Evidence map›Paper›PMID 34490933›Full record

ArticleRisk analysis : an official publication of the Society for Risk Analysis2022

A Framework that Considers the Impacts of Time, Cost, and Uncertainty in the Determination of the Cost Effectiveness of Toxicity-Testing Methodologies.

Paul S Price, Bryan J Hubbell, Shintaro Hagiwara, Greg M Paoli, Daniel Krewski, Annette Guiseppi-Elie, Maureen R Gwinn, Norman L Adkins, Russell S Thomas

Open access · hybridAbstract read
In one paragraph

Article in Risk analysis : an official publication of the Society for Risk Analysis, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.1field-weighted citation impact, top 9% 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

6 citing papers in PubMed, 14 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Bioactive limonoids fromCurrent research in toxicology · 2023
    Article
  6. 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

9 authors at 3 institutions in 3 countries.

Paul S PriceCenter for Computational Toxicology and Exposure, US Environmental Protection Agency, Research Triangle Park, Durham, NC, USA.ORCID 0000-0003-2098-8274
Bryan J HubbellAir, Climate, and Energy Research Program, US Environmental Protection Agency, Research Triangle Park, Durham, NC, USA.
Shintaro HagiwaraSchool of Mathematics and Statistics, Carleton University, Ottawa, Canada.
Greg M PaoliRisk Sciences International, Ottawa, Canada.
Daniel KrewskiMcLaughlin Centre for Population Health Risk Assessment, University of Ottawa, Ottawa, Canada.
Annette Guiseppi-ElieCenter for Computational Toxicology and Exposure, US Environmental Protection Agency, Research Triangle Park, Durham, NC, USA.
Maureen R GwinnSustainable and Healthy Communities Research Program, US Environmental Protection Agency, Research Triangle Park, NC, USA.
Norman L AdkinsCenter for Computational Toxicology and Exposure, US Environmental Protection Agency, Research Triangle Park, Durham, NC, USA.
Russell S ThomasCenter for Computational Toxicology and Exposure, US Environmental Protection Agency, Research Triangle Park, Durham, NC, USA.
Environmental Protection Agency · USRisk Engineering (Bulgaria) · BGUniversity of Ottawa · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Regulatory agencies are required to evaluate the impacts of thousands of chemicals. Toxicological tests currently used in such evaluations are time-consuming and resource intensive; however, advances in toxicology and related fields are providing new testing methodologies that reduce the cost and time required for testing. The selection of a preferred methodology is challenging because the new methodologies vary in duration and cost, and the data they generate vary in the level of uncertainty. This article presents a framework for performing cost-effectiveness analyses (CEAs) of toxicity tests that account for cost, duration, and uncertainty. This is achieved by using an output metric-the cost per correct regulatory decision-that reflects the three elements. The framework is demonstrated in two example CEAs, one for a simple decision of risk acceptability and a second, more complex decision, involving the selection of regulatory actions. Each example CEA evaluates five hypothetical toxicity-testing methodologies which differ with respect to cost, time, and uncertainty. The results of the examples indicate that either a fivefold reduction in cost or duration can be a larger driver of the selection of an optimal toxicity-testing methodology than a fivefold reduction in uncertainty. Uncertainty becomes of similar importance to cost and duration when decisionmakers are required to make more complex decisions that require the determination of small differences in risk predictions. The framework presented in this article may provide a useful basis for the identification of cost-effective methods for toxicity testing of large numbers of chemicals.

Indexed as

Toxicity TestsCost-Benefit AnalysisUncertaintyCost effectiveness analysisdecision makingtoxicity testing

Identifiers

PMID34490933
PMCPMC9290960
OpenAlexW3197281762

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.