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Assessing Causal Mechanistic Interactions: A Peril Ratio Index of Synergy Based on Multiplicativity

The assessments of interactions in epidemiology have traditionally been based on risk-ratio, odds-ratio or rate-ratio multiplicativity. However, many epidemiologists fail to recognize that this is mainly for statistical conveniences and often will misinterpret a statistically significant interaction...

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Autor principal: Lee, Wen-Chung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3691192/
https://www.ncbi.nlm.nih.gov/pubmed/23826299
http://dx.doi.org/10.1371/journal.pone.0067424
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author Lee, Wen-Chung
author_facet Lee, Wen-Chung
author_sort Lee, Wen-Chung
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description The assessments of interactions in epidemiology have traditionally been based on risk-ratio, odds-ratio or rate-ratio multiplicativity. However, many epidemiologists fail to recognize that this is mainly for statistical conveniences and often will misinterpret a statistically significant interaction as a genuine mechanistic interaction. The author adopts an alternative metric system for risk, the ‘peril’. A peril is an exponentiated cumulative rate, or simply, the inverse of a survival (risk complement) or one plus an odds. The author proposes a new index based on multiplicativity of peril ratios, the ‘peril ratio index of synergy based on multiplicativity’ (PRISM). Under the assumption of no redundancy, PRISM can be used to assess synergisms in sufficient cause sense, i.e., causal co-actions or causal mechanistic interactions. It has a less stringent threshold to detect a synergy as compared to a previous index of ‘relative excess risk due to interaction’. Using the new PRISM criterion, many situations in which there is not evidence of interaction judged by the traditional indices are in fact corresponding to bona fide positive or negative synergisms.
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spelling pubmed-36911922013-07-03 Assessing Causal Mechanistic Interactions: A Peril Ratio Index of Synergy Based on Multiplicativity Lee, Wen-Chung PLoS One Research Article The assessments of interactions in epidemiology have traditionally been based on risk-ratio, odds-ratio or rate-ratio multiplicativity. However, many epidemiologists fail to recognize that this is mainly for statistical conveniences and often will misinterpret a statistically significant interaction as a genuine mechanistic interaction. The author adopts an alternative metric system for risk, the ‘peril’. A peril is an exponentiated cumulative rate, or simply, the inverse of a survival (risk complement) or one plus an odds. The author proposes a new index based on multiplicativity of peril ratios, the ‘peril ratio index of synergy based on multiplicativity’ (PRISM). Under the assumption of no redundancy, PRISM can be used to assess synergisms in sufficient cause sense, i.e., causal co-actions or causal mechanistic interactions. It has a less stringent threshold to detect a synergy as compared to a previous index of ‘relative excess risk due to interaction’. Using the new PRISM criterion, many situations in which there is not evidence of interaction judged by the traditional indices are in fact corresponding to bona fide positive or negative synergisms. Public Library of Science 2013-06-24 /pmc/articles/PMC3691192/ /pubmed/23826299 http://dx.doi.org/10.1371/journal.pone.0067424 Text en © 2013 Wen-Chung Lee http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Lee, Wen-Chung
Assessing Causal Mechanistic Interactions: A Peril Ratio Index of Synergy Based on Multiplicativity
title Assessing Causal Mechanistic Interactions: A Peril Ratio Index of Synergy Based on Multiplicativity
title_full Assessing Causal Mechanistic Interactions: A Peril Ratio Index of Synergy Based on Multiplicativity
title_fullStr Assessing Causal Mechanistic Interactions: A Peril Ratio Index of Synergy Based on Multiplicativity
title_full_unstemmed Assessing Causal Mechanistic Interactions: A Peril Ratio Index of Synergy Based on Multiplicativity
title_short Assessing Causal Mechanistic Interactions: A Peril Ratio Index of Synergy Based on Multiplicativity
title_sort assessing causal mechanistic interactions: a peril ratio index of synergy based on multiplicativity
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3691192/
https://www.ncbi.nlm.nih.gov/pubmed/23826299
http://dx.doi.org/10.1371/journal.pone.0067424
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