Re: [NMusers] Sparse (pediatric) and rich (adult) data

Steve,
The original question was whether it is beneficial to add adult data to
the pediatric (in the specific case under study). Your previous e-mail
could be interpreted as the suggestion that one can estimate model
parameters with the pediatric data alone if the pediatric study design
is optimal. I think one should use both datasets together (in the
specific case that was described) and it looks like we are in agreement
on this point.
Regards,
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:
> Leonid
>
>> 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)?
>
> I definitely do not dispute the need to have both adult and paediatric data
> in the analysis (so I agree :-) ). I see two reasons for this (perhaps more
> if I took more time). The first and most important reason is combining
> adult and paediatric data together is a great (only) way to learn how
> children differ pharmacokinetically from adults and how doses can be scaled
> to achieve equivalent exposures. Secondly, especially in this case, it is
> often helpful to combine data sets together to improve the informativeness
> of the overall design. This latter point, however was the point of my
> previous email. Some care must be taken to assess the accuracy of covariate
> effects given the unbalanced nature of the design.
>
>> 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.
>
> You always gain by summing over data (unless the new data is negatively
> informative which is unlikely in any PK situation). So I don't exactly
> follow your point. The question to me is simply, what chance do I have of
> identifying a model that allows me to draw appropriately accurate
> conclusions. Optimal design is a way that allows investigators to improve
> the informativeness of data. Obviously, no data = no information.
>
> Steve
> --
> Professor Stephen Duffull
> Chair of Clinical Pharmacy
> School of Pharmacy
> University of Otago
> PO Box 913 Dunedin
> New Zealand
> E: stephen.duffull_at_otago.ac.nz
> P: +64 3 479 5044
> F: +64 3 479 7034
>
> Design software: www.winpopt.com
>
>
>
Received on Wed May 28 2008 - 22:46:42 EDT