Re: RE: Weight based dosing
Abdullah,
I agree with Stefanie's advice.
Here are some references for you to read to help you understand about using biology not statistics for weight based dosing.
The use of a standard (70 kg) and theory based allometry (exponent 3/4 for clearance and 1 for volume) is important to allow comparison of different studies and for integration of pharmacokinetic knowledge (Holford, Heo & Anderson 2013).
It is difficult to obtain reliable estimates of allometric exponents using empirical estimation (Anderson & Holford 2008) because you need a broad size distribution and also to account for all other factors correlated with weight (e.g. age) in order to obtain true allometric exponents. The theory of allometry is well explained by West & Brown (2005).
Best wishes,
Nick
Holford N, Heo YA, Anderson B. A pharmacokinetic standard for babies and adults. J Pharm Sci. 2013;102(9):2941-52. Anderson BJ, Holford NH. Mechanism-based concepts of size and maturity in pharmacokinetics. Annu Rev Pharmacol Toxicol. 2008;48:303-32. West GB, Brown JH. The origin of allometric scaling laws in biology from genomes to ecosystems: towards a quantitative unifying theory of biological structure and organization. J Exp Biol. 2005;208(9):1575-92.
Quoted reply history
On 09-Dec-15 14:59, Stefanie Hennig wrote:
> Dear Abdullah,
>
> I assume that you have only looked at the decrease in the variance around CL comparing the base model and the covariate model, when you state :“only explained 9% of the variability”.
>
> We have shown that total parameter variability is changing throughout model building and a decrease in unexplained parameter variability is not equal to an increase in explained parameter variability when adding covariates in your model. So the explained parameter variability might have increased by more than 9%.
>
> Please see the reference below. This methodology is now also implemented in PsN and you can perform it alongside your covariate model building. You might want to try this. The manuscript below also discusses the difference between improved model fit and clinical significance of a covariate.
>
> (Hennig S, Karlsson MO. Concordance between criteria for covariate model building. J. Pharmacokinet. Pharmacodyn. 2014;41:109-125.)
>
> Further, I would like to highlight to you that others have previously discussed on NMusers and in the literature that for an easier comparison of study results it is preferred to use a standard weight of 70kg.
>
> Also, if you did use an allometric scaling model on CL/F, you would have used an power exponent of ¾ or estimated this exponent, but not a slope. So I am unsure about the slope effect that you are talking about and cannot comment further on this.
>
> Best wishes and a Happy holiday season
>
> Stefanie
>
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> *From:* [email protected] [ mailto: [email protected] ] *On Behalf Of *Sultan,Abdullah S
>
> *Sent:* Wednesday, 9 December 2015 10:40 AM
> *To:* [email protected]
> *Subject:* [NMusers] Weight based dosing
>
> Hi everyone,
>
> I am developing a POP PK model for an anti-infective drug, I am trying to determine if dosing should be weight based or not. The range of weight in the study was 40-100 kg.
>
> Weight was statistically significant for Cl/F but only explained 9% of the variability observed for Cl.
>
> I used allometric scaling to describe weights effect on Cl/F and slope effect of weight was 0.58, and scaled to 60 kg (the median).
>
> Based on the slope effect estimated, AUC is predicted to decrease by 15% for an 80 kg individual, and increase by 25% for an individual that weights 40 kg compared to a 60 kg individual.
>
> How much should I trust the slope effect determined by my study? and should I rely on it to develop the dosing regimen?
>
> if weight only explained 9% of variability observed with Cl/F, could that indicate that it is not clinically significant and weight based dosing is not required?
>
> Thanks,
>
> Abdullah Sultan, PhD candidate
>
> University of Florida
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Holford SD, Allegaert K, Anderson BJ, Kukanich B, Sousa AB, Steinman A, Pypendop,
B., Mehvar, R., Giorgi, M., Holford,N.H.G. Parent-metabolite pharmacokinetic models
- tests of assumptions and predictions. Journal of Pharmacology & Clinical
Toxicology. 2014;2(2):1023-34.
Holford N. Clinical pharmacology = disease progression + drug action. Br J Clin
Pharmacol. 2015;79(1):18-27.