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AW: Meta-analysis with Nonmem

From: Garmann, Dirk <Dirk.Garmann>
Date: Thu, 25 Feb 2010 11:10:25 +0100

Dear Leonid, Andreas,
I would suggest to simulate each study with N subjects based on the known=
 distribution, mean value (DV), SD,N. This would consider the number of s=
ubjects in each study as well as the study specific variability.
The datasets can be merged and used for a combined NONMEM analysis

If the number of subjects in a study is small, it might be useful to repe=
at the simulation and produce different combined datasets

The NONMEM results based on all combined datasets can be compared/analyze=
d

Best regards
Dirk


Dirk Garmann, PhD
Clinical Scientific Expert /Pharmacokineticist
Merz Pharmaceuticals
Eckenheimer Landstrasse 100
60318 Frankfurt
Phone +49 (69) 1503 720



-----Ursprüngliche Nachricht-----
Von: owner-nmusers
m Auftrag von Leonid Gibiansky
Gesendet: Wednesday, February 24, 2010 4:45 PM
An: alindauer-research
Cc: nmusers
Betreff: Re: [NMusers] Meta-analysis with Nonmem

Andreas,
I think if you have only study-level data, you can treat each study as a
"subject", build meta-population dose-PD model in the usual way,

IPRED=Emax (or some other) function of DOSE

and modify the error part as follows: For each data point, you know the
mean value (DV), SD, and N. From SD and N you can get an estimate of
standard error of the mean as SE=SD/sqrt(N) (computed for each data
point and included into the data file). Then your error model would inclu=
de

Y=IPRED+SE*EPS(1)

I am not sure whether you need to fix SIGMA
$SIGMA
1 FIXED ; for EPS(1)

thus assuming that all error in your model comes from the "assay", or
estimate it thus allowing for unexplained model misspecification and
extra error. I would try both ways to see the difference.

This is the simplest version that can be further improved (? or at
least, made more complicated) by adding the study effect on error (thus
accounting for possible differences in study populations;
Y=IPRED+SE*EXP(ETA(1))*EPS(1)), etc.

Leonid

--------------------------------------
Leonid Gibiansky, Ph.D.
President, QuantPharm LLC
web: www.quantpharm.com
e-mail: LGibiansky at quantpharm.com
tel: (301) 767 5566




alindauer-research
>
> Dear NMUSERS,
>
> I wanted to investigate the dose-response relationship (Emax model) of =
a
> drug with NONMEM, based on data from literature (i.e. a meta-analysis).=
 
> However, I am not quite sure how to deal with the different levels of
> random effects. Suppose I have 10 studies of different size where
> different doses were given and the response is presented as average
> change of a biomarker +/- standard deviation for each dose level. How
> would I incorporate the standard deviation of the biomarker measurement=
s
> reported in each study for each dose level and how would I account for
> the different number of patients in the study?
> I would greatly appreciate your help, maybe with a NM-code snippet or
> reference to a paper where something similar has been done.
>
> Thanks in advance, 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
>
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Merz Pharmaceuticals GmbH, Frankfurt am Main
Amtsgericht Frankfurt am Main, HRB 53808
Geschäftsführung: Dr. Martin Zügel (Vors.), Dr. Alexander Gebauer,
Dr. Karsten Schlemm, Dr. Eugen Wilbert



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Received on Thu Feb 25 2010 - 05:10:25 EST

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