Re: RE: Zähneputzen VOR oder NACH dem Frühstück? What comes fir st? BSV, BOV, or covariates?

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 > > > > > > > > This e-mail is subject to the UCT ICT policies and e-mail disclaimer > > > > published on our website at > > > > http://www.uct.ac.za/about/policies/emaildisclaimer/ or obtainable > > > > from +27 > > > > 21 650 9111. This e-mail is intended only for the person(s) to whom it > > > > is addressed. 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