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Clinical Pharmacokinetics

, Volume 58, Issue 1, pp 89–100 | Cite as

Choosing the Allometric Exponent in Covariate Model Building

  • Jaydeep SinhaEmail author
  • Hesham S. Al-Sallami
  • Stephen B. Duffull
Original Research Article
  • 184 Downloads

Abstract

Background

Allometric scaling is often used to describe the covariate model linking total body weight (WT) to clearance (CL); however, there is no consensus on how to select its value.

Objectives

The aims of this study were to assess the influence of between-subject variability (BSV) and study design on (1) the power to correctly select the exponent from a priori choices, and (2) the power to obtain unbiased exponent estimates.

Methods

The influence of WT distribution range (randomly sampled from the Third National Health and Nutrition Examination Survey, 1988–1994 [NHANES III] database), sample size (N = 10, 20, 50, 100, 200, 500, 1000 subjects), and BSV on CL (low 20%, normal 40%, high 60%) were assessed using stochastic simulation estimation. A priori exponent values used for the simulations were 0.67, 0.75, and 1, respectively.

Results

For normal to high BSV drugs, it is almost impossible to correctly select the exponent from an a priori set of exponents, i.e. 1 vs. 0.75, 1 vs. 0.67, or 0.75 vs. 0.67 in regular studies involving < 200 adult participants. On the other hand, such regular study designs are sufficient to appropriately estimate the exponent. However, regular studies with < 100 patients risk potential bias in estimating the exponent.

Conclusion

Those study designs with limited sample size and narrow range of WT (e.g. < 100 adult participants) potentially risk either selection of a false value or yielding a biased estimate of the allometric exponent; however, such bias is only relevant in cases of extrapolating the value of CL outside the studied population, e.g. analysis of a study of adults that is used to extrapolate to children.

Notes

Compliance with Ethical Standards

Conflict of interest

Jaydeep Sinha, Hesham S. Al-Sallami and Stephen B. Duffull declare no conflicts of interest.

Ethics approval

No ethical approval was required for this simulation-based work.

Funding

This work received no specific funding. Jaydeep Sinha received a doctoral scholarship from the School of Pharmacy, University of Otago, New Zealand, during the course of this work.

Supplementary material

40262_2018_667_MOESM1_ESM.docx (34 kb)
Supplementary material 1 (DOCX 33 kb)
40262_2018_667_MOESM2_ESM.pdf (67 kb)
Supplementary material 2 (PDF 67 kb)
40262_2018_667_MOESM3_ESM.pdf (67 kb)
Supplementary material 3 (PDF 67 kb)
40262_2018_667_MOESM4_ESM.pdf (201 kb)
Supplementary material 4 (PDF 201 kb)

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of PharmacyUniversity of OtagoDunedinNew Zealand

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