### CHANCE OF REMISSION FOLLOWING A BREAKTHROUGH SEIZURE ###

library(cmprsk)
library(MASS)

# read in data #
rpat <- read.csv("Risk of Breakthrough Seizure.csv")

# arma data #
sdata <- subset(rpat,with.Arm=="CBZ")
sdatb <- subset(rpat,with.Arm=="VPS")

# Kaplan-Meier curve #
library(prodlim)
tiff(file="Fig 2.tiff",width=2250,heigh=2625,units="px",res=300)
ttime <- rpat$ttbs.bttime/365
fit <- prodlim(Surv(ttime,ttbs.btcens)~1,data=rpat)
plot(fit,type="cuminc",percent=FALSE,background=FALSE,lwd=0.7,atRisk.dist=1,xlab="Time from achieving 12-month remission (years)",ylab="Probability of Breakthrough Seizure",confint=FALSE,legend.x=0,legend.y=1,atrisk.labels="No. at risk:",atRisk.times=c(0,1,2,3,4,5),atRisk.adjust.labels=FALSE)
dev.off()

# Risk of a breakthrough seizure 2 years following remission #
summary(fit,times=2)

## Patient Characteristics ##
# No. breakthrough seizures #
sum(rpat$ttbs.btcens)

# Time to breakthrough #
btpeeps <- subset(rpat,ttbs.btcens==1)
summary(btpeeps$ttbs.bttime/365)

# Duration of follow-up after acheiving 12 month remission #
summary((rpat$lastfup.dlfu-(rpat$all.rand+rpat$rem.Remtime))/365)

# Median time to breakthrough seizure #
summary(sdata$ttbs.bttime/365)
summary(sdatb$ttbs.bttime/365)
summary(rpat$ttbs.bttime/365)

# Gender #
table(sdata$all.sex)
prop.table(table(sdata$all.sex))
table(sdatb$all.sex)
prop.table(table(sdatb$all.sex))
table(rpat$all.sex)
prop.table(table(rpat$all.sex))

# Febrile Seizure History #
table(sdata$all.feb)
prop.table(table(sdata$all.feb))
table(sdatb$all.feb)
prop.table(table(sdatb$all.feb))
table(rpat$all.feb)
prop.table(table(rpat$all.feb))

# First degree relative #
table(sdata$all.rels)
prop.table(table(sdata$all.rels))
table(sdatb$all.rels)
prop.table(table(sdatb$all.rels))
table(rpat$all.rels)
prop.table(table(rpat$all.rels))

# Neurological Insult #
neuro <- function(data)
	{
	neuro <- rep(0,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.neur[i]=="Y")
	neuro[i] <- 1
	}
	return(neuro)
	}
neuroa <- neuro(sdata)
neurob <- neuro(sdatb)
neuroab <- neuro(rpat)
learn <- function(data)
	{
	learn <- rep(0,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.learn[i]=="Y")
	learn[i] <- 1
	}
	return(learn)
	}
learna <- learn(sdata)
learnb <- learn(sdatb)
learnab <- learn(rpat)
nsigna <- neuroa + learna
nsignb <- neurob + learnb
nsignab <- neuroab + learnab

nsign <- function(data)
	{
	nsign <- rep(-1/2,length(data))
	for(i in 1:length(data)){
	if(data[i]>0)
	nsign[i] <- 1/2
	}
	return(nsign)
	}
table(nsign(nsigna))
prop.table(table(nsign(nsigna)))
table(nsign(nsignb))
prop.table(table(nsign(nsignb)))
table(nsign(nsignab))
prop.table(table(nsign(nsignab)))

# Stype #
stype <- function(data) 
	{
	for(i in 1:nrow(data)){
	if(is.na(data$all.sp)[i])
	data$all.sp[i]<-0
	if(is.na(data$all.cp)[i])
	data$all.cp[i]<-0
	if(is.na(data$all.scgtc)[i])
	data$all.scgtc[i]<-0
	if(is.na(data$all.tc)[i])
	data$all.tc[i] <- 0
	if(is.na(data$all.ta)[i])
	data$all.ta[i] <- 0
	if(is.na(data$all.aa)[i])
	data$all.aa[i] <- 0
	if(is.na(data$all.m)[i])
	data$all.m[i] <- 0
	if(is.na(data$all.otc)[i])
	data$all.otc[i] <- 0
	if(is.na(data$all.o)[i])
	data$all.o[i] <- 0
	}
	stype <- rep(7,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.sp[i]>=1 && data$all.scgtc[i]==0)
	stype[i] <- 1
	if(data$all.cp[i]>=1  && data$all.scgtc[i]==0)
	stype[i] <- 1
	if(data$all.sp[i]>=1 && data$all.scgtc[i]>=1)
	stype[i] <- 2
	if(data$all.cp[i]>=1  && data$all.scgtc[i]>=1)
	stype[i] <- 2
	if(data$all.scgtc[i]>=1)
	stype[i] <- 2	
	if(data$all.tc[i]>=1 && data$all.aa[i]==0 && data$all.ta[i]==0 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- 3
	if(data$all.aa[i]>=1 && data$all.tc[i]==0 && data$all.ta[i]==0 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- 4
	if(data$all.ta[i]>=1 && data$all.tc[i]==0 && data$all.aa[i]==0 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- 4
	if(data$all.ta[i]>=1 && data$all.tc[i]==0 && data$all.aa[i]>=1 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- 4 
	if(data$all.m[i]>=1 && data$all.ta[i]>=1)
	stype[i] <- 4
	if(data$all.m[i]>=1 && data$all.aa[i]>=1)
	stype[i] <- 4
	if(data$all.aa[i]>=1 && data$all.tc[i]>=1)
	stype[i] <- 5
	if(data$all.m[i]>=1 && data$all.tc[i]>=1)
	stype[i] <- 5
	if(data$all.ta[i]>=1 && data$all.tc[i]>=1)
	stype[i] <- 5
	if(data$all.otc[i]>=1)
	stype[i] <- 6
	if(data$all.o[i]>=1)
	stype[i] <- 7
	}
	return(stype)
	}	
table(stype(sdata))
prop.table(table(stype(sdata)))
table(stype(sdatb))
prop.table(table(stype(sdatb)))
table(stype(rpat))
prop.table(table(stype(rpat)))

table(sdata$all.type)
prop.table(table(sdata$all.type))
table(sdatb$all.type)
prop.table(table(sdatb$all.type))
table(rpat$all.type)
prop.table(table(rpat$all.type))

eegfour <- function(data)
	{
	for(i in 1:nrow(data)){
	if(is.na(data$all.nonspecab)[i])
	data$all.nonspecab[i]<-"N"
	}
	eegfour <- rep(3,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.eegabnormal[i]=="NR")
	eegfour[i]<-1
	if(data$all.eegabnormal[i]=="N")
	eegfour[i]<-0
	if(data$all.eegabnormal[i]=="Y" && data$all.nonspecab[i]=="Y")
	eegfour[i]<-2
	}
	return(eegfour)
	}
# Normal = 0
# Non-spec = 2
# Abnorm = 3
# Not indicated = 1
table(eegfour(sdata))
prop.table(table(eegfour(sdata)))
table(eegfour(sdatb))
prop.table(table(eegfour(sdatb)))
table(eegfour(rpat))
prop.table(table(eegfour(rpat)))

# CT/MRI Scan Result #
table(sdata$all.ctabnormal)
prop.table(table(sdata$all.ctabnormal))
table(sdatb$all.ctabnormal)
prop.table(table(sdatb$all.ctabnormal))
table(rpat$all.ctabnormal)
prop.table(table(rpat$all.ctabnormal))

# Randomised treatment #
table(sdata$with.Treat)
prop.table(table(sdata$with.Treat))
table(sdatb$with.Treat)
prop.table(table(sdatb$with.Treat))
table(rpat$with.Treat)
prop.table(table(rpat$with.Treat))	

# Number of drugs to achieve remission #
mono <- function(data)
	{
	for(i in 1:nrow(data)){
	if(is.na(data$ttbs.nodrugs)[i])
	data$ttbs.nodrugs[i]<-0
	}
	mono <- rep(0,nrow(data))
	for(i in 1:nrow(data)){
	if(data$ttbs.nodrugs[i]<=1)
	mono[i] <- 0
	if(data$ttbs.nodrugs[i]>=2)
	mono[i] <- 1
	}
	return(mono)
	}
table(mono(sdata))
prop.table(table(mono(sdata)))
table(mono(sdatb))
prop.table(table(mono(sdatb)))
table(mono(rpat))
prop.table(table(mono(rpat)))

# Number t-c at achievement of remission #
summary(sdata$newtc)
summary(sdatb$newtc)
summary(rpat$newtc)

# Age at achievement of remission #
summary(sdata$newage)
summary(sdatb$newage)
summary(rpat$newage)

# Time to achieve 12 month remission #
summary(sdata$rem.Remtime/365)
summary(sdatb$rem.Remtime/365)
summary(rpat$rem.Remtime/365)

# Time on randomised (monotherapy) treatment #
summary(sdata$with.Withtime/365)
summary(sdatb$with.Withtime/365)
summary(rpat$with.Withtime/365)


## Univariable analysis ##

# Gender #
sind <- function(data)
	{
	sind <- rep(1/2,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.sex[i]=="F")
	sind[i] <- -1/2
	}
	return(sind)
	}
coxfita=coxph(Surv(ttbs.bttime,ttbs.btcens)~sind(rpat)+strata(with.Arm),data=rpat)
coxfita
exp(coxfita$coefficients)
exp(confint(coxfita))

# Febrile Seizure History # 
fsh <- function(data)
	{
	fsh <- rep(-1/2,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.feb[i]=="Y")
	fsh[i] <- 1/2
	}
	return(fsh)
	}
coxfita=coxph(Surv(ttbs.bttime,ttbs.btcens)~fsh(rpat)+strata(with.Arm),data=rpat)
coxfita
exp(coxfita$coefficients)
exp(confint(coxfita))

# First degree relative with epilepsy # 
fdr <- function(data)
	{
	fdr <- rep(-1/2,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.rels[i]=="Y")
	fdr[i] <- 1/2
	}
	return(fdr)
	}
coxfita=coxph(Surv(ttbs.bttime,ttbs.btcens)~fdr(rpat)+strata(with.Arm),data=rpat)
coxfita
exp(coxfita$coefficients)
exp(confint(coxfita))

# Neurological Signs #
neuro <- function(data)
	{
	neuro <- rep(0,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.neur[i]=="Y")
	neuro[i] <- 1
	}
	return(neuro)
	}
neuroa <- neuro(rpat)
learn <- function(data)
	{
	learn <- rep(0,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.learn[i]=="Y")
	learn[i] <- 1
	}
	return(learn)
	}
learna <- learn(rpat)
nsigna <- neuroa + learna
nsign <- function(data)
	{
	nsign <- rep(-1/2,length(data))
	for(i in 1:length(data)){
	if(data[i]>0)
	nsign[i] <- 1/2
	}
	return(nsign)
	}
coxfita=coxph(Surv(ttbs.bttime,ttbs.btcens)~nsign(nsigna)+strata(with.Arm),data=rpat)
coxfita
exp(coxfita$coefficients)
exp(confint(coxfita))

# Seizure Type #
stype <- function(data) 
	{
	for(i in 1:nrow(data)){
	if(is.na(data$all.sp)[i])
	data$all.sp[i]<-0
	if(is.na(data$all.cp)[i])
	data$all.cp[i]<-0
	if(is.na(data$all.scgtc)[i])
	data$all.scgtc[i]<-0
	if(is.na(data$all.tc)[i])
	data$all.tc[i] <- 0
	if(is.na(data$all.ta)[i])
	data$all.ta[i] <- 0
	if(is.na(data$all.aa)[i])
	data$all.aa[i] <- 0
	if(is.na(data$all.m)[i])
	data$all.m[i] <- 0
	if(is.na(data$all.otc)[i])
	data$all.otc[i] <- 0
	if(is.na(data$all.o)[i])
	data$all.o[i] <- 0
	}
	stype <- rep(7,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.sp[i]>=1 && data$all.scgtc[i]==0)
	stype[i] <- 2
	if(data$all.cp[i]>=1  && data$all.scgtc[i]==0)
	stype[i] <- 2
	if(data$all.sp[i]>=1 && data$all.scgtc[i]>=1)
	stype[i] <- 1
	if(data$all.cp[i]>=1  && data$all.scgtc[i]>=1)
	stype[i] <- 1
	if(data$all.scgtc[i]>=1)
	stype[i] <- 1	
	if(data$all.tc[i]>=1 && data$all.aa[i]==0 && data$all.ta[i]==0 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- 3
	if(data$all.aa[i]>=1 && data$all.tc[i]==0 && data$all.ta[i]==0 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- 4
	if(data$all.ta[i]>=1 && data$all.tc[i]==0 && data$all.aa[i]==0 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- 4
	if(data$all.ta[i]>=1 && data$all.tc[i]==0 && data$all.aa[i]>=1 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- 4 
	if(data$all.m[i]>=1 && data$all.ta[i]>=1)
	stype[i] <- 4
	if(data$all.m[i]>=1 && data$all.aa[i]>=1)
	stype[i] <- 4
	if(data$all.aa[i]>=1 && data$all.tc[i]>=1)
	stype[i] <- 5
	if(data$all.m[i]>=1 && data$all.tc[i]>=1)
	stype[i] <- 5
	if(data$all.ta[i]>=1 && data$all.tc[i]>=1)
	stype[i] <- 5
	if(data$all.otc[i]>=1)
	stype[i] <- 6
	if(data$all.o[i]>=1)
	stype[i] <- 7
	}
	return(stype)
	}	
stype1 <- function(data) 
	{
	for(i in 1:nrow(data)){
	if(is.na(data$all.sp)[i])
	data$all.sp[i]<-0
	if(is.na(data$all.cp)[i])
	data$all.cp[i]<-0
	if(is.na(data$all.scgtc)[i])
	data$all.scgtc[i]<-0
	if(is.na(data$all.tc)[i])
	data$all.tc[i] <- 0
	if(is.na(data$all.ta)[i])
	data$all.ta[i] <- 0
	if(is.na(data$all.aa)[i])
	data$all.aa[i] <- 0
	if(is.na(data$all.m)[i])
	data$all.m[i] <- 0
	if(is.na(data$all.otc)[i])
	data$all.otc[i] <- 0
	if(is.na(data$all.o)[i])
	data$all.o[i] <- 0
	}
	stype <- rep(-1/7,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.sp[i]>=1 && data$all.scgtc[i]==0)
	stype[i] <- 6/7
	if(data$all.cp[i]>=1  && data$all.scgtc[i]==0)
	stype[i] <- 6/7
	if(data$all.sp[i]>=1 && data$all.scgtc[i]>=1)
	stype[i] <- -1/7
	if(data$all.cp[i]>=1  && data$all.scgtc[i]>=1)
	stype[i] <- -1/7
	if(data$all.scgtc[i]>=1)
	stype[i] <- -1/7	
	if(data$all.tc[i]>=1 && data$all.aa[i]==0 && data$all.ta[i]==0 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- -1/7
	if(data$all.aa[i]>=1 && data$all.tc[i]==0 && data$all.ta[i]==0 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- -1/7
	if(data$all.ta[i]>=1 && data$all.tc[i]==0 && data$all.aa[i]==0 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- -1/7
	if(data$all.ta[i]>=1 && data$all.tc[i]==0 && data$all.aa[i]>=1 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- -1/7 
	if(data$all.m[i]>=1 && data$all.ta[i]>=1)
	stype[i] <- -1/7
	if(data$all.m[i]>=1 && data$all.aa[i]>=1)
	stype[i] <- -1/7
	if(data$all.aa[i]>=1 && data$all.tc[i]>=1)
	stype[i] <- -1/7
	if(data$all.m[i]>=1 && data$all.tc[i]>=1)
	stype[i] <- -1/7
	if(data$all.ta[i]>=1 && data$all.tc[i]>=1)
	stype[i] <- -1/7
	if(data$all.otc[i]>=1)
	stype[i] <- -1/7
	if(data$all.o[i]>=1)
	stype[i] <- -1/7
	}
	return(stype)
	}	
stype2 <- function(data) 
	{
	for(i in 1:nrow(data)){
	if(is.na(data$all.sp)[i])
	data$all.sp[i]<-0
	if(is.na(data$all.cp)[i])
	data$all.cp[i]<-0
	if(is.na(data$all.scgtc)[i])
	data$all.scgtc[i]<-0
	if(is.na(data$all.tc)[i])
	data$all.tc[i] <- 0
	if(is.na(data$all.ta)[i])
	data$all.ta[i] <- 0
	if(is.na(data$all.aa)[i])
	data$all.aa[i] <- 0
	if(is.na(data$all.m)[i])
	data$all.m[i] <- 0
	if(is.na(data$all.otc)[i])
	data$all.otc[i] <- 0
	if(is.na(data$all.o)[i])
	data$all.o[i] <- 0
	}
	stype <- rep(-1/7,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.sp[i]>=1 && data$all.scgtc[i]==0)
	stype[i] <- -1/7
	if(data$all.cp[i]>=1  && data$all.scgtc[i]==0)
	stype[i] <- -1/7
	if(data$all.sp[i]>=1 && data$all.scgtc[i]>=1)
	stype[i] <- -1/7
	if(data$all.cp[i]>=1  && data$all.scgtc[i]>=1)
	stype[i] <- -1/7
	if(data$all.scgtc[i]>=1)
	stype[i] <- -1/7	
	if(data$all.tc[i]>=1 && data$all.aa[i]==0 && data$all.ta[i]==0 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- 6/7
	if(data$all.aa[i]>=1 && data$all.tc[i]==0 && data$all.ta[i]==0 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- -1/7
	if(data$all.ta[i]>=1 && data$all.tc[i]==0 && data$all.aa[i]==0 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- -1/7
	if(data$all.ta[i]>=1 && data$all.tc[i]==0 && data$all.aa[i]>=1 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- -1/7 
	if(data$all.m[i]>=1 && data$all.ta[i]>=1)
	stype[i] <- -1/7
	if(data$all.m[i]>=1 && data$all.aa[i]>=1)
	stype[i] <- -1/7
	if(data$all.aa[i]>=1 && data$all.tc[i]>=1)
	stype[i] <- -1/7
	if(data$all.m[i]>=1 && data$all.tc[i]>=1)
	stype[i] <- -1/7
	if(data$all.ta[i]>=1 && data$all.tc[i]>=1)
	stype[i] <- -1/7
	if(data$all.otc[i]>=1)
	stype[i] <- -1/7
	if(data$all.o[i]>=1)
	stype[i] <- -1/7
	}
	return(stype)
	}	
stype3 <- function(data) 
	{
	for(i in 1:nrow(data)){
	if(is.na(data$all.sp)[i])
	data$all.sp[i]<-0
	if(is.na(data$all.cp)[i])
	data$all.cp[i]<-0
	if(is.na(data$all.scgtc)[i])
	data$all.scgtc[i]<-0
	if(is.na(data$all.tc)[i])
	data$all.tc[i] <- 0
	if(is.na(data$all.ta)[i])
	data$all.ta[i] <- 0
	if(is.na(data$all.aa)[i])
	data$all.aa[i] <- 0
	if(is.na(data$all.m)[i])
	data$all.m[i] <- 0
	if(is.na(data$all.otc)[i])
	data$all.otc[i] <- 0
	if(is.na(data$all.o)[i])
	data$all.o[i] <- 0
	}
	stype <- rep(-1/7,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.sp[i]>=1 && data$all.scgtc[i]==0)
	stype[i] <- -1/7
	if(data$all.cp[i]>=1  && data$all.scgtc[i]==0)
	stype[i] <- -1/7
	if(data$all.sp[i]>=1 && data$all.scgtc[i]>=1)
	stype[i] <- -1/7
	if(data$all.cp[i]>=1  && data$all.scgtc[i]>=1)
	stype[i] <- -1/7
	if(data$all.scgtc[i]>=1)
	stype[i] <- -1/7	
	if(data$all.tc[i]>=1 && data$all.aa[i]==0 && data$all.ta[i]==0 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- -1/7
	if(data$all.aa[i]>=1 && data$all.tc[i]==0 && data$all.ta[i]==0 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- 6/7
	if(data$all.ta[i]>=1 && data$all.tc[i]==0 && data$all.aa[i]==0 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- 6/7
	if(data$all.ta[i]>=1 && data$all.tc[i]==0 && data$all.aa[i]>=1 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- 6/7 
	if(data$all.m[i]>=1 && data$all.ta[i]>=1)
	stype[i] <- 6/7
	if(data$all.m[i]>=1 && data$all.aa[i]>=1)
	stype[i] <- 6/7
	if(data$all.aa[i]>=1 && data$all.tc[i]>=1)
	stype[i] <- -1/7
	if(data$all.m[i]>=1 && data$all.tc[i]>=1)
	stype[i] <- -1/7
	if(data$all.ta[i]>=1 && data$all.tc[i]>=1)
	stype[i] <- -1/7
	if(data$all.otc[i]>=1)
	stype[i] <- -1/7
	if(data$all.o[i]>=1)
	stype[i] <- -1/7
	}
	return(stype)
	}
stype4 <- function(data) 
	{
	for(i in 1:nrow(data)){
	if(is.na(data$all.sp)[i])
	data$all.sp[i]<-0
	if(is.na(data$all.cp)[i])
	data$all.cp[i]<-0
	if(is.na(data$all.scgtc)[i])
	data$all.scgtc[i]<-0
	if(is.na(data$all.tc)[i])
	data$all.tc[i] <- 0
	if(is.na(data$all.ta)[i])
	data$all.ta[i] <- 0
	if(is.na(data$all.aa)[i])
	data$all.aa[i] <- 0
	if(is.na(data$all.m)[i])
	data$all.m[i] <- 0
	if(is.na(data$all.otc)[i])
	data$all.otc[i] <- 0
	if(is.na(data$all.o)[i])
	data$all.o[i] <- 0
	}
	stype <- rep(-1/7,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.sp[i]>=1 && data$all.scgtc[i]==0)
	stype[i] <- -1/7
	if(data$all.cp[i]>=1  && data$all.scgtc[i]==0)
	stype[i] <- -1/7
	if(data$all.sp[i]>=1 && data$all.scgtc[i]>=1)
	stype[i] <- -1/7
	if(data$all.cp[i]>=1  && data$all.scgtc[i]>=1)
	stype[i] <- -1/7
	if(data$all.scgtc[i]>=1)
	stype[i] <- -1/7	
	if(data$all.tc[i]>=1 && data$all.aa[i]==0 && data$all.ta[i]==0 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- -1/7
	if(data$all.aa[i]>=1 && data$all.tc[i]==0 && data$all.ta[i]==0 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- -1/7
	if(data$all.ta[i]>=1 && data$all.tc[i]==0 && data$all.aa[i]==0 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- -1/7
	if(data$all.ta[i]>=1 && data$all.tc[i]==0 && data$all.aa[i]>=1 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- -1/7 
	if(data$all.m[i]>=1 && data$all.ta[i]>=1)
	stype[i] <- -1/7
	if(data$all.m[i]>=1 && data$all.aa[i]>=1)
	stype[i] <- -1/7
	if(data$all.aa[i]>=1 && data$all.tc[i]>=1)
	stype[i] <- 6/7
	if(data$all.m[i]>=1 && data$all.tc[i]>=1)
	stype[i] <- 6/7
	if(data$all.ta[i]>=1 && data$all.tc[i]>=1)
	stype[i] <- 6/7
	if(data$all.otc[i]>=1)
	stype[i] <- -1/7
	if(data$all.o[i]>=1)
	stype[i] <- -1/7
	}
	return(stype)
	}	
stype5 <- function(data) 
	{
	for(i in 1:nrow(data)){
	if(is.na(data$all.sp)[i])
	data$all.sp[i]<-0
	if(is.na(data$all.cp)[i])
	data$all.cp[i]<-0
	if(is.na(data$all.scgtc)[i])
	data$all.scgtc[i]<-0
	if(is.na(data$all.tc)[i])
	data$all.tc[i] <- 0
	if(is.na(data$all.ta)[i])
	data$all.ta[i] <- 0
	if(is.na(data$all.aa)[i])
	data$all.aa[i] <- 0
	if(is.na(data$all.m)[i])
	data$all.m[i] <- 0
	if(is.na(data$all.otc)[i])
	data$all.otc[i] <- 0
	if(is.na(data$all.o)[i])
	data$all.o[i] <- 0
	}
	stype <- rep(-1/7,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.sp[i]>=1 && data$all.scgtc[i]==0)
	stype[i] <- -1/7
	if(data$all.cp[i]>=1  && data$all.scgtc[i]==0)
	stype[i] <- -1/7
	if(data$all.sp[i]>=1 && data$all.scgtc[i]>=1)
	stype[i] <- -1/7
	if(data$all.cp[i]>=1  && data$all.scgtc[i]>=1)
	stype[i] <- -1/7
	if(data$all.scgtc[i]>=1)
	stype[i] <- -1/7	
	if(data$all.tc[i]>=1 && data$all.aa[i]==0 && data$all.ta[i]==0 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- -1/7
	if(data$all.aa[i]>=1 && data$all.tc[i]==0 && data$all.ta[i]==0 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- -1/7
	if(data$all.ta[i]>=1 && data$all.tc[i]==0 && data$all.aa[i]==0 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- -1/7
	if(data$all.ta[i]>=1 && data$all.tc[i]==0 && data$all.aa[i]>=1 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- -1/7 
	if(data$all.m[i]>=1 && data$all.ta[i]>=1)
	stype[i] <- -1/7
	if(data$all.m[i]>=1 && data$all.aa[i]>=1)
	stype[i] <- -1/7
	if(data$all.aa[i]>=1 && data$all.tc[i]>=1)
	stype[i] <- -1/7
	if(data$all.m[i]>=1 && data$all.tc[i]>=1)
	stype[i] <- -1/7
	if(data$all.ta[i]>=1 && data$all.tc[i]>=1)
	stype[i] <- -1/7
	if(data$all.otc[i]>=1)
	stype[i] <- 6/7
	if(data$all.o[i]>=1)
	stype[i] <- -1/7
	}
	return(stype)
	}	
stype6 <- function(data) 
	{
	for(i in 1:nrow(data)){
	if(is.na(data$all.sp)[i])
	data$all.sp[i]<-0
	if(is.na(data$all.cp)[i])
	data$all.cp[i]<-0
	if(is.na(data$all.scgtc)[i])
	data$all.scgtc[i]<-0
	if(is.na(data$all.tc)[i])
	data$all.tc[i] <- 0
	if(is.na(data$all.ta)[i])
	data$all.ta[i] <- 0
	if(is.na(data$all.aa)[i])
	data$all.aa[i] <- 0
	if(is.na(data$all.m)[i])
	data$all.m[i] <- 0
	if(is.na(data$all.otc)[i])
	data$all.otc[i] <- 0
	if(is.na(data$all.o)[i])
	data$all.o[i] <- 0
	}
	stype <- rep(6/7,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.sp[i]>=1 && data$all.scgtc[i]==0)
	stype[i] <- -1/7
	if(data$all.cp[i]>=1  && data$all.scgtc[i]==0)
	stype[i] <- -1/7
	if(data$all.sp[i]>=1 && data$all.scgtc[i]>=1)
	stype[i] <- -1/7
	if(data$all.cp[i]>=1  && data$all.scgtc[i]>=1)
	stype[i] <- -1/7
	if(data$all.scgtc[i]>=1)
	stype[i] <- -1/7	
	if(data$all.tc[i]>=1 && data$all.aa[i]==0 && data$all.ta[i]==0 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- -1/7
	if(data$all.aa[i]>=1 && data$all.tc[i]==0 && data$all.ta[i]==0 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- -1/7
	if(data$all.ta[i]>=1 && data$all.tc[i]==0 && data$all.aa[i]==0 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- -1/7
	if(data$all.ta[i]>=1 && data$all.tc[i]==0 && data$all.aa[i]>=1 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- -1/7 
	if(data$all.m[i]>=1 && data$all.ta[i]>=1)
	stype[i] <- -1/7
	if(data$all.m[i]>=1 && data$all.aa[i]>=1)
	stype[i] <- -1/7
	if(data$all.aa[i]>=1 && data$all.tc[i]>=1)
	stype[i] <- -1/7
	if(data$all.m[i]>=1 && data$all.tc[i]>=1)
	stype[i] <- -1/7
	if(data$all.ta[i]>=1 && data$all.tc[i]>=1)
	stype[i] <- -1/7
	if(data$all.otc[i]>=1)
	stype[i] <- -1/7
	if(data$all.o[i]>=1)
	stype[i] <- 6/7
	}
	return(stype)
	}		
coxfita=coxph(Surv(ttbs.bttime,ttbs.btcens)~stype1(rpat)+stype2(rpat)+stype3(rpat)+stype4(rpat)+stype5(rpat)+stype6(rpat)+strata(with.Arm),data=rpat)
coxfita
exp(coxfita$coefficients)
exp(confint(coxfita))

# Epilepsy type analysis #
pgu1 <- function(data)
	{
	x1 <- rep(-1/3,nrow(data))
	for(i in 1:nrow(data)){
	if(is.na(data$all.type)[i])
	data$all.type[i]<-"U"
	}
	for(i in 1:nrow(data)){
	if(data$all.type[i]=="P")
	x1[i] <- -1/3
	if(data$all.type[i]=="G")
	x1[i] <- 2/3
	if(data$all.type[i]=="U")
	x1[i] <- -1/3
	}
	return(x1)
	}
pgu2 <- function(data)
	{
	x2 <- rep(-1/3,nrow(data))
	for(i in 1:nrow(data)){
	if(is.na(data$all.type)[i])
	data$all.type[i]<-"U"
	}
	for(i in 1:nrow(data)){
	if(data$all.type[i]=="P")
	x2[i]<- -1/3
	if(data$all.type[i]=="G")
	x2[i]<- -1/3
	if(data$all.type[i]=="U")
	x2[i]<- 2/3
	}
	return(x2)
	}
coxfita=coxph(Surv(ttbs.bttime,ttbs.btcens)~pgu1(rpat)+pgu2(rpat)+strata(with.Arm),data=rpat)
coxfita
exp(coxfita$coefficients)
exp(confint(coxfita))

# EEG Results #
eegfour <- function(data)
	{
	for(i in 1:nrow(data)){
	if(is.na(data$all.nonspecab)[i])
	data$all.nonspecab[i]<-"N"
	}
	eegfour <- rep(3,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.eegabnormal[i]=="NR")
	eegfour[i]<-1
	if(data$all.eegabnormal[i]=="N")
	eegfour[i]<-0
	if(data$all.eegabnormal[i]=="Y" && data$all.nonspecab[i]=="Y")
	eegfour[i]<-2
	}
	return(eegfour)
	}
eeg1 <- function(data)
	{
	for(i in 1:nrow(data)){
	if(is.na(data$all.nonspecab)[i])
	data$all.nonspecab[i]<-"N"
	}
	eegfour <- rep(-1/4,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.eegabnormal[i]=="NR")
	eegfour[i]<-3/4
	if(data$all.eegabnormal[i]=="N")
	eegfour[i]<--1/4
	if(data$all.eegabnormal[i]=="Y" && data$all.nonspecab[i]=="Y")
	eegfour[i]<--1/4
	}
	return(eegfour)
	}
eeg2 <- function(data)
	{
	for(i in 1:nrow(data)){
	if(is.na(data$all.nonspecab)[i])
	data$all.nonspecab[i]<-"N"
	}
	eegfour <- rep(-1/4,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.eegabnormal[i]=="NR")
	eegfour[i]<--1/4
	if(data$all.eegabnormal[i]=="N")
	eegfour[i]<--1/4
	if(data$all.eegabnormal[i]=="Y" && data$all.nonspecab[i]=="Y")
	eegfour[i]<-3/4
	}
	return(eegfour)
	}
eeg3 <- function(data)
	{
	for(i in 1:nrow(data)){
	if(is.na(data$all.nonspecab)[i])
	data$all.nonspecab[i]<-"N"
	}
	eegfour <- rep(3/4,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.eegabnormal[i]=="NR")
	eegfour[i]<--1/4
	if(data$all.eegabnormal[i]=="N")
	eegfour[i]<--1/4
	if(data$all.eegabnormal[i]=="Y" && data$all.nonspecab[i]=="Y")
	eegfour[i]<--1/4
	}
	return(eegfour)
	}
coxfita=coxph(Surv(ttbs.bttime,ttbs.btcens)~eeg1(rpat)+eeg2(rpat)+eeg3(rpat)+strata(with.Arm),data=rpat)
coxfita
exp(coxfita$coefficients)
exp(confint(coxfita))

# CT/MR Results #
ctmr1 <- function(data)
	{
	ctmr <- rep(-1/3,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.ctabnormal[i]=="Y")
	ctmr[i] <- 2/3
	if(data$all.ctabnormal[i]=="NR")
	ctmr[i] <- -1/3
	}
	return(ctmr)
	}
ctmr2 <- function(data)
	{
	ctmr <- rep(-1/3,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.ctabnormal[i]=="Y")
	ctmr[i] <- -1/3
	if(data$all.ctabnormal[i]=="NR")
	ctmr[i] <- 2/3
	}
	return(ctmr)
	}
coxfita=coxph(Surv(ttbs.bttime,ttbs.btcens)~ctmr1(rpat)+ctmr2(rpat)+strata(with.Arm),data=rpat)
coxfita
exp(coxfita$coefficients)
exp(confint(coxfita))

# Treatment #
treat <- function(data)
	{
	treat <- rep(0,nrow(data))
	for(i in 1:nrow(data)){
	if(data$with.Treat[i]=="CBZ")
	treat[i] <- 1
	if(data$with.Treat[i]=="GBP")
	treat[i] <- 2
	if(data$with.Treat[i]=="LTG")
	treat[i] <- 3
	if(data$with.Treat[i]=="OXC")
	treat[i] <- 4
	if(data$with.Treat[i]=="TPM")
	treat[i] <- 5
	if(data$with.Treat[i]=="VPS")
	treat[i] <- 6
	}
	return(treat)
	}

treat1 <- function(data)
	{
	treat <- rep(0,nrow(data))
	for(i in 1:nrow(data)){
	if(data$with.Treat[i]=="CBZ")
	treat[i] <- -1/6
	if(data$with.Treat[i]=="GBP")
	treat[i] <- 5/6
	if(data$with.Treat[i]=="LTG")
	treat[i] <- -1/6
	if(data$with.Treat[i]=="OXC")
	treat[i] <- -1/6
	if(data$with.Treat[i]=="TPM")
	treat[i] <- -1/6
	if(data$with.Treat[i]=="VPS")
	treat[i] <- -1/6
	}
	return(treat)
	}
treat2 <- function(data)
	{
	treat <- rep(0,nrow(data))
	for(i in 1:nrow(data)){
	if(data$with.Treat[i]=="CBZ")
	treat[i] <- -1/6
	if(data$with.Treat[i]=="GBP")
	treat[i] <- -1/6
	if(data$with.Treat[i]=="LTG")
	treat[i] <- 5/6
	if(data$with.Treat[i]=="OXC")
	treat[i] <- -1/6
	if(data$with.Treat[i]=="TPM")
	treat[i] <- -1/6
	if(data$with.Treat[i]=="VPS")
	treat[i] <- -1/6
	}
	return(treat)
	}
treat3 <- function(data)
	{
	treat <- rep(0,nrow(data))
	for(i in 1:nrow(data)){
	if(data$with.Treat[i]=="CBZ")
	treat[i] <- -1/6
	if(data$with.Treat[i]=="GBP")
	treat[i] <- -1/6
	if(data$with.Treat[i]=="LTG")
	treat[i] <- -1/6
	if(data$with.Treat[i]=="OXC")
	treat[i] <- 5/6
	if(data$with.Treat[i]=="TPM")
	treat[i] <- -1/6
	if(data$with.Treat[i]=="VPS")
	treat[i] <- -1/6
	}
	return(treat)
	}
treat4 <- function(data)
	{
	treat <- rep(0,nrow(data))
	for(i in 1:nrow(data)){
	if(data$with.Treat[i]=="CBZ")
	treat[i] <- -1/6
	if(data$with.Treat[i]=="GBP")
	treat[i] <- -1/6
	if(data$with.Treat[i]=="LTG")
	treat[i] <- -1/6
	if(data$with.Treat[i]=="OXC")
	treat[i] <- -1/6
	if(data$with.Treat[i]=="TPM")
	treat[i] <- 5/6
	if(data$with.Treat[i]=="VPS")
	treat[i] <- -1/6
	}
	return(treat)
	}
treat5 <- function(data)
	{
	treat <- rep(0,nrow(data))
	for(i in 1:nrow(data)){
	if(data$with.Treat[i]=="CBZ")
	treat[i] <- -1/6
	if(data$with.Treat[i]=="GBP")
	treat[i] <- -1/6
	if(data$with.Treat[i]=="LTG")
	treat[i] <- -1/6
	if(data$with.Treat[i]=="OXC")
	treat[i] <- -1/6
	if(data$with.Treat[i]=="TPM")
	treat[i] <- -1/6
	if(data$with.Treat[i]=="VPS")
	treat[i] <- 5/6
	}
	return(treat)
	}
coxfita=coxph(Surv(ttbs.bttime,ttbs.btcens)~treat1(rpat)+treat2(rpat)+treat3(rpat)+treat4(rpat)+treat5(rpat)+strata(with.Arm),data=rpat)
coxfita
exp(coxfita$coefficients)
exp(confint(coxfita))

# Monotherapy to achieve remission #
mono <- function(data)
	{
	for(i in 1:nrow(data)){
	if(is.na(data$ttbs.nodrugs)[i])
	data$ttbs.nodrugs[i]<-0
	}
	mono <- rep(0,nrow(data))
	for(i in 1:nrow(data)){
	if(data$ttbs.nodrugs[i]<=1)
	mono[i] <- 0
	if(data$ttbs.nodrugs[i]>=2)
	mono[i] <- 1
	}
	return(mono)
	}
monodat <- mono(rpat)
mntp <- function(data)
	{
	mntp <- rep(-1/2,length(data))
	for(i in 1:length(data)){
	if(data[i]==1)
	mntp[i] <- 1/2
	}
	return(mntp)
	}
coxfita=coxph(Surv(ttbs.bttime,ttbs.btcens)~mntp(monodat)+strata(with.Arm),data=rpat)
coxfita
exp(coxfita$coefficients)
exp(confint(coxfita))

# Number of tonic-clonic seizures #
library(mfp)
library(Hmisc)

fit1 <- coxph(Surv(ttbs.bttime,ttbs.btcens)~newtc+strata(with.Arm),data=rpat)
extractAIC(fit1)
fit2 <- coxph(Surv(ttbs.bttime,ttbs.btcens)~log(newtc+1)+strata(with.Arm),data=rpat)
extractAIC(fit2)
fit3 <- mfp(Surv(ttbs.bttime,ttbs.btcens)~fp(newtc)+strata(with.Arm),family=cox,data=rpat,select=0.05,verbose=TRUE)
extractAIC(fit3)

tccount <- log((rpat$newtc+1)/10)
fit1 <- coxph(Surv(ttbs.bttime,ttbs.btcens)~tccount+strata(with.Arm),data=rpat)
summary(fit2)
summary(rpat$newtc)

# Age at 12-month remission #
fit1 <- coxph(Surv(ttbs.bttime,ttbs.btcens)~newage+strata(with.Arm),data=rpat)
extractAIC(fit1)
fit2 <- coxph(Surv(ttbs.bttime,ttbs.btcens)~log(newage)+strata(with.Arm),data=rpat)
extractAIC(fit2)
coxfitf1 <- mfp(Surv(ttbs.bttime,ttbs.btcens)~fp(newage)+strata(with.Arm),family=cox,data=rpat,select=0.05,verbose=TRUE)
extractAIC(coxfitf1)

summary(fit2)
summary(rpat$newage)

# Time to achieve first period of 12 month remission #
rem1 <- rpat$rem.Remtime
fit1 <- coxph(Surv(ttbs.bttime,ttbs.btcens)~rem1+strata(with.Arm),data=rpat)
extractAIC(fit1)
fit2 <- coxph(Surv(ttbs.bttime,ttbs.btcens)~log(rem1)+strata(with.Arm),data=rpat)
extractAIC(fit2)
coxfitf1 <- mfp(Surv(ttbs.bttime,ttbs.btcens)~fp(rem1)+strata(with.Arm),family=cox,data=rpat,select=0.05,verbose=TRUE)
extractAIC(coxfitf1)

remtime <- (rem1/1000)^(-2)
fit1 <- coxph(Surv(ttbs.bttime,ttbs.btcens)~remtime+strata(with.Arm),data=rpat)
summary(fit1)
summary(rem1)
rcspline.eval(rem1,knots.only=T)

# Time on randomised treatment #
fit1 <- coxph(Surv(ttbs.bttime,ttbs.btcens)~with.Withtime+strata(with.Arm),data=rpat)
extractAIC(fit1)
fit2 <- coxph(Surv(ttbs.bttime,ttbs.btcens)~log(with.Withtime)+strata(with.Arm),data=rpat)
extractAIC(fit2)
coxfitf1 <- mfp(Surv(ttbs.bttime,ttbs.btcens)~fp(with.Withtime)+strata(with.Arm),family=cox,data=rpat,select=0.05,verbose=TRUE)
extractAIC(coxfitf1)

summary(fit2)
summary(rpat$with.Withtime)
rcspline.eval(rpat$with.Withtime,knots.only=T)

### Multivariable Model ###
neuro <- function(data)
	{
	neuro <- rep(0,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.neur[i]=="Y")
	neuro[i] <- 1
	}
	return(neuro)
	}
neuroa <- neuro(rpat)
learn <- function(data)
	{
	learn <- rep(0,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.learn[i]=="Y")
	learn[i] <- 1
	}
	return(learn)
	}
learna <- learn(rpat)
nsigna <- neuroa + learna
nsign <- function(data)
	{
	nsign <- rep(0,length(data))
	for(i in 1:length(data)){
	if(data[i]>0)
	nsign[i] <- 1
	}
	return(nsign)
	}
stype <- function(data) 
	{
	for(i in 1:nrow(data)){
	if(is.na(data$all.sp)[i])
	data$all.sp[i]<-0
	if(is.na(data$all.cp)[i])
	data$all.cp[i]<-0
	if(is.na(data$all.scgtc)[i])
	data$all.scgtc[i]<-0
	if(is.na(data$all.tc)[i])
	data$all.tc[i] <- 0
	if(is.na(data$all.ta)[i])
	data$all.ta[i] <- 0
	if(is.na(data$all.aa)[i])
	data$all.aa[i] <- 0
	if(is.na(data$all.m)[i])
	data$all.m[i] <- 0
	if(is.na(data$all.otc)[i])
	data$all.otc[i] <- 0
	if(is.na(data$all.o)[i])
	data$all.o[i] <- 0
	}
	stype <- rep(7,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.sp[i]>=1 && data$all.scgtc[i]==0)
	stype[i] <- 2
	if(data$all.cp[i]>=1  && data$all.scgtc[i]==0)
	stype[i] <- 2
	if(data$all.sp[i]>=1 && data$all.scgtc[i]>=1)
	stype[i] <- 1
	if(data$all.cp[i]>=1  && data$all.scgtc[i]>=1)
	stype[i] <- 1
	if(data$all.scgtc[i]>=1)
	stype[i] <- 1	
	if(data$all.tc[i]>=1 && data$all.aa[i]==0 && data$all.ta[i]==0 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- 3
	if(data$all.aa[i]>=1 && data$all.tc[i]==0 && data$all.ta[i]==0 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- 4
	if(data$all.ta[i]>=1 && data$all.tc[i]==0 && data$all.aa[i]==0 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- 4
	if(data$all.ta[i]>=1 && data$all.tc[i]==0 && data$all.aa[i]>=1 && data$all.m[i]==0 && data$all.otc[i]==0 && data$all.o[i]==0)
	stype[i] <- 4 
	if(data$all.m[i]>=1 && data$all.ta[i]>=1)
	stype[i] <- 4
	if(data$all.m[i]>=1 && data$all.aa[i]>=1)
	stype[i] <- 4
	if(data$all.aa[i]>=1 && data$all.tc[i]>=1)
	stype[i] <- 5
	if(data$all.m[i]>=1 && data$all.tc[i]>=1)
	stype[i] <- 5
	if(data$all.ta[i]>=1 && data$all.tc[i]>=1)
	stype[i] <- 5
	if(data$all.otc[i]>=1)
	stype[i] <- 6
	if(data$all.o[i]>=1)
	stype[i] <- 7
	}
	return(stype)
	}
type <- function(data)
	{
	for(i in 1:nrow(data)){
	if(is.na(data$all.type)[i])
	data$all.type[i]<-"U"
	}
	type <- rep(0,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.type[i]=="P")
	type[i] <- 1
	if(data$all.type[i]=="G")
	type[i] <- 2
	if(data$all.type[i]=="U")
	type[i] <- 3
	}
	return(type)
	}	
eegfour <- function(data)
	{
	for(i in 1:nrow(data)){
	if(is.na(data$all.nonspecab)[i])
	data$all.nonspecab[i]<-"N"
	}
	eegfour <- rep(3,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.eegabnormal[i]=="NR")
	eegfour[i]<-1
	if(data$all.eegabnormal[i]=="N")
	eegfour[i]<-0
	if(data$all.eegabnormal[i]=="Y" && data$all.nonspecab[i]=="Y")
	eegfour[i]<-2
	}
	return(eegfour)
	}
mono <- function(data)
	{
	for(i in 1:nrow(data)){
	if(is.na(data$ttbs.nodrugs)[i])
	data$ttbs.nodrugs[i]<-0
	}
	mono <- rep(0,nrow(data))
	for(i in 1:nrow(data)){
	if(data$ttbs.nodrugs[i]<=1)
	mono[i] <- 0
	if(data$ttbs.nodrugs[i]>=2)
	mono[i] <- 1
	}
	return(mono)
	}
tccount <- log((rpat$newtc+1)/10)
newage2 <- log(rpat$newage)
remtime <- (rpat$rem.Remtime/1000)^(-2)
coxfit1=coxph(Surv(ttbs.bttime,ttbs.btcens)~all.sex+all.feb+all.rels+nsign(nsigna)+factor(stype(rpat))+factor(eegfour(rpat))+factor(all.ctabnormal)+mono(rpat)+tccount+newage2+remtime+strata(with.Arm),data=rpat)
rema.step=stepAIC(coxfit1,scope=list(upper=~all.sex+all.feb+all.rels+nsign(nsigna)+factor(stype(rpat))+factor(eegfour(rpat))+factor(all.ctabnormal)+mono(rpat)+tccount+newage2+remtime+strata(with.Arm)),direction="backward",trace=FALSE)
rema.step

remb.step=stepAIC(coxfit1,scope=list(upper=~all.sex+all.feb+all.rels+nsign(nsigna)+factor(stype(rpat))+factor(eegfour(rpat))+factor(all.ctabnormal)+mono(rpat)+tccount+newage2+remtime+strata(with.Arm)),direction="both",trace=FALSE)
remb.step

remamod = coxph(Surv(ttbs.bttime,ttbs.btcens)~nsign(nsigna)+tccount+remtime+strata(with.Arm),data=rpat)
summary(remamod)
exp(remamod$coef)
exp(confint(remamod))

## Forest Plot #
library(grid)

# load relevant data: breakthrough #
breakthrough <- read.table("Risk Factor Combos - Breakthrough.txt",header=TRUE)

Ys=seq(from=1,to=nrow(breakthrough),by=1)
par(mfrow=c(1,4),mar=c(5,1,1,1))
plot(0,0,xlim=c(0,100),ylim=c(0,nrow(breakthrough)+3),type="n",axes=F,xlab="",ylab="",main="")
text(10,Ys,rev(breakthrough$nele),cex=0.7)
text(50,Ys,rev(breakthrough$tccount),cex=0.7)
text(90,Ys,rev(breakthrough$remtime),cex=0.7)
text(10,nrow(breakthrough)+3,"Neuro.",font=2,cex=0.7)
text(10,nrow(breakthrough)+2,"insult",font=2,cex=0.7)
text(50,nrow(breakthrough)+3,"TC",font=2,cex=0.7)
text(50,nrow(breakthrough)+2,"count",font=2,cex=0.7)
text(90,nrow(breakthrough)+3,"Time to",font=2,cex=0.7)
text(90,nrow(breakthrough)+2,"remission",font=2,cex=0.7)
text(90,nrow(breakthrough)+1,"(years)",font=2,cex=0.7)
abline(h=9.5)

plot(0,0,xlim=c(0,100),ylim=c(0,nrow(breakthrough)+3),type="n",axes=F,xlab="Risk of breakthrough at 1 year after remission (%)",ylab="",main="",cex.lab=0.7)
estimate1y <- rev(breakthrough$HR1)*100
lower1y <- rev(breakthrough$Lower1)*100
upper1y <- rev(breakthrough$Upper1)*100
points(estimate1y,Ys,pch=15,cex=1.5,)
for(i in 1:length(Ys)){
lines(c(lower1y[i],upper1y[i]),rep(Ys[i],2),lwd=1.0)
}
axis(1,at=c(0,10,20,30,40,50,60,70,80,90,100),c(0,10,20,30,40,50,60,70,80,90,100),cex.axis=0.65)
abline(h=9.5)

plot(0,0,xlim=c(0,100),ylim=c(0,nrow(breakthrough)+3),type="n",axes=F,xlab="Risk of breakthrough at 2 years after remission (%)",ylab="",main="",cex.lab=0.7)
estimate2y <- rev(breakthrough$HR2)*100
lower2y <- rev(breakthrough$Lower2)*100
upper2y <- rev(breakthrough$Upper2)*100
points(estimate2y,Ys,pch=15,cex=1.5,)
for(i in 1:length(Ys)){
lines(c(lower2y[i],upper2y[i]),rep(Ys[i],2),lwd=1.0)
}
axis(1,at=c(0,10,20,30,40,50,60,70,80,90,100),c(0,10,20,30,40,50,60,70,80,90,100),cex.axis=0.65)
abline(h=9.5)

plot(0,0,xlim=c(0,100),ylim=c(0,nrow(breakthrough)+3),type="n",axes=F,xlab="Risk of breakthrough at 3 years after remission (%)",ylab="",main="",cex.lab=0.7)
estimate3y <- rev(breakthrough$HR3)*100
lower3y <- rev(breakthrough$Lower3)*100
upper3y <- rev(breakthrough$Upper3)*100
points(estimate3y,Ys,pch=15,cex=1.5,)
for(i in 1:length(Ys)){
lines(c(lower3y[i],upper3y[i]),rep(Ys[i],2),lwd=1.0)
}
axis(1,at=c(0,10,20,30,40,50,60,70,80,90,100),c(0,10,20,30,40,50,60,70,80,90,100),cex.axis=0.65)
abline(h=9.5)