NONMEM Users Network Archive

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RE: Meta-analysis with Nonmem

From: Martin Bergstrand <martin.bergstrand>
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
martin.bergstrand

-----------------------------------------------

Work: +46 18 471 4639

Mobile: +46 709 994 396

 

From: owner-nmusers
On Behalf Of alindauer-research
Sent: den 4 mars 2010 16:21
To: Elodie Plan
Cc: nmusers
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


www.ferrergrupo.com

        
        
        
        
        

 


Recicla

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"Elodie Plan" <elodie.plan

04/03/2010 14:33


Para

<alindauer-research


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
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.


Ferrer


Andreas Lindauer


Pharmacokineticist


Pharmacokinetics and Metabolism


R&D Center. Ferrer Internacional S.A.


Juan de Sada 32, 08028 Barcelona

        
        

 <mailto:alindauer-research
alindauer-research


 <http://www.ferrergrupo.com/> www.ferrergrupo.com

        
        
        
        
        


  


Recicla

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Este mensaje, y en su caso, cualquier fichero anexo al mismo, puede =
contener información confidencial, siendo para uso exclusivo del =
destinatario, quedando prohibida su divulgación, copia o =
distribución a terceros sin la autorización expresa del =
remitente. Si Vd. ha recibido este mensaje erróneamente, se ruega =
lo notifique al remitente y proceda a su borrado. Gracias por su =
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.


  



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Received on Fri Mar 05 2010 - 04:14:48 EST

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