Date: Fri, 5 Mar 2010 10:14:48 +0100
Dear Andreas,
Your interpretation is the same as mine (correct or not). My guessing is =
that you are actually never all that interested in precisely estimating =
BSV in this type of analysis. The approach nevertheless has advantages =
in assessing the overall between subject variability and average =
response. One advantage is that you could also include measurements of =
average response where the SD is unknown.
One thing worth considering will be if it is geometric means or =
arithmetic means that you are dealing with. The example in Elodies =
example assumes arithmetic means but geometric means could easily be =
handled with Y = AV * EXP(SEAV*EPS(1)).
Best regards,
Martin Bergstrand, MSc, PhD student
-----------------------------------------------
Pharmacometrics Research Group,
Department of Pharmaceutical Biosciences,
Uppsala University
-----------------------------------------------
<mailto:martin.bergstrand_at_farmbio.uu.se> =
martin.bergstrand_at_farmbio.uu.se
-----------------------------------------------
Work: +46 18 471 4639
Mobile: +46 709 994 396
From: owner-nmusers_at_globomaxnm.com [mailto:owner-nmusers_at_globomaxnm.com] =
On Behalf Of alindauer-research_at_ferrergrupo.com
Sent: den 4 mars 2010 16:21
To: Elodie Plan
Cc: nmusers_at_globomaxnm.com
Subject: RE: [NMusers] Meta-analysis with Nonmem
Hi Elodie, Martin and Mats,
Thanks for your suggestion, a very interesting approach. So, THETA1 =
would give me an estimate of the global between patient variability, =
expressed as SD, across all studies and OMEGA1 would be an estimate of =
the between study variability (BSV) of this SD. OMEGA2 would be the BSV =
of the average response. Is this interpretation correct? I suppose the =
number of studies has to be quite large to get precise estimates of the =
BSV.
Best regards, Andreas.
Ferrer
Andreas Lindauer
Pharmacokineticist
Pharmacokinetics and Metabolism
R&D Center. Ferrer Internacional S.A.
Juan de Sada 32, 08028 Barcelona
alindauer-research_at_ferrergrupo.com
www.ferrergrupo.com
Recicla
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"Elodie Plan" <elodie.plan_at_farmbio.uu.se>
04/03/2010 14:33
Para
<alindauer-research_at_ferrergrupo.com>, <nmusers_at_globomaxnm.com>
cc
Asunto
RE: [NMusers] Meta-analysis with Nonmem
Dear Andreas,
An approach you may consider is to model both the standard deviation and =
the average as dependent variables:
SD=THETA(1)*EXP(ETA(1))
AV=(THETA(2)+DOSE*THETA(3))*EXP(ETA(2))
SESD=SD/(2*(N-1)**.5)
SEAV=SD/N**.5
IF(FLAG.EQ.0) THEN
Y = SD+SESD*EPS(1)
ELSE
Y = AV+SEAV*EPS(1)
ENDIF
$SIGMA 1 FIX
Your dataset would treat study as individuals, include N the number of =
individuals in the study arm and incorporate a flag, so would look like: =
STUD=ID DV N FLAG DOSE
1 SD1 N1 0 D1
1 AV1 N1 1 D1
1 SD2 N2 0 D2
1 AV2 N2 1 D2
…
Note: this is only valid when there was only 1 endpoint per subject.
Hope this helps.
Best regards,
Elodie, Martin and Mats
Elodie L. Plan, PharmD, MSc, PhD student
********************************************
Uppsala Pharmacometrics Research Group,
Department of Pharmaceutical Biosciences,
P.O. Box 591, SE-751 24 Uppsala, SWEDEN
Office +46 18-471 4385, Fax +46 18-471 4003
From: owner-nmusers_at_globomaxnm.com [mailto:owner-nmusers_at_globomaxnm.com] =
On Behalf Of alindauer-research_at_ferrergrupo.com
Sent: Friday, February 26, 2010 10:26 AM
To: nmusers_at_globomaxnm.com
Subject: Re: [NMusers] Meta-analysis with Nonmem
Thank you Leonid and Dirk for your replies. They were very helpful.
Leonid, what would you think about the following:
Y=IPRED+SE*EPS(1)+ETA(1)
With SIGMA fixed to 1 and OMEGA being the inter-study =
standard-deviation? What would be the interpretation of SIGMA if it were =
not fixed to 1?
You wrote:
>>Y=IPRED+SE*EXP(ETA(1))*EPS(1)), etc.
Wouldn't this be somehow transformed by NONMEM because of the =
linearization process? Similarly to why we cannot use the exponential =
residual error model directly in NONMEM, but have to do the =
transform-both-sides approach.
Dirk, good idea. However, estimation of the simulated datasets might =
become very time consuming when you combine data from several large =
studies. And, as you said:
>> If the number of subjects in a study is small, it might be useful to =
repeat the simulation and produce different combined datasets.
I would even go further and say, that it is absolutly necessary to =
repeat the simulation-reestimation procedure many times in order to get =
"stable" results.
Best regards, Andreas.
Ferrer
Andreas Lindauer
Pharmacokineticist
Pharmacokinetics and Metabolism
R&D Center. Ferrer Internacional S.A.
Juan de Sada 32, 08028 Barcelona
<mailto:alindauer-research_at_ferrergrupo.com> =
alindauer-research_at_ferrergrupo.com
<http://www.ferrergrupo.com/> www.ferrergrupo.com
Recicla
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Este mensaje, y en su caso, cualquier fichero anexo al mismo, puede =
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colaboración.
This message and its annexed files may contain confidential information =
which is exclusively for the use of the addressee. It is strictly =
forbidden to distribute copies to third parties without the explicit =
permission of the sender. If you receive this message by mistake, please =
notify it to the sender and make sure to delete it. Thank you for your =
kind cooperation.
