### CHANCE OF SECOND SEIZURE FOLLOWING A FIRST BREAKTHROUGH SEIZURE ###

library(cmprsk)
library(MASS)

# load dataset #
sdat2 <- read.csv("Outcomes following Breakthrough.csv")

sdata <- subset(sdat2,with.Arm=="CBZ")
sdatb <- subset(sdat2,with.Arm=="VPS")

# Kaplan-Meier curve #
library(prodlim)
tiff(file="Fig 3.tiff",width=2250,heigh=2625,units="px",res=300)
ttime <- sdat2$ttss.sseztime/365
fit <- prodlim(Surv(ttime,ttss.sscens)~1,data=sdat2)
plot(fit,type="cuminc",percent=FALSE,background=FALSE,lwd=0.7,atRisk.dist=1,xlab="Time from 1st Breakthrough Seizure (years)",ylab="Probability of Seizure Recurrence",confint=FALSE,legend.x=0,legend.y=1,atrisk.labels="No. at risk:",atRisk.times=c(0,1,2,3,4),atRisk.adjust.labels=FALSE)
dev.off()

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

## Patient Characteristics ##
# No. seizure recurrences #
sum(sdat2$ttss.sscens)

# Time to seizure recurrence #
sezpeeps <- subset(sdat2,ttss.sscens==1)
summary(sezpeeps$ttss.sseztime)

# Duration of follow-up after acheiving 12 month remission #
summary((sdat2$lastfup.dlfu-sdat2$ttss.mdfsez)/365)

# Gender #
table(sdata$all.sex)
prop.table(table(sdata$all.sex))
table(sdatb$all.sex)
prop.table(table(sdatb$all.sex))
table(sdat2$all.sex)
prop.table(table(sdat2$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(sdat2$all.feb)
prop.table(table(sdat2$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(sdat2$all.rels)
prop.table(table(sdat2$all.rels))

# Neurological Insult #
neuro <- function(data)
	{
	neuro <- rep(0,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.neur[i]=="Y")
	neuro[i] <- 1
	}
	return(neuro)
	}
neuroa <- neuro(sdata)
neurob <- neuro(sdatb)
neuroab <- neuro(sdat2)
learn <- function(data)
	{
	learn <- rep(0,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.learn[i]=="Y")
	learn[i] <- 1
	}
	return(learn)
	}
learna <- learn(sdata)
learnb <- learn(sdatb)
learnab <- learn(sdat2)
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(sdat2))
prop.table(table(stype(sdat2)))

# Epilepsy Type #
table(sdata$all.type)
prop.table(table(sdata$all.type))
table(sdatb$all.type)
prop.table(table(sdatb$all.type))
table(sdat2$all.type)
prop.table(table(sdat2$all.type))

# EEG result #
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(sdat2))
prop.table(table(eegfour(sdat2)))

# 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(sdat2$all.ctabnormal)
prop.table(table(sdat2$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(sdat2$with.Treat)
prop.table(table(sdat2$with.Treat))	

# Number of drugs to achieve remission #
mono <- function(data)
	{
	for(i in 1:nrow(data)){
	if(is.na(data$drugs.nodrugs)[i])
	data$drugs.nodrugs[i]<-0
	}
	mono <- rep(0,nrow(data))
	for(i in 1:nrow(data)){
	if(data$drugs.nodrugs[i]<=1)
	mono[i] <- 0
	if(data$drugs.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(sdat2))
prop.table(table(mono(sdat2)))

# Number t-c at achievement of remission #
summary(sdata$newtc)
summary(sdatb$newtc)
summary(sdat2$newtc)

# Age at achievement of remission #
summary(sdata$newage)
summary(sdatb$newage)
summary(sdat2$newage)

# Time to achieve 12 month remission #
summary(sdata$rem.Remtime/365)
summary(sdatb$rem.Remtime/365)
summary(sdat2$rem.Remtime/365)

# Time on randomised (monotherapy) treatment #
summary(sdata$with.Withtime/365)
summary(sdatb$with.Withtime/365)
summary(sdat2$with.Withtime/365)

# Pre-breakthrough decision #
table(sdata$ttss.predec)
prop.table(table(sdata$ttss.predec))
table(sdatb$ttss.predec)
prop.table(table(sdatb$ttss.predec))
table(sdat2$ttss.predec)
prop.table(table(sdat2$ttss.predec))

# Post-breakthrough decision #
table(sdata$ttss.postdec)
prop.table(table(sdata$ttss.postdec))
table(sdatb$ttss.postdec)
prop.table(table(sdatb$ttss.postdec))
table(sdat2$ttss.postdec)
prop.table(table(sdat2$ttss.postdec))

# Duration of follow-up after breakthrough seizure #
summary((sdata$lastfup.dlfu-sdata$ttss.mdfsez)/365)
summary((sdatb$lastfup.dlfu-sdatb$ttss.mdfsez)/365)
summary((sdat2$lastfup.dlfu-sdat2$ttss.mdfsez)/365)


## Univariable analysis ##
# Gender #
sind <- function(data)
	{
	sind <- rep(1/2,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.sex[i]=="F")
	sind[i] <- -1/2
	}
	return(sind)
	}
coxfita=coxph(Surv(ttss.sseztime,ttss.sscens)~sind(sdat2)+strata(with.Arm),data=sdat2)
coxfita
exp(coxfita$coefficients)
exp(confint(coxfita))

# Febrile Seizure History # 
fsh <- function(data)
	{
	fsh <- rep(-1/2,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.feb[i]=="Y")
	fsh[i] <- 1/2
	}
	return(fsh)
	}
coxfita=coxph(Surv(ttss.sseztime,ttss.sscens)~fsh(sdat2)+strata(with.Arm),data=sdat2)
coxfita
exp(coxfita$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$all.rels[i]=="Y")
	fdr[i] <- 1/2
	}
	return(fdr)
	}
coxfita=coxph(Surv(ttss.sseztime,ttss.sscens)~fdr(sdat2)+strata(with.Arm),data=sdat2)
coxfita
exp(coxfita$coefficients)
exp(confint(coxfita))

# Neurological Signs #
neuro <- function(data)
	{
	neuro <- rep(0,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.neur[i]=="Y")
	neuro[i] <- 1
	}
	return(neuro)
	}
neuroa <- neuro(sdat2)
learn <- function(data)
	{
	learn <- rep(0,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.learn[i]=="Y")
	learn[i] <- 1
	}
	return(learn)
	}
learna <- learn(sdat2)
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(ttss.sseztime,ttss.sscens)~nsign(nsigna)+strata(with.Arm),data=sdat2)
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$all.o[i]>=1)
	stype[i] <- 6/7
	}
	return(stype)
	}		
coxfita=coxph(Surv(ttss.sseztime,ttss.sscens)~stype1(sdat2)+stype2(sdat2)+stype3(sdat2)+stype4(sdat2)+stype5(sdat2)+stype6(sdat2)+strata(with.Arm),data=sdat2)
coxfita
exp(coxfita$coefficients)
exp(confint(coxfita))

# P/G/U 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(ttss.sseztime,ttss.sscens)~pgu1(sdat2)+pgu2(sdat2)+strata(with.Arm),data=sdat2)
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(ttss.sseztime,ttss.sscens)~eeg1(sdat2)+eeg2(sdat2)+eeg3(sdat2)+strata(with.Arm),data=sdat2)
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(ttss.sseztime,ttss.sscens)~ctmr1(sdat2)+ctmr2(sdat2)+strata(with.Arm),data=sdat2)
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(ttss.sseztime,ttss.sscens)~treat1(sdat2)+treat2(sdat2)+treat3(sdat2)+treat4(sdat2)+treat5(sdat2)+strata(with.Arm),data=sdat2)
coxfita
exp(coxfita$coefficients)
exp(confint(coxfita))

# Monotherapy to achieve remission #
mono <- function(data)
	{
	for(i in 1:nrow(data)){
	if(is.na(data$drugs.nodrugs)[i])
	data$drugs.nodrugs[i]<-0
	}
	mono <- rep(0,nrow(data))
	for(i in 1:nrow(data)){
	if(data$drugs.nodrugs[i]<=1)
	mono[i] <- 0
	if(data$drugs.nodrugs[i]>=2)
	mono[i] <- 1
	}
	return(mono)
	}
monodat <- mono(sdat2)
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(ttss.sseztime,ttss.sscens)~mntp(monodat)+strata(with.Arm),data=sdat2)
coxfita
exp(coxfita$coefficients)
exp(confint(coxfita))

# Post-seizure decision #
post1 <- function(data)
	{
	for(i in 1:nrow(data)){
	if(is.na(data$ttss.postdec)[i])
	data$ttss.postdec[i]<-4
	}
	post1 <- rep(-1/3,nrow(data))
	for(i in 1:nrow(data)){
	if(data$ttss.postdec[i]==1)
	post1[i] <- -1/3
	if(data$ttss.postdec[i]==2)
	post1[i] <- 2/3
	if(data$ttss.postdec[i]==3)
	post1[i] <- -1/3
	if(data$ttss.postdec[i]==4)
	post1[i] <- -1/3
	}
	return(post1)
	}
post2 <- function(data)
	{
	for(i in 1:nrow(data)){
	if(is.na(data$ttss.postdec)[i])
	data$ttss.postdec[i]<-4
	}
	post2 <- rep(-1/3,nrow(data))
	for(i in 1:nrow(data)){
	if(data$ttss.postdec[i]==1)
	post2[i] <- -1/3
	if(data$ttss.postdec[i]==2)
	post2[i] <- -1/3
	if(data$ttss.postdec[i]==3)
	post2[i] <- 2/3
	if(data$ttss.postdec[i]==4)
	post2[i] <- 2/3
	}
	return(post2)
	}
coxfita=coxph(Surv(ttss.sseztime,ttss.sscens)~post1(sdat2)+post2(sdat2)+strata(with.Arm),data=sdat2)
coxfita
exp(coxfita$coefficients)
exp(confint(coxfita))

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

fit1 <- coxph(Surv(ttss.sseztime,ttss.sscens)~newtc+strata(with.Arm),data=sdat2)
extractAIC(fit1)
fit2 <- coxph(Surv(ttss.sseztime,ttss.sscens)~log(newtc+1)+strata(with.Arm),data=sdat2)
extractAIC(fit2)
fit3 <- mfp(Surv(ttss.sseztime,ttss.sscens)~fp(newtc)+strata(with.Arm),family=cox,data=sdat2,select=0.05,verbose=TRUE)
extractAIC(fit3)

summary(fit1)
summary(sdat2$newtc)

# Age at first breakthrough seizure #
fit1 <- coxph(Surv(ttss.sseztime,ttss.sscens)~newage+strata(with.Arm),data=sdat2)
extractAIC(fit1)
fit2 <- coxph(Surv(ttss.sseztime,ttss.sscens)~log(newage)+strata(with.Arm),data=sdat2)
extractAIC(fit2)
coxfitf1 <- mfp(Surv(ttss.sseztime,ttss.sscens)~fp(newage)+strata(with.Arm),family=cox,data=sdat2,select=0.05,verbose=TRUE)
extractAIC(coxfitf1)

summary(fit1)
summary(sdat2$newage)

# Time to achieve first period of 12 month remission #
fit1 <- coxph(Surv(ttss.sseztime,ttss.sscens)~rem.Remtime+strata(with.Arm),data=sdat2)
extractAIC(fit1)
fit2 <- coxph(Surv(ttss.sseztime,ttss.sscens)~log(rem.Remtime)+strata(with.Arm),data=sdat2)
extractAIC(fit2)
coxfitf1 <- mfp(Surv(ttss.sseztime,ttss.sscens)~fp(rem.Remtime)+strata(with.Arm),family=cox,data=sdat2,select=0.05,verbose=TRUE)
extractAIC(coxfitf1)

summary(fit2)
summary(sdat2$rem.Remtime)

# Time on randomised treatment #
fit1 <- coxph(Surv(ttss.sseztime,ttss.sscens)~with.Withtime+strata(with.Arm),data=sdat2)
extractAIC(fit1)
fit2 <- coxph(Surv(ttss.sseztime,ttss.sscens)~log(with.Withtime)+strata(with.Arm),data=sdat2)
extractAIC(fit2)
coxfitf1 <- mfp(Surv(ttss.sseztime,ttss.sscens)~fp(with.Withtime)+strata(with.Arm),family=cox,data=sdat2,select=0.05,verbose=TRUE)
extractAIC(coxfitf1)

summary(fit1)
summary(sdat2$with.Withtime)

### Multivariable Model ###
neuro <- function(data)
	{
	neuro <- rep(0,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.neur[i]=="Y")
	neuro[i] <- 1
	}
	return(neuro)
	}
neuroa <- neuro(sdat2)
learn <- function(data)
	{
	learn <- rep(0,nrow(data))
	for(i in 1:nrow(data)){
	if(data$all.learn[i]=="Y")
	learn[i] <- 1
	}
	return(learn)
	}
learna <- learn(sdat2)
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$all.o[i]>=1)
	stype[i] <- 7
	}
	return(stype)
	}
eegfour <- function(data)
	{
	for(i in 1:nrow(data)){
	if(is.na(data$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$all.nonspecab[i]=="Y")
	eegfour[i]<-2
	}
	return(eegfour)
	}
post1a <- function(data)
		{
		for(i in 1:nrow(data)){
		if(is.na(data$ttss.postdec)[i])
		data$ttss.postdec[i] <- 4
		}
		post1a <- rep(0,nrow(data)) 
		for(i in 1:nrow(data)){
		if(data$ttss.postdec[i]==1)
		post1a[i] <- 1
		if(data$ttss.postdec[i]==2)
		post1a[i] <- 2
		if(data$ttss.postdec[i]==3)
		post1a[i] <- 3
		if(data$ttss.postdec[i]==4)
		post1a[i] <- 3
		}
		return(post1a)
		}
aeds1a <- function(data)
	{
	aeda <- rep(0,nrow(data))
	for(i in 1:nrow(data)){
	if(is.na(data$drugs.nodrugs)[i])
	data$drugs.nodrugs[i]<-0
	}
	for(i in 1:nrow(data)){
	if(data$drugs.nodrugs[i]==2)
	aeda[i] <- 1
	if(data$drugs.nodrugs[i]==3)
	aeda[i] <- 1
	}
	return(aeda)
	}

coxfitb=coxph(Surv(ttss.sseztime,ttss.sscens)~all.sex+all.feb+all.rels+nsign(nsigna)+factor(stype(sdat2))+factor(eegfour(sdat2))+factor(all.ctabnormal)+aeds1a(sdat2)+newtc+newage+log(rem.Remtime)+factor(post1a(sdat2))+strata(with.Arm),data=sdat2)
rema.step=stepAIC(coxfitb,scope=list(upper=~all.sex+all.feb+all.rels+nsign(nsigna)+factor(stype(sdat2))+factor(eegfour(sdat2))+factor(all.ctabnormal)+aeds1a(sdat2)+newtc+newage+log(rem.Remtime)+factor(post1a(sdat2))+strata(with.Arm)),direction="backward",trace=FALSE)
rema.step

remb.step=stepAIC(coxfitb,scope=list(upper=~all.sex+all.feb+all.rels+nsign(nsigna)+factor(stype(sdat2))+factor(eegfour(sdat2))+factor(all.ctabnormal)+aeds1a(sdat2)+newtc+newage+log(rem.Remtime)+factor(post1a(sdat2))+strata(with.Arm)),direction="both",trace=FALSE)
remb.step

remamod = coxph(Surv(ttss.sseztime,ttss.sscens)~aeds1a(sdat2)+log(rem.Remtime)+factor(post1a(sdat2))+strata(with.Arm),data=sdat2)
summary(remamod)
exp(remamod$coef)
exp(confint(remamod))


## Forest Plot #
library(grid)

# read in relevant dataset #
seizure <- read.table("Risk Factor Combos - Seizure.txt",header=TRUE)

Ys=seq(from=1,to=nrow(seizure),by=1)
par(mfrow=c(1,3),mar=c(5,1,1,1))
plot(0,0,xlim=c(0,100),ylim=c(0,nrow(seizure)+3),type="n",axes=F,xlab="",ylab="",main="")
text(10,Ys,rev(seizure$aeds),cex=0.7)
text(50,Ys,c(rep("No Change",3),rep("Increase",3),rep("No Change",3),rep("Increase",3)),cex=0.7)
text(90,Ys,rev(seizure$rtime),cex=0.7)
text(10,nrow(seizure)+3,"No. drugs",font=2,cex=0.7)
text(10,nrow(seizure)+2,"attempted",font=2,cex=0.7)
text(50,nrow(seizure)+3,"Treatment",font=2,cex=0.7)
text(50,nrow(seizure)+2,"decision",font=2,cex=0.7)
text(90,nrow(seizure)+3,"Time to",font=2,cex=0.7)
text(90,nrow(seizure)+2,"remission",font=2,cex=0.7)
text(90,nrow(seizure)+1,"(years)",font=2,cex=0.7)
abline(h=6.5)

plot(0,0,xlim=c(0,100),ylim=c(0,nrow(seizure)+3),type="n",axes=F,xlab="Risk of Seizure Recurrence at 0.5 years after breakthrough (%)",ylab="",main="",cex.lab=0.7)
estimate0.5y <- rev(seizure$HR0.5)*100
lower0.5y <- rev(seizure$Lower0.5)*100
upper0.5y <- rev(seizure$Upper0.5)*100
points(estimate0.5y,Ys,pch=15,cex=1.5,)
for(i in 1:length(Ys)){
lines(c(lower0.5y[i],upper0.5y[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=0.7)
abline(h=6.5)

plot(0,0,xlim=c(0,100),ylim=c(0,nrow(seizure)+3),type="n",axes=F,xlab="Risk of Seizure Recurrence at 1 year after breakthrough (%)",ylab="",main="",cex.lab=0.7)
estimate1y <- rev(seizure$HR1)*100
lower1y <- rev(seizure$Lower1)*100
upper1y <- rev(seizure$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=0.7)
abline(h=6.5)