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RE: CrcL or Cr in pediatric model

From: Ribbing, Jakob <Jakob.Ribbing>
Date: Tue, 13 Jan 2009 07:31:50 -0000

Thank you for this, Nick.

Regarding estimating separate eta for the two CL components I completely
agree with you. When I talked about a possible correlation component
between renal and non-renal CL that could not be attributed to size, my
intention was not to estimate separate random components for the two
processes. What would be possible, however, were to estimate a
(fixed-effect) interaction component between WT and CRCL (with the hope
of concluding it is not needed). This test can thus provide some further
support to that other important covariates have been integrated
correctly, or point to a potential problem.


-----Original Message-----
From: owner-nmusers
On Behalf Of Nick Holford
Sent: 13 January 2009 01:44
To: nmusers
Subject: Re: [NMusers] CrcL or Cr in pediatric model

Peter, Jakob, Leonid,

A practical example of how to deal with collinearity of age and weight
over a wide range (premature neonates to young adults) using GFR has
been recently reported (Rhodin et al 2008).

One way to overcome the somewhat imagined concern about using weight for

Clcr and weight for overall clearance is to predict Clcr for a standard
weight person and compute renal function relative to a normal standard
weight person. Then you can apply weight to clearance and not worry
about using weight 'twice' (Mould et al. 2002; Matthews et al. 2004).

Jakob's concern about using the same random effect for both portions of
clearance with and additive non-renal plus non-renal clearance model is
quite reasonable. However, I think it might be quite difficult to
estimate separate ETAs for each component of clearance unless one has
more than one estimate of total clearance with a different renal
function in order to estimate the individual components of clearance.

As I am sure you know I dont think it is a good idea to try to estimate
allometric exponents unless you have lots of subjects with a very wide
weight range AND you can be pretty confident (or dont care) that you
have accounted for all other factors affecting clearance that are
correlated with weight (see Anderson & Holford 2008 for an example of
how hard it is to get precise estimates).


Rhodin, M. M., B. J. Anderson, et al. (2008). "Human renal function
maturation: a quantitative description using weight and postmenstrual
age." Pediatr Nephrol. Epub
Mould, D. R., N. H. Holford, et al. (2002). "Population pharmacokinetic
and adverse event analysis of topotecan in patients with solid tumors."
Clinical Pharmacology & Therapeutics. 71(5): 334-48.
Matthews, I., C. Kirkpatrick, et al. (2004). "Quantitative justification

for target concentration intervention - Parameter variability and
predictive performance using population pharmacokinetic models for
aminoglycosides." British Journal of Clinical Pharmacology 58(1): 8-19.
Anderson, B. J. and N. H. Holford (2008). "Mechanism-based concepts of
size and maturity in pharmacokinetics." Annu Rev Pharmacol Toxicol 48:

Ribbing, Jakob wrote:
> Correction, I meant WT 50 and 75 in the example below:
> 75^0.75/(50^0.75)=1.36
> -----Original Message-----
> From: Ribbing, Jakob
> Sent: 13 January 2009 00:50
> To: nmusers
> Subject: RE: [NMusers] CrcL or Cr in pediatric model
> Leonid,
> I usually prefer multiplicative parameterisation as well, since it is
> easier to set boundaries (which is not necessary for power models, but
> for multiplicative-linear models). However, boundaries on the additive
> covariate models can still be set indirectly, using EXIT statements
> as neat as boundaries directly on the THETAS, I admit).
> In this case it may possibly be more mechanistic using the additive
> parameterisation: For example if the non-renal CL is mainly liver, the
> two blood flows run in parallel and the two elimination processes are
> independent (except there may be a correlation between liver function
> and renal function related to something other than size). A
> multiplicative parameterisation contains an assumed interaction which
> fixed and in this case may not be appropriate. If the drug is mainly
> eliminated via filtration, why would two persons, with WT 50 and 70 kg
> but otherwise identical (including CRCL and any other covariates,
> WT), be expected to differ by 36% in CL? This is what you get using a
> multiplicative parameterisation. The fixed interaction may also drive
> the selection of the functional form (e.g. a power model vs a linear
> model for CRCL on CL). I do not know anything about Peter's specific
> example so this is just theoretical.
> Regarding 3 below, is the suggestion to estimate independent
> models on CL for each level of renal function?
> Thanks
> Jakob
> -----Original Message-----
> From: owner-nmusers
> On Behalf Of Leonid Gibiansky
> Sent: 12 January 2009 23:30
> To: Bonate, Peter
> Cc: nmusers
> Subject: Re: [NMusers] CrcL or Cr in pediatric model
> Hi Peter,
> If allometric exponent is fixed, collinearity is not an issue from the

> mathematical point of view (convergence, CI on parameter estimates,
> etc.). However, in this case CRCL can end up being significant due to
> additional WT dependence (that could differ from allometric) rather
> due to renal function influence (that is not good if you need to
> interpret it as the renal impairment influence on PK).
> Few points to consider:
> 1. I usually normalize CRCL by WT^(3/4) or by (1.73 m^2 BSA) to get

> rid of WT - CRCL dependence. If you need to use it in pediatric
> population, normalization could be different but the idea to normalize

> CRCL by something that is "normal CRCL for a given WT" should be
> 2. In the pediatric population used for the analysis, are there any

> reasons to suspect that kids have impaired renal function ? If not, I
> would hesitate to use CRCL as a covariate.
> 3. Often, categorical description of renal impairment allows to
> decrease or remove the WT-CRCL correlation
> 4. Expressions to compute CRCL in pediatric population (note that
> most of those are normalized by BSA, as suggested in (1)) can be found
> here:
> 5. Couple of recent papers:
> Thanks
> Leonid
> P.S. I do not think that this is a good idea to use additive
> --------------------------------------
> Leonid Gibiansky, Ph.D.
> President, QuantPharm LLC
> web:
> e-mail: LGibiansky at
> tel: (301) 767 5566
> Bonate, Peter wrote:
>> I have an interesting question I'd like to get the group's collective

>> opinion on. I am fitting a pediatric and adult pk dataset. I have
>> fixed weight a priori to its allometric exponents in the model. When
> I
>> test serum creatinine and estimated creatinine clearance equation as
>> covariates in the model (power function), both are statistically
>> significant. CrCL appears to be a better predictor than serum Cr
> =
>> 22.7 vs 16.7). I have an issue with using CrCL as a predictor in the

>> model since it's estimate is based on weight and weight is already in

>> the model. Also, there might be collinearity issues with CrCL and
>> weight in the same model, even though they are both significant.
>> anyone have a good argument for using CrCL in the model instead of
> serum Cr?
>> Thanks
>> Pete bonate
>> Peter L. Bonate, PhD, FCP
>> Genzyme Corporation
>> Senior Director
>> Clinical Pharmacology and Pharmacokinetics
>> 4545 Horizon Hill Blvd
>> San Antonio, TX 78229 USA
>> _peter.bonate
>> phone: 210-949-8662
>> fax: 210-949-8219
>> crackberry: 210-315-2713
>> alea jacta est - The die is cast.
>> Julius Caesar

Nick Holford, Dept Pharmacology & Clinical Pharmacology
University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New
Received on Tue Jan 13 2009 - 02:31:50 EST

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