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
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