RE: [Fwd: occasions during pregnancy]
Paul
As another "rule" protein binding decreases throughout pregnancy to a low at
term due to dilution. This with a purported increase in CL makes for
interesting modelling.
I think as an initial approach a biologically plausible model is better than
moving down the various variance routes. Once you have something that you
think describes the biology then I think it would be important and interesting
to explore inclusion of hierarchical random effects.
Regards
Steve
--
Professor Stephen Duffull
Chair of Clinical Pharmacy
School of Pharmacy
University of Otago
PO Box 56 Dunedin
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Quoted reply history
> -----Original Message-----
> From: [email protected] [mailto:[email protected]] On
> Behalf Of [email protected]
> Sent: Wednesday, 2 March 2011 8:24 a.m.
> To: [email protected]; [email protected]; [email protected]
> Subject: Re: [NMusers] [Fwd: occasions during pregnancy]
>
> Paul
> Another suggestion
> As a general rule, drug clearance increases during pregnancy due to increased
> blood perfusion, especially during the last trimesters. You might also
> consider a time covariate effect over your clearance rather than on etas, with
> fewer parameters.
>
> Best wishes,
> Armel
>
> Armel Stockis
> UCB Pharma
> Brussels
>
> ----- Original Message -----
> From: Kevin Dykstra [mailto:[email protected]]
> Sent: Tuesday, March 01, 2011 05:59 PM
> To: [email protected] <[email protected]>; 'nm nm' <[email protected]>
> Subject: RE: [NMusers] [Fwd: occasions during pregnancy]
>
> Paul,
> You might try plotting your etas 6-9 vs. trimester (coded at four levels) to
> ensure that the IOV is truly random by occasion, as your model assumes.
> Obviously, it is not unheard of that the IOV should be much larger than IIV,
> but I wouldn't start with that assumption. Usually there is at least some
> correlation within an individual. Good luck.
> Kevin
>
> Kevin Dykstra, PhD, FCP
>
> +1 978.655.1943 (O)
> +1 978.289.2987 (M)
> [email protected] | http://qPharmetra.com
>
>
> -----Original Message-----
> From: [email protected] [mailto:[email protected]] On
> Behalf Of [email protected]
> Sent: Tuesday, March 01, 2011 10:53 AM
> To: nm nm
> Subject: [NMusers] [Fwd: occasions during pregnancy]
>
> ---------------------------- Original Message ----------------------------
> Subject: occasions during pregnancy
> From: [email protected]
> Date: Tue, March 1, 2011 10:49 am
> To: "nm nm" <[email protected]>
> --------------------------------------------------------------------------
>
> Hi all nmusers,
>
> I thank all who responded my questions yesterday. Almost all the responses
> suggested that several occasions of one patient should be put under one ID
> #. I re-code my control stream and adjusted the data file as following:
>
> $PK
> K12 = THETA(1)*EXP(ETA(1))
> CL=
> THETA(2)*EXP(ETA(2)+ETA(6)*TRI1+ETA(7)*TRI2+ETA(8)*TRI3+ETA(9)*TRI4)
> $OMEGA
> .8;
> .1 .8;
> .1 .1 .8;
> .1 .1 .1 .8;
> .1 .1 .1 .1 .8;
> $OMEGA BLOCK(1) 0.9;
> $OMEGA BLOCK(1) SAME;
> $OMEGA BLOCK(1) SAME;
> $OMEGA BLOCK(1) SAME;
>
>
> where TRI1,TRI2,TRI3, and TRI4 are different stages of pregnancy.
>
> This model fits poorly for the data (from the plot of PRED, IPRED VS. DV),
> although the estimates are stable and reasonable.
>
> If I treat the different occasions as different patients, ignoring the
> correlation within the same patients, then the model fits quite well and the
> results are reasonable.
>
> I also noticed one note from Lewis Sheiner:
>
> Note that, as happens more often, at least with human data, than one might
> have thought, the IOV>IIV, then treating each occaasion as though it were a
> distinct individual is a reasonable approximation.
>
>
> --------------Date: Wed, 17 Nov 1999 13:57:18 -0800
> From: Lewis Sheiner <[email protected]>
> Subject: Re: repeating cases---------
>
> The parameters during pregnancy change quite large, so I am not sure if it
> is a reasonalble approximation to treat occasions as distinct individual, or
> I have to search the better models of putting those occasions under one ID?
> and what is the direction to improve the model?
>
> Any suggestion is greatly appreciated.
>
> Paul
>
> School of Pharmacy
> University of Pittsburgh
> 716 Salk Hall
> 3501 Terrace Street
> Pittsburgh, PA 15261
> Phone: 412-648-8546
> E-mail: [email protected]
>
>
> Yuanyue (Paul) Gao
>
> School of Pharmacy
> University of Pittsburgh
> 716 Salk Hall
> 3501 Terrace Street
> Pittsburgh, PA 15261
> Phone: 412-648-8546
> E-mail: [email protected]
>
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