Re: 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).
Nick
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: 303-32.
Ribbing, Jakob wrote:
> Correction, I meant WT 50 and 75 in the example below:
> 75^0.75/(50^0.75)=1.36
>
Quoted reply history
> -----Original Message-----
>
> From: Ribbing, Jakob Sent: 13 January 2009 00:50
>
> To: [email protected]; 'Leonid Gibiansky'; Bonate, Peter
> 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 (not
> 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 is
> 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, except
> 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 allometric
> models on CL for each level of renal function?
>
> Thanks
>
> Jakob
>
> -----Original Message-----
> From: [email protected] [mailto:[email protected]]
> On Behalf Of Leonid Gibiansky
> Sent: 12 January 2009 23:30
> To: Bonate, Peter
> Cc: [email protected]
> 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 than
>
> 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 valid. 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:
> http://www.globalrph.com/specialpop.htm
> http://www.thedrugmonitor.com/clcreqs.html
> 5. Couple of recent papers:
> http://www.clinchem.org/cgi/content/full/49/6/1011
> http://www.ajhp.org/cgi/content/abstract/37/11/1514
>
> Thanks
> Leonid
>
> P.S. I do not think that this is a good idea to use additive dependence:
>
> TVCL=THETA(X)*(WT/70)**0.75+THETA(Y)*CRCL
> --------------------------------------
> Leonid Gibiansky, Ph.D.
> President, QuantPharm LLC
> web: www.quantpharm.com
> e-mail: LGibiansky at quantpharm.com
> 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 (LRT
>
> =
>
> > 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. Does
>
> > 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
> > [email protected]_ <mailto:[email protected]>
> > 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 Zealand
[email protected] tel:+64(9)923-6730 fax:+64(9)373-7090
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford