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RE: lab values

From: Martin Bergstrand <martin.bergstrand>
Date: Wed, 13 Jan 2010 15:37:40 +0100

Dear Dirk and Jakob,

 

I agree with all of Jakobs suggestions but would like to come with an
additional suggestion. If you are going to use any type of imputation =
method
(LOCF, LOCB, linear interpolation, random imputation, baseline =
imputation,
substitution with population/individual median etc.) then create =
different
data-set using several imputation methods (that at least make some =
sense).
Choose the data-set with your primary choice of imputation and perform =
your
model building with this data-set. With you final model it can be wise =
to
make sure that the conclusions and parameter estimates based on this =
model
is not heavily dependent on the imputations made in your data-set. To do
this you can re-estimate parameter estimates of your final model using
data-sets with one or more alternative imputation methods. Similarly you =
can
reassess important likelihood ratio tests with the alternative =
data-sets.

 

Last I would like to point out that the imputation methods all rely on =
the
fact that the missingness of the observation is completely random and =
not
dependent on your primary dependent variable of interest. If this is
suspected only simultaneous modeling of the two variables are likely to =
give
unbiased results.

 

Best regards,

 

Martin Bergstrand, MSc, PhD student

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

Pharmacometrics Research Group,

Department of Pharmaceutical Biosciences,

Uppsala University

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

 <mailto:martin.bergstrand
martin.bergstrand

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

 

From: owner-nmusers
On
Behalf Of Ribbing, Jakob
Sent: den 13 januari 2010 14:34
To: Garmann, Dirk; nmusers
Subject: RE: [NMusers] lab values

 

Dirk,

 

I think the approach is influenced by what this lab value represents. If =
it
is a biomarker/endpoint that is influenced by drug treatment then the =
best
approach is to include this in your PK-PD model as a dependent variable. =
If
you treat this as a traditional covariate it should not be influenced by
treatment. Assuming your drug improves disease symptom or progression =
(as
measured by this biomarker) it would not be ideal to use either LOCF or
LOCB. The baseline for this biomarker (DAY -1 in your case) can be used =
as a
covariate in your PK model, as it is not influenced by drug treatment.

 

If you can not spend the time to build a proper PK-PD model but still
believe this covariate is important for your PK model then maybe you can =
do
something simple, like assuming a linear slope in this biomarker between =
the
two measurements and use the two observed values for interpolation?

 

Best regards

 

Jakob

 

  _____

From: owner-nmusers
On
Behalf Of Garmann, Dirk
Sent: 13 January 2010 12:41
To: nmusers
Subject: [NMusers] lab values

 

Dear NMUSERS,#

 

I would like to ask for some opinions regarding the handling of missing =
lab
values in a NONMEM Dataset;

 

Our normal procedure:

Parameter values will be carried backward to the first visit if the =
first
visit value is missing, it will be carry forward to the last visit if no
value is available at the last visit and will be set at the median value =
of
two adjacent visits in other cases.

 

Now we have a phase III study (multiple doses), one safety lab at day -1 =
and
one safety lab at final examination only, no lab in between (>6 month)

 

Two main strategies are possible

 

1.) Different from our standard procedure:

Carry the lab value at final examination backward to day -1.

 

2.) According to our standard: Use the median (or perhaps a =
regression
between the first and final examination)

:

My assumptions:

The first strategy might be useful to reflect the influence of the drug =
on
lab values and will reflect the steady state situation.

 

The second strategy might be better to characterize the influence of the =
lab
values on the PK of the drug, e.g if a disease worsens during the study.

 

As our main focus will be the last one, I would use the standard =
approach.

 

I know that this is quite basic, however as this was discussed during a
meeting I would appreciate to have your opinion.

 

Many thanks in advance

 

Dirk

 

Dirk Garmann, PhD

Clinical Scientific Expert /Pharmacokineticist

Merz Pharmaceuticals

Eckenheimer Landstrasse 100

60318 Frankfurt

Phone +49 (69) 1503 720

 

  _____

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 Wed Jan 13 2010 - 09:37:40 EST

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