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Systematic Reviews
Published in: Systematic Reviews 1/2018

Open Access 01-12-2018 | Protocol

Effect of the duration of antimicrobial exposure on the development of antimicrobial resistance (AMR) for macrolide antibiotics: protocol for a systematic review with a network meta-analysis

Authors: Titus H. Divala, Elizabeth L. Corbett, Helen R. Stagg, Marriott Nliwasa, Derek J. Sloan, Neil French, Katherine L. Fielding

Published in: Systematic Reviews | Issue 1/2018

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Abstract

Background

Antimicrobial resistance generates a huge health and economic burden and has the potential to become the leading cause of death globally, but its underlying drivers are yet to be fully described. The association between a microbe’s exposure to antimicrobials and subsequent development of, or selection for, resistance is well documented, as are the exacerbating microbial and human factors. However, the nature and extent of this risk, and how it varies by antimicrobial class and duration of treatment, is poorly defined. The goal of our systematic review and network meta-analysis is to determine the relationship between the duration of antimicrobial exposure and selection for resistance. We will use macrolides as the antimicrobial class of interest and Streptococcus pneumoniae carriage as an indicator organism. Our secondary outcomes include duration of symptoms, risk of treatment failure and recurrence, and descriptions of resistance mechanisms.

Methods

We will conduct a systematic review, selecting studies if they are published randomised controlled trials (RCTs) which report the relationship between taking a macrolide for any indication and incidence of resistant Streptococcus pneumoniae in patients of any age group. We will use a predefined search strategy to identify studies meeting these eligibility criteria in MEDLINE, Embase, Global Health and the Cochrane Central Register of RCTs. Two authors will independently screen titles and abstracts, review the full texts and undertake data extraction. We will use the Cochrane Collaboration’s tool to assess the quality of included RCTs. If feasible, we will perform pair-wise meta-analysis modelling to determine the relationship between the duration of macrolide treatment and development of macrolide resistant Streptococcus pneumoniae. If the identified studies meet the assumptions for a network meta-analysis (NMA), we will additionally model this relationship using indirect comparisons. Our protocol utilises reporting guidance by Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) and the extensions for protocols (PRISMA-P) and network meta-analyses (PRISMA for NMA). Our review will also report to these standards.

Discussion

Establishing the relationship between the duration of antimicrobial exposure and development of, or selection for, resistance will inform the design of antimicrobial prescriptions, treatment guidelines and the behaviour of both physicians and patients. This work will therefore be a strong contribution towards the full realisation of current antimicrobial resistance stewardship strategies.

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Appendix
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Literature
1.
Zaman SB, Hussain MA, Nye R, Mehta V, Mamun KT, Hossain N. A review on antibiotic resistance: alarm bells are ringing. Cureus. 2017;9(6):e1403.PubMedPubMedCentral
2.
Holmes AH, Moore LS, Sundsfjord A, et al. Understanding the mechanisms and drivers of antimicrobial resistance. Lancet. 2016;387(10014):176–87.PubMedCrossRef
3.
World Health Organization. Antimicrobial resistance: global report on surveillance: World Health Organization; 2014.
4.
Goossens H, Ferech M, Vander Stichele R, Elseviers M, Group EP. Outpatient antibiotic use in Europe and association with resistance: a cross-national database study. Lancet. 2005;365(9459):579–87.PubMedCrossRef
5.
6.
Salmond GPC, Welch M. Antibiotic resistance: adaptive evolution. Lancet. 2008;372:S97–S103.CrossRef
7.
Brown ED, Wright GD. Antibacterial drug discovery in the resistance era. Nature. 2016;529(7586):336–43.PubMedCrossRef
8.
United Nations General Assembly. Draft political declaration of the high-level meeting of the United Nations General Assembly on antimicrobial resistance. New York: United Nations; 2016.
9.
Control CfD, Prevention. Office of Infectious Disease. Antibiotic resistance threats in the United States, 2013. 2013. 2015.
10.
ECDC E. The bacterial challenge: time to react. Stockholm: European Center for Disease Prevention and Control; 2009.
11.
O’Neill J. Tackling drug-resistant infections globally: final report and recommendations. Review of antimicrobial resistance. London: HM Government and Wellcome trust; 2016.
12.
13.
Colijn C, Cohen T, Ganesh A, Murray M. Spontaneous emergence of multiple drug resistance in tuberculosis before and during therapy. PLoS One. 2011;6(3):e18327.PubMedPubMedCentralCrossRef
14.
15.
Wang G, Wilson TJ, Jiang Q, Taylor DE. Spontaneous mutations that confer antibiotic resistance in Helicobacter pylori. Antimicrob Agents Chemother. 2001;45(3):727–33.PubMedPubMedCentralCrossRef
16.
Malhotra-Kumar S, Van Heirstraeten L, Coenen S, et al. Impact of amoxicillin therapy on resistance selection in patients with community-acquired lower respiratory tract infections: a randomized, placebo-controlled study. J Antimicrob Chemother. 2016;71(11):3258–67.PubMedCrossRef
17.
Malhotra-Kumar S, Lammens C, Coenen S, Van Herck K, Goossens H. Effect of azithromycin and clarithromycin therapy on pharyngeal carriage of macrolide-resistant streptococci in healthy volunteers: a randomised, double-blind, placebo-controlled study. Lancet. 2007;369(9560):482–90.PubMedCrossRef
18.
Costelloe C, Metcalfe C, Lovering A, Mant D, Hay AD. Effect of antibiotic prescribing in primary care on antimicrobial resistance in individual patients: systematic review and meta-analysis. BMJ. 2010;340:c2096.PubMedCrossRef
19.
World Health Organization. Global action plan on antimicrobial resistance, 2015.
20.
Dolk FCK, Pouwels KB, Smith DRM, Robotham JV, Smieszek T. Antibiotics in primary care in England: which antibiotics are prescribed and for which conditions? J Antimicrob Chemother. 2018;73(suppl_2):ii2–ii10.PubMedCrossRef
21.
22.
Mazzei T, Mini E, Novelli A, Periti P. Chemistry and mode of action of macrolides. J Antimicrob Chemother. 1993;31(suppl_C):1–9.PubMedCrossRef
23.
24.
Musicha P, Cornick JE, Bar-Zeev N, et al. Trends in antimicrobial resistance in bloodstream infection isolates at a large urban hospital in Malawi (1998–2016): a surveillance study. Lancet Infect Dis. 2017;17(10):1042–52.PubMedPubMedCentralCrossRef
25.
Everett DB, Mukaka M, Denis B, et al. Ten years of surveillance for invasive Streptococcus pneumoniae during the era of antiretroviral scale-up and cotrimoxazole prophylaxis in Malawi. PLoS One. 2011;6(3):e17765.PubMedPubMedCentralCrossRef
26.
Gordon SB, Chaponda M, Walsh AL, et al. Pneumococcal disease in HIV-infected Malawian adults: acute mortality and long-term survival. AIDS. 2002;16(10):1409–17.PubMedPubMedCentralCrossRef
27.
Murray PR, Baron EJ, Pfaller MA, Tenover FC, Yolken RH. Manual of Clinical Microbiology In: Woods GL, Washington JA (eds). Antimicrobial Agents and Susceptibility Testing. Am. Soc. Microbiol. Washington, DC.. 1995.
28.
Organization WH. Manual for the national surveillance of antimicrobial resistance of S. pneumoniae and H. influenzae: epidemiological and microbiological methods. Geneva and Atlanta: WHO, CDC; 1994.
29.
30.
31.
Goldblatt D, Hussain M, Andrews N, et al. Antibody responses to nasopharyngeal carriage of Streptococcus pneumoniae in adults: a longitudinal household study. J Infect Dis. 2005;192(3):387–93.PubMedCrossRef
32.
Skalet AH, Cevallos V, Ayele B, et al. Antibiotic selection pressure and macrolide resistance in nasopharyngeal Streptococcus pneumoniae: a cluster-randomized clinical trial. PLoS Med. 2010;7(12):e1000377.PubMedPubMedCentralCrossRef
33.
34.
Higgins J, Savović J, Page M, Sterne J. Revised Cochrane risk of bias tool for randomized trials (RoB 2.0): additional considerations for cluster-randomized trials. ROB2 Development Group; 2018.
35.
36.
Furukawa TA, Miura T, Chaimani A, et al. Using the contribution matrix to evaluate complex study limitations in a network meta-analysis: a case study of bipolar maintenance pharmacotherapy review. BMC Res Notes. 2016;9(1):218.PubMedPubMedCentralCrossRef
37.
Salanti G, Ades AE, Ioannidis JP. Graphical methods and numerical summaries for presenting results from multiple-treatment meta-analysis: an overview and tutorial. J Clin Epidemiol. 2011;64(2):163–71.PubMedCrossRef
38.
Bucher HC, Guyatt GH, Griffith LE, Walter SD. The results of direct and indirect treatment comparisons in meta-analysis of randomized controlled trials. J Clin Epidemiol. 1997;50(6):683–91.PubMedCrossRef
39.
Dias S, Welton NJ, Caldwell DM, Ades AE. Checking consistency in mixed treatment comparison meta-analysis. Stat Med. 2010;29(7–8):932–44.PubMedCrossRef
40.
Higgins JP, Jackson D, Barrett JK, Lu G, Ades AE, White IR. Consistency and inconsistency in network meta-analysis: concepts and models for multi-arm studies. Res Synth Methods. 2012;3(2):98–110.PubMedPubMedCentralCrossRef
41.
Jackson D, Barrett JK, Rice S, White IR, Higgins JP. A design-by-treatment interaction model for network meta-analysis with random inconsistency effects. Stat Med. 2014;33(21):3639–54.PubMedPubMedCentralCrossRef
42.
Veroniki AA, Mavridis D, Higgins JPT, Salanti G. Characteristics of a loop of evidence that affect detection and estimation of inconsistency: a simulation study. BMC Med Res Methodol. 2014;14(1):106.PubMedPubMedCentralCrossRef
43.
Lunn D, Spiegelhalter D, Thomas A, Best N. The BUGS project: evolution, critique and future directions. Stat Med. 2009;28(25):3049–67.PubMedCrossRef
44.
Gelman A, Rubin DB. Inference from iterative simulation using multiple sequences. Stat Sci. 1992;7(4):457–72.CrossRef
45.
Brooks SP, Gelman A. General methods for monitoring convergence of iterative simulations. J Comput Graph Stat. 1998;7(4):434–55.
46.
White IR, Barrett JK, Jackson D, Higgins JP. Consistency and inconsistency in network meta-analysis: model estimation using multivariate meta-regression. Res Synth Methods. 2012;3(2):111–25.PubMedPubMedCentralCrossRef
47.
Puhan MA, Schünemann HJ, Murad MH, et al. A GRADE working group approach for rating the quality of treatment effect estimates from network meta-analysis. BMJ. 2014;349:g5630.PubMedCrossRef
48.
Guyatt G, Oxman AD, Akl EA, et al. GRADE guidelines: 1. Introduction—GRADE evidence profiles and summary of findings tables. J Clin Epidemiol. 2011;64(4):383–94.PubMedCrossRef
49.
Moher D, Liberati A, Tetzlaff J, Altman DG, Group P. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ. 2009;339:b2535.PubMedPubMedCentralCrossRef
50.
Hutton B, Salanti G, Caldwell DM, et al. The PRISMA extension statement for reporting of systematic reviews incorporating network meta-analyses of health care interventions: checklist and explanations. Ann Intern Med. 2015;162(11):777–84.PubMedCrossRef
Metadata
Title
Effect of the duration of antimicrobial exposure on the development of antimicrobial resistance (AMR) for macrolide antibiotics: protocol for a systematic review with a network meta-analysis
Authors
Titus H. Divala
Elizabeth L. Corbett
Helen R. Stagg
Marriott Nliwasa
Derek J. Sloan
Neil French
Katherine L. Fielding
Publication date
01-12-2018
Publisher
BioMed Central
Published in
Systematic Reviews / Issue 1/2018
Electronic ISSN: 2046-4053
DOI
https://doi.org/10.1186/s13643-018-0917-0

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