Antonanzas, Fernando

Juarez-Castello, Carmello

Postma, Maarten

Rojas, Paula

van Asselt, A D I

van der Pol, Simon

English

University of Groningen

   University of GroningenHealth-economic modelling of infectious disease diagnostics: current approaches and futureopportunitiesvan der Pol, Simon; Rojas, Paula; Juarez-Castello, Carmello; van Asselt, A D I; Antonanzas,Fernando; Postma, MaartenIMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite fromit. Please check the document version below.Document VersionFinal author's version (accepted by publisher, after peer review)Publication date:2019Link to publication in University of Groningen/UMCG research databaseCitation for published version (APA):van der Pol, S., Rojas, P., Juarez-Castello, C., van Asselt, A. D. I., Antonanzas, F., & Postma, M. (2019).Health-economic modelling of infectious disease diagnostics: current approaches and future opportunities.Poster session presented at ISPOR Europe 2019, Copenhagen, Denmark.CopyrightOther than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of theauthor(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons).Take-down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediatelyand investigate your claim.Downloaded from the University of Groningen/UMCG research database (Pure): http://www.rug.nl/research/portal. For technical reasons thenumber of authors shown on this cover page is limited to 10 maximum.Download date: 21-02-2020HEALTH-ECONOMIC MODELLING OF INFECTIOUS DISEASE DIAGNOSTICS: CURRENT APPROACHES AND FUTURE OPPORTUNITIESSimon van der Pol, Paula Rojas, Carmelo Juárez, Thea van Asselt, Fernando Antoñanzas,  Maarten PostmaUniversity Medical Center Groningen (the Netherlands), University of La Rioja (Spain)Correspondence: s.van.der.pol@rug.nlThis project has received funding from the Innovative Medicines Init iat ive 2 Joint Undertaking under grant agreement No 820755.This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIAand bioMérieux SA, Janssen Pharmaceutica NV, Accelerate Diagnostics S.L. , Abbott , Bio-Rad Laboratories, BD Switzerland Sàrl,and The Wellcome Trust Limited.www.imi.Europa.euwww.value-dx.euAntimicrobial resistance (AMR) is a public health threat;infections with resistant organisms are estimated tocause over 650.000 infections and over 30.000 deaths inEurope1. AMR is associated with antibiotic consumption:appropriate prescribing of antibiotics is key in combatingAMR2,3. To fight this threat, it has been suggested thatpoint-of-care diagnostics to inform antibioticsprescribing are an important tool in reducing antibioticsprescriptions.We searched the literaturecomprehensively through the PUBMED,Web of Science and EMBASE databases,as well as grey literature for the period2000-2018. We included economicevaluations for diagnostic strategies forinfectious disease in all geographicareas. Studies dealing with (population)screenings or disease monitoring wereexplicitly excluded. Data extraction wasbased on the CHEERS checklist4, using astandardized digital (Google) form, withan emphasis on model types andinclusion of AMR.KeyFindingsMost cost-effectiveness analyses dealing with diagnosticsare for certain types of respiratory tract infections: suchas general respiratory tract infections, influenza ortuberculosis. Sexual transmitted disease, malaria andgastroenteritis (e.g. helicobacter infections) are alsocommon disease groups.Although bacterial or viral resistance is often discussed inthe included papers, it is rarely included in the analysis.Examples of methods to include resistance are: an ICERwith prescriptions saved as an outcome; calculating thethreshold cost of resistance that would change theconclusion of cost-effectiveness; or a point estimate ofresistant pathogens.Methods1. Cassini A, Högberg LD, Plachouras D, et al. Attributable deaths and disability-adjusted life-years caused by infections with antibiotic-resistant bacteria in the EU and the European Economic Area in 2015: a population-level modelling analysis. Lancet Infect Dis. 2018;0(0). doi:10.1016/S1473-3099(18)30605-422. Bell BG, Schellevis F, Stobberingh E, Goossens H, Pringle M. A systematic review and meta-analysis of the effects of antibiotic consumption on antibiotic resistance. BMC Infect Dis. 2014;14(1):13. doi:10.1186/1471-2334-14-133. Aryee A, Price N. Antimicrobial stewardship – can we afford to do without it? Br J Clin Pharmacol. 2015;79(2):173-181. doi:10.1111/bcp.124174. Husereau D, Drummond M, Petrou S, et al. Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement. BMJ. 2013;346:f1049. doi:10.1136/bmj.f1049BibTeX file for articles included in review: https://tinyurl.com/y423k22kReferencesThe flow diagram of included articles isshown above. Most papers are set in theprimary care setting, followed by thehospital setting. A large majority ofpapers analyzed use a decision treemodel for the calculation of quality-adjusted life years (QALYs) and costs.Often, these models use shorter timehorizons, (e.g. one flu season), ratherthan a lifetime approach. The diseasetypes investigated are shown in the piechart below. Looking at the author’sconclusions (see figure to the left),influenza diagnostics are not cost-effective in 50% of the articles, but forrespiratory infections, improveddiagnostics always is cost-effective orcost-saving.ResultsRecords identified through database searching(n = 4638)                                         Records screened(n = 3538)Full-text articles assessed for eligibility(n = 500)Studies included in qualitative synthesis(n = 127)Full-text articles excluded(n =  373 )Population screenings (n = 218)(Other) no diagnostic strategies (n = 61)No cost-effectiveness analysis (n = 35)Records excluded(n =   3186)No cost-effectiveness analysis (n = 2066)No infectious disease (n = 534)Duplicates removed (n = 1100)                                                                                                                   Flow chart of paper inclusionPie chart of disease types included in systematic reviewWith the objective of knowing the state of the art ondiagnostic, health-economic models, we reviewed cost-effectiveness analyses (CEAs) on diagnostics forinfectious disease, focusing on model types and AMR.Main objectivesBackgroundQ14I n fe c t i ou s d i se a se se ss i onNove mbe r  5I S P OR  Eu rope  2 019respiratory tract infection20%STDs8%fungal infection5%urinary tract infection7%other13%influenza12%malaria10%tropical (other)5%gastroenteritis7%tuberculosis13%Cost-saving27%Cost-saving8%Cost-effective73%Cost-effective42%Not cost-effective50%Respiratory tract infection(general)InfluenzaGeneral conclusions of articles in two disease areas** Preliminary results* no exhaustive list of exclusion criteria is provided here

Health-economic modelling of infectious disease diagnostics: current approaches and future opportunities

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Health-economic modelling of infectious disease diagnostics: current approaches and future opportunities

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