NONMEM Users Network Archive

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RE: Meta-analysis with Nonmem

From: alindauer-research
Date: Thu, 4 Mar 2010 16:21:58 +0100

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.


Andreas Lindauer
Pharmacokineticist
Pharmacokinetics and Metabolism
R&D Center. Ferrer Internacional S.A.
Juan de Sada 32, 08028 Barcelona


alindauer-research o.com
www.ferrergrupo.com







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"Elodie Plan" <elodie.plan
04/03/2010 14:33

Para
<alindauer-research m>, <nmusers
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
On Behalf Of alindauer-research om
Sent: Friday, February 26, 2010 10:26 AM
To: nmusers
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.


Andreas Lindauer
Pharmacokineticist
Pharmacokinetics and Metabolism
R&D Center. Ferrer Internacional S.A.
Juan de Sada 32, 08028 Barcelona


alindauer-research
www.ferrergrupo.com





 


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su borrado. Gracias por su colaboración.

This message and its annexed files may contain confidential information
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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
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Received on Thu Mar 04 2010 - 10:21:58 EST

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