 1) {
str8 <- paste0("piecewiseSurvivalTime = ", s$piecewiseSurvivalTime, ",")
str8 <- paste(str8, paste0("lambda1 = ", s$lambda1, ","), sep="<br/>")
str8 <- paste(str8, paste0("lambda2 = ", s$lambda2, ","), sep="<br/>")
} else {
str8 <- paste0("piecewiseSurvivalTime = c(",
paste(s$piecewiseSurvivalTime, collapse=", "), "),")
str8 <- paste(str8, paste0("lambda1 = c(",
paste(s$lambda1, collapse=", "),
"),"), sep="<br/>")
str8 <- paste(str8, paste0("lambda2 = c(",
paste(s$lambda2, collapse=", "),
"),"), sep="<br/>")
}
str9 <- paste0("gamma1 = ", s$gamma1, ",")
str9 <- paste(str9, paste0("gamma2 = ", s$gamma2, ","), sep="<br/>")
str10 <- paste0("accrualDuration = ", round(a$accrualDuration, 2), ",")
str11 <- paste0("followupTime = ", round(a$followupTime, 2), ",")
str12 <- paste0("fixedFollowup = ", a$fixedFollowup, ",")
str13 <- paste0("rho1 = ", a$rho1, ",")
str13 <- paste(str13, paste0("rho2 = ", a$rho2, ","), sep="<br/>")
if (a$kMax == 1) {
str14 <- paste("plannedEvents = ", input$bounardies[,2], ",")
} else {
str14 <- paste0("plannedEvents = c(",
paste(as.vector(input$boundaries[,2], "numeric"),
collapse=", "), "),")
}
str15 <- paste0("maxNumberOfIterations = ", input$nIterations, ",")
str16 <- paste0("maxNumberOfRawDatasetsPerStage = ",
input$nRawDatasets, ",")
str17 <- paste0("seed = ", input$seed, "))")
if (a$kMax == 1) {
paste(str1, str2, str4, str6, str7, str8, str9, str10,
str11, str12, str13, str14, str15, str16, str17, sep = '<br/>')
} else {
paste(str1, str2, str3, str4, str5, str6, str7, str8, str9, str10,
str11, str12, str13, str14, str15, str16, str17, sep = '<br/>')
}
})
# save inputs
output$saveInputs <- downloadHandler(
filename = function() {
paste0("inputs-", Sys.Date(), ".rds")
},
content = function(file) {
x <- list(
kMax = kMax(),
target = input$target,
alpha = alpha(),
power = 1-beta(),
accrualDuration = accrualDuration(),
followupTime = followupTime(),
allocationRatioPlanned = allocationRatioPlanned(),
fixedFollowup = input$fixedFollowup,
rho1 = rho1(),
rho2 = rho2(),
rounding = input$rounding,
xIA = matrix(informationRates(), ncol=1,
dimnames = list(paste0("Look ", seq_len(kMax())),
c("Information rate"))
),
xES = efficacyStopping(),
xFS = futilityStopping(),
xUA = matrix(userAlphaSpending(), ncol=1,
dimnames = list(paste0("Look ", seq_len(kMax())),
c("Cumulative alpha"))
),
asf = typeAlphaSpending(),
deltaAlpha = input$deltaAlpha,
rhoAlpha = input$rhoAlpha,
gammaAlpha = input$gammaAlpha,
bsf = typeBetaSpending(),
rhoBeta = input$rhoBeta,
gammaBeta = input$gammaBeta,
survival = matrix(as.numeric(input$survival),
ncol=ncol(input$survival),
dimnames = list(
NULL, c("Starting time",
"Treatment hazard rate",
"Control hazard rate"))
),
accrual = matrix(as.numeric(input$accrual),
ncol=ncol(input$accrual),
dimnames = list(
NULL, c("Starting time",
"Accrual intensity"))
),
dropout = matrix(as.numeric(input$dropout),
ncol=ncol(input$dropout),
dimnames = list(
NULL, c("Treatment hazard rate",
"Control hazard rate"))
),
plottype = input$plottype,
plottype2 = input$plottype2,
boundaries = matrix(
as.numeric(input$boundaries),
ncol=ncol(input$boundaries),
dimnames = list(paste0("Look ", seq_len(kMax())),
c("Information rates",
"Planned events",
"Efficacy boundary",
"Futility boundary"))),
nIterations = nIterations(),
nRawDatasets = nRawDatasets(),
seed = input$seed
)
save(x, file = file)
}
)
# load inputs
observeEvent(input$loadInputs, {
file <- input$loadInputs
ext <- tools::file_ext(file$datapath)
req(file)
valid <- (ext == "rds")
if (!valid) showNotification("Please upload an rds file")
req(valid)
load(file=file$datapath)
updateSelectInput(session, "kMax", selected=x$kMax)
updateRadioButtons(session, "target", selected=x$target)
updateNumericInput(session, "alpha", value=x$alpha)
if (x$target != "power") {
updateNumericInput(session, "power", value=x$power)
}
if (x$target != "accrualDuration") {
updateNumericInput(session, "accrualDuration", value=x$accrualDuration)
}
if (x$target != "followupTime") {
updateNumericInput(session, "followupTime", value=x$followupTime)
}
updateNumericInput(session, "allocationRatioPlanned",
value=x$allocationRatioPlanned)
updateCheckboxInput(session, "fixedFollowup", value=x$fixedFollowup)
updateNumericInput(session, "rho1", value=x$rho1)
updateNumericInput(session, "rho2", value=x$rho2)
updateCheckboxInput(session, "rounding", value=x$rounding)
if (x$kMax > 1) {
updateMatrixInput(
session, paste0("xIA_", x$kMax),
value=matrix(x$xIA[-x$kMax,], ncol = 1,
dimnames = list(paste0("Look ", seq_len(x$kMax-1)),
c("Information rate"))))
updateCheckboxGroupInput(
session, paste0("xES_", x$kMax),
selected=paste0("Look ", which(x$xES[-x$kMax]==1)))
updateCheckboxGroupInput(
session, paste0("xFS_", x$kMax),
selected=paste0("Look ", which(x$xFS[-x$kMax]==1)))
}
if (x$kMax >1 && x$asf=="user") {
updateMatrixInput(
session, paste0("xUA_", x$kMax),
value=matrix(x$xUA[-x$kMax,], ncol=1,
dimnames = list(paste0("Look ", seq_len(x$kMax-1)),
c("Cumulative alpha"))))
}
updateSelectInput(session, "asf", selected=x$asf)
updateNumericInput(session, "deltaAlpha", value=x$deltaAlpha)
updateNumericInput(session, "gammaAlpha", value=x$gammaAlpha)
updateSelectInput(session, "bsf", selected=x$bsf)
updateNumericInput(session, "deltaBeta", value=x$deltaBeta)
updateNumericInput(session, "gammaBeta", value=x$gammaBeta)
updateMatrixInput(session, "survival", value=x$survival)
updateMatrixInput(session, "accrual", value=x$accrual)
updateMatrixInput(session, "dropout", value=x$dropout)
updateSelectInput(session, "plottype", selected=x$plottype)
updateSelectInput(session, "plottype2", selected=x$plottype2)
updateMatrixInput(session, "boundaries", value=x$boundaries)
updateNumericInput(session, "nIterations", value=x$nIterations)
updateNumericInput(session, "nRawDatasets", value=x$nRawDatasets)
updateNumericInput(session, "seed", value=x$seed)
})
}
# Run the application
shinyApp(ui = ui, server = server)
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