Evidence map›Paper›PMID 22439649›Full record

SynthesisClinical pharmacokinetics2012

The relationship between drug clearance and body size: systematic review and meta-analysis of the literature published from 2000 to 2007.

Sarah C McLeay, Glynn A Morrish, Carl M J Kirkpatrick, Bruce Green

Abstract readMeta-AnalysisSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Clinical pharmacokinetics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 83 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
83citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

83 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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23 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Sarah C McLeaySchool of Pharmacy, University of Queensland, Brisbane, QLD, Australia.
Glynn A Morrish
Carl M J Kirkpatrick
Bruce Green

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA 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.

aimThe 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.

methodsPopulation 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).

resultsA 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.

conclusionsTo 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.

Indexed as

Models, BiologicalPharmacokineticsBody Surface AreaBody WeightDose-Response Relationship, DrugHumansNonlinear DynamicsObesityPharmaceutical PreparationsPharmaceutical Preparations

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.