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

Author:

Bruyndonckx Robin12ORCID,Coenen Samuel13ORCID,Adriaenssens Niels13,Versporten Ann1,Monnet Dominique L4,Goossens Herman1,Molenberghs Geert25,Weist Klaus4,Hens Niel26,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,Fortinguerra Filomena,Seilis Andis,Valintėlienė Rolanda,Bruch Marcel,Zarb Peter,Natsch Stephanie,Blix Hege Salvesen,Olczak-Pieńkowska Anna,Silva Ana,Popescu Gabriel Adrian,Tesař Tomáš,Čižman Milan,Navas Antonio López,Bergfeldt Vendela,Müller-Pebody Berit,

Affiliation:

1. Laboratory of Medical Microbiology, Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium

2. Interuniversity Institute for Biostatistics and statistical Bioinformatics (I-BIOSTAT), Data Science Institute, Hasselt University, Hasselt, Belgium

3. Centre for General Practice, Department of Family Medicine & Population Health (FAMPOP), University of Antwerp, Antwerp, Belgium

4. Disease Programmes, European Centre for Disease Prevention and Control, Stockholm, Sweden

5. Interuniversity Institute for Biostatistics and statistical Bioinformatics (I-BIOSTAT), Catholic University of Leuven, Leuven, Belgium

6. Centre for Health Economic Research and Modelling Infectious Diseases, Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium

Abstract

Abstract 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.

Funder

Research Foundation—Flanders (FWO

University of Antwerp scientific chair in Evidence-Based Vaccinology

Pfizer

GSK

Methusalem

Flemish Government

Publisher

Oxford University Press (OUP)

Subject

Infectious Diseases,Pharmacology (medical),Pharmacology,Microbiology (medical)

Reference36 articles.

1. European Surveillance of Antimicrobial Consumption (ESAC): outpatient antibiotic use in Europe (1997-2009);Adriaenssens;J Antimicrob Chemother,2011

2. European Surveillance of Antimicrobial Consumption (ESAC): outpatient penicillin use in Europe (1997-2009);Versportern;J Antimicrob Chemother,2011

3. European Surveillance of Antimicrobial Consumption (ESAC): outpatient cephalosporin use in Europe (1997-2009);Versporten;J Antimicrob Chemother,2011

4. European Surveillance of Antimicrobial Consumption (ESAC): outpatient macrolide, lincosamide and streptogramin (MLS) use in Europe (1997-2009.);Adriaenssens;J Antimicrob Chemother,2011

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