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      International Journal of COPD (submit here)

      This international, peer-reviewed Open Access journal by Dove Medical Press focuses on pathophysiological processes underlying Chronic Obstructive Pulmonary Disease (COPD) interventions, patient focused education, and self-management protocols. Sign up for email alerts here.

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      The impact of dual bronchodilation on cardiovascular serious adverse events and mortality in COPD: a quantitative synthesis

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          Abstract

          Objective

          Long-acting β 2-agonists (LABAs) and long-acting muscarinic antagonists (LAMAs) are burdened by the potential risk of inducing cardiovascular serious adverse events (SAEs) in COPD patients. Since the risk of combining a LABA with a LAMA could be greater, we have carried out a quantitative synthesis to investigate the cardiovascular safety profile of LABA/LAMA fixed-dose combinations (FDCs).

          Methods

          A pair-wise and network meta-analysis was performed by using the data of the repository database ClinicalTrials.gov concerning the impact of approved LABA/LAMA FDCs versus monocomponents and/or placebo on cardiovascular SAEs in COPD.

          Results

          Overall, LABA/LAMA FDCs did not significantly ( P>0.05) modulate the risk of cardiovascular SAEs versus monocomponents. However, the network meta-analysis indicated that aclidinium/formoterol 400/12 µg and tiotropium/olodaterol 5/5 µg were the safest FDCs, followed by umeclidinium/vilanterol 62.5/25 µg which was as safe as placebo, whereas glycopyrronium/formoterol 14.9/9.6, glycopyrronium/indacaterol 15.6/27.5 µg, and glycopyrronium/indacaterol 50/110 µg were the least safe FDCs. No impact on mortality was detected for each specific FDC.

          Conclusion

          This meta-analysis indicates that LABA/LAMA FDC therapy is characterized by an excellent cardiovascular safety profile in COPD patients. However, the findings of this quantitative synthesis have been obtained from populations that participated in randomized clinical trials, and were devoid of major cardiovascular diseases. Thus, post-marketing surveillance and observational studies may help to better define the real impact of specific FDCs with regard to the cardiovascular risk.

          Most cited references65

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          Evidence Synthesis for Decision Making 4

          Inconsistency can be thought of as a conflict between “direct” evidence on a comparison between treatments B and C and “indirect” evidence gained from AC and AB trials. Like heterogeneity, inconsistency is caused by effect modifiers and specifically by an imbalance in the distribution of effect modifiers in the direct and indirect evidence. Defining inconsistency as a property of loops of evidence, the relation between inconsistency and heterogeneity and the difficulties created by multiarm trials are described. We set out an approach to assessing consistency in 3-treatment triangular networks and in larger circuit structures, its extension to certain special structures in which independent tests for inconsistencies can be created, and describe methods suitable for more complex networks. Sample WinBUGS code is given in an appendix. Steps that can be taken to minimize the risk of drawing incorrect conclusions from indirect comparisons and network meta-analysis are the same steps that will minimize heterogeneity in pairwise meta-analysis. Empirical indicators that can provide reassurance and the question of how to respond to inconsistency are also discussed.
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            Is network meta-analysis as valid as standard pairwise meta-analysis? It all depends on the distribution of effect modifiers

            Background In the last decade, network meta-analysis of randomized controlled trials has been introduced as an extension of pairwise meta-analysis. The advantage of network meta-analysis over standard pairwise meta-analysis is that it facilitates indirect comparisons of multiple interventions that have not been studied in a head-to-head fashion. Although assumptions underlying pairwise meta-analyses are well understood, those concerning network meta-analyses are perceived to be more complex and prone to misinterpretation. Discussion In this paper, we aim to provide a basic explanation when network meta-analysis is as valid as pairwise meta-analysis. We focus on the primary role of effect modifiers, which are study and patient characteristics associated with treatment effects. Because network meta-analysis includes different trials comparing different interventions, the distribution of effect modifiers cannot only vary across studies for a particular comparison (as with standard pairwise meta-analysis, causing heterogeneity), but also between comparisons (causing inconsistency). If there is an imbalance in the distribution of effect modifiers between different types of direct comparisons, the related indirect comparisons will be biased. If it can be assumed that this is not the case, network meta-analysis is as valid as pairwise meta-analysis. Summary The validity of network meta-analysis is based on the underlying assumption that there is no imbalance in the distribution of effect modifiers across the different types of direct treatment comparisons, regardless of the structure of the evidence network.
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              Automated generation of node‐splitting models for assessment of inconsistency in network meta‐analysis

              Network meta‐analysis enables the simultaneous synthesis of a network of clinical trials comparing any number of treatments. Potential inconsistencies between estimates of relative treatment effects are an important concern, and several methods to detect inconsistency have been proposed. This paper is concerned with the node‐splitting approach, which is particularly attractive because of its straightforward interpretation, contrasting estimates from both direct and indirect evidence. However, node‐splitting analyses are labour‐intensive because each comparison of interest requires a separate model. It would be advantageous if node‐splitting models could be estimated automatically for all comparisons of interest. We present an unambiguous decision rule to choose which comparisons to split, and prove that it selects only comparisons in potentially inconsistent loops in the network, and that all potentially inconsistent loops in the network are investigated. Moreover, the decision rule circumvents problems with the parameterisation of multi‐arm trials, ensuring that model generation is trivial in all cases. Thus, our methods eliminate most of the manual work involved in using the node‐splitting approach, enabling the analyst to focus on interpreting the results. © 2015 The Authors Research Synthesis Methods Published by John Wiley & Sons Ltd.
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                Author and article information

                Journal
                Int J Chron Obstruct Pulmon Dis
                Int J Chron Obstruct Pulmon Dis
                International Journal of COPD
                International Journal of Chronic Obstructive Pulmonary Disease
                Dove Medical Press
                1176-9106
                1178-2005
                2017
                05 December 2017
                : 12
                : 3469-3485
                Affiliations
                [1 ]Department of Experimental Medicine and Surgery, University of Rome Tor Vergata, Rome, Italy
                [2 ]Division of Respiratory Medicine, University Hospital Tor Vergata, Rome, Italy
                [3 ]Department of Experimental Medicine, University of Campania Luigi Vanvitelli, Naples, Italy
                Author notes
                Correspondence: Paola Rogliani, Department of Experimental Medicine and Surgery, University of Rome Tor Vergata, Via Montpellier 1, 00133, Roma, Italy, Email paola.rogliani@ 123456uniroma2.it
                Article
                copd-12-3469
                10.2147/COPD.S146338
                5723113
                7712b96a-51c9-4744-b5a8-e012eea251de
                © 2017 Rogliani et al. This work is published and licensed by Dove Medical Press Limited

                The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.

                History
                Categories
                Original Research

                Respiratory medicine
                copd,laba/lama fdc,cardiovascular safety,mortality,meta-analysis
                Respiratory medicine
                copd, laba/lama fdc, cardiovascular safety, mortality, meta-analysis

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