Evidence map›Paper›PMID 29750840›Full record

ArticleRisk analysis : an official publication of the Society for Risk Analysis2020

Advances on a Decision Analytic Approach to Exposure-Based Chemical Prioritization.

Matthew D Wood, Kenton Plourde, Sabrina Larkin, Peter P Egeghy, Antony J Williams, Valerie Zemba, Igor Linkov, Daniel A Vallero

Open access · greenAbstract read
In one paragraph

Article in Risk analysis : an official publication of the Society for Risk Analysis, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.5field-weighted citation impact, top 13% 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

3 citing papers in PubMed, 35 citations in OpenAlex.

  1. Article
  2. Review
  3. 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

8 authors at 3 institutions in 3 countries.

Matthew D WoodU.S. Army Engineer Research and Development Center, Environmental Laboratory, Concord, MA, USA.ORCID 0000-0002-1140-1526
Kenton PlourdeBrigham and Women's Hospital, Boston, MA, USA.
Sabrina LarkinContractor to U.S. Army Engineer Research and Development Center, Environmental Laboratory, Concord, MA, USA.
Peter P EgeghyU.S. Environmental Protection Agency, National Exposure Research Laboratory, RTP, NC, USA.
Antony J WilliamsU.S. Environmental Protection Agency, National Computational Toxicology Center, RTP, NC, USA.
Valerie ZembaContractor to U.S. Army Engineer Research and Development Center, Environmental Laboratory, Concord, MA, USA.
Igor LinkovU.S. Army Engineer Research and Development Center, Environmental Laboratory, Concord, MA, USA.
Daniel A ValleroU.S. Environmental Protection Agency, National Exposure Research Laboratory, RTP, NC, USA.
United States Army · USEnvironmental Protection Agency · USBrigham and Women's Hospital · US

Funding

Intramural EPA EPA999999
6 · The paper itself

Abstract

The volume and variety of manufactured chemicals is increasing, although little is known about the risks associated with the frequency and extent of human exposure to most chemicals. The EPA and the recent signing of the Lautenberg Act have both signaled the need for high-throughput methods to characterize and screen chemicals based on exposure potential, such that more comprehensive toxicity research can be informed. Prior work of Mitchell et al. using multicriteria decision analysis tools to prioritize chemicals for further research is enhanced here, resulting in a high-level chemical prioritization tool for risk-based screening. Reliable exposure information is a key gap in currently available engineering analytics to support predictive environmental and health risk assessments. An elicitation with 32 experts informed relative prioritization of risks from chemical properties and human use factors, and the values for each chemical associated with each metric were approximated with data from EPA's CP_CAT database. Three different versions of the model were evaluated using distinct weight profiles, resulting in three different ranked chemical prioritizations with only a small degree of variation across weight profiles. Future work will aim to include greater input from human factors experts and better define qualitative metrics.

Indexed as

Engineering risk analyticsexpert elicitationexposure sciencemulticriteria decision analysisscreening prioritization

Identifiers

PMID29750840
PMCPMC7076565
OpenAlexW2803076701

What OpenQuestion holds

Textmetadata
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.