Dear NONMEM users, Dear Uppsala Folks, Dear Christopher
I was looking for some Xpose function that would automatically create a forest
plot from NONMEM output in order to present the results of covariate analysis,
assuming that all covariate models have been implemented the same way with same
NULL value. The only thing I found was the Covariates function in the popPK
package, which makes use of Xpose, developed by Christoffer Tornoe while he was
at FDA. http://www2.uaem.mx/r-mirror/web/packages/popPK/popPK.pdf
But this package looks like to be no longer supported and has been removed from
the CRAN.
Has anyone developed such a package?
With best regards / Mit freundlichen Grüßen / Cordialement / 祝好 / よろしくお願いします
Pascal
Pascal Girard
Director, Pharmacometry
Merck Serono | Global Early Development
"Merck – Living Innovation"
Merck Institute for Pharmacometrics - Merck Serono S.A.
EPFL Innovation Park - Building I, CH-1015 Lausanne, Switzerland
Phone: +41 21 900 3702 | Mobile: +41 79 508 7898
Email: [email protected] | www.merckserono.com
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forest plots in Xpose?
dear Pascal,
there seem to be copies of that library e.g. here
(* http://www2.uaem.mx/r-mirror/web/packages/popPK/index.html
http://www2.uaem.mx/r-mirror/web/packages/popPK/index.html*) and here (
https://cran.r-project.org/src/contrib/Archive/popPK/). You should be able
to download from there and install from the local zip file. I don't know
this library, so I'm not sure if it still works with current version of
Xpose. I also don't know of a different module that creates these plots,
but with the dplyr and ggplot2 libraries it shouldn't be more than 5-10
lines of code to create such a plot.
On a sidenote, I'm not a fan of the term "Forest plot" for these plots. The
"original" Forest plots show data across multiple studies (e.g. in a
meta-analysis), so calling it "Forest plot" could lead to confusion with
statisticians or clinicians. A more important reason, however, is that it
is not immediately clear what is actually shown in the plot. Various
covariate data can be summarized using the "Forest plot style", such as:
- uncertainty in covariate effect size (e.g. obtained from covariance step,
bootstrap, or posterior distribution from MCMC)
- inter-individual variability in covariate effect (distribution of
observed covariate values * covariate effect size)
- time-variance of the covariate effects
- a combination of 1 and 2?
So a covariate "Forest" covariate-plot should always be accompanied with a
description of what data is actually shown.
BTW, I think all of the above plots have utility in some way, either in
diagnosis, data checkout, or communicating modeling results. Would be great
if someone implemented an R package that could do all of the above :) I
assume the popPK package makes type 2, but it is not mentioned in the
manual.
best regards,
Ron
Quoted reply history
On Wed, Sep 16, 2015 at 12:57 AM, Pascal Girard <
[email protected]> wrote:
> Dear NONMEM users, Dear Uppsala Folks, Dear Christopher
>
>
>
> I was looking for some Xpose function that would automatically create a
> forest plot from NONMEM output in order to present the results of covariate
> analysis, assuming that all covariate models have been implemented the same
> way with same NULL value. The only thing I found was the Covariates
> function in the popPK package, which makes use of Xpose, developed by
> Christoffer
> Tornoe while he was at FDA.
> http://www2.uaem.mx/r-mirror/web/packages/popPK/popPK.pdf
>
>
>
> But this package looks like to be no longer supported and has been removed
> from the CRAN.
>
>
>
> Has anyone developed such a package?
>
>
>
> *With best regards / Mit freundlichen Grüßen / Cordialement */ 祝好 /
> よろしくお願いします
>
> Pascal
>
>
>
> Pascal Girard
>
> Director, Pharmacometry
>
> Merck Serono | Global Early Development
>
>
>
> * "Merck – Living Innovation" *
>
>
>
> Merck Institute for Pharmacometrics - Merck Serono S.A.
>
> EPFL Innovation Park - Building I, CH-1015 Lausanne, Switzerland
>
> Phone: +41 21 900 3702 | Mobile: +41 79 508 7898
>
> Email: [email protected] | www.merckserono.com
>
> Mandatory information can be found at:
> http://www.merckgroup.com/mandatories
>
> *Please consider your environmental responsibility before printing this
> e-mail*
>
>
>
>
>
> This message and any attachment are confidential and may be privileged or
> otherwise protected from disclosure. If you are not the intended recipient,
> you must not copy this message or attachment or disclose the contents to
> any other person. If you have received this transmission in error, please
> notify the sender immediately and delete the message and any attachment
> from your system. Merck KGaA, Darmstadt, Germany and any of its
> subsidiaries do not accept liability for any omissions or errors in this
> message which may arise as a result of E-Mail-transmission or for damages
> resulting from any unauthorized changes of the content of this message and
> any attachment thereto. Merck KGaA, Darmstadt, Germany and any of its
> subsidiaries do not guarantee that this message is free of viruses and does
> not accept liability for any damages caused by any virus transmitted
> therewith.
>
>
>
> Click http://www.merckgroup.com/disclaimer to access the German, French,
> Spanish and Portuguese versions of this disclaimer.
>
-------------------------------
Pirana Software & Consulting BV
@ronpirana
Dear all,
Folks at Metrum published some R-code on how to generate these kind of
covariate plots, including uncertainty of the effect size from a bootstrap:
http://metrumrg.googlecode.com/svn/trunk/inst/example/project/script/covplot.pdf
Here is also a very nice presentation from Marc Gastonguay about this topic:
http://metrumrg.com/assets/pubs/GastonguayPAGE2011.pdf
Regards, Andreas.
Quoted reply history
From: [email protected] [mailto:[email protected]] On
Behalf Of Ron Keizer
Sent: Thursday, September 17, 2015 02:09
To: Pascal Girard <[email protected]>
Cc: [email protected]
Subject: Re: [NMusers] forest plots in Xpose?
dear Pascal,
there seem to be copies of that library e.g. here
( http://www2.uaem.mx/r-mirror/web/packages/popPK/index.html) and here
( https://cran.r-project.org/src/contrib/Archive/popPK/). You should be able to
download from there and install from the local zip file. I don't know this
library, so I'm not sure if it still works with current version of Xpose. I
also don't know of a different module that creates these plots, but with the
dplyr and ggplot2 libraries it shouldn't be more than 5-10 lines of code to
create such a plot.
On a sidenote, I'm not a fan of the term "Forest plot" for these plots. The
"original" Forest plots show data across multiple studies (e.g. in a
meta-analysis), so calling it "Forest plot" could lead to confusion with
statisticians or clinicians. A more important reason, however, is that it is
not immediately clear what is actually shown in the plot. Various covariate
data can be summarized using the "Forest plot style", such as:
- uncertainty in covariate effect size (e.g. obtained from covariance step,
bootstrap, or posterior distribution from MCMC)
- inter-individual variability in covariate effect (distribution of observed
covariate values * covariate effect size)
- time-variance of the covariate effects
- a combination of 1 and 2?
So a covariate "Forest" covariate-plot should always be accompanied with a
description of what data is actually shown.
BTW, I think all of the above plots have utility in some way, either in
diagnosis, data checkout, or communicating modeling results. Would be great if
someone implemented an R package that could do all of the above :) I assume the
popPK package makes type 2, but it is not mentioned in the manual.
best regards,
Ron
On Wed, Sep 16, 2015 at 12:57 AM, Pascal Girard
<[email protected]<mailto:[email protected]>> wrote:
Dear NONMEM users, Dear Uppsala Folks, Dear Christopher
I was looking for some Xpose function that would automatically create a forest
plot from NONMEM output in order to present the results of covariate analysis,
assuming that all covariate models have been implemented the same way with same
NULL value. The only thing I found was the Covariates function in the popPK
package, which makes use of Xpose, developed by Christoffer Tornoe while he was
at FDA. http://www2.uaem.mx/r-mirror/web/packages/popPK/popPK.pdf
But this package looks like to be no longer supported and has been removed from
the CRAN.
Has anyone developed such a package?
With best regards / Mit freundlichen Grüßen / Cordialement / 祝好 / よろしくお願いします
Pascal
Pascal Girard
Director, Pharmacometry
Merck Serono | Global Early Development
"Merck – Living Innovation"
Merck Institute for Pharmacometrics - Merck Serono S.A.
EPFL Innovation Park - Building I, CH-1015 Lausanne, Switzerland
Phone: +41 21 900 3702<tel:%2B41%2021%20900%203702> | Mobile: +41 79 508
7898<tel:%2B41%2079%20508%207898>
Email: [email protected]<mailto:[email protected]> |
http://www.merckserono.com
Mandatory information can be found at: http://www.merckgroup.com/mandatories
Please consider your environmental responsibility before printing this e-mail
This message and any attachment are confidential and may be privileged or
otherwise protected from disclosure. If you are not the intended recipient, you
must not copy this message or attachment or disclose the contents to any other
person. If you have received this transmission in error, please notify the
sender immediately and delete the message and any attachment from your system.
Merck KGaA, Darmstadt, Germany and any of its subsidiaries do not accept
liability for any omissions or errors in this message which may arise as a
result of E-Mail-transmission or for damages resulting from any unauthorized
changes of the content of this message and any attachment thereto. Merck KGaA,
Darmstadt, Germany and any of its subsidiaries do not guarantee that this
message is free of viruses and does not accept liability for any damages caused
by any virus transmitted therewith.
Click http://www.merckgroup.com/disclaimer to access the German, French,
Spanish and Portuguese versions of this disclaimer.
-------------------------------
Pirana Software & Consulting BV
@ronpirana
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Ron, Pascal & NMUsers
Quoted reply history
On 9/17/2015 2:08, Ron Keizer wrote:
> On a sidenote, I'm not a fan of the term "Forest plot" for these plots.
> The "original" Forest plots show data across multiple studies (e.g. in a
> meta-analysis), so calling it "Forest plot" could lead to confusion with
> statisticians or clinicians.
I agree with Ron that Forest plots primarily exist in the meta analysis
world.
Pascal, maybe you are looking for "tornado plots"?
( https://en.wikipedia.org/wiki/Tornado_diagram)
Here's a pointer to building a tornado plot with ggplot():
http://stackoverflow.com/questions/6916698/tornado-chart-diagram-with-ggplot2
--
Paul Matthias Diderichsen, PhD
Quantitative Solutions B.V.
+31 624 330 706
Dear All,
Thanks all for your replies. I will not reply to each. Just to say that of
course I know that forest plots come from Meta Analysis, which by the way may
be already familiar to clinicians.
It has been advocated by FDA to report DDI see (Menon-Andersen D, Yu B,
Madabushi R, Bhattaram V, Hao W, Uppoor RS, Mehta M, Lesko L, Temple R,
Stockbridge N, Laughren T, Gobburu JV. Essential pharmacokinetic information
for drug dosage decisions: a concise visual presentation in the drug label.
Clin Pharmacol Ther. 2011 Sep;90(3):471-4. ) and is suggested in Guidance doc:
http://www.fda.gov/downloads/drugs/guidancecomplianceregulatoryinformation/guidances/ucm292362.pdf
http://www.fda.gov/downloads/AdvisoryCommittees/CommitteesMeetingMaterials/Drugs/AdvisoryCommitteeforPharmaceuticalScienceandClinicalPharmacology/UCM370535.pdf
I think it is an excellent way to communicate the results of covariate
analysis, rather than giving an allometric/ power equation and a value of a
parameter that does not speak to clinicians. I agree with Ron that it should be
clearly stated what is presented and there are several ways of building it. In
this respect the one given in the slides of Marc Gastonguay (thanks Andreas) is
particularly appealing.
With best regards / Mit freundlichen Grüßen / Cordialement
Pascal
Quoted reply history
-----Original Message-----
From: [email protected] [mailto:[email protected]] On
Behalf Of Paul Matthias Diderichsen
Sent: 17 September 2015 09:12
To: [email protected]
Subject: Re: [NMusers] forest plots in Xpose?
Ron, Pascal & NMUsers
On 9/17/2015 2:08, Ron Keizer wrote:
> On a sidenote, I'm not a fan of the term "Forest plot" for these plots.
> The "original" Forest plots show data across multiple studies (e.g. in
> a meta-analysis), so calling it "Forest plot" could lead to confusion
> with statisticians or clinicians.
I agree with Ron that Forest plots primarily exist in the meta analysis world.
Pascal, maybe you are looking for "tornado plots"?
( https://en.wikipedia.org/wiki/Tornado_diagram)
Here's a pointer to building a tornado plot with ggplot():
http://stackoverflow.com/questions/6916698/tornado-chart-diagram-with-ggplot2
--
Paul Matthias Diderichsen, PhD
Quantitative Solutions B.V.
+31 624 330 706
This message and any attachment are confidential and may be privileged or
otherwise protected from disclosure. If you are not the intended recipient, you
must not copy this message or attachment or disclose the contents to any other
person. If you have received this transmission in error, please notify the
sender immediately and delete the message and any attachment from your system.
Merck KGaA, Darmstadt, Germany and any of its subsidiaries do not accept
liability for any omissions or errors in this message which may arise as a
result of E-Mail-transmission or for damages resulting from any unauthorized
changes of the content of this message and any attachment thereto. Merck KGaA,
Darmstadt, Germany and any of its subsidiaries do not guarantee that this
message is free of viruses and does not accept liability for any damages caused
by any virus transmitted therewith.
Click http://www.merckgroup.com/disclaimer to access the German, French,
Spanish and Portuguese versions of this disclaimer.
Dear all,
As a late entrant to this discussion, indeed there are many ways to Rome.
The dotplot function in R (lattice) could provide a similar visual output,
though not as elegant as the Metrum approach.The metrumrg package is not
available on the CRAN repository any longer, but on R forge.
best wishes
Amit Taneja
Research fellow, Pharmacometrics
Dept of Pharmacokinetics, Toxicology and Targeting
University of Groningen
The Netherlands
Quoted reply history
> From: [email protected]
> To: [email protected]; [email protected]
> Subject: RE: [NMusers] forest plots in Xpose?
> Date: Fri, 18 Sep 2015 20:51:20 +0000
>
> Dear All,
>
> Thanks all for your replies. I will not reply to each. Just to say that of
> course I know that forest plots come from Meta Analysis, which by the way may
> be already familiar to clinicians.
>
> It has been advocated by FDA to report DDI see (Menon-Andersen D, Yu B,
> Madabushi R, Bhattaram V, Hao W, Uppoor RS, Mehta M, Lesko L, Temple R,
> Stockbridge N, Laughren T, Gobburu JV. Essential pharmacokinetic information
> for drug dosage decisions: a concise visual presentation in the drug label.
> Clin Pharmacol Ther. 2011 Sep;90(3):471-4. ) and is suggested in Guidance
> doc:
> http://www.fda.gov/downloads/drugs/guidancecomplianceregulatoryinformation/guidances/ucm292362.pdf
> http://www.fda.gov/downloads/AdvisoryCommittees/CommitteesMeetingMaterials/Drugs/AdvisoryCommitteeforPharmaceuticalScienceandClinicalPharmacology/UCM370535.pdf
>
> I think it is an excellent way to communicate the results of covariate
> analysis, rather than giving an allometric/ power equation and a value of a
> parameter that does not speak to clinicians. I agree with Ron that it should
> be clearly stated what is presented and there are several ways of building
> it. In this respect the one given in the slides of Marc Gastonguay (thanks
> Andreas) is particularly appealing.
>
> With best regards / Mit freundlichen Grüßen / Cordialement
>
> Pascal
>
> -----Original Message-----
> From: [email protected] [mailto:[email protected]] On
> Behalf Of Paul Matthias Diderichsen
> Sent: 17 September 2015 09:12
> To: [email protected]
> Subject: Re: [NMusers] forest plots in Xpose?
>
> Ron, Pascal & NMUsers
>
> On 9/17/2015 2:08, Ron Keizer wrote:
> > On a sidenote, I'm not a fan of the term "Forest plot" for these plots.
> > The "original" Forest plots show data across multiple studies (e.g. in
> > a meta-analysis), so calling it "Forest plot" could lead to confusion
> > with statisticians or clinicians.
>
> I agree with Ron that Forest plots primarily exist in the meta analysis world.
>
> Pascal, maybe you are looking for "tornado plots"?
> ( https://en.wikipedia.org/wiki/Tornado_diagram)
>
> Here's a pointer to building a tornado plot with ggplot():
>
> http://stackoverflow.com/questions/6916698/tornado-chart-diagram-with-ggplot2
>
> --
> Paul Matthias Diderichsen, PhD
> Quantitative Solutions B.V.
> +31 624 330 706
>
>
> This message and any attachment are confidential and may be privileged or
> otherwise protected from disclosure. If you are not the intended recipient,
> you must not copy this message or attachment or disclose the contents to any
> other person. If you have received this transmission in error, please notify
> the sender immediately and delete the message and any attachment from your
> system. Merck KGaA, Darmstadt, Germany and any of its subsidiaries do not
> accept liability for any omissions or errors in this message which may arise
> as a result of E-Mail-transmission or for damages resulting from any
> unauthorized changes of the content of this message and any attachment
> thereto. Merck KGaA, Darmstadt, Germany and any of its subsidiaries do not
> guarantee that this message is free of viruses and does not accept liability
> for any damages caused by any virus transmitted therewith.
>
>
>
> Click http://www.merckgroup.com/disclaimer to access the German, French,
> Spanish and Portuguese versions of this disclaimer.
Hi,
I echo with Amit, I have used the dotplot function, and it gives with
something very much same.
Thanks
Rakesh
Quoted reply history
On Sat, Oct 10, 2015 at 4:20 PM, amit <[email protected]> wrote:
>
> Dear all,
>
> As a late entrant to this discussion, indeed there are many ways to Rome.
>
> The dotplot function in R (lattice) could provide a similar visual output,
> though not as elegant as the Metrum approach.The metrumrg package is not
> available on the CRAN repository any longer, but on R forge.
>
> best wishes
>
> Amit Taneja
>
> Research fellow, Pharmacometrics
> Dept of Pharmacokinetics, Toxicology and Targeting
> University of Groningen
> The Netherlands
>
>
>
> > From: [email protected]
> > To: [email protected]; [email protected]
> > Subject: RE: [NMusers] forest plots in Xpose?
> > Date: Fri, 18 Sep 2015 20:51:20 +0000
>
> >
> > Dear All,
> >
> > Thanks all for your replies. I will not reply to each. Just to say that
> of course I know that forest plots come from Meta Analysis, which by the
> way may be already familiar to clinicians.
> >
> > It has been advocated by FDA to report DDI see (Menon-Andersen D, Yu B,
> Madabushi R, Bhattaram V, Hao W, Uppoor RS, Mehta M, Lesko L, Temple R,
> Stockbridge N, Laughren T, Gobburu JV. Essential pharmacokinetic
> information for drug dosage decisions: a concise visual presentation in the
> drug label. Clin Pharmacol Ther. 2011 Sep;90(3):471-4. ) and is suggested
> in Guidance doc:
> >
> http://www.fda.gov/downloads/drugs/guidancecomplianceregulatoryinformation/guidances/ucm292362.pdf
> >
> http://www.fda.gov/downloads/AdvisoryCommittees/CommitteesMeetingMaterials/Drugs/AdvisoryCommitteeforPharmaceuticalScienceandClinicalPharmacology/UCM370535.pdf
> >
> > I think it is an excellent way to communicate the results of covariate
> analysis, rather than giving an allometric/ power equation and a value of a
> parameter that does not speak to clinicians. I agree with Ron that it
> should be clearly stated what is presented and there are several ways of
> building it. In this respect the one given in the slides of Marc Gastonguay
> (thanks Andreas) is particularly appealing.
> >
> > With best regards / Mit freundlichen Grüßen / Cordialement
> >
> > Pascal
> >
> > -----Original Message-----
> > From: [email protected] [mailto:[email protected]]
> On Behalf Of Paul Matthias Diderichsen
> > Sent: 17 September 2015 09:12
> > To: [email protected]
> > Subject: Re: [NMusers] forest plots in Xpose?
> >
> > Ron, Pascal & NMUsers
> >
> > On 9/17/2015 2:08, Ron Keizer wrote:
> > > On a sidenote, I'm not a fan of the term "Forest plot" for these plots.
> > > The "original" Forest plots show data across multiple studies (e.g. in
> > > a meta-analysis), so calling it "Forest plot" could lead to confusion
> > > with statisticians or clinicians.
> >
> > I agree with Ron that Forest plots primarily exist in the meta analysis
> world.
> >
> > Pascal, maybe you are looking for "tornado plots"?
> > ( https://en.wikipedia.org/wiki/Tornado_diagram)
> >
> > Here's a pointer to building a tornado plot with ggplot():
> >
> >
> http://stackoverflow.com/questions/6916698/tornado-chart-diagram-with-ggplot2
> >
> > --
> > Paul Matthias Diderichsen, PhD
> > Quantitative Solutions B.V.
> > +31 624 330 706
> >
> >
> > This message and any attachment are confidential and may be privileged
> or otherwise protected from disclosure. If you are not the intended
> recipient, you must not copy this message or attachment or disclose the
> contents to any other person. If you have received this transmission in
> error, please notify the sender immediately and delete the message and any
> attachment from your system. Merck KGaA, Darmstadt, Germany and any of its
> subsidiaries do not accept liability for any omissions or errors in this
> message which may arise as a result of E-Mail-transmission or for damages
> resulting from any unauthorized changes of the content of this message and
> any attachment thereto. Merck KGaA, Darmstadt, Germany and any of its
> subsidiaries do not guarantee that this message is free of viruses and does
> not accept liability for any damages caused by any virus transmitted
> therewith.
> >
> >
> >
> > Click http://www.merckgroup.com/disclaimer to access the German,
> French, Spanish and Portuguese versions of this disclaimer.
>