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

Our plain-English summary of Toxicology and epidemiology: improving the science with a framework for combining toxicological and epidemiological evidence to establish causal inference, by H.O. Adami, S.C. Berry, C.B. Breckenridge, et al (Toxicological Sciences, 2011).

The study

• Authors: H.O. Adami, S.C. Berry, C.B. Breckenridge, L.L. Smith, J.A. Swenberg, D. Trichopoulos, N.S. Weiss, T.P. Pastoor
• Journal: Toxicological Sciences
• Published: 2011;122(2):223-34
• Cited by: 77 articles, as counted by NIH iCite
• Read it: PubMed · Publisher · Free full text

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.

In plain English

This article is not a study of asbestos and reports no new data. It is a methods paper proposing a five-step 'Epid-Tox' framework for combining animal and laboratory (toxicological) evidence with human (epidemiological) evidence to judge whether an agent causes disease. The steps were: collect all relevant studies, grade their quality, weigh the evidence, score each kind of evidence from a neutral midpoint, and place the result on a grid labelled Likely, Uncertain, Uncertain but plausible, or Unlikely. Asbestos appeared twice. In the opening summary, the authors listed asbestos and mesothelioma among cases where agents suggested to cause human disease were tested in animals to firmly establish a causal link. Later they named asbestos as a cause of mesothelioma, alongside tobacco smoke and lung cancer, as an example of the Likely category. They did not review asbestos studies or name fiber types. Other examples included HIV and Kaposi's sarcoma, electromagnetic fields and brain cancer, melamine, and D-limonene. The authors concluded that the framework offers a trackable way to reach conclusions. They acknowledged that it will need modification and that quality grading is partly subjective.

We wrote this plain-English summary from the full article with the help of AI, and a second AI model checked each sentence against the article. It is not the authors' wording; the abstract and the article are their own account.

What the study did and found

• Design: Methods and commentary paper proposing a framework for causal inference; no new study was carried out and no data were analysed
• Exposure: No specific exposure was studied. The paper concerns environmental agents in general. Asbestos is mentioned only as an example, with no fiber type specified.
• Main results:
  • The proposed framework has five steps. The first is to collect all relevant toxicology and epidemiology studies. The others are quality grading, weighing the evidence, assigning a scalable conclusion, and placement on a causal relationship grid.
  • On the proposed grid, biological plausibility (toxicology) is scaled on one axis and the weight of epidemiological evidence on the other. Scoring starts from the center of each scale.
  • The authors designed the grid so that animal studies require more evidence than epidemiology before they move a conclusion away from 'insufficient information'.
  • In the opening summary, the authors cited asbestos and mesothelioma as a recent example of agents suggested to cause human disease being tested in animals to establish a causal link.
  • The authors gave asbestos as a cause of mesothelioma, together with tobacco smoke and lung cancer, as examples of the 'Likely' category. No asbestos studies were evaluated in this paper.
  • The authors illustrated the framework with non-asbestos examples: HIV and Kaposi's sarcoma, electromagnetic fields and brain cancer, melamine, and D-limonene.
• The authors' conclusion: The authors concluded that the framework provides a systematic way of working through all the evidence and reaching a conclusion that can be tracked, debated, and changed as more data arrive.
• Limitations the authors state:
  • The authors stated that the framework will need critique and modification.
  • The availability of evidence is a weakness, because unpublished and 'negative' studies are often missing.
  • There is no agreed method for grading the quality of studies that fall between poor and excellent.
  • Sorting studies into quality categories involves subjective judgment.
  • A more finely divided grid might lead to unproductive disputes over exactly where a point should sit.

Topics

Medical terms in this study, explained in our Lexicon: Epidemiology, Lung Cancer, Mesothelioma.

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