Background: A variety of body size covariates have been used in population pharmacokinetic analyses to describe variability in drug clearance (CL), such as total body weight (TBW), body surface area (BSA), lean body weight (LBW) and allometric TBW. There is controversy, however, as to which body size covariate is most suitable for describing CL across the whole population. Given the increasing worldwide prevalence of obesity, it is essential to identify the best size descriptor so that dosing regimens can be developed that are suitable for patients of any size.
Aim: The aim of this study was to explore the use of body size covariates in population pharmacokinetic analyses for describing CL. In particular, we sought to determine if any body size covariate was preferential to describe CL and quantify its relationship with CL, and also identify study design features that result in the identification of a nonlinear relationship between TBW and CL.
Methods: Population pharmacokinetic articles were identified from MEDLINE using defined keywords. A database was developed to collect information about study designs, model building and covariate analysis strategies, and final reported models for CL. The success of inclusion for a variety of covariates was determined. A meta-analysis of studies was then performed to determine the average relationship reported between CL and TBW. For each study, CL was calculated across the range of TBW for the study population and normalized to allow comparison between studies. BSA, LBW, and allometric TBW and LBW relationships with exponents of 3/4, 2/3, and estimated values were evaluated to determine the relationship that best described the data overall. Additionally, joint distributions of TBW were compared between studies reporting a ‘nonlinear’ relationship between CL and TBW (i.e. LBW, BSA and allometric TBW-shaped relationships) and those reporting ‘other’ relationships (e.g. linear increase in CL with TBW, ideal body weight or height).
Results: A total of 458 out of 2384 articles were included in the analysis, from which 484 pharmacokinetic studies were reviewed. Fifty-six percent of all models for CL included body size as a covariate, with 52% of models including a nonlinear relationship between CL and TBW. No single size descriptor was more successful than others for describing CL. LBW with a fixed exponent of 2/3, i.e. (LBW/50.45)2/3, or estimated exponent of 0.646, i.e. ∼2/3, was found to best describe the average reported relationship between CL and TBW. The success of identifying a nonlinear increase in CL with TBW was found to be higher for those studies that included a wider range of subject TBW.
Conclusions: To the best of our knowledge, this is the first study to have performed a meta-analysis of covariate relationships between CL and body size. Although many studies reported a linear relationship between CL and TBW, the average relationship was found to be nonlinear. LBW with an allometric exponent of ∼2/3 may be most suitable for describing an increase in CL with body size as it accounts for both body composition and allometric scaling principles concerning differences in metabolic rates across size.
Body Size Body Surface Area Nonlinear Relationship Basal Metabolic Rate Total Body Weight
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Sarah C. McLeay was supported by a grant from Pfizer Global R&D. All authors declare no conflicts of interest. The authors wish to thank Karl Brendel, France Mentré and other contributing authors to Brendel et al. and Dartois et al. for kindly sharing their references, which were used to define and test the Boolean search used for this review.
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