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Bruyndonckx, Robin; Coenen, Samuel; Adriaenssens, Niels; Versporten, Ann; Monnet, Dominique L; Goossens, Herman; Molenberghs, Geert; Weist, Klaus; Hens, Niel; Strauss, Reinhild; Vandael, Eline; Sabtcheva, Stefana; Payerl-Pal, Marina; Kyriakidou, Isavella; Vlček, Jiří; Sönksen, Ute Wolff; Linask, Elviira; Sarvikivi, Emmi; Cavalié, Philippe; Eckmanns, Tim; Kontopidou, Flora; Matuz, Mária; Aspelund, Gudrun; Burns, Karen; [...]

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

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  • Media type: E-Article
  • Title: Analysing the trend over time of antibiotic consumption in the community: a tutorial on the detection of common change-points
  • Contributor: Bruyndonckx, Robin; Coenen, Samuel; Adriaenssens, Niels; Versporten, Ann; Monnet, Dominique L; Goossens, Herman; Molenberghs, Geert; Weist, Klaus; Hens, Niel; Strauss, Reinhild; Vandael, Eline; Sabtcheva, Stefana; Payerl-Pal, Marina; Kyriakidou, Isavella; Vlček, Jiří; Sönksen, Ute Wolff; Linask, Elviira; Sarvikivi, Emmi; Cavalié, Philippe; Eckmanns, Tim; Kontopidou, Flora; Matuz, Mária; Aspelund, Gudrun; Burns, Karen; [...]
  • imprint: Oxford University Press (OUP), 2021
  • Published in: Journal of Antimicrobial Chemotherapy
  • Language: English
  • DOI: 10.1093/jac/dkab180
  • ISSN: 0305-7453; 1460-2091
  • Keywords: Infectious Diseases ; Pharmacology (medical) ; Pharmacology ; Microbiology (medical)
  • Origination:
  • Footnote:
  • Description: <jats:title>Abstract</jats:title> <jats:sec> <jats:title>Objectives</jats:title> <jats:p>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.</jats:p> </jats:sec> <jats:sec> <jats:title>Methods</jats:title> <jats:p>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.</jats:p> </jats:sec> <jats:sec> <jats:title>Results</jats:title> <jats:p>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.</jats:p> </jats:sec> <jats:sec> <jats:title>Conclusions</jats:title> <jats:p>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.</jats:p> </jats:sec>
  • Access State: Open Access