Evidence map›Paper›PMID 29704107›Full record

ArticleClinical pharmacokinetics2019

Choosing the Allometric Exponent in Covariate Model Building.

Jaydeep Sinha, Hesham S Al-Sallami, Stephen B Duffull

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Article in Clinical pharmacokinetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–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

18 citing papers in PubMed.

  1. Trial
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  4. Observational
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  6. Review
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  18. Population Pharmacokinetics of Doxycycline in Children.Antimicrobial agents and chemotherapy · 2019
    Article
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

3 authors.

Jaydeep SinhaSchool of Pharmacy, University of Otago, PO Box 56, Dunedin, 9054, New Zealand. jaydeep.sinha@postgrad.otago.ac.nz.ORCID 0000-0002-2110-3370
Hesham S Al-SallamiSchool of Pharmacy, University of Otago, PO Box 56, Dunedin, 9054, New Zealand.
Stephen B DuffullSchool of Pharmacy, University of Otago, PO Box 56, Dunedin, 9054, New Zealand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAllometric 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.

objectivesThe 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.

methodsThe 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.

resultsFor 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.

conclusionThose 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.

Indexed as

Models, BiologicalAdultBiological Variation, IndividualBody WeightHumansMetabolic Clearance RateResearch Design

Identifiers

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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.