Re: Sparse (pediatric) and rich (adult) data
Leonid and Steve,
Thanks for your comments. While optimal design with/without combining with adults can help learn more about children in both cases it comes with assumptions. One of the assumptions is adults are big children.
Exactly how to implement that assumption is controversial but it will determine what is learned eg. should we assume allometric theory with fixed coefficients of 3/4 for clearance and 1 for volume? Or should we use up 2 degrees of freedom and estimate the coefficents? Depending on whether or not you use 2 parameters to describe how big adults are will influence the conclusions about other covariate relationships which may not be so well understood.
Nick
Leonid Gibiansky wrote:
> Steve,
>
> I hope that you do not dispute that in this particular case you need to use adult data (50 full profiles) rather than discard them and use only kids data (3 sample per subject, 20 subjects)? While optimal design can be used to extract more information from the same number of samples, it is not a substitute for the real data. Even with optimal design of the pediatric study (with the same 20 subjects, 3 optimal sample points) I bet you would gain by using adult data as well.
>
> Leonid
>
> --------------------------------------
> Leonid Gibiansky, Ph.D.
> President, QuantPharm LLC
> web: www.quantpharm.com
> e-mail: LGibiansky at quantpharm.com
> tel: (301) 767 5566
>
> Stephen Duffull wrote:
>
> > Chandra, Nick et al
> >
> > It is worth noting that while three samples won't support a 4 parameter
> > model if all patients contribute these samples at exactly the same time
> >
> > (i.e. the patients are exchangeable from a design perspective) this is not
> >
> > necessarily the case if the design is optimized to learn about the PK.
> >
> > We have designed and conducted a number of studies where the number of
> > samples is less than the number of parameters and achieved good results.
> >
> > Some of the issues that you need to consider are:
> >
> > 1) Your design will probably lead to some shrinkage in the empirical Bayes
> >
> > estimates which may be problematic if you intend to use the EBEs for
> >
> > inferential purposes. However if you're after the population estimates only
> >
> > (which is often the case) then this is not an issue.
> > 2) Your design is unbalanced with respect to covariates. Adults are
> >
> > providing much more information about the model and parameter values than
> >
> > the children (even if the design in children was optimized) - which will
> >
> > affect your ability to identify some covariate relationships with accuracy.
> >
> > This can be assessed relatively easily using both optimal design and
> > simulation based investigations.
> >
> > Regards
> >
> > 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
> >
> > > -----Original Message-----
> > >
Quoted reply history
> > > From: [EMAIL PROTECTED] [ mailto:[EMAIL PROTECTED] On Behalf Of Chandrasekhar Udata
> > >
> > > Sent: Thursday, 29 May 2008 9:16 a.m.
> > > To: [email protected]
> > > Subject: Re: [NMusers] Sparse (pediatric) and rich (adult) data
> > >
> > > Thank you Nick and Leonid for your comments. Follow-up question: I do understand that 3 samples per subject may not support 4 parameters model. However, historically, the compound showed bi-phasic characteristics (in adults) and I do like to use the same model in pediatrics. Also, the model (ADVAN3, TRANS4) did converge with no issues/errors (with pediatric data alone). Is there something I am missing? or is TRANS5 (AOB, ALPHA, BETA) an alternative for such limited data? Regards,
> > >
> > > - Chandra
> > >
> > > > > > Nick Holford <[EMAIL PROTECTED]> 5/28/2008 1:38:07 PM >>>
> > >
> > > Chandra,
> > >
> > > With such a small sample its hard to learn much about differences between adults and children. Your principled approach using allometric scaling is a reasonable way to bridge the gap in recognizing that adults and children are all the same species (see reference below).
> > >
> > > "Children are just small adults"
> > >
> > > I would not be too worried about individual parameter estimate in children being different. With only 3 samples per child and a 2 cmt model requiring at least 4 parameters you will always get different results if you use different assumptions.
> > >
> > > Nick
> > >
> > > Anderson BJ, Holford NH. Mechanism-Based Concepts of Size and Maturity in Pharmacokinetics. Annu Rev Pharmacol Toxicol. 2008;48:303-32.
> > >
> > > Chandrasekhar Udata wrote:
> > >
> > > > Hi,
> > > >
> > > > I am working on a pop PK model to estimate PK parameters in
> > >
> > > pediatric
> > >
> > > > and adult patients. Pediatric study (n=20, age <6 yrs) has fewer samples (3) per subject whereas the adult study (n=50,
> > >
> > > median age 20
> > >
> > > > yrs) has 12 samples per subject. A two-compartment model best describes the data for each data set. Although a
> > >
> > > two-compartment model
> > >
> > > > best describes the combined data, the individual parameter
> > >
> > > estimates
> > >
> > > > in pediatric population are different compared to those obtained using with pediatric data alone. Note that the parameter
> > >
> > > estimates in
> > >
> > > > adults were not significantly altered with either combined or adult data alone. Body weight is the only covariate included in the model with allometric exponents fixed to 0.75 on CL and 1 on V1. I would like to hear your thoughts on this and any
> > >
> > > suggestions on how
> > >
> > > > to proceed with modeling combined data from pediatric and
> > >
> > > adult studies.
> > >
> > > > Regards,
> > > >
> > > > - Chandra
> > >
> > > --
> > > 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
> > > www.health.auckland.ac.nz/pharmacology/staff/nholford
--
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
www.health.auckland.ac.nz/pharmacology/staff/nholford