Zähn eputzen VOR oder NACH dem Frühst ück? What comes first? BSV, BOV, or covariates?

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. If the e-mail has reached you in error, please notify the >> author. >> If you are not the intended recipient of the e-mail you may not use, >> disclose, copy, redirect or print the content. If this e-mail is not >> related to the business of UCT it is sent by the sender in the >> sender's individual capacity. >> >> ### >> >> >> > > -- > ------------------------------------------------ > 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. If the e-mail has reached you in error, please notify the author. > If you are not the intended recipient of the e-mail you may not use, > disclose, copy, redirect or print the content. If this e-mail is not related > to the business of UCT it is sent by the sender in the sender's individual > capacity. > > ### > > > > This message and any attachments are solely for the intended recipient. If > you are not the intended recipient, disclosure, copying, use or distribution > of the information included in this message is prohibited --- Please > immediately and permanently delete.