Evidence map›Paper›PMID 30968312›Full record

ArticleJournal of pharmacokinetics and pharmacodynamics2019

Development of visual predictive checks accounting for multimodal parameter distributions in mixture models.

Usman Arshad, Estelle Chasseloup, Rikard Nordgren, Mats O Karlsson

Open access · hybridAbstract read
In one paragraph

Article in Journal of pharmacokinetics and pharmacodynamics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.5field-weighted citation impact, top 36% of its field
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

7 citing papers in PubMed, 11 citations in OpenAlex.

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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 at 1 institution in 2 countries.

Usman ArshadDepartment of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden. usman.arshad@uk-koeln.de.ORCID 0000-0002-7003-5300
Estelle ChasseloupDepartment of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden.
Rikard NordgrenDepartment of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden.
Mats O KarlssonDepartment of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden.
Uppsala University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The assumption of interindividual variability being unimodally distributed in nonlinear mixed effects models does not hold when the population under study displays multimodal parameter distributions. Mixture models allow the identification of parameters characteristic to a subpopulation by describing these multimodalities. Visual predictive check (VPC) is a standard simulation based diagnostic tool, but not yet adapted to account for multimodal parameter distributions. Mixture model analysis provides the probability for an individual to belong to a subpopulation (IP

Indexed as

Models, BiologicalComputer SimulationGlucuronosyltransferaseHumansIrinotecanNonlinear DynamicsProbabilityUGT1A1 EnzymeGlucuronosyltransferaseIrinotecanUGT1A1 EnzymeMixture modelsMultimodal parameter distributionsPharmacodynamicsPharmacokineticsVisual predictive checks

Identifiers

PMID30968312
PMCPMC6560505
OpenAlexW2937483084

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.