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Analysing the trend over time of antibiotic consumption in the community: a tutorial on the detection of common change-points

OBJECTIVES: This tutorial describes and illustrates statistical methods to detect time trends possibly including abrupt changes (referred to as change-points) in the consumption of antibiotics in the community. METHODS: For the period 1997–2017, data on consumption of antibacterials for systemic use...

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Autores principales: Bruyndonckx, Robin, Coenen, Samuel, Adriaenssens, Niels, Versporten, Ann, Monnet, Dominique L, Goossens, Herman, Molenberghs, Geert, Weist, Klaus, Hens, Niel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8314099/
https://www.ncbi.nlm.nih.gov/pubmed/34312655
http://dx.doi.org/10.1093/jac/dkab180
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author Bruyndonckx, Robin
Coenen, Samuel
Adriaenssens, Niels
Versporten, Ann
Monnet, Dominique L
Goossens, Herman
Molenberghs, Geert
Weist, Klaus
Hens, Niel
author_facet Bruyndonckx, Robin
Coenen, Samuel
Adriaenssens, Niels
Versporten, Ann
Monnet, Dominique L
Goossens, Herman
Molenberghs, Geert
Weist, Klaus
Hens, Niel
author_sort Bruyndonckx, Robin
collection PubMed
description OBJECTIVES: This tutorial describes and illustrates statistical methods to detect time trends possibly including abrupt changes (referred to as change-points) in the consumption of antibiotics in the community. METHODS: For the period 1997–2017, data on consumption of antibacterials for systemic use (ATC group J01) in the community, aggregated at the level of the active substance, were collected using the WHO ATC/DDD methodology and expressed in DDD (ATC/DDD index 2019) per 1000 inhabitants per day. Trends over time and presence of common change-points were studied through a set of non-linear mixed models. RESULTS: After a thorough description of the set of models used to assess the time trend and presence of common change-points herein, the methodology was applied to the consumption of antibacterials for systemic use (ATC J01) in 25 EU/European Economic Area (EEA) countries. The best fit was obtained for a model including two change-points: one in the first quarter of 2004 and one in the last quarter of 2008. CONCLUSIONS: Allowing for the inclusion of common change-points improved model fit. Individual countries investigating changes in their antibiotic consumption pattern can use this tutorial to analyse their country data.
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spelling pubmed-83140992021-07-27 Analysing the trend over time of antibiotic consumption in the community: a tutorial on the detection of common change-points Bruyndonckx, Robin Coenen, Samuel Adriaenssens, Niels Versporten, Ann Monnet, Dominique L Goossens, Herman Molenberghs, Geert Weist, Klaus Hens, Niel J Antimicrob Chemother Supplement Papers OBJECTIVES: This tutorial describes and illustrates statistical methods to detect time trends possibly including abrupt changes (referred to as change-points) in the consumption of antibiotics in the community. METHODS: For the period 1997–2017, data on consumption of antibacterials for systemic use (ATC group J01) in the community, aggregated at the level of the active substance, were collected using the WHO ATC/DDD methodology and expressed in DDD (ATC/DDD index 2019) per 1000 inhabitants per day. Trends over time and presence of common change-points were studied through a set of non-linear mixed models. RESULTS: After a thorough description of the set of models used to assess the time trend and presence of common change-points herein, the methodology was applied to the consumption of antibacterials for systemic use (ATC J01) in 25 EU/European Economic Area (EEA) countries. The best fit was obtained for a model including two change-points: one in the first quarter of 2004 and one in the last quarter of 2008. CONCLUSIONS: Allowing for the inclusion of common change-points improved model fit. Individual countries investigating changes in their antibiotic consumption pattern can use this tutorial to analyse their country data. Oxford University Press 2021-08-01 /pmc/articles/PMC8314099/ /pubmed/34312655 http://dx.doi.org/10.1093/jac/dkab180 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Supplement Papers
Bruyndonckx, Robin
Coenen, Samuel
Adriaenssens, Niels
Versporten, Ann
Monnet, Dominique L
Goossens, Herman
Molenberghs, Geert
Weist, Klaus
Hens, Niel
Analysing the trend over time of antibiotic consumption in the community: a tutorial on the detection of common change-points
title Analysing the trend over time of antibiotic consumption in the community: a tutorial on the detection of common change-points
title_full Analysing the trend over time of antibiotic consumption in the community: a tutorial on the detection of common change-points
title_fullStr Analysing the trend over time of antibiotic consumption in the community: a tutorial on the detection of common change-points
title_full_unstemmed Analysing the trend over time of antibiotic consumption in the community: a tutorial on the detection of common change-points
title_short Analysing the trend over time of antibiotic consumption in the community: a tutorial on the detection of common change-points
title_sort analysing the trend over time of antibiotic consumption in the community: a tutorial on the detection of common change-points
topic Supplement Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8314099/
https://www.ncbi.nlm.nih.gov/pubmed/34312655
http://dx.doi.org/10.1093/jac/dkab180
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