Evidence map›Paper›PMID 28118146›Full record

ArticleReviews on environmental health2017

An open-sourced statistical application for identifying complex toxicological interactions of environmental pollutants.

Jordan T Perkins, Michael C Petriello, Li Xu, Arnold Stromberg, Bernhard Hennig

Abstract read
In one paragraph

Article in Reviews on environmental health, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

5 authors.

Jordan T Perkins
Michael C Petriello
Li Xu
Arnold Stromberg
Bernhard Hennig

Funding

Vascular Mechanisms of PCB-Induced Brain MetastasesP42ES007380 · NIEHS · UNIVERSITY OF KENTUCKY · PI PENNELL, KELLY G · 1997 to 2024
$47.8M
2016 Central and Eastern European Conference on Health and the EnvironmentR13ES026036 · NIEHS · UNIVERSITY OF KENTUCKY · PI HENNIG, BERNHARD · 2016 to 2016
$40k
NIEHS NIH HHS P42 ES007380NIEHS NIH HHS R13 ES026036
6 · The paper itself

Abstract

The rising number of chemicals that humans are exposed to on a daily basis, as well as advances in biomonitoring and detection technologies have highlighted the diversity of individual exposure profiles (complex body burdens). To address this, the toxicological sciences have begun to shift away from examining toxic agents or stressors individually to focusing on more complex models with multiple agents or stressors present. Literature on interactions between chemicals is fairly limited in comparison with dose-response studies on individual toxicants, which is largely due to experimental and statistical challenges. Experimental designs capable of identifying these complex interactions are often avoided or not evaluated to their fullest potential because of the difficulty associated with appropriate analysis as well as logistical factors. To assist with statistical analysis of these types of experiments, an online, open-sourced statistical application was created for investigators to use to analyze and interpret potential toxicant interactions in laboratory experimental data using a full-factorial three-way analysis of variance (ANOVA). This model utilizes backward selection on interaction terms to model main effects and interactions.

Indexed as

Data Interpretation, StatisticalEnvironmental MonitoringEnvironmental PollutantsHazardous SubstancesHumansModels, TheoreticalEnvironmental PollutantsHazardous Substances

Identifiers

PMID28118146
PMCPMC5489228

What OpenQuestion holds

Textmetadata
LicenceTDM
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.