Evidence map›Paper›PMID 21561883›Full record

ArticleToxicological sciences : an official journal of the Society of Toxicology2011

Toxicology and epidemiology: improving the science with a framework for combining toxicological and epidemiological evidence to establish causal inference.

Hans-Olov Adami, Sir Colin L Berry, Charles B Breckenridge, Lewis L Smith, James A Swenberg, Dimitrios Trichopoulos, Noel S Weiss, Timothy P Pastoor

Open access · hybridAbstract read
In one paragraph

Article in Toxicological sciences : an official journal of the Society of Toxicology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 5 pooled it
8.6field-weighted citation impact, top 2% 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

31 citing papers in PubMed, 5 syntheses or guidelines pooled it, 111 citations in OpenAlex.

  1. Cancer and occupational exposure to pesticides: an umbrella review.International archives of occupational and environmental health · 2021
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  18. Mitochondrial Toxicity.Toxicological sciences : an official journal of the Society of Toxicology · 2018
    Review
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  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 6 institutions in 4 countries.

Hans-Olov AdamiDepartment of Epidemiology, Harvard School of Public Health, Boston, Massachusetts 02215, USA.
Sir Colin L Berry
Charles B Breckenridge
Lewis L Smith
James A Swenberg
Dimitrios Trichopoulos
Noel S Weiss
Timothy P Pastoor
Harvard University · USSyngenta (United States) · USQueen Mary University of London · GBUniversity of Leicester · GBUniversity of North Carolina at Chapel Hill · USUniversity of Washington · US

Funding

STOCHASTIC ANALYSIS OF FLOW AND TRANSPORT PHENOMENAP42ES005948 · NIEHS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI FRY, REBECCA · 1992 to 2017
$45.4M
UNC-CH CENTER FOR ENVIRONMENTAL HEALTH &SUSCEPTIBILITYP30ES010126 · NIEHS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Melissa A. Troester · 2001 to 2026
$36.3M
NIEHS NIH HHS P30 ES010126NIEHS NIH HHS P42 ES005948
6 · The paper itself

Abstract

Historically, toxicology has played a significant role in verifying conclusions drawn on the basis of epidemiological findings. Agents that were suggested to have a role in human diseases have been tested in animals to firmly establish a causative link. Bacterial pathogens are perhaps the oldest examples, and tobacco smoke and lung cancer and asbestos and mesothelioma provide two more recent examples. With the advent of toxicity testing guidelines and protocols, toxicology took on a role that was intended to anticipate or predict potential adverse effects in humans, and epidemiology, in many cases, served a role in verifying or negating these toxicological predictions. The coupled role of epidemiology and toxicology in discerning human health effects by environmental agents is obvious, but there is currently no systematic and transparent way to bring the data and analysis of the two disciplines together in a way that provides a unified view on an adverse causal relationship between an agent and a disease. In working to advance the interaction between the fields of toxicology and epidemiology, we propose here a five-step "Epid-Tox" process that would focus on: (1) collection of all relevant studies, (2) assessment of their quality, (3) evaluation of the weight of evidence, (4) assignment of a scalable conclusion, and (5) placement on a causal relationship grid. The causal relationship grid provides a clear view of how epidemiological and toxicological data intersect, permits straightforward conclusions with regard to a causal relationship between agent and effect, and can show how additional data can influence conclusions of causality.

Indexed as

CausalityEpidemiologyToxicologyAnimalsGuidelines as TopicHumansToxicity Tests

Identifiers

PMID21561883
PMCPMC3155086
OpenAlexW2140018398

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.