Re: weight as a covariate in kids

From:Edmund Capparelli Subject:Re: [NMusers] weight as a covariate in kids Date:Wed, 30 Oct 2002 13:18:02 -0800 After being involved primarily in pediatric population pharmacokinetic analyses over the past 12 plus years, I feel very strongly that accounting for size upfront is critical to modeling pediatric pharmacokinetic data. It is my underlying assumption that "the truth" is that pharmacokinetic parameters scale with subject size. Since size is highly correlated with many other covariates (age, creatinine clearance etc.) and is an extremely powerful covariate, any evaluation of other covariates in a structural model without size will have little resemblance to their impact in a multivariate analysis with size and thus provide limited insight. In general pediatric pharmacokinetic studies minimize the data collected and are not designed to robustly answer the size question in regards to all pharmacokinetic parameters. However in these situations, if one does not include size in PK parameters because it does improve the fit by some statistical criteria, there needs to be recognition that an assumption has been made, that the study design was powerful enough to determine the impact of size on all pharmacokinetic parameters. In this setting ignoring size make fit the data as just as well, but it leads to bizarre unrealistic extrapolations just outside age, covariate, dose-sampling domain that generated the data. And even if we cautions against extrapolation in these settings, we modelers need to recognize that the general lack and fragmentation of pediatric pharmacokinetic information make extrapolation of pediatric PK data a common practice. Not including size also ignores a large knowledge of pharmacokinetics in children were we have good pharmacokinetic information from toddler to adults and size has born out to be a significant covariate on Vd and Cl (without exception to my knowledge). I include size on all of my size dependant parameters which may include absorption. if zero order. In the modeling process it is also important to recognize that size affects multiple pharmacokinetic parameters and there are interactions in these influences, so the standard forward covariate selection approach can grossly underestimate the impact of size on individual parameters or miss a size covariate entirely. Use of a backwards elimination approach prevents missing these complex interactions but rarely are there sufficient data in pediatric pharmacokinetic studies to support this approach for all covariates. Lastly getting to how specifics of how to incorporate size into the model really depends on what questions one is asking. As a starting point I agree with Nick Holford's approach to used standardized allometric scaling. It promotes comparability of data, has a sound scientific theoretic basis, is frequently very close to fitted exponents and in most situations superior to a linear weight function. However, I would caution that it does not account for the ontogeny of clearance processes and other potential age related pharmacokinetic differences. I also keep in the forefront of mind the quote by Box that "all models are wrong but some are useful" and do not believe in an ultimate "final" correct model. There are "final" models given any specific approach (and underlying assumptions) and there may be usefulness in developing various "final" models with different sizing approaches to develop and justify pediatric dosing paradigms. Best Regards, Edmund ___________________________________