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Causal Inference Analysis for Poorly Soluble Low Toxicity Particles, Lung Function, and Malignancy

Poorly soluble low toxicity particles such as carbon black and titanium dioxide have raised concern about possible nonmalignant and malignant pulmonary effects. This paper illustrates application of causal inference analysis to assessing these effects. A framework for analysis is created using direc...

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Detalles Bibliográficos
Autor principal: Harber, Philip
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9294315/
https://www.ncbi.nlm.nih.gov/pubmed/35865253
http://dx.doi.org/10.3389/fpubh.2022.863402
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author Harber, Philip
author_facet Harber, Philip
author_sort Harber, Philip
collection PubMed
description Poorly soluble low toxicity particles such as carbon black and titanium dioxide have raised concern about possible nonmalignant and malignant pulmonary effects. This paper illustrates application of causal inference analysis to assessing these effects. A framework for analysis is created using directed acyclic graphs to define pathways from exposure to potential lung cancer or chronic airflow obstruction outcomes. Directed acyclic graphs define influences of confounders, backdoor pathways, and analytic models. Potential mechanistic pathways such as intermediate pulmonary inflammation are illustrated. An overview of available data for each of the inter-node links is presented. Individual empirical epidemiologic studies have limited ability to confirm mechanisms of potential causal relationships due to the complexity of causal pathways and the extended time course over which disease may develop. Therefore, an explicit conceptual and graphical framework to facilitate synthesizing data from several studies to consider pulmonary inflammation as a common pathway for both chronic airflow obstruction and lung cancer is suggested. These methods are useful to clarify potential bona fide and artifactual observed relationships. They also delineate variables which should be included in analytic models for single study data and biologically relevant variables unlikely to be available from a single study.
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spelling pubmed-92943152022-07-20 Causal Inference Analysis for Poorly Soluble Low Toxicity Particles, Lung Function, and Malignancy Harber, Philip Front Public Health Public Health Poorly soluble low toxicity particles such as carbon black and titanium dioxide have raised concern about possible nonmalignant and malignant pulmonary effects. This paper illustrates application of causal inference analysis to assessing these effects. A framework for analysis is created using directed acyclic graphs to define pathways from exposure to potential lung cancer or chronic airflow obstruction outcomes. Directed acyclic graphs define influences of confounders, backdoor pathways, and analytic models. Potential mechanistic pathways such as intermediate pulmonary inflammation are illustrated. An overview of available data for each of the inter-node links is presented. Individual empirical epidemiologic studies have limited ability to confirm mechanisms of potential causal relationships due to the complexity of causal pathways and the extended time course over which disease may develop. Therefore, an explicit conceptual and graphical framework to facilitate synthesizing data from several studies to consider pulmonary inflammation as a common pathway for both chronic airflow obstruction and lung cancer is suggested. These methods are useful to clarify potential bona fide and artifactual observed relationships. They also delineate variables which should be included in analytic models for single study data and biologically relevant variables unlikely to be available from a single study. Frontiers Media S.A. 2022-07-05 /pmc/articles/PMC9294315/ /pubmed/35865253 http://dx.doi.org/10.3389/fpubh.2022.863402 Text en Copyright © 2022 Harber. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Public Health
Harber, Philip
Causal Inference Analysis for Poorly Soluble Low Toxicity Particles, Lung Function, and Malignancy
title Causal Inference Analysis for Poorly Soluble Low Toxicity Particles, Lung Function, and Malignancy
title_full Causal Inference Analysis for Poorly Soluble Low Toxicity Particles, Lung Function, and Malignancy
title_fullStr Causal Inference Analysis for Poorly Soluble Low Toxicity Particles, Lung Function, and Malignancy
title_full_unstemmed Causal Inference Analysis for Poorly Soluble Low Toxicity Particles, Lung Function, and Malignancy
title_short Causal Inference Analysis for Poorly Soluble Low Toxicity Particles, Lung Function, and Malignancy
title_sort causal inference analysis for poorly soluble low toxicity particles, lung function, and malignancy
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9294315/
https://www.ncbi.nlm.nih.gov/pubmed/35865253
http://dx.doi.org/10.3389/fpubh.2022.863402
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