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Distributional interaction: Interpretational problems when using incidence odds ratios to assess interaction
It is well known that the incidence odds ratio approximates the risk ratio when the disease of interest is rare, but increasingly overestimates the risk ratio as the disease becomes more common. However when assessing interaction, incidence odds ratios may not approximate risk ratios even when the d...
Autores principales: | , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2005
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1079911/ https://www.ncbi.nlm.nih.gov/pubmed/15745447 http://dx.doi.org/10.1186/1742-5573-2-1 |
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author | Campbell, Ulka B Gatto, Nicolle M Schwartz, Sharon |
author_facet | Campbell, Ulka B Gatto, Nicolle M Schwartz, Sharon |
author_sort | Campbell, Ulka B |
collection | PubMed |
description | It is well known that the incidence odds ratio approximates the risk ratio when the disease of interest is rare, but increasingly overestimates the risk ratio as the disease becomes more common. However when assessing interaction, incidence odds ratios may not approximate risk ratios even when the disease is rare. We use the term "distributional interaction" to refer to interaction that appears when using incidence odds ratios that does not appear, or appears to a lesser degree, when using risk ratios. The interpretational problems that arise from this discrepancy can have important implications in epidemiologic research. Therefore, quantification of the relationship between the interaction odds ratio and the interaction risk ratio is warranted. In this paper, we provide a formula to quantify the differences between incidence odds ratios and risk ratios when they are used to estimate effect modification on a multiplicative scale. Using this formula, we examine the conditions under which these two estimates diverge. Furthermore, we expand this discussion to the implications of using incidence odds ratios to assess effect modification on an additive scale. Finally, we illustrate how distributional interaction arises and the problems that it causes using an example from the literature. Whenever the risk of the outcome variable is non-negligible, distributional interaction is possible. This is true even when the disease is rare (e.g., disease risk is less than 5%). Therefore, when assessing interaction on either an additive or multiplicative scale, caution should be taken in interpreting interaction estimates based on incidence odds ratios. |
format | Text |
id | pubmed-1079911 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2005 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-10799112005-04-15 Distributional interaction: Interpretational problems when using incidence odds ratios to assess interaction Campbell, Ulka B Gatto, Nicolle M Schwartz, Sharon Epidemiol Perspect Innov Analytic Perspective It is well known that the incidence odds ratio approximates the risk ratio when the disease of interest is rare, but increasingly overestimates the risk ratio as the disease becomes more common. However when assessing interaction, incidence odds ratios may not approximate risk ratios even when the disease is rare. We use the term "distributional interaction" to refer to interaction that appears when using incidence odds ratios that does not appear, or appears to a lesser degree, when using risk ratios. The interpretational problems that arise from this discrepancy can have important implications in epidemiologic research. Therefore, quantification of the relationship between the interaction odds ratio and the interaction risk ratio is warranted. In this paper, we provide a formula to quantify the differences between incidence odds ratios and risk ratios when they are used to estimate effect modification on a multiplicative scale. Using this formula, we examine the conditions under which these two estimates diverge. Furthermore, we expand this discussion to the implications of using incidence odds ratios to assess effect modification on an additive scale. Finally, we illustrate how distributional interaction arises and the problems that it causes using an example from the literature. Whenever the risk of the outcome variable is non-negligible, distributional interaction is possible. This is true even when the disease is rare (e.g., disease risk is less than 5%). Therefore, when assessing interaction on either an additive or multiplicative scale, caution should be taken in interpreting interaction estimates based on incidence odds ratios. BioMed Central 2005-03-03 /pmc/articles/PMC1079911/ /pubmed/15745447 http://dx.doi.org/10.1186/1742-5573-2-1 Text en Copyright © 2005 Campbell et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Analytic Perspective Campbell, Ulka B Gatto, Nicolle M Schwartz, Sharon Distributional interaction: Interpretational problems when using incidence odds ratios to assess interaction |
title | Distributional interaction: Interpretational problems when using incidence odds ratios to assess interaction |
title_full | Distributional interaction: Interpretational problems when using incidence odds ratios to assess interaction |
title_fullStr | Distributional interaction: Interpretational problems when using incidence odds ratios to assess interaction |
title_full_unstemmed | Distributional interaction: Interpretational problems when using incidence odds ratios to assess interaction |
title_short | Distributional interaction: Interpretational problems when using incidence odds ratios to assess interaction |
title_sort | distributional interaction: interpretational problems when using incidence odds ratios to assess interaction |
topic | Analytic Perspective |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1079911/ https://www.ncbi.nlm.nih.gov/pubmed/15745447 http://dx.doi.org/10.1186/1742-5573-2-1 |
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