Dear NMusers:
As you know, body weight is an important covariate that is integrated into
the final or covariate model in some cases. When analyzing pediatric pop PK
data, body weight-based allometric ¾ power model is used frequently. By
definition, base model is a model without any covariates. But, in the
literature on the population PK in pediatrics, I noted that body weight is
added to the structural model (following the principles of allometry) before
starting the covariate model building in some but not in all studies. That
means that some models are called allometric base models and others are not.
What are their differences? For the allometric base model, body weight has
been added into the base model regardless of whether it is an important
covariate (in some cases, body weight is not). If body weight is not an
important covariate as determined by further covariate model building, is
there still the need to add body weight into the final allometric model
(if its corresponding base model is one without a body weight-associated
allometric component)? Logically, such a need seems to be not reasonable.
How to deal with this conflict? Is there an almost agreeable thought on this
issue in our community?
Thank you,
Hong-Guang
Your suggestions/thoughts needed on allometric base or final model
This has been discussed ad infinitum. Try the archives:
http://www.cognigencorp.com/nonmem/nm/
Quoted reply history
________________________________
From: owner-nmusers
On Behalf Of Hong-Guang Xie
Sent: Friday, July 11, 2008 12:36 PM
To: nmusers
Subject: [NMusers] Your suggestions/thoughts needed on allometric base or final model
Dear NMusers:
As you know, body weight is an important covariate that is integrated into the final or covariate model in some cases. When analyzing pediatric pop PK data, body weight-based allometric power model is used frequently. By definition, base model is a model without any covariates. But, in the literature on the population PK in pediatrics, I noted that body weight is added to the structural model (following the principles of allometry) before starting the covariate model building in some but not in all studies. That means that some models are called allometric base models and others are not. What are their differences? For the allometric base model, body weight has been added into the base model regardless of whether it is an important covariate (in some cases, body weight is not). If body weight is not an important covariate as determined by further covariate model building, is there still the need to add body weight into the final allometric model (if its corresponding base model is one without a body weight-associated allometric component)? Logically, such a need seems to be not reasonable. How to deal with this conflict? Is there an almost agreeable thought on this issue in our community?
Thank you,
Hong-Guang
Hello Hong-Guang
It is always a good idea to estimate the allometric coefficient if you have
adequate (weight ranges, PK sampling etc) data collected. If body weight is
not important (although that is rare in pediatrics), then it need not be
included in the model.
Atul
Venkatesh Atul Bhattaram
Pharmacometrics
US Food and Drug Administration
"The contents of this message are mine personally and do not necessarily
reflect any position of the Government or the Food and Drug Administration."
________________________________
Quoted reply history
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of
Hong-Guang Xie
Sent: Friday, July 11, 2008 12:36 PM
To: [email protected]
Subject: [NMusers] Your suggestions/thoughts needed on allometric base
or final model
Dear NMusers:
As you know, body weight is an important covariate that is integrated
into the final or covariate model in some cases. When analyzing pediatric pop
PK data, body weight-based allometric ¾ power model is used frequently. By
definition, base model is a model without any covariates. But, in the
literature on the population PK in pediatrics, I noted that body weight is
added to the structural model (following the principles of allometry) before
starting the covariate model building in some but not in all studies. That
means that some models are called allometric base models and others are not.
What are their differences? For the allometric base model, body weight has been
added into the base model regardless of whether it is an important covariate
(in some cases, body weight is not). If body weight is not an important
covariate as determined by further covariate model building, is there still the
need to add body weight into the final allometric model (if its corresponding
base model is one without a body weight-associated allometric component)?
Logically, such a need seems to be not reasonable. How to deal with this
conflict? Is there an almost agreeable thought on this issue in our community?
Thank you,
Hong-Guang
This has been discussed ad infinitum. Try the archives:
http://www.cognigencorp.com/nonmem/nm/
Quoted reply history
________________________________
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Hong-Guang Xie
Sent: Friday, July 11, 2008 12:36 PM
To: [email protected]
Subject: [NMusers] Your suggestions/thoughts needed on allometric base or final
model
Dear NMusers:
As you know, body weight is an important covariate that is integrated into the
final or covariate model in some cases. When analyzing pediatric pop PK data,
body weight-based allometric ¾ power model is used frequently. By definition,
base model is a model without any covariates. But, in the literature on the
population PK in pediatrics, I noted that body weight is added to the
structural model (following the principles of allometry) before starting the
covariate model building in some but not in all studies. That means that some
models are called allometric base models and others are not. What are their
differences? For the allometric base model, body weight has been added into the
base model regardless of whether it is an important covariate (in some cases,
body weight is not). If body weight is not an important covariate as determined
by further covariate model building, is there still the need to add body weight
into the final allometric model (if its corresponding base model is one without
a body weight-associated allometric component)? Logically, such a need seems to
be not reasonable. How to deal with this conflict? Is there an almost agreeable
thought on this issue in our community?
Thank you,
Hong-Guang
Atul
> It is always a good idea to estimate the allometric
> coefficient if you have adequate (weight ranges, PK sampling
> etc) data collected.
An interesting point. If you estimate the allometric coefficient then it
will almost always give a better fit to your data as your model has more
degrees of freedom. However if you do estimate it you will invariably get
it wrong. Many studies would be underpowered to detect this parameter and
estimating it will therefore tend to find more extreme values (either bigger
or smaller) since these are the only values that will be detected at your
predetermined alpha-level.
The question remains:
Do you go with biology and fix the coefficient at 0.75 for CL? or
Do you go with your data and estimate the coefficient?
In the latter setting you run the risk of describing your data too well at
the cost of generality to other data sets. In the former setting you may
inflate your remaining random BSV with noise from weight ...
I'm sure there is no absolute answer here.
Steve
PS Body weight is always important - we just can't always detect it.
Atul,
As Steve Duffull has pointed out you can decide to be an empiricist and ignore all prior biological knowledge and try to estimate empirically an allometric coefficient or you can put trust in prior knowledge which means PK parameters such as clearance will increase with weight. Empiricists will often misinterpret their statistical tests to conclude there is no association between weight and PK parameters when in fact the weight distribution is inadequate or they have not properly acccounted for important factors such as body composition.
If you believe in biology then it is foolish in most cases to attempt to estimate an allometric coefficient because the estimate will be biased unless you have a very informative weight distribution and good estimates of PK parameters (dont bother if you are relying on sparse PK sampling methods). See Anderson, B.J. and N.H. Holford, Mechanism-Based Concepts of Size and Maturity in Pharmacokinetics. Annu Rev Pharmacol Toxicol, 2008. 48: p. 303-332. for a discussion of the problem and experimental evidence of the difficulties in assessing allometric coefficients.
Body weight is always important (in adults and children) even if the data set you are studying is inadequate to reject a null hypothesis because of unsuitable design.
Hong-Guang,
In my opinion all PK *base* models will include allometric weight scaling of clearance and volume. If you ignore weight then is is like ignoring dose in PK models. Both weight and dose are fundamental covariates for predicting drug concentrations.
Nick
Bhattaram, Atul wrote:
> Hello Hong-Guang
>
> It is always a good idea to estimate the allometric coefficient if you have adequate (weight ranges, PK sampling etc) data collected. If body weight is not important (although that is rare in pediatrics), then it need not be included in the model.
>
> Atul
>
> Venkatesh Atul Bhattaram
> Pharmacometrics
> US Food and Drug Administration
>
> "The contents of this message are mine personally and do not necessarily reflect any position of the Government or the Food and Drug Administration."
>
> ------------------------------------------------------------------------
> *From:* [EMAIL PROTECTED]
> [mailto:[EMAIL PROTECTED] *On Behalf Of *Hong-Guang Xie
> *Sent:* Friday, July 11, 2008 12:36 PM
> *To:* [email protected]
> *Subject:* [NMusers] Your suggestions/thoughts needed on
> allometric base or final model
>
> Dear NMusers:
>
> As you know, body weight is an important covariate that is
> integrated into the final or covariate model in some cases. When
> analyzing pediatric pop PK data, body weight-based allometric ¾
> power model is used frequently. By definition, base model is a
> model without any covariates. But, in the literature on the
> population PK in pediatrics, I noted that body weight is added to
> the structural model (following the principles of allometry)
> before starting the covariate model building in some but not in
> all studies. That means that some models are called allometric
> base models and others are not. What are their differences? For
> the allometric base model, body weight has been added into the
> base model regardless of whether it is an important covariate (in
> some cases, body weight is not). If body weight is not an
> important covariate as determined by further covariate model
> building, is there still the need to add body weight into the
> final allometric model (if its corresponding base model is one
> without a body weight-associated allometric component)? Logically,
> such a need seems to be not reasonable. How to deal with this
> conflict? Is there an almost agreeable thought on this issue in
> our community?
>
> Thank you,
>
> Hong-Guang
--
Nick Holford, Dept Pharmacology & Clinical Pharmacology
University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New Zealand
[EMAIL PROTECTED] tel:+64(9)373-7599x86730 fax:+64(9)373-7090
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford
Hi
Perhaps it is worth noting at this point that (as we know) not all
covariates are equal. Nick indicated that some covariates are fundamental
and hence should not be discarded or even tested for. Perhaps a slightly
more generic framework is to consider that covariates naturally align to a
hierarchical framework, for instance I think it is indisputable in this
community that dose and time are at the most important covariates and we
wouldn't want to construct a PK model without them. Other covariates, such
as extracorporeal elimination (when relevant) are likely to be of a higher
order of importance than covariates based on phenotype, then biologically
meaningful covariates such as renal function, allometric weight, lean body
weight are more important than empirical covariates such as age... And so
forth.
So, when adding covariates into the model the hierarchy in which they enter
should, under a bioligical framework, not necessarily be up for statistical
testing. Since all of our models are nonlinear and therefore most linear
operations such as forward addition/back elimination are not consistent then
we really have no choice but to construct our hierarchy and consider tests
for covariates from the same hierarchical level (but perhaps not between
them). So under this construct you wouldn't consider swapping dose for
weight if it turned out that weight was statistically better than dose and
you also wouldn't consider swapping weight for age if age was statistically
better ...
At what stage you consider a covariate to be "fundamental" meaning it should
never be excluded will depend on the circumstance.
Steve
--
Professor Stephen Duffull
Chair of Clinical Pharmacy
School of Pharmacy
University of Otago
PO Box 913 Dunedin
New Zealand
E: [EMAIL PROTECTED]
P: +64 3 479 5044
F: +64 3 479 7034
Design software: www.winpopt.com
>Nick Holford wrote:
>Body weight is always important (in adults and children) even if the
>data set you are studying is inadequate to reject a null hypothesis
>because of unsuitable design.
The truth of this statement depends on what you mean by "important".
Dose is important because, for the majority of drugs, doubling dose
doubles plasma exposure, and this can lead to changes in side-effects
and/or efficacy. The effect of dose is fundamental to PK for 3 reasons:
1) It's magnitude - dose usually has a big effect on PK.
2) Dose is partially controlled by the prescriber
3) AUC is proportional to dose for the majority of drugs, with
an intercept of zero.
Comparing weight to dose seems to be stretching the point just a little.
I would be happy to accept the statement:
"Weight always has some effect on pharmacokinetics, though it may be so
small as to be practically irrelevant"
But that is a long way from:
"Weight is always important, in that it should alter dose selection"
Best regards, James
James G Wright PhD
Scientist
Wright Dose Ltd
Tel: 44 (0) 772 5636914
Quoted reply history
-----Original Message-----
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]
On Behalf Of Nick Holford
Sent: 14 July 2008 05:32
To: [email protected]
Subject: Re: [NMusers] Your suggestions/thoughts needed on allometric
base or final model
Atul,
As Steve Duffull has pointed out you can decide to be an empiricist and
ignore all prior biological knowledge and try to estimate empirically an
allometric coefficient or you can put trust in prior knowledge which
means PK parameters such as clearance will increase with weight.
Empiricists will often misinterpret their statistical tests to conclude
there is no association between weight and PK parameters when in fact
the weight distribution is inadequate or they have not properly
acccounted for important factors such as body composition.
If you believe in biology then it is foolish in most cases to attempt to
estimate an allometric coefficient because the estimate will be biased
unless you have a very informative weight distribution and good
estimates of PK parameters (dont bother if you are relying on sparse PK
sampling methods). See Anderson, B.J. and N.H. Holford,
Mechanism-Based Concepts of Size and Maturity in Pharmacokinetics. Annu
Rev Pharmacol Toxicol, 2008. 48: p. 303-332. for a discussion of the
problem and experimental evidence of the difficulties in assessing
allometric coefficients.
Body weight is always important (in adults and children) even if the
data set you are studying is inadequate to reject a null hypothesis
because of unsuitable design.
Hong-Guang,
In my opinion all PK *base* models will include allometric weight
scaling of clearance and volume. If you ignore weight then is is like
ignoring dose in PK models. Both weight and dose are fundamental
covariates for predicting drug concentrations.
Nick
Bhattaram, Atul wrote:
>
> Hello Hong-Guang
>
>
>
> It is always a good idea to estimate the allometric coefficient if you
> have adequate (weight ranges, PK sampling etc) data collected. If
> body weight is not important (although that is rare in pediatrics),
> then it need not be included in the model.
>
>
>
> Atul
>
>
>
> Venkatesh Atul Bhattaram
> Pharmacometrics
> US Food and Drug Administration
>
>
> "The contents of this message are mine personally and do not
> necessarily reflect any position of the Government or the Food and
> Drug Administration."
>
>
>
>
------------------------------------------------------------------------
> *From:* [EMAIL PROTECTED]
> [mailto:[EMAIL PROTECTED] *On Behalf Of *Hong-Guang
Xie
> *Sent:* Friday, July 11, 2008 12:36 PM
> *To:* [email protected]
> *Subject:* [NMusers] Your suggestions/thoughts needed on
> allometric base or final model
>
> Dear NMusers:
>
>
>
> As you know, body weight is an important covariate that is
> integrated into the final or covariate model in some cases. When
> analyzing pediatric pop PK data, body weight-based allometric ¾
> power model is used frequently. By definition, base model is a
> model without any covariates. But, in the literature on the
> population PK in pediatrics, I noted that body weight is added to
> the structural model (following the principles of allometry)
> before starting the covariate model building in some but not in
> all studies. That means that some models are called allometric
> base models and others are not. What are their differences? For
> the allometric base model, body weight has been added into the
> base model regardless of whether it is an important covariate (in
> some cases, body weight is not). If body weight is not an
> important covariate as determined by further covariate model
> building, is there still the need to add body weight into the
> final allometric model (if its corresponding base model is one
> without a body weight-associated allometric component)? Logically,
> such a need seems to be not reasonable. How to deal with this
> conflict? Is there an almost agreeable thought on this issue in
> our community?
>
>
>
> Thank you,
>
>
>
> Hong-Guang
>
--
Nick Holford, Dept Pharmacology & Clinical Pharmacology
University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New
Zealand
[EMAIL PROTECTED] tel:+64(9)373-7599x86730 fax:+64(9)373-7090
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford
James,
Intepretation of my remarks implicitly requires that you consider "all other things being equal" e.g. if the dose is doubled but the patient does not take the dose then the concentration will not double. I think dose and weight are equally important for predicting concentrations -- all other things being equal.
I did not write this and do not agree with it:
"Weight is always important, in that it should alter dose selection"
I can accept that weight based dosing may be unnecessary if other sources of variability are much larger but my remarks were made in the context of trying to describe the PK parameters of a drug. To imagine that clearance and volume are not related to weight is just foolish.
Nick
James G Wright wrote:
> > Nick Holford wrote:
>
> > Body weight is always important (in adults and children) even if the data set you are studying is inadequate to reject a null hypothesis because of unsuitable design.
>
> The truth of this statement depends on what you mean by "important".
> Dose is important because, for the majority of drugs, doubling dose
> doubles plasma exposure, and this can lead to changes in side-effects
> and/or efficacy. The effect of dose is fundamental to PK for 3 reasons:
> 1) It's magnitude - dose usually has a big effect on PK.
> 2) Dose is partially controlled by the prescriber
> 3) AUC is proportional to dose for the majority of drugs, with
> an intercept of zero.
>
> Comparing weight to dose seems to be stretching the point just a little.
> I would be happy to accept the statement:
>
> "Weight always has some effect on pharmacokinetics, though it may be so
> small as to be practically irrelevant"
>
> But that is a long way from:
>
> "Weight is always important, in that it should alter dose selection"
>
> Best regards, James
>
> James G Wright PhD
> Scientist
> Wright Dose Ltd
> Tel: 44 (0) 772 5636914
>
Quoted reply history
> -----Original Message-----
> From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]
> On Behalf Of Nick Holford
> Sent: 14 July 2008 05:32
> To: [email protected]
> Subject: Re: [NMusers] Your suggestions/thoughts needed on allometric
> base or final model
>
> Atul,
>
> As Steve Duffull has pointed out you can decide to be an empiricist and ignore all prior biological knowledge and try to estimate empirically an
>
> allometric coefficient or you can put trust in prior knowledge which means PK parameters such as clearance will increase with weight. Empiricists will often misinterpret their statistical tests to conclude there is no association between weight and PK parameters when in fact the weight distribution is inadequate or they have not properly acccounted for important factors such as body composition.
>
> If you believe in biology then it is foolish in most cases to attempt to
>
> estimate an allometric coefficient because the estimate will be biased unless you have a very informative weight distribution and good estimates of PK parameters (dont bother if you are relying on sparse PK sampling methods). See Anderson, B.J. and N.H. Holford, Mechanism-Based Concepts of Size and Maturity in Pharmacokinetics. Annu Rev Pharmacol Toxicol, 2008. 48: p. 303-332. for a discussion of the problem and experimental evidence of the difficulties in assessing allometric coefficients.
>
> Body weight is always important (in adults and children) even if the data set you are studying is inadequate to reject a null hypothesis because of unsuitable design.
>
> Hong-Guang,
>
> In my opinion all PK *base* models will include allometric weight scaling of clearance and volume. If you ignore weight then is is like ignoring dose in PK models. Both weight and dose are fundamental covariates for predicting drug concentrations.
>
> Nick
>
> Bhattaram, Atul wrote:
>
> > Hello Hong-Guang
> >
> > It is always a good idea to estimate the allometric coefficient if you
>
> > have adequate (weight ranges, PK sampling etc) data collected. If body weight is not important (although that is rare in pediatrics), then it need not be included in the model.
> >
> > Atul
> >
> > Venkatesh Atul Bhattaram
> > Pharmacometrics
> > US Food and Drug Administration
> >
> > "The contents of this message are mine personally and do not necessarily reflect any position of the Government or the Food and Drug Administration."
>
> ------------------------------------------------------------------------
>
> > *From:* [EMAIL PROTECTED]
> > [mailto:[EMAIL PROTECTED] *On Behalf Of *Hong-Guang
>
> Xie
>
> > *Sent:* Friday, July 11, 2008 12:36 PM
> > *To:* [email protected]
> > *Subject:* [NMusers] Your suggestions/thoughts needed on
> > allometric base or final model
> >
> > Dear NMusers:
> >
> > As you know, body weight is an important covariate that is
> > integrated into the final or covariate model in some cases. When
> > analyzing pediatric pop PK data, body weight-based allometric ¾
> > power model is used frequently. By definition, base model is a
> > model without any covariates. But, in the literature on the
> > population PK in pediatrics, I noted that body weight is added to
> > the structural model (following the principles of allometry)
> > before starting the covariate model building in some but not in
> > all studies. That means that some models are called allometric
> > base models and others are not. What are their differences? For
> > the allometric base model, body weight has been added into the
> > base model regardless of whether it is an important covariate (in
> > some cases, body weight is not). If body weight is not an
> > important covariate as determined by further covariate model
> > building, is there still the need to add body weight into the
> > final allometric model (if its corresponding base model is one
> > without a body weight-associated allometric component)? Logically,
> > such a need seems to be not reasonable. How to deal with this
> > conflict? Is there an almost agreeable thought on this issue in
> > our community?
> >
> > Thank you,
> >
> > Hong-Guang
--
Nick Holford, Dept Pharmacology & Clinical Pharmacology
University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New Zealand
[EMAIL PROTECTED] tel:+64(9)373-7599x86730 fax:+64(9)373-7090
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford
Hi Nick,
Perhaps I am foolish, as I must be misunderstanding your point.
If the goal is predicting concentrations, I struggle to imagine a
situation where knowing a covariate is anywhere near as valuable as
knowing the dose administered. Dose appears explicitly in
pharmacokinetic formulae and concentrations are typically proportional
to dose. Weight is just a covariate, meaning that it can improve your
guess of the pharmacokinetic parameters. It's not even a particularly
good covariate...
Best regards, James
James G Wright PhD
Scientist
Wright Dose Ltd
Tel: 44 (0) 772 5636914
Quoted reply history
-----Original Message-----
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]
On Behalf Of Nick Holford
Sent: 15 July 2008 23:05
To: [email protected]
Subject: Re: [NMusers] Your suggestions/thoughts needed on allometric
base or final model
James,
Intepretation of my remarks implicitly requires that you consider "all
other things being equal" e.g. if the dose is doubled but the patient
does not take the dose then the concentration will not double. I think
dose and weight are equally important for predicting concentrations --
all other things being equal.
I did not write this and do not agree with it:
"Weight is always important, in that it should alter dose selection"
I can accept that weight based dosing may be unnecessary if other
sources of variability are much larger but my remarks were made in the
context of trying to describe the PK parameters of a drug. To imagine
that clearance and volume are not related to weight is just foolish.
Nick
James G Wright wrote:
>> Nick Holford wrote:
>>
>
>
>> Body weight is always important (in adults and children) even if the
>> data set you are studying is inadequate to reject a null hypothesis
>> because of unsuitable design.
>>
>
>
> The truth of this statement depends on what you mean by "important".
> Dose is important because, for the majority of drugs, doubling dose
> doubles plasma exposure, and this can lead to changes in side-effects
> and/or efficacy. The effect of dose is fundamental to PK for 3
reasons:
> 1) It's magnitude - dose usually has a big effect on PK.
> 2) Dose is partially controlled by the prescriber
> 3) AUC is proportional to dose for the majority of drugs, with
> an intercept of zero.
>
> Comparing weight to dose seems to be stretching the point just a
little.
> I would be happy to accept the statement:
>
> "Weight always has some effect on pharmacokinetics, though it may be
so
> small as to be practically irrelevant"
>
> But that is a long way from:
>
> "Weight is always important, in that it should alter dose selection"
>
> Best regards, James
>
> James G Wright PhD
> Scientist
> Wright Dose Ltd
> Tel: 44 (0) 772 5636914
>
>
> -----Original Message-----
> From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED]
> On Behalf Of Nick Holford
> Sent: 14 July 2008 05:32
> To: [email protected]
> Subject: Re: [NMusers] Your suggestions/thoughts needed on allometric
> base or final model
>
> Atul,
>
> As Steve Duffull has pointed out you can decide to be an empiricist
and
> ignore all prior biological knowledge and try to estimate empirically
an
>
> allometric coefficient or you can put trust in prior knowledge which
> means PK parameters such as clearance will increase with weight.
> Empiricists will often misinterpret their statistical tests to
conclude
> there is no association between weight and PK parameters when in fact
> the weight distribution is inadequate or they have not properly
> acccounted for important factors such as body composition.
>
> If you believe in biology then it is foolish in most cases to attempt
to
>
> estimate an allometric coefficient because the estimate will be biased
> unless you have a very informative weight distribution and good
> estimates of PK parameters (dont bother if you are relying on sparse
PK
> sampling methods). See Anderson, B.J. and N.H. Holford,
> Mechanism-Based Concepts of Size and Maturity in Pharmacokinetics.
Annu
> Rev Pharmacol Toxicol, 2008. 48: p. 303-332. for a discussion of the
> problem and experimental evidence of the difficulties in assessing
> allometric coefficients.
>
> Body weight is always important (in adults and children) even if the
> data set you are studying is inadequate to reject a null hypothesis
> because of unsuitable design.
>
> Hong-Guang,
>
> In my opinion all PK *base* models will include allometric weight
> scaling of clearance and volume. If you ignore weight then is is like
> ignoring dose in PK models. Both weight and dose are fundamental
> covariates for predicting drug concentrations.
>
> Nick
>
> Bhattaram, Atul wrote:
>
>> Hello Hong-Guang
>>
>>
>>
>> It is always a good idea to estimate the allometric coefficient if
you
>>
>
>
>> have adequate (weight ranges, PK sampling etc) data collected. If
>> body weight is not important (although that is rare in pediatrics),
>> then it need not be included in the model.
>>
>>
>>
>> Atul
>>
>>
>>
>> Venkatesh Atul Bhattaram
>> Pharmacometrics
>> US Food and Drug Administration
>>
>>
>> "The contents of this message are mine personally and do not
>> necessarily reflect any position of the Government or the Food and
>> Drug Administration."
>>
>>
>>
>>
>>
>
------------------------------------------------------------------------
>
>> *From:* [EMAIL PROTECTED]
>> [mailto:[EMAIL PROTECTED] *On Behalf Of *Hong-Guang
>>
> Xie
>
>> *Sent:* Friday, July 11, 2008 12:36 PM
>> *To:* [email protected]
>> *Subject:* [NMusers] Your suggestions/thoughts needed on
>> allometric base or final model
>>
>> Dear NMusers:
>>
>>
>>
>> As you know, body weight is an important covariate that is
>> integrated into the final or covariate model in some cases. When
>> analyzing pediatric pop PK data, body weight-based allometric ¾
>> power model is used frequently. By definition, base model is a
>> model without any covariates. But, in the literature on the
>> population PK in pediatrics, I noted that body weight is added to
>> the structural model (following the principles of allometry)
>> before starting the covariate model building in some but not in
>> all studies. That means that some models are called allometric
>> base models and others are not. What are their differences? For
>> the allometric base model, body weight has been added into the
>> base model regardless of whether it is an important covariate (in
>> some cases, body weight is not). If body weight is not an
>> important covariate as determined by further covariate model
>> building, is there still the need to add body weight into the
>> final allometric model (if its corresponding base model is one
>> without a body weight-associated allometric component)?
Logically,
>> such a need seems to be not reasonable. How to deal with this
>> conflict? Is there an almost agreeable thought on this issue in
>> our community?
>>
>>
>>
>> Thank you,
>>
>>
>>
>> Hong-Guang
>>
>>
>
>
--
Nick Holford, Dept Pharmacology & Clinical Pharmacology
University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New
Zealand
[EMAIL PROTECTED] tel:+64(9)373-7599x86730 fax:+64(9)373-7090
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford