Evidence map›Paper›PMID 29470495›Full record

ArticlePLoS biology2018

Reproducibility of preclinical animal research improves with heterogeneity of study samples.

Bernhard Voelkl, Lucile Vogt, Emily S Sena, Hanno Würbel

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PLoS biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 132 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
132citing papers in PubMed, 7 pooled it
38.2field-weighted citation impact, top 1% 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

132 citing papers in PubMed, 7 syntheses or guidelines pooled it, 260 citations in OpenAlex.

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72 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 at 2 institutions in 2 countries.

Bernhard VoelklDivision of Animal Welfare, VPH Institute, Vetsuisse Faculty, University of Bern, Bern, Switzerland.ORCID 0000-0001-5454-2508
Lucile VogtDivision of Animal Welfare, VPH Institute, Vetsuisse Faculty, University of Bern, Bern, Switzerland.
Emily S SenaCentre for Clinical Brain Sciences, Chancellors Building, University of Edinburgh, Edinburgh, United Kingdom.
Hanno WürbelDivision of Animal Welfare, VPH Institute, Vetsuisse Faculty, University of Bern, Bern, Switzerland.
University of Bern · CHUniversity of Edinburgh · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single-laboratory studies conducted under highly standardized conditions are the gold standard in preclinical animal research. Using simulations based on 440 preclinical studies across 13 different interventions in animal models of stroke, myocardial infarction, and breast cancer, we compared the accuracy of effect size estimates between single-laboratory and multi-laboratory study designs. Single-laboratory studies generally failed to predict effect size accurately, and larger sample sizes rendered effect size estimates even less accurate. By contrast, multi-laboratory designs including as few as 2 to 4 laboratories increased coverage probability by up to 42 percentage points without a need for larger sample sizes. These findings demonstrate that within-study standardization is a major cause of poor reproducibility. More representative study samples are required to improve the external validity and reproducibility of preclinical animal research and to prevent wasting animals and resources for inconclusive research.

Indexed as

Animal ExperimentationAnimalsDisease Models, AnimalLaboratoriesProbabilityReproducibility of ResultsResearch DesignSample Size

Identifiers

PMID29470495
PMCPMC5823461
OpenAlexW2787981664

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.