Network meta-analysis: a technique to gather evidence from direct and indirect comparisons.
Systematic reviews and pairwise meta-analyses of randomized controlled trials, at the intersection of clinical medicine, epidemiology and statistics, are positioned at the top of evidence-based practice hierarchy. These are important tools to base drugs approval, clinical protocols and guidelines fo...
| Published in: | Pharmacy Practice (1886-3655) Vol. 15; no. 1; pp. 1 - 12 |
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| Main Authors: | , , , |
| Format: | research tables/charts Journal Article |
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Centro de Investigaciones y Publicaciones Farmaceuticas S.L.
Jan-Mar2017
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=122614036&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 122614036 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 1885642X 3EAU jtl: Pharmacy Practice (1886-3655) issn: 1885642X maglogo: N pubinfo: dt: Jan-Mar2017 vid: 15 iid: 1 pid: 36266 pub: Centro de Investigaciones y Publicaciones Farmaceuticas S.L. artinfo: ui: 122614036 122614036 122614036 10.18549/PharmPract.2017.01.943 122614036 ppf: 1 ppct: 11 formats: fmt: @attributes: type: P tig: atl: Network meta-analysis: a technique to gather evidence from direct and indirect comparisons. aug: au: TONIN, Fernanda S. ROTTA, Inajara MENDES, Antonio M. PONTAROLO, Roberto affil: MSc. (Pharm). Pharmaceutical Sciences Postgraduate Programme, Federal University of Paraná. Curitiba (Brazil) sug: subj: Decision Support Techniques Mental Health Software Statistics Methods Decision Support Systems, Management ab: Systematic reviews and pairwise meta-analyses of randomized controlled trials, at the intersection of clinical medicine, epidemiology and statistics, are positioned at the top of evidence-based practice hierarchy. These are important tools to base drugs approval, clinical protocols and guidelines formulation and for decision-making. However, this traditional technique only partially yield information that clinicians, patients and policy-makers need to make informed decisions, since it usually compares only two interventions at the time. In the market, regardless the clinical condition under evaluation, usually many interventions are available and few of them have been studied in head-to-head studies. This scenario precludes conclusions to be drawn from comparisons of all interventions profile (e.g. efficacy and safety). The recent development and introduction of a new technique – usually referred as network meta-analysis, indirect meta-analysis, multiple or mixed treatment comparisons – has allowed the estimation of metrics for all possible comparisons in the same model, simultaneously gathering direct and indirect evidence. Over the last years this statistical tool has matured as technique with models available for all types of raw data, producing different pooled effect measures, using both Frequentist and Bayesian frameworks, with different software packages. However, the conduction, report and interpretation of network meta-analysis still poses multiple challenges that should be carefully considered, especially because this technique inherits all assumptions from pairwise meta-analysis but with increased complexity. Thus, we aim to provide a basic explanation of network meta-analysis conduction, highlighting its risks and benefits for evidence-based practice, including information on statistical methods evolution, assumptions and steps for performing the analysis. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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