Leonid,
thank you for your suggestion.
I probably did not explain well. I did introduce BOV on CL first, which was significant. If I tested BSV on top of BOV (or even alone, for what matters) it was not significant and poorly estimated. Since there was a trend in BOV between the two occasions, I captured it with the the covariate, and after that the model was able to separate BSV and BOV.
This is actually one of the reasons I normally include BOV first, I want first to see if there is a difference, and then I try to explain it with the covariate.
Thank you,
Paolo
Quoted reply history
On 24/11/2010 17:53, Leonid Gibiansky wrote:
> Paolo,
> I would not comment on the philosophical issues of brushing teeth, but
> the examples that you refer may have different explanations.
>
> In both examples, if the effect of a covariate was not taken into
> account, there was no observable (identifiable) inter-occasion
> variability. Then you introduced this effect (thus forcing the
> clearance to be different on two occasions) and the only way to
> compensate for possible over-correction was to introduce
> inter-occasion variability. Of course, this is playing devil's
> advocate, so I wonder whether you looked on the distributions of the
> inter-occasion variability ETAs: if the model is correct, they should
> be centered (for each occasion).
>
> Thanks
> Leonid
>
> --------------------------------------
> Leonid Gibiansky, Ph.D.
> President, QuantPharm LLC
> web: www.quantpharm.com
> e-mail: LGibiansky at quantpharm.com
> tel: (301) 767 5566
>
> On 11/24/2010 9:05 AM, Paolo Denti wrote:
>
> > Dear all,
> > thank you for the useful input.
> >
> > I agree with Jeroen about the fact that "those model parts that describe
> > most of variance in the most plausible manner should be introduced
> > first".
> >
> > In fact, I can think of a couple of situations in my not so long
> > experience, in which the inclusion of a very significant covariate was
> > necessary to correctly identify some of the other components of the
> > model.
> >
> > We had a study where some patients were sampled in two occasions, once
> > while given only the drug under test, and another time with
> > co-administration of a known inducer. If the effect of this inducer was
> > not taken into account, the model was not able to separate BSV and BOV
> > for CL. In another case, if a similar covariate effect was not included,
> > BOV in bioavailability was not found significant, while it greatly
> > improved the model, if incorporated after accounting for the covariate.
> >
> > In other words, I guess there's no rule that will work 100% of the
> > times, but my feeling is that, even in the worst case scenario, the ETAs
> > (both BOV and BSV) are very easy to remove from a model, since the
> > corresponding OMEGA will tend to shrink as they become less significant.
> > Also, the inclusion of the ETAs and the inspection of their plots
> > against time and other covariates might help to identify significant
> > covariate or time-dependent effects, as long as the shrinkage is not too
> > large. This was suggested to me by Martin Bergstrand in a private
> > message.
> >
> > Finally, I also agree with Bill about the fact that not always we will
> > reach the same "best" model independently of the modelling strategy
> > employed.. Obvioulsy re-testing some assumptions along the way may be a
> > more robust approach, but there's probably no complete guarantee...
> >
> > So probably Oscar is right, you should brush your teeth again and
> > again... But again, probably modelling cannot be compared to only a
> > simple breakfast, it is much rather a multi-course meal... ;)
> >
> > Regards,
> > Paolo
> >
> > On 24/11/2010 00:12, Denney, William S. wrote:
> >
> > > Hi Jeroen,
> > >
> > > Jumping in a bit later, I agree generally with what has been said so
> > > far, but I do disagree with one point. I think that the models we work
> > > with tend to have local minima that cause us to find different "best
> > > models" depending on the path taken to get there.
> > >
> > > And, I brush after breakfast to preserve the taste of the meal.
> > >
> > > Thanks,
> > >
> > > Bill
> > >
> > > On Nov 23, 2010, at 4:49 PM, "Elassaiss - Schaap, J.
> > > (Jeroen)"<[email protected]> wrote:
> > >
> > > > Hi Paolo,
> > > >
> > > > It is a bit late to chime in but I can't resist... Great discussion
> > > > point! I am of the opinion that if we develop models robustly, it in
> > > > the end should not matter. If we would introduce a structural bias by
> > > > neglecting BOV early on, we should be able to see a reflection of
> > > > that in a diagnostic plot after introduction of BOV. And that in turn
> > > > should lead to evaluation of other structural models. But this
> > > > obviously depends on close scrutiny of diagnostics and frequent
> > > > back-tracing.
> > > >
> > > > Perhaps the question could be restated as: which method is more
> > > > efficient? - retaining the original answer.
> > > >
> > > > It may even be generalized by stating that those model parts that
> > > > describe most of variance in the most plausible manner should be
> > > > introduced first. This should prevent bias that complicates
> > > > evaluation of more detailed parts because of nonlinearity issues as
> > > > you described.
> > > >
> > > > Such a rule could be applied to any model and result in e.g. BSV on
> > > > baseline be added early on for a PK-PD problem, body weight for
> > > > general PK, BOV for multi-occasion/rich sampling problems, to name a
> > > > few.
> > > >
> > > > Last but not least, I skip breakfast completely ;-).
> > > >
> > > > Best regards,
> > > > Jeroen
> > > >
> > > > Modeling& Simulation Expert
> > > > Pharmacokinetics, Pharmacodynamics& Pharmacometrics (P3) - DMPK
> > > > MSD
> > > > PO Box 20 - AP1112
> > > > 5340 BH Oss
> > > > The Netherlands
> > > > [email protected]
> > > > T: +31 (0)412 66 9320
> > > > M: +31 (0)6 46 101 283
> > > > F: +31 (0)412 66 2506
> > > > www.msd.com
> > > >
> > > > -----Original Message-----
> > > > From: [email protected]
> > > > [mailto:[email protected]] On Behalf Of Paolo Denti
> > > > Sent: Wednesday, 17 November, 2010 17:23
> > > > To: Elodie Plan
> > > > Cc: 'nmusers'
> > > > Subject: Re: [NMusers] Zähneputzen VOR oder NACH dem Frühstück?
> > > > What comes first? BSV, BOV, or covariates?
> > > >
> > > > Thank you Elodie,
> > > > the reference you mention also states that the covariates were tested
> > > > only on parameters for which BOV and BSV were significant. This is
> > > > generally the approach I use, so that I can test whether the
> > > > mentioned variabilities are indeed explained with the inclusion of
> > > > covariates. I wonder if somebody can think of any exceptions to this
> > > > "rule"?
> > > >
> > > > Also, both Oscar della Pasqua and Coen Van Hasselt pointed to me this
> > > > PAGE poster (unfortunately presented in a literally burning hot
> > > > poster session in Berlin):
> > > > http://www.page-meeting.org/default.asp?abstract=1887
> > > > which seems to stress that disregarding BOV might lead to model
> > > > misspecification.
> > > >
> > > > I also got a reply from Alwin Huitema, who told me that his
> > > > experience with modelling in HIV is that ignoring IOV early in the
> > > > modelling process might guide to wrong models.
> > > >
> > > > Any supporters of an alternative approach or shall I just assume that
> > > > I was doing the same as everybody else?
> > > >
> > > > Who would brush teeth before breakfast anyway? ;) Another, safer,
> > > > option is suggested by Oscar:
> > > >
> > > > > Paolo,
> > > > >
> > > > > By the way, hygiene rules do suggest you brush your teeth before and
> > > > > after breakfast.
> > > > > I don't want to infer that this is the same for modelling but I can
> > > > > say that you can recognise the individual ingredients in your
> > > > > breakfast if your taste butts are clean:)
> > > > >
> > > > > Oscar
> > > >
> > > > Ciao,
> > > > Paolo
> > > >
> > > > On 16/11/2010 22:15, Elodie Plan wrote:
> > > >
> > > > > Dear Paolo,
> > > > >
> > > > > Thanks for this interesting NMusers thread.
> > > > >
> > > > > I think the order you are describing really makes sense in theory,
> > > > > for
> > > > > the reasons you describe, but in brief because it seems covariates
> > > > > should be incorporated on a model already fully developed
> > > > > structurally
> > > > > and statistically, so this includes IOV. Moreover, the covariates
> > > > > will
> > > > > increase the predictive performance (and the understanding) of the
> > > > > model, by being introduced on structural parameters, but also
> > > > > possibly
> > > > > directly on IIV and IOV.
> > > > >
> > > > > I also wanted to verify that this was what was done in practice,
> > > > > there
> > > > > were
> > > > > 6 entries when searching for "occasion AND covariate AND NONMEM" on
> > > > > PubMed, I can recommend the following where the decrease in
> > > > > variability magnitude following the covariate model building is
> > > > > nicely
> > > > > discussed: Sandström M, Lindman H, Nygren P, Johansson M, Bergh J,
> > > > > Karlsson MO. Population analysis of the pharmacokinetics and the
> > > > > haematological toxicity of the
> > > > > fluorouracil-epirubicin-cyclophosphamide regimen in breast cancer
> > > > > patients.
> > > > > Cancer Chemother Pharmacol. 2006 Aug;58(2):143-56.
> > > > >
> > > > > Best regards,
> > > > > Elodie
> > > > >
> > > > > PS: IOV or breakfast, I like it first :)
> > > > >
> > > > > Elodie L. Plan, PharmD, MSc, PhD student
> > > > > ********************************************
> > > > > Uppsala Pharmacometrics Research Group Department of Pharmaceutical
> > > > > Biosciences P.O. Box 591, SE-751 24 Uppsala, SWEDEN Mob +46 76-242
> > > > > 1256, Skype "ppeloo"
> > > > >
> > > > > -----Original Message-----
> > > > > From:[email protected]
> > > > > [mailto:[email protected]] On Behalf Of Paolo Denti
> > > > > Sent: Tuesday, November 16, 2010 10:10 AM
> > > > > To: nmusers
> > > > > Subject: [NMusers] Zähneputzen VOR oder NACH dem Frühstück? What
> > > > > comes
> > > > > first? BSV, BOV, or covariates?
> > > > >
> > > > > Dear all,
> > > > > don't be discouraged by the subject, this is indeed NMUsers and not
> > > > > German 101, and this post is about pharmacometrics, please read on...
> > > > > ;)
> > > > >
> > > > > The subject of the message comes from when I was studying German, and
> > > > > from an exercise in our book with lots of colourful pictures. The
> > > > > point of the exercise was only to teach us how to say "tooth
> > > > > brushing", "have breakfast", "before" and "after", but instead it
> > > > > sprouted a lively discussion in the class about what comes first and
> > > > > last in everybody's morning routine... So I thought it would be an
> > > > > appropriate title for this post, which is a survey/question about
> > > > > what
> > > > > modelling approach people use/recommend for model development.
> > > > >
> > > > > Just to contextualize a bit, here at UCT we mainly study HIV and TB
> > > > > drugs, which are dosed repeatedly (once or twice per day) and
> > > > > administered orally.
> > > > > We often have data available on more than one sampling occasion, and
> > > > > many times these occasions are virtually
> > > > > equivalent: no changes in co-treatment or other covariates, just a
> > > > > mere repetition of the experiment on a different day. Confirming what
> > > > > Mats recently pointed out in a post about the use of BOV, our
> > > > > experience is that, especially in the absorption phase, the
> > > > > contribution of BOV is dominant, and cannot be ignored. The
> > > > > absorption
> > > > > is often subject to random delays and factors that are mostly
> > > > > occasion-specific and not measurable/available in the dataset.
> > > > >
> > > > > Therefore, when I start modelling new data, I normally proceed as
> > > > > follows:
> > > > > 1. I initially assume every occasion as a separate profile, either
> > > > > using dummy IDs (and pretending it's different subjects) or coding
> > > > > all
> > > > > variability as BOV. I believe this allows the maximum flexibility to
> > > > > test the structural model, and I find that, if I don't proceed like
> > > > > this, I may run into troubles detecting the correct structural model.
> > > > > In this early stage of model development, I mostly use individual
> > > > > plots, and try to see if my prediction profile is flexible enough to
> > > > > run through the points.
> > > > >
> > > > > 2. Then I try to see if some of the variability is subject-specific
> > > > > (normally V and CL) and can be better explained either by only BSV or
> > > > > both BSV and BOV. I use the OFV to guide this process, but if the BOV
> > > > > is much larger than BSV, and physiology supports the hypothesis that
> > > > > the parameter be occasion-specific, I tend to disregard BSV.
> > > > >
> > > > > 3. Once I believe I got my structural model right, and organized the
> > > > > hierarchy of random variability in a decent way, I start
> > > > > incorporating
> > > > > the covariates. If they turn out to be significant, I see that BOV
> > > > > and
> > > > > BSV decrease, and sometimes become superfluous in the model and can
> > > > > be removed.
> > > > >
> > > > > I know other modellers would recommend first introducing BSV and/or
> > > > > covariates, before considering BOV and I would be interested in
> > > > > knowing people's opinion about this. Each method probably has its
> > > > > pros
> > > > > and cons, and I would really value your input about this topic. What
> > > > > are the advantages and disadvantages of the different approaches?
> > > > >
> > > > > Since I favour the modus operandi I just explained, I give my
> > > > > reasons,
> > > > > and look forward to some comments. My opinion (but I am obviously
> > > > > biased) is that it does not hurt to include BOV first, since it is
> > > > > easy to remove from the model if the same variability is explained by
> > > > > covariates, and likely, if this is the case, BOV will decrease in
> > > > > size.
> > > > > On the other hand, disregarding BOV might prevent the identification
> > > > > of the correct structural model. I am thinking, for example, about a
> > > > > comparison between 2-cmpt vs 1-cmpt when the absorption is subject to
> > > > > substantial random delays. If BOV is not considered, this is
> > > > > equivalent to pooling the data from all occasions, with the potential
> > > > > result of having a cloud of points without much structure... And
> > > > > also,
> > > > > as a general rule, I would allow a parameter to move with an ETA,
> > > > > before I try to explain its changes with a covariate effect. In this
> > > > > way I can also test better if the covariate is explaining some of
> > > > > this variability.
> > > > >
> > > > > Ok, I've been once again way too lengthy, apologies. Any
> > > > > comments/thoughts?
> > > > > In other words, do you first brush your teeth or have breakfast?
> > > > > Please join the survey! ;)
> > > > >
> > > > > Greetings from Cape Town,
> > > > > Paolo
> > > > >
> > > > > PS Ich putze die Zähne immer NACH dem Frühstück... I can't enjoy
> > > > > coffee with that minty toothpaste after-taste... :)
> > > > >
> > > > > -- ------------------------------------------------
> > > > >
> > > > > Paolo Denti, PhD
> > > > > Post-Doctoral Fellow
> > > > > Division of Clinical Pharmacology
> > > > > Department of Medicine
> > > > > University of Cape Town
> > > > >
> > > > > K45 Old Main Building
> > > > > Groote Schuur Hospital
> > > > > Observatory, Cape Town
> > > > > 7925 South Africa
> > > > > phone: +27 21 404 7719
> > > > > fax: +27 21 448 1989
> > > > > email:[email protected]
> > > > > ------------------------------------------------
> > > > >
> > > > > ###
> > > > > UNIVERSITY OF CAPE TOWN
> > > > >
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> > > > -- ------------------------------------------------
> > > >
> > > > Paolo Denti, PhD
> > > > Post-Doctoral Fellow
> > > > Division of Clinical Pharmacology
> > > > Department of Medicine
> > > > University of Cape Town
> > > >
> > > > K45 Old Main Building
> > > > Groote Schuur Hospital
> > > > Observatory, Cape Town
> > > > 7925 South Africa
> > > > phone: +27 21 404 7719
> > > > fax: +27 21 448 1989
> > > > email:[email protected]
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------------------------------------------------
Paolo Denti, PhD
Post-Doctoral Fellow
Division of Clinical Pharmacology
Department of Medicine
University of Cape Town
K45 Old Main Building
Groote Schuur Hospital
Observatory, Cape Town
7925 South Africa
phone: +27 21 404 7719
fax: +27 21 448 1989
email: [email protected]
------------------------------------------------
--
------------------------------------------------
Paolo Denti, PhD
Post-Doctoral Fellow
Division of Clinical Pharmacology
Department of Medicine
University of Cape Town
K45 Old Main Building
Groote Schuur Hospital
Observatory, Cape Town
7925 South Africa
phone: +27 21 404 7719
fax: +27 21 448 1989
email: [email protected]
------------------------------------------------
###
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