extras/secondaryOutcomePlotting.r
In ohdsi-studies/TicagrelorVsClopidogrel: A Package Skeleton for Comparative Effectiveness Studies
library(forestplot)
library(dplyr)
outputFolder<-""
analysisSummary <- read.csv(file.path(outputFolder,"cohort_method_result.csv"),stringsAsFactors = FALSE)
analysis <- read.csv(file.path(outputFolder,"cohort_method_analysis.csv"),stringsAsFactors = FALSE)
outcomes <- read.csv(file.path(outputFolder,"outcome_of_interest.csv"),stringsAsFactors = FALSE)
#covBal <- read.csv(file.path(outputFolder,"covariate_balance.csv"),stringsAsFactors = FALSE)
#Camel To Snake
colnames(analysisSummary)<-SqlRender::snakeCaseToCamelCase(colnames(analysisSummary))
colnames(analysis)<-SqlRender::snakeCaseToCamelCase(colnames(analysis))
colnames(outcomes)<-SqlRender::snakeCaseToCamelCase(colnames(outcomes))
#colnames(covBal)<-SqlRender::snakeCaseToCamelCase(colnames(covBal))
outcomeOfInterest <- outcomes$outcomeId
outcomeNameOfInterest <- c("NACE","IschemicEvent","ischemicStroke","Revascularization","AMI",
"HemorrhagicEvent","hemorrhagicStroke","giBleeding",
"anyDeath","dyspnea")
outcomeIdOfInterest<-outcomes$outcomeId[outcomes$outcomeName %in% outcomeNameOfInterest]
outcomeIdOrder<-outcomes$outcomeId [match(outcomeNameOfInterest,outcomes$outcomeName)]
outcomeNameOfInterestNarrow <- c("NACE_narrow","IschemicEvent_narrow","ischemicStroke_narrow","AMI_narrow",
"HemorrhagicEvent_narrow","ICH_narrow","giBleeding_narrow")
outcomeNameOrder <- c("Net Adverse Clinical Event",
"Ischemic event",
"Ischemic stroke",
"Revascularization",
"Acute MI",
"Hemorrhagic Event",
"Hemorrhagic stroke",
"GI bleeding",
"Any death",
"Dyspnea")
analysisIds <- analysis$analysisId
analysisIdsOfInterest <- c(1,2,3,4,7,8,9,10,11,12,13,1142)
analysisIdOrder <- c(1,2,4,
7,8,13,
10,11,1142,
3,9,12)
# ##Trim strings for outcome Name
# analysisSummary$outcomeName <- gsub("SCYou:","",analysisSummary$outcomeName)
# analysisSummary$outcomeName <- gsub("outcome","",analysisSummary$outcomeName)
# analysisSummary$outcomeName <- gsub("and primary condition and first event","",analysisSummary$outcomeName)
# analysisSummary$outcomeName <- gsub("and primary condition and all event","",analysisSummary$outcomeName)
# analysisSummary$outcomeName <- gsub("inpatient or ED","",analysisSummary$outcomeName)
# analysisSummary$outcomeName <- gsub(")","",analysisSummary$outcomeName)
# analysisSummary$outcomeName <- gsub('\\(',"",analysisSummary$outcomeName)
# analysisSummary$outcomeName <- trimws(analysisSummary$outcomeName)
#
# ##Trim strings for analysis Name
# analysisSummary$analysisDescription <- gsub("Time To First Post Index Event ","",analysisSummary$analysisDescription)
# analysisSummary$analysisDescription <- gsub("Time to First Post Index Event ","",analysisSummary$analysisDescription)
for(analysisIdOfInterest in analysisIds){
#analysisIdOfInterest <- analysisIds[1]
#analysisIdOfInterest=6
data <- analysisSummary %>%
filter (analysisId == analysisIdOfInterest) %>%
filter (outcomeId %in% outcomeIdOfInterest) %>%
filter (targetId == 874 & comparatorId == 929 )
#reorder the data according to the outcome order
data <- data[ match(outcomeIdOrder,data$outcomeId),]
data$outcomeName <- outcomeNameOrder
tabletext <- cbind(
c("Outcome","\n",as.character(data$outcomeName)),
c(sprintf("Target (n= %d)", data$targetSubjects[1]),"Event Rate, %/yr",
sprintf("%.2f",data$targetOutcomes/data$targetDays*100*365) ),
#c("\n","Mean followup days", round(data$targetDays/data$target,0)),
c(sprintf("Comparator (n= %d)", data$comparatorSubjects[1]),"Event Rate, %/yr",
sprintf("%.2f",data$comparatorOutcomes/data$comparatorDays*100*365)),
#c("\n","Mean followup days", round(data$comparatorDays/data$comparator,0)),
c( "HR","(95% CI)", sprintf("%.2f \n (%.2f-%.2f)",data$rr, data$ci95Lb, data$ci95Ub) ),
c(paste0("P"," value"),"\n", sprintf("%.3f",data$p) )
)
try({
tiff(file.path(outputFolder,paste0("forestplot_Analysis",analysisIdOfInterest,".tiff")), width = 1050, height =600)
forestplot::forestplot(labeltext=tabletext,
graph.pos=5,
graphwidth = unit(60,'mm'),
mean=c(NA,NA,data$rr),
lower=c(NA,NA,data$ci95Lb), upper=c(NA,NA,data$ci95Ub),
title=analysis$description[analysis$analysisId==analysisIdOfInterest],
xlab="<--Ticagrelor Better-- --Clopidogrel Better--->",
xlog = TRUE,
clip=c(0.5,2.0),
#xticks = c(0.5,1.0,2.0),
# hrzl_lines=list("3" = gpar(lwd=1, col="#99999922"),
# "5" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "7" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "23" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "31" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922")
#),
txt_gp=fpTxtGp(label=gpar(cex=1.1),
ticks=gpar(cex=1.1),
xlab=gpar(cex = 1.2),
title=gpar(cex = 1.2)),
col=fpColors(box="black", lines="black", zero = "gray50"),
zero=1, cex=0.9, lineheight = "auto", boxsize=0.2, colgap=unit(6,"mm"),
lwd.ci=2, ci.vertices=TRUE, ci.vertices.height = 0.2
)
dev.off()
})
}
#From 2013 to 2015
for(analysisIdOfInterest in analysisIds){
#From 2013 to 2015
data <- analysisSummary %>%
filter (analysisId == analysisIdOfInterest) %>%
filter (outcomeName %in% outcomeNameOfInterest) %>%
filter (targetId == 1253 & comparatorId == 1254 )
#reorder the data according to the outcome order
data <- data[ match(outcomeNameOfInterest,data$outcomeName),]
tabletext <- cbind(
c("Outcome","\n",as.character(data$outcomeName)),
c(sprintf("Target (n= %d)", data$target[1]),"Event Rate, %/yr",sprintf("%.2f",data$eventsTarget/data$targetDays*100*365) ),
#c("\n","Mean followup days", round(data$targetDays/data$target,0)),
c(sprintf("Comparator (n= %d)", data$comparator[1]),"Event Rate, %/yr",sprintf("%.2f",data$eventsComparator/data$comparatorDays*100*365)),
#c("\n","Mean followup days", round(data$comparatorDays/data$comparator,0)),
c( "HR","(95% CI)", sprintf("%.2f \n (%.2f-%.2f)",data$rr, data$ci95lb, data$ci95ub) ),
c(paste0("P"," value"),"\n", sprintf("%.3f",data$p) )
)
try({
tiff(file.path(outputFolder,paste0("forestplot_Analysis_2013_2015",analysisIdOfInterest,".tiff")), width = 1050, height =600)
forestplot::forestplot(labeltext=tabletext,
graph.pos=5,
graphwidth = unit(60,'mm'),
mean=c(NA,NA,data$rr),
lower=c(NA,NA,data$ci95lb), upper=c(NA,NA,data$ci95ub),
title=data$analysisDescription[1],
xlab="<--Ticagrelor Better-- --Clopidogrel Better--->",
xlog = TRUE,
clip=c(0.5,2.0),
#xticks = c(0.5,1.0,2.0),
# hrzl_lines=list("3" = gpar(lwd=1, col="#99999922"),
# "5" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "7" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "23" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "31" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922")
#),
txt_gp=fpTxtGp(label=gpar(cex=1.1),
ticks=gpar(cex=1.1),
xlab=gpar(cex = 1.2),
title=gpar(cex = 1.2)),
col=fpColors(box="black", lines="black", zero = "gray50"),
zero=1, cex=0.9, lineheight = "auto", boxsize=0.2, colgap=unit(6,"mm"),
lwd.ci=2, ci.vertices=TRUE, ci.vertices.height = 0.2
)
dev.off()
})
}
#From 2013 to 2015
for(analysisIdOfInterest in analysisIds){
##Narrow definition
data <- analysisSummary %>%
filter (analysisId == analysisIdOfInterest) %>%
filter (outcomeName %in% outcomeNameOfInterestNarrow)%>%
filter (targetId == 874 & comparatorId == 929 )
#reorder the data according to the outcome order
data <- data[ match(outcomeNameOfInterestNarrow,data$outcomeName),]
tabletext <- cbind(
c("Outcome","\n",as.character(data$outcomeName)),
c(sprintf("Target (n= %d)", data$target[1]),"Event Rate, %/yr",sprintf("%.2f",data$eventsTarget/data$targetDays*100*365) ),
#c("\n","Mean followup days", round(data$targetDays/data$target,0)),
c(sprintf("Comparator (n= %d)", data$comparator[1]),"Event Rate, %/yr",sprintf("%.2f",data$eventsComparator/data$comparatorDays*100*365)),
#c("\n","Mean followup days", round(data$comparatorDays/data$comparator,0)),
c( "HR","(95% CI)", sprintf("%.2f \n (%.2f-%.2f)",data$rr, data$ci95lb, data$ci95ub) ),
c(paste0("P"," value"),"\n", sprintf("%.3f",data$p) )
)
try({
tiff(file.path(outputFolder,paste0("forestplot_Analysis_Narrow",analysisIdOfInterest,".tiff")), width = 1050, height =600)
forestplot::forestplot(labeltext=tabletext,
graph.pos=5,
graphwidth = unit(60,'mm'),
mean=c(NA,NA,data$rr),
lower=c(NA,NA,data$ci95lb), upper=c(NA,NA,data$ci95ub),
title=data$analysisDescription[1],
xlab="<--Ticagrelor Better-- --Clopidogrel Better--->",
xlog = TRUE,
clip=c(0.5,2.0),
#xticks = c(0.5,1.0,2.0),
# hrzl_lines=list("3" = gpar(lwd=1, col="#99999922"),
# "5" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "7" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "23" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "31" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922")
#),
txt_gp=fpTxtGp(label=gpar(cex=1.1),
ticks=gpar(cex=1.1),
xlab=gpar(cex = 1.2),
title=gpar(cex = 1.2)),
col=fpColors(box="black", lines="black", zero = "gray50"),
zero=1, cex=0.9, lineheight = "auto", boxsize=0.2, colgap=unit(6,"mm"),
lwd.ci=2, ci.vertices=TRUE, ci.vertices.height = 0.2
)
dev.off()
})
}
for(outcomeIdSp in outcomeOfInterest){
#outcomeIdSp <- outcomeOfInterest[2]
data <- analysisSummary %>%
filter (outcomeId == outcomeIdSp) %>%
filter (analysisId %in% analysisIdsOfInterest) %>%
filter (targetId == 874 & comparatorId == 929 )
data <- data[ match(analysisIdOrder,data$analysisId),]
tabletext <- cbind(
c("Analysis","\n",as.character(analysis$description[match(analysisIdOrder,analysis$analysisId)])),
c(sprintf("Target (n= %d)", data$targetSubjects[1]),"Event Rate, %/yr",
sprintf("%.2f",data$targetOutcomes/data$targetDays*100*365) ),
#c("\n","Mean followup days", round(data$targetDays/data$target,0)),
c(sprintf("Comparator (n= %d)", data$comparatorSubjects[1]),"Event Rate, %/yr",
sprintf("%.2f",data$comparatorOutcomes/data$comparatorDays*100*365)),
#c("\n","Mean followup days", round(data$comparatorDays/data$comparator,0)),
c( "HR","(95% CI)", sprintf("%.2f \n (%.2f-%.2f)",data$rr, data$ci95Lb, data$ci95Ub) ),
c(paste0("P"," value"),"\n", sprintf("%.3f",data$p) )
)
try({
tiff(file.path(outputFolder,paste0("forestplot_Outcome",outcomes$outcomeName[outcomes$outcomeId==outcomeIdSp],".tiff")), width = 1300, height =600)
forestplot::forestplot(labeltext=tabletext,
graph.pos=5,
graphwidth = unit(60,'mm'),
mean=c(NA,NA,data$rr),
lower=c(NA,NA,data$ci95Lb), upper=c(NA,NA,data$ci95Ub),
title=outcomes$outcomeName[outcomes$outcomeId==outcomeIdSp],
xlab="<--Ticagrelor Better-- --Clopidogrel Better--->",
xlog = TRUE,
clip=c(0.5,2.0),
#xticks = c(0.5,1.0,2.0),
# hrzl_lines=list("3" = gpar(lwd=1, col="#99999922"),
# "5" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "7" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "23" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "31" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922")
#),
txt_gp=fpTxtGp(label=gpar(cex=1.1),
ticks=gpar(cex=1.1),
xlab=gpar(cex = 1.2),
title=gpar(cex = 1.2)),
col=fpColors(box="black", lines="black", zero = "gray50"),
zero=1, cex=0.9, lineheight = "auto", boxsize=0.2, colgap=unit(6,"mm"),
lwd.ci=2, ci.vertices=TRUE, ci.vertices.height = 0.2
)
dev.off()
})
}
outputFolder<-"/Users/chan/OneDrive/Study/Ticagrelor/Result/181119"
cmOutput<-file.path(outputFolder, "cmOutput")
analysisSummary<-read.csv(file.path(outputFolder,"analysisSummary.csv"),stringsAsFactors =F)
outcomeOfInterest<-unique(analysisSummary$outcomeId[grepl("SCYou",analysisSummary$outcomeName)])
outcomeOrder <- c("Net Adverse Clinical Event",
"Ischemic event",
"Ischemic stroke",
"Revascularization",
"Acute myocardial infarction",
"Hemorrhagic Event",
"Intracranial hemorrhage",
"GI bleeding",
"SuddenCardiacDeath")
##Trim strings for outcome Name
analysisSummary$outcomeName <- gsub("SCYou:","",analysisSummary$outcomeName)
analysisSummary$outcomeName <- gsub("SCYou","",analysisSummary$outcomeName)
analysisSummary$outcomeName <- gsub("outcome","",analysisSummary$outcomeName)
analysisSummary$outcomeName <- gsub("\\[","",analysisSummary$outcomeName)
analysisSummary$outcomeName <- gsub("]","",analysisSummary$outcomeName)
analysisSummary$outcomeName <- gsub(")","",analysisSummary$outcomeName)
analysisSummary$outcomeName <- gsub('\\(',"",analysisSummary$outcomeName)
analysisSummary$outcomeName <- trimws(analysisSummary$outcomeName)
##Trim strings for analysis Name
analysisSummary$analysisDescription <- gsub("Time To First Post Index Event ","",analysisSummary$analysisDescription)
analysisSummary$analysisDescription <- gsub("Time to First Post Index Event ","",analysisSummary$analysisDescription)
for(analysisIdOfInterest in analysisIds){
#analysisIdOfInterest <- analysisIds[1]
data <- analysisSummary %>%
filter (analysisId == analysisIdOfInterest) %>%
filter (outcomeId %in% outcomeOfInterest) %>%
filter (targetId == 874 & comparatorId == 929 )
#reorder the data according to the outcome order
data <- data[ match(outcomeOrder,data$outcomeName),]
tabletext <- cbind(
c("Outcome","\n",as.character(data$outcomeName)),
c(sprintf("Target (n= %d)", data$target[1]),"Event Rate, %/yr",sprintf("%.2f",data$eventsTarget/data$targetDays*100*365,1) ),
#c("\n","Mean followup days", round(data$targetDays/data$target,0)),
c(sprintf("Comparator (n= %d)", data$comparator[1]),"Event Rate, %/yr",sprintf("%.2f",data$eventsComparator/data$comparatorDays*100*365,1)),
#c("\n","Mean followup days", round(data$comparatorDays/data$comparator,0)),
c( "HR","(95% CI)", sprintf("%.2f \n (%.2f-%.2f)",data$rr, data$ci95lb, data$ci95ub) ),
c(paste0("P"," value"),"\n", sprintf("%.3f",data$p) )
)
try({
tiff(file.path(outputFolder,paste0("forestplot_Analysis",analysisIdOfInterest,".tiff")), width = 1050, height =600)
forestplot::forestplot(labeltext=tabletext,
graph.pos=5,
graphwidth = unit(60,'mm'),
mean=c(NA,NA,data$rr),
lower=c(NA,NA,data$ci95lb), upper=c(NA,NA,data$ci95ub),
title=data$analysisDescription[1],
xlab="<--Ticagrelor Better-- --Clopidogrel Better--->",
xlog = TRUE,
clip=c(0.5,2.0),
#xticks = c(0.5,1.0,2.0),
# hrzl_lines=list("3" = gpar(lwd=1, col="#99999922"),
# "5" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "7" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "23" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "31" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922")
#),
txt_gp=fpTxtGp(label=gpar(cex=1.1),
ticks=gpar(cex=1.1),
xlab=gpar(cex = 1.2),
title=gpar(cex = 1.2)),
col=fpColors(box="black", lines="black", zero = "gray50"),
zero=1, cex=0.9, lineheight = "auto", boxsize=0.2, colgap=unit(6,"mm"),
lwd.ci=2, ci.vertices=TRUE, ci.vertices.height = 0.2
)
dev.off()
})
}
for(outcomeIdSp in outcomeOfInterest){
#outcomeIdSp <- outcomeOfInterest[3]
data <- analysisSummary %>%
filter (outcomeId == outcomeIdSp) %>%
filter (analysisId %in% analysisIds)
tabletext <- cbind(
c("Analysis","\n",as.character(data$analysisDescription)),
c("Cumulative outcome \n /Target population", "(%/year)", sprintf("%d/%d \n %.2f", data$eventsTarget,data$target,data$eventsTarget/data$targetDays*100*365)),
c("Cumulative outcome \n /Comparator population", "(%/year)", sprintf("%d/%d \n %.2f", data$eventsComparator,data$comparator,data$eventsComparator/data$comparatorDays*100*365)),
#c("\n","Mean followup days", round(data$comparatorDays/data$comparator,0)),
c( "HR","(95% CI)", sprintf("%.2f \n (%.2f-%.2f)",data$rr, data$ci95lb, data$ci95ub) ),
c(paste0("P"," value"),"\n", sprintf("%.3f",data$p) )
)
try({
tiff(file.path(outputFolder,paste0("forestplot_Outcome",outcomeIdSp,".tiff")), width = 1300, height =600)
forestplot::forestplot(labeltext=tabletext,
graph.pos=5,
graphwidth = unit(60,'mm'),
mean=c(NA,NA,data$rr),
lower=c(NA,NA,data$ci95lb), upper=c(NA,NA,data$ci95ub),
title=data$outcomeName[1],
xlab="<--Ticagrelor Better-- --Clopidogrel Better--->",
xlog = TRUE,
clip=c(0.5,2.0),
#xticks = c(0.5,1.0,2.0),
# hrzl_lines=list("3" = gpar(lwd=1, col="#99999922"),
# "5" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "7" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "23" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "31" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922")
#),
txt_gp=fpTxtGp(label=gpar(cex=1.1),
ticks=gpar(cex=1.1),
xlab=gpar(cex = 1.2),
title=gpar(cex = 1.2)),
col=fpColors(box="black", lines="black", zero = "gray50"),
zero=1, cex=0.9, lineheight = "auto", boxsize=0.2, colgap=unit(6,"mm"),
lwd.ci=2, ci.vertices=TRUE, ci.vertices.height = 0.2
)
dev.off()
})
}
ohdsi-studies/TicagrelorVsClopidogrel documentation built on Oct. 13, 2020, 4:48 a.m.
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library(forestplot)
library(dplyr)
outputFolder<-""
analysisSummary <- read.csv(file.path(outputFolder,"cohort_method_result.csv"),stringsAsFactors = FALSE)
analysis <- read.csv(file.path(outputFolder,"cohort_method_analysis.csv"),stringsAsFactors = FALSE)
outcomes <- read.csv(file.path(outputFolder,"outcome_of_interest.csv"),stringsAsFactors = FALSE)
#covBal <- read.csv(file.path(outputFolder,"covariate_balance.csv"),stringsAsFactors = FALSE)
#Camel To Snake
colnames(analysisSummary)<-SqlRender::snakeCaseToCamelCase(colnames(analysisSummary))
colnames(analysis)<-SqlRender::snakeCaseToCamelCase(colnames(analysis))
colnames(outcomes)<-SqlRender::snakeCaseToCamelCase(colnames(outcomes))
#colnames(covBal)<-SqlRender::snakeCaseToCamelCase(colnames(covBal))
outcomeOfInterest <- outcomes$outcomeId
outcomeNameOfInterest <- c("NACE","IschemicEvent","ischemicStroke","Revascularization","AMI",
"HemorrhagicEvent","hemorrhagicStroke","giBleeding",
"anyDeath","dyspnea")
outcomeIdOfInterest<-outcomes$outcomeId[outcomes$outcomeName %in% outcomeNameOfInterest]
outcomeIdOrder<-outcomes$outcomeId [match(outcomeNameOfInterest,outcomes$outcomeName)]
outcomeNameOfInterestNarrow <- c("NACE_narrow","IschemicEvent_narrow","ischemicStroke_narrow","AMI_narrow",
"HemorrhagicEvent_narrow","ICH_narrow","giBleeding_narrow")
outcomeNameOrder <- c("Net Adverse Clinical Event",
"Ischemic event",
"Ischemic stroke",
"Revascularization",
"Acute MI",
"Hemorrhagic Event",
"Hemorrhagic stroke",
"GI bleeding",
"Any death",
"Dyspnea")
analysisIds <- analysis$analysisId
analysisIdsOfInterest <- c(1,2,3,4,7,8,9,10,11,12,13,1142)
analysisIdOrder <- c(1,2,4,
7,8,13,
10,11,1142,
3,9,12)
# ##Trim strings for outcome Name
# analysisSummary$outcomeName <- gsub("SCYou:","",analysisSummary$outcomeName)
# analysisSummary$outcomeName <- gsub("outcome","",analysisSummary$outcomeName)
# analysisSummary$outcomeName <- gsub("and primary condition and first event","",analysisSummary$outcomeName)
# analysisSummary$outcomeName <- gsub("and primary condition and all event","",analysisSummary$outcomeName)
# analysisSummary$outcomeName <- gsub("inpatient or ED","",analysisSummary$outcomeName)
# analysisSummary$outcomeName <- gsub(")","",analysisSummary$outcomeName)
# analysisSummary$outcomeName <- gsub('\\(',"",analysisSummary$outcomeName)
# analysisSummary$outcomeName <- trimws(analysisSummary$outcomeName)
#
# ##Trim strings for analysis Name
# analysisSummary$analysisDescription <- gsub("Time To First Post Index Event ","",analysisSummary$analysisDescription)
# analysisSummary$analysisDescription <- gsub("Time to First Post Index Event ","",analysisSummary$analysisDescription)
for(analysisIdOfInterest in analysisIds){
#analysisIdOfInterest <- analysisIds[1]
#analysisIdOfInterest=6
data <- analysisSummary %>%
filter (analysisId == analysisIdOfInterest) %>%
filter (outcomeId %in% outcomeIdOfInterest) %>%
filter (targetId == 874 & comparatorId == 929 )
#reorder the data according to the outcome order
data <- data[ match(outcomeIdOrder,data$outcomeId),]
data$outcomeName <- outcomeNameOrder
tabletext <- cbind(
c("Outcome","\n",as.character(data$outcomeName)),
c(sprintf("Target (n= %d)", data$targetSubjects[1]),"Event Rate, %/yr",
sprintf("%.2f",data$targetOutcomes/data$targetDays*100*365) ),
#c("\n","Mean followup days", round(data$targetDays/data$target,0)),
c(sprintf("Comparator (n= %d)", data$comparatorSubjects[1]),"Event Rate, %/yr",
sprintf("%.2f",data$comparatorOutcomes/data$comparatorDays*100*365)),
#c("\n","Mean followup days", round(data$comparatorDays/data$comparator,0)),
c( "HR","(95% CI)", sprintf("%.2f \n (%.2f-%.2f)",data$rr, data$ci95Lb, data$ci95Ub) ),
c(paste0("P"," value"),"\n", sprintf("%.3f",data$p) )
)
try({
tiff(file.path(outputFolder,paste0("forestplot_Analysis",analysisIdOfInterest,".tiff")), width = 1050, height =600)
forestplot::forestplot(labeltext=tabletext,
graph.pos=5,
graphwidth = unit(60,'mm'),
mean=c(NA,NA,data$rr),
lower=c(NA,NA,data$ci95Lb), upper=c(NA,NA,data$ci95Ub),
title=analysis$description[analysis$analysisId==analysisIdOfInterest],
xlab="<--Ticagrelor Better-- --Clopidogrel Better--->",
xlog = TRUE,
clip=c(0.5,2.0),
#xticks = c(0.5,1.0,2.0),
# hrzl_lines=list("3" = gpar(lwd=1, col="#99999922"),
# "5" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "7" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "23" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "31" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922")
#),
txt_gp=fpTxtGp(label=gpar(cex=1.1),
ticks=gpar(cex=1.1),
xlab=gpar(cex = 1.2),
title=gpar(cex = 1.2)),
col=fpColors(box="black", lines="black", zero = "gray50"),
zero=1, cex=0.9, lineheight = "auto", boxsize=0.2, colgap=unit(6,"mm"),
lwd.ci=2, ci.vertices=TRUE, ci.vertices.height = 0.2
)
dev.off()
})
}
#From 2013 to 2015
for(analysisIdOfInterest in analysisIds){
#From 2013 to 2015
data <- analysisSummary %>%
filter (analysisId == analysisIdOfInterest) %>%
filter (outcomeName %in% outcomeNameOfInterest) %>%
filter (targetId == 1253 & comparatorId == 1254 )
#reorder the data according to the outcome order
data <- data[ match(outcomeNameOfInterest,data$outcomeName),]
tabletext <- cbind(
c("Outcome","\n",as.character(data$outcomeName)),
c(sprintf("Target (n= %d)", data$target[1]),"Event Rate, %/yr",sprintf("%.2f",data$eventsTarget/data$targetDays*100*365) ),
#c("\n","Mean followup days", round(data$targetDays/data$target,0)),
c(sprintf("Comparator (n= %d)", data$comparator[1]),"Event Rate, %/yr",sprintf("%.2f",data$eventsComparator/data$comparatorDays*100*365)),
#c("\n","Mean followup days", round(data$comparatorDays/data$comparator,0)),
c( "HR","(95% CI)", sprintf("%.2f \n (%.2f-%.2f)",data$rr, data$ci95lb, data$ci95ub) ),
c(paste0("P"," value"),"\n", sprintf("%.3f",data$p) )
)
try({
tiff(file.path(outputFolder,paste0("forestplot_Analysis_2013_2015",analysisIdOfInterest,".tiff")), width = 1050, height =600)
forestplot::forestplot(labeltext=tabletext,
graph.pos=5,
graphwidth = unit(60,'mm'),
mean=c(NA,NA,data$rr),
lower=c(NA,NA,data$ci95lb), upper=c(NA,NA,data$ci95ub),
title=data$analysisDescription[1],
xlab="<--Ticagrelor Better-- --Clopidogrel Better--->",
xlog = TRUE,
clip=c(0.5,2.0),
#xticks = c(0.5,1.0,2.0),
# hrzl_lines=list("3" = gpar(lwd=1, col="#99999922"),
# "5" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "7" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "23" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "31" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922")
#),
txt_gp=fpTxtGp(label=gpar(cex=1.1),
ticks=gpar(cex=1.1),
xlab=gpar(cex = 1.2),
title=gpar(cex = 1.2)),
col=fpColors(box="black", lines="black", zero = "gray50"),
zero=1, cex=0.9, lineheight = "auto", boxsize=0.2, colgap=unit(6,"mm"),
lwd.ci=2, ci.vertices=TRUE, ci.vertices.height = 0.2
)
dev.off()
})
}
#From 2013 to 2015
for(analysisIdOfInterest in analysisIds){
##Narrow definition
data <- analysisSummary %>%
filter (analysisId == analysisIdOfInterest) %>%
filter (outcomeName %in% outcomeNameOfInterestNarrow)%>%
filter (targetId == 874 & comparatorId == 929 )
#reorder the data according to the outcome order
data <- data[ match(outcomeNameOfInterestNarrow,data$outcomeName),]
tabletext <- cbind(
c("Outcome","\n",as.character(data$outcomeName)),
c(sprintf("Target (n= %d)", data$target[1]),"Event Rate, %/yr",sprintf("%.2f",data$eventsTarget/data$targetDays*100*365) ),
#c("\n","Mean followup days", round(data$targetDays/data$target,0)),
c(sprintf("Comparator (n= %d)", data$comparator[1]),"Event Rate, %/yr",sprintf("%.2f",data$eventsComparator/data$comparatorDays*100*365)),
#c("\n","Mean followup days", round(data$comparatorDays/data$comparator,0)),
c( "HR","(95% CI)", sprintf("%.2f \n (%.2f-%.2f)",data$rr, data$ci95lb, data$ci95ub) ),
c(paste0("P"," value"),"\n", sprintf("%.3f",data$p) )
)
try({
tiff(file.path(outputFolder,paste0("forestplot_Analysis_Narrow",analysisIdOfInterest,".tiff")), width = 1050, height =600)
forestplot::forestplot(labeltext=tabletext,
graph.pos=5,
graphwidth = unit(60,'mm'),
mean=c(NA,NA,data$rr),
lower=c(NA,NA,data$ci95lb), upper=c(NA,NA,data$ci95ub),
title=data$analysisDescription[1],
xlab="<--Ticagrelor Better-- --Clopidogrel Better--->",
xlog = TRUE,
clip=c(0.5,2.0),
#xticks = c(0.5,1.0,2.0),
# hrzl_lines=list("3" = gpar(lwd=1, col="#99999922"),
# "5" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "7" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "23" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "31" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922")
#),
txt_gp=fpTxtGp(label=gpar(cex=1.1),
ticks=gpar(cex=1.1),
xlab=gpar(cex = 1.2),
title=gpar(cex = 1.2)),
col=fpColors(box="black", lines="black", zero = "gray50"),
zero=1, cex=0.9, lineheight = "auto", boxsize=0.2, colgap=unit(6,"mm"),
lwd.ci=2, ci.vertices=TRUE, ci.vertices.height = 0.2
)
dev.off()
})
}
for(outcomeIdSp in outcomeOfInterest){
#outcomeIdSp <- outcomeOfInterest[2]
data <- analysisSummary %>%
filter (outcomeId == outcomeIdSp) %>%
filter (analysisId %in% analysisIdsOfInterest) %>%
filter (targetId == 874 & comparatorId == 929 )
data <- data[ match(analysisIdOrder,data$analysisId),]
tabletext <- cbind(
c("Analysis","\n",as.character(analysis$description[match(analysisIdOrder,analysis$analysisId)])),
c(sprintf("Target (n= %d)", data$targetSubjects[1]),"Event Rate, %/yr",
sprintf("%.2f",data$targetOutcomes/data$targetDays*100*365) ),
#c("\n","Mean followup days", round(data$targetDays/data$target,0)),
c(sprintf("Comparator (n= %d)", data$comparatorSubjects[1]),"Event Rate, %/yr",
sprintf("%.2f",data$comparatorOutcomes/data$comparatorDays*100*365)),
#c("\n","Mean followup days", round(data$comparatorDays/data$comparator,0)),
c( "HR","(95% CI)", sprintf("%.2f \n (%.2f-%.2f)",data$rr, data$ci95Lb, data$ci95Ub) ),
c(paste0("P"," value"),"\n", sprintf("%.3f",data$p) )
)
try({
tiff(file.path(outputFolder,paste0("forestplot_Outcome",outcomes$outcomeName[outcomes$outcomeId==outcomeIdSp],".tiff")), width = 1300, height =600)
forestplot::forestplot(labeltext=tabletext,
graph.pos=5,
graphwidth = unit(60,'mm'),
mean=c(NA,NA,data$rr),
lower=c(NA,NA,data$ci95Lb), upper=c(NA,NA,data$ci95Ub),
title=outcomes$outcomeName[outcomes$outcomeId==outcomeIdSp],
xlab="<--Ticagrelor Better-- --Clopidogrel Better--->",
xlog = TRUE,
clip=c(0.5,2.0),
#xticks = c(0.5,1.0,2.0),
# hrzl_lines=list("3" = gpar(lwd=1, col="#99999922"),
# "5" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "7" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "23" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "31" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922")
#),
txt_gp=fpTxtGp(label=gpar(cex=1.1),
ticks=gpar(cex=1.1),
xlab=gpar(cex = 1.2),
title=gpar(cex = 1.2)),
col=fpColors(box="black", lines="black", zero = "gray50"),
zero=1, cex=0.9, lineheight = "auto", boxsize=0.2, colgap=unit(6,"mm"),
lwd.ci=2, ci.vertices=TRUE, ci.vertices.height = 0.2
)
dev.off()
})
}
outputFolder<-"/Users/chan/OneDrive/Study/Ticagrelor/Result/181119"
cmOutput<-file.path(outputFolder, "cmOutput")
analysisSummary<-read.csv(file.path(outputFolder,"analysisSummary.csv"),stringsAsFactors =F)
outcomeOfInterest<-unique(analysisSummary$outcomeId[grepl("SCYou",analysisSummary$outcomeName)])
outcomeOrder <- c("Net Adverse Clinical Event",
"Ischemic event",
"Ischemic stroke",
"Revascularization",
"Acute myocardial infarction",
"Hemorrhagic Event",
"Intracranial hemorrhage",
"GI bleeding",
"SuddenCardiacDeath")
##Trim strings for outcome Name
analysisSummary$outcomeName <- gsub("SCYou:","",analysisSummary$outcomeName)
analysisSummary$outcomeName <- gsub("SCYou","",analysisSummary$outcomeName)
analysisSummary$outcomeName <- gsub("outcome","",analysisSummary$outcomeName)
analysisSummary$outcomeName <- gsub("\\[","",analysisSummary$outcomeName)
analysisSummary$outcomeName <- gsub("]","",analysisSummary$outcomeName)
analysisSummary$outcomeName <- gsub(")","",analysisSummary$outcomeName)
analysisSummary$outcomeName <- gsub('\\(',"",analysisSummary$outcomeName)
analysisSummary$outcomeName <- trimws(analysisSummary$outcomeName)
##Trim strings for analysis Name
analysisSummary$analysisDescription <- gsub("Time To First Post Index Event ","",analysisSummary$analysisDescription)
analysisSummary$analysisDescription <- gsub("Time to First Post Index Event ","",analysisSummary$analysisDescription)
for(analysisIdOfInterest in analysisIds){
#analysisIdOfInterest <- analysisIds[1]
data <- analysisSummary %>%
filter (analysisId == analysisIdOfInterest) %>%
filter (outcomeId %in% outcomeOfInterest) %>%
filter (targetId == 874 & comparatorId == 929 )
#reorder the data according to the outcome order
data <- data[ match(outcomeOrder,data$outcomeName),]
tabletext <- cbind(
c("Outcome","\n",as.character(data$outcomeName)),
c(sprintf("Target (n= %d)", data$target[1]),"Event Rate, %/yr",sprintf("%.2f",data$eventsTarget/data$targetDays*100*365,1) ),
#c("\n","Mean followup days", round(data$targetDays/data$target,0)),
c(sprintf("Comparator (n= %d)", data$comparator[1]),"Event Rate, %/yr",sprintf("%.2f",data$eventsComparator/data$comparatorDays*100*365,1)),
#c("\n","Mean followup days", round(data$comparatorDays/data$comparator,0)),
c( "HR","(95% CI)", sprintf("%.2f \n (%.2f-%.2f)",data$rr, data$ci95lb, data$ci95ub) ),
c(paste0("P"," value"),"\n", sprintf("%.3f",data$p) )
)
try({
tiff(file.path(outputFolder,paste0("forestplot_Analysis",analysisIdOfInterest,".tiff")), width = 1050, height =600)
forestplot::forestplot(labeltext=tabletext,
graph.pos=5,
graphwidth = unit(60,'mm'),
mean=c(NA,NA,data$rr),
lower=c(NA,NA,data$ci95lb), upper=c(NA,NA,data$ci95ub),
title=data$analysisDescription[1],
xlab="<--Ticagrelor Better-- --Clopidogrel Better--->",
xlog = TRUE,
clip=c(0.5,2.0),
#xticks = c(0.5,1.0,2.0),
# hrzl_lines=list("3" = gpar(lwd=1, col="#99999922"),
# "5" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "7" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "23" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "31" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922")
#),
txt_gp=fpTxtGp(label=gpar(cex=1.1),
ticks=gpar(cex=1.1),
xlab=gpar(cex = 1.2),
title=gpar(cex = 1.2)),
col=fpColors(box="black", lines="black", zero = "gray50"),
zero=1, cex=0.9, lineheight = "auto", boxsize=0.2, colgap=unit(6,"mm"),
lwd.ci=2, ci.vertices=TRUE, ci.vertices.height = 0.2
)
dev.off()
})
}
for(outcomeIdSp in outcomeOfInterest){
#outcomeIdSp <- outcomeOfInterest[3]
data <- analysisSummary %>%
filter (outcomeId == outcomeIdSp) %>%
filter (analysisId %in% analysisIds)
tabletext <- cbind(
c("Analysis","\n",as.character(data$analysisDescription)),
c("Cumulative outcome \n /Target population", "(%/year)", sprintf("%d/%d \n %.2f", data$eventsTarget,data$target,data$eventsTarget/data$targetDays*100*365)),
c("Cumulative outcome \n /Comparator population", "(%/year)", sprintf("%d/%d \n %.2f", data$eventsComparator,data$comparator,data$eventsComparator/data$comparatorDays*100*365)),
#c("\n","Mean followup days", round(data$comparatorDays/data$comparator,0)),
c( "HR","(95% CI)", sprintf("%.2f \n (%.2f-%.2f)",data$rr, data$ci95lb, data$ci95ub) ),
c(paste0("P"," value"),"\n", sprintf("%.3f",data$p) )
)
try({
tiff(file.path(outputFolder,paste0("forestplot_Outcome",outcomeIdSp,".tiff")), width = 1300, height =600)
forestplot::forestplot(labeltext=tabletext,
graph.pos=5,
graphwidth = unit(60,'mm'),
mean=c(NA,NA,data$rr),
lower=c(NA,NA,data$ci95lb), upper=c(NA,NA,data$ci95ub),
title=data$outcomeName[1],
xlab="<--Ticagrelor Better-- --Clopidogrel Better--->",
xlog = TRUE,
clip=c(0.5,2.0),
#xticks = c(0.5,1.0,2.0),
# hrzl_lines=list("3" = gpar(lwd=1, col="#99999922"),
# "5" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "7" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "23" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922"),
# "31" = gpar(lwd=60, lineend="butt", columns=c(2:6), col="#99999922")
#),
txt_gp=fpTxtGp(label=gpar(cex=1.1),
ticks=gpar(cex=1.1),
xlab=gpar(cex = 1.2),
title=gpar(cex = 1.2)),
col=fpColors(box="black", lines="black", zero = "gray50"),
zero=1, cex=0.9, lineheight = "auto", boxsize=0.2, colgap=unit(6,"mm"),
lwd.ci=2, ci.vertices=TRUE, ci.vertices.height = 0.2
)
dev.off()
})
}
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