Re: [NMusers] Genotype data missing in some individuals

From: Jeroen Elassaiss-Schaap <jeroen_at_pd-value.com>
Date: Wed, 19 Nov 2014 12:16:10 +0100

Dear SoJeong,

First you might want to answer the question whether that phenotype is indeed important in your dataset. With the initial popPK model you could plot posthoc clearance against bodyweight and/or inspect the posthocs of clearance for evidence of multiple peaks in your distribution. You also may see the impact of phenotype in stratified concentration versus time plots. Depending on the dataset, with its sampling scheme, number of subjects (perhaps a low number) and distribution across age, it could be masked.

If the impact is clear however, it might be benificial to try to include the subjects wih missing genotype. With a clear effect, you might be able to develop a mixture model. The mixture  approach would describe the different populations in your dataset corresponding to the different phenotypes. The genotype would than inform the mixture as a covariate - the missing information would fall back to the pure mixture approach. As a warning, this approach is quite difficult. I would advise you to read up on the nonmem guides ($MIX) on this and look in the literature for examples - the Karlsson group has published about it, most recently this one (it contains code): http://link.springer.com/article/10.1208/s12248-009-9093-4. A search in the literature gives you additional background such as http://www.page-meeting.org/pdf_assets/9595-PAGE2007_3.pdf and http://link.springer.com/article/10.1007/s10928-006-9038-9.

If the impact is not clear, a more empirical approach might be called for, in this case a subset analysis, i.e. where you exclude the missing subjects, of the covariate relationship might be all that you could achieve. If there is no impact at all, you do not need the genotype of course.

Hope this helps!

Best regards,

Jeroen

http://pd-value.com
jeroen_at_pd-value.com
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+31 6 23118438
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On Nov 19, 2014, 7:57 AM, at 7:57 AM, "이소정" <sjlpharm_at_gmail.com> wrote:
>Dear all,
>
>
>
>I’ve analyzed a tacrolimus PopPK in pediatric patients.
>
>As you know, CYP3A5 genotype can change the tacrolimus PK
>significantly, 3A5 genotyping was performed in the study,
>
>however, in 20% of the subjects, the genotype data was missed.
>
>
>
>Then, how can I reflect the CYP3A5 genotype effect to the tacrolimus
>population model appropriately?
>
>Is there any solution?
>
>
>
>Best regards,
>
>SoJeong Yi
>
>


Received on Wed Nov 19 2014 - 06:16:10 EST

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