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      CINeMA: An approach for assessing confidence in the results of a network meta-analysis

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          Abstract

          Background

          The evaluation of the credibility of results from a meta-analysis has become an important part of the evidence synthesis process. We present a methodological framework to evaluate confidence in the results from network meta-analyses, Confidence in Network Meta-Analysis (CINeMA), when multiple interventions are compared.

          Methodology

          CINeMA considers 6 domains: (i) within-study bias, (ii) reporting bias, (iii) indirectness, (iv) imprecision, (v) heterogeneity, and (vi) incoherence. Key to judgments about within-study bias and indirectness is the percentage contribution matrix, which shows how much information each study contributes to the results from network meta-analysis. The contribution matrix can easily be computed using a freely available web application. In evaluating imprecision, heterogeneity, and incoherence, we consider the impact of these components of variability in forming clinical decisions.

          Conclusions

          Via 3 examples, we show that CINeMA improves transparency and avoids the selective use of evidence when forming judgments, thus limiting subjectivity in the process. CINeMA is easy to apply even in large and complicated networks.

          Abstract

          Adriani Nikolakopoulou and co-authors discuss CINeMA, an approach for evaluating the findings of network meta-analyses.

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          Most cited references25

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          Pharmaceutical industry sponsorship and research outcome and quality: systematic review.

          Joel Lexchin, Lisa A Bero, Benjamin Djulbegovic … (2003)
          To investigate whether funding of drug studies by the pharmaceutical industry is associated with outcomes that are favourable to the funder and whether the methods of trials funded by pharmaceutical companies differ from the methods in trials with other sources of support. Medline (January 1966 to December 2002) and Embase (January 1980 to December 2002) searches were supplemented with material identified in the references and in the authors' personal files. Data were independently abstracted by three of the authors and disagreements were resolved by consensus. 30 studies were included. Research funded by drug companies was less likely to be published than research funded by other sources. Studies sponsored by pharmaceutical companies were more likely to have outcomes favouring the sponsor than were studies with other sponsors (odds ratio 4.05; 95% confidence interval 2.98 to 5.51; 18 comparisons). None of the 13 studies that analysed methods reported that studies funded by industry was of poorer quality. Systematic bias favours products which are made by the company funding the research. Explanations include the selection of an inappropriate comparator to the product being investigated and publication bias.
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            Systematic Review of the Empirical Evidence of Study Publication Bias and Outcome Reporting Bias

            Kerry Dwan, Douglas G. Altman, Juan A. Arnaiz … (2008)
            Background The increased use of meta-analysis in systematic reviews of healthcare interventions has highlighted several types of bias that can arise during the completion of a randomised controlled trial. Study publication bias has been recognised as a potential threat to the validity of meta-analysis and can make the readily available evidence unreliable for decision making. Until recently, outcome reporting bias has received less attention. Methodology/Principal Findings We review and summarise the evidence from a series of cohort studies that have assessed study publication bias and outcome reporting bias in randomised controlled trials. Sixteen studies were eligible of which only two followed the cohort all the way through from protocol approval to information regarding publication of outcomes. Eleven of the studies investigated study publication bias and five investigated outcome reporting bias. Three studies have found that statistically significant outcomes had a higher odds of being fully reported compared to non-significant outcomes (range of odds ratios: 2.2 to 4.7). In comparing trial publications to protocols, we found that 40–62% of studies had at least one primary outcome that was changed, introduced, or omitted. We decided not to undertake meta-analysis due to the differences between studies. Conclusions Recent work provides direct empirical evidence for the existence of study publication bias and outcome reporting bias. There is strong evidence of an association between significant results and publication; studies that report positive or significant results are more likely to be published and outcomes that are statistically significant have higher odds of being fully reported. Publications have been found to be inconsistent with their protocols. Researchers need to be aware of the problems of both types of bias and efforts should be concentrated on improving the reporting of trials.
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              The results of direct and indirect treatment comparisons in meta-analysis of randomized controlled trials.

              H. C. Bucher, G H Guyatt, L Griffith … (1997)
              When little or no data directly comparing two treatments are available, investigators often rely on indirect comparisons from studies testing the treatments against a control or placebo. One approach to indirect comparison is to pool findings from the active treatment arms of the original controlled trials. This approach offers no advantage over a comparison of observational study data and is prone to bias. We present an alternative model that evaluates the differences between treatment and placebo in two sets of clinical trials, and preserves the randomization of the originally assigned patient groups. We apply the method to data on sulphamethoxazole-trimethoprim or dapsone/pyrimethamine as prophylaxis against Pneumocystis carinii in HIV infected patients. The indirect comparison showed substantial increased benefit from the former (odds ratio 0.37, 95% CI 0.21 to 0.65), while direct comparisons from randomized trials suggests a much smaller difference (risk ratio 0.64, 95% CI 0.45 to 0.90; p-value for difference of effect = 0.11). Direct comparisons of treatments should be sought. When direct comparisons are unavailable, indirect comparison meta-analysis should evaluate the magnitude of treatment effects across studies, recognizing the limited strength of inference.
              Article 0 comments Cited 376 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (nlm-ta): PLoS Med
                Journal ID (iso-abbrev): PLoS Med
                Journal ID (publisher-id): plos
                Journal ID (pmc): plosmed
                Title: PLoS Medicine
                Publisher: Public Library of Science (San Francisco, CA USA )
                ISSN (Print): 1549-1277
                ISSN (Electronic): 1549-1676
                Publication date (Electronic): 3 April 2020
                Publication date Collection: April 2020
                Volume: 17
                Issue: 4
                Electronic Location Identifier: e1003082
                Affiliations
                [1 ] Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
                [2 ] Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
                [3 ] Université de Paris, Research Center of Epidemiology and Statistics Sorbonne Paris Cité (CRESS UMR1153), INSERM, INRA, Paris, France
                [4 ] Cochrane France, Paris, France
                [5 ] Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland
                Author notes

                I have read the journal's policy and the authors of this manuscript have the following competing interests: ME is a member of the Editorial Board of PLOS Medicine.

                Author information
                http://orcid.org/0000-0002-8323-2514
                http://orcid.org/0000-0002-6630-6817
                http://orcid.org/0000-0003-2828-6832
                http://orcid.org/0000-0001-7462-5132
                http://orcid.org/0000-0002-3830-8508
                Article
                Publisher ID: PMEDICINE-D-19-00636
                DOI: 10.1371/journal.pmed.1003082
                PMC ID: 7122720
                PubMed ID: 32243458
                SO-VID: ad5bc4f2-cf0c-4d48-9124-e6e1071b3b50
                Copyright © © 2020 Nikolakopoulou et al
                License:

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Page count
                Figures: 4, Tables: 2, Pages: 19
                Funding
                Funded by: Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (CH)
                Award ID: 179158
                Award Recipient :
                ORCID: http://orcid.org/0000-0002-3830-8508
                Funded by: Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (CH)
                Award ID: 174281
                Award Recipient :
                ORCID: http://orcid.org/0000-0001-7462-5132
                Funded by: Campbell Collaboration
                Award Recipient :
                ORCID: http://orcid.org/0000-0002-3830-8508
                Funded by: Cochrane Collaboration
                Award Recipient :
                ORCID: http://orcid.org/0000-0002-3830-8508
                The development of the software and part of the presented work was supported by the Cochrane Collaboration and the Campbell Collaboration. GS, AN, TP were supported by project funding (Grant No. 179158) from the Swiss National Science Foundation. ME was supported by special project funding (Grant No. 174281) from the Swiss National Science Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Subject: Guidelines and Guidance
                Subject: Research and Analysis Methods
                Subject: Mathematical and Statistical Techniques
                Subject: Statistical Methods
                Subject: Metaanalysis
                Subject: Physical Sciences
                Subject: Mathematics
                Subject: Statistics
                Subject: Statistical Methods
                Subject: Metaanalysis
                Subject: Research and Analysis Methods
                Subject: Bioassays and Physiological Analysis
                Subject: Electrophysiological Techniques
                Subject: Cardiac Electrophysiology
                Subject: Electrocardiography
                Subject: Medicine and Health Sciences
                Subject: Vascular Medicine
                Subject: Coronary Heart Disease
                Subject: Medicine and Health Sciences
                Subject: Cardiology
                Subject: Coronary Heart Disease
                Subject: Medicine and Health Sciences
                Subject: Diagnostic Medicine
                Subject: Diagnostic Radiology
                Subject: Magnetic Resonance Imaging
                Subject: Research and Analysis Methods
                Subject: Imaging Techniques
                Subject: Diagnostic Radiology
                Subject: Magnetic Resonance Imaging
                Subject: Medicine and Health Sciences
                Subject: Radiology and Imaging
                Subject: Diagnostic Radiology
                Subject: Magnetic Resonance Imaging
                Subject: Medicine and Health Sciences
                Subject: Pharmacology
                Subject: Drugs
                Subject: Statins
                Subject: Medicine and Health Sciences
                Subject: Diagnostic Medicine
                Subject: Research and Analysis Methods
                Subject: Research Design
                Subject: Clinical Research Design
                Subject: Adverse Events
                Subject: Computer and Information Sciences
                Subject: Network Analysis

                ScienceOpen disciplines: Medicine
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                ScienceOpen disciplines: Medicine

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