6 replies to this topic

[Georgia Charkoftaki]

Hi,

I have one more question. I am running a VPC and I can't find the plot of DV vs VAR over all individuals with the shaded areas which are the liimits.

Can you please help me?

Thanks,

Georgia

[serge guzy]

Dear Georgia

Can you share the project?

Best

Serge

[Georgia Charkoftaki]

The project I am working on is about a POPPK model of cyclophosphamide in populations with Acute Kidney Disease. So, now I want to check the VPC, but as I am used to working with nonmem, I am a little bit lost with Phoenix. Next stage of my project is to add the metabolite model.

Georgia

[Simon Davis]

Georgia, we don't natively support shading in Phoenix plots yet so I think the equivalent plots would be;



however you can also use the work sheet produced as a source to replot this in R if you want;
#PCDATA <- read.csv ("PredCheck_ObsQ_SimQCI.csv")

let me check if I can post this project

Simon

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[Georgia Charkoftaki]

Well, I don't know why, but my POP PredCheck look like this,
while my Individual Pred check look fine.

I really can't figure out what is wrong and my POP PredCheck look like that.

Thanks,
Georgia [file name=Individual_PredCheck.png size=44831]http://www.pharsight.com/extranet/media/kunena/attachments/legacy/files/Individual_PredCheck.png[/file] Check.png' alt='Posted Image' />

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[Georgia Charkoftaki]

Maybe I got the previous Overall PredCheck because I didn't use Binning?
If I check Binning, then I get this.
Thanks,
Georgia

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[Samer Mouksassi]

of course binning is very important.

Phoenix has optimal built in binning using K-means algorithm and more options are upcoming.

 

I wrote additional scripts that help visualize the graphs in R lattice or GGPLOT with automatic stratification:

 

 

################################################# code starts

# The user is responsible to edit the code to make sure it works for his model

# make sure you have all required pacakges

#Samer Mouksassi

 

attach(PCDATA) #WNL_IN Scenario Strat IVAR DV0 DV ObsName QI QE#

#PCDATA <- read.csv ("PredCheck_ObsQ_SimQCI.csv")

 

Stratname <- "Sex"

StratLevels <- c("Women","Men")

Transparencysetting <- 0.2

 

require(lattice)

require(reshape2)

require(ggplot2)

 

 

 

 

##########################################################

PCDATA$PK <- with(PCDATA,ifelse( is.na(DV),DV0,DV))

PCDATA<- PCDATA[, c("Strat","IVAR","PK","QI","QE")]

 

PCDATAm <- melt(PCDATA,id=c("Strat","IVAR","QE","QI"))

PCDATAm <- dcast ( PCDATAm , IVAR +QI +Strat ~ QE +variable)

 

#PCDATAm $Strat <- ifelse ( PCDATAm $Strat==1,"Men","Women")

# this line above if you want to change the labels

 

 

 

##########################################################

png(file = "vpcplotggplot.png", bg = "transparent")

 

   ggplot(PCDATAm ,aes(IVAR,`--_PK`,ymin=`05%_PK`,ymax=`95%_PK`,fill=QI,col=QI))+

   geom_ribbon(alpha=0.1,col=NA ) +

scale_fill_manual(name="Observerd (lines)\nPrediction Intervals (ribbons)",

breaks=c("05%", "50%", "95%"),

values=c("red","blue","red"))+

 geom_line() +

facet_grid(~Strat,, labeller = label_value,scales="free_x") +

scale_colour_manual(name="Observerd (lines)\nPrediction Intervals (ribbons)",

breaks=c("05%", "50%", "95%"),

values=c("red","blue","red"))+

ylab("Simulated and Observed Quantiles of\n Concentrations (pg/mL)")+

  xlab("Time After Dose (h)")+

 theme(legend.position="bottom")

 

dev.off()

 

 

 

########## the same but with lattice

 

 

panel.bands <-

    function(x, y, upper, lower,

             fill, col,

             subscripts, ..., font, fontface)

{

    upper <- upper[subscripts]

    lower <- lower[subscripts]

    panel.polygon(c(x, rev(x)), c(upper, rev(lower)),

                  col = fill, border = FALSE,

                  ...)

}

png(file = "vpcplotlattice.png", bg = "transparent")

 

xyplot( `--_PK` ~IVAR |Strat,data=PCDATAm, scales=list(x=list(relation="free")),

ylim=c(min (PCDATAm[,4:7] ,na.rm=T), max (PCDATAm[,4:7],na.rm=T)),

ylab = "Simulated and Observed Quantiles of\n Concentrations (pg/mL)",

xlab = "Time After Dose (h)",

group=PCDATAm$QI,lower= PCDATAm[,5] ,upper = PCDATAm[,7] ,

panel= function(x,y,subscript=T,group,ylow=ylow,yup=yup,...){

panel.superpose(x, y, panel.groups = 'panel.bands',fill=c("red","blue","red"),alpha=0.2, ...)

panel.superpose(x,y,type="l",col=c("red","blue","red"),...)

 

}

, key=list(space="bottom",columns=2,

 text =list(lab=c("SIM 95% PI","SIM Median","SIM 05% PI","OBS 95% PI","OBS Median","OBS 05% PI")),

 rectangles=list(col=c("red","blue","red","transparent","transparent","transparent"),alpha=0.2,border="transparent")

,lines=list(lty=c(0,0,0,1,1,1),lwd=1,col=c("transparent","transparent","transparent","red","blue","red"))

)

 )

 

dev.off()

 

 

 = list(cex = 1.2)

,var.name=Stratname ,factor.levels=StratLevels)

)

,more=F)

 

dev.off()