Several studies have shown that both acupuncture and dry needling are effective in the treatment of musculoskeletal pains. Especially for networks with many competing interventions that involve many comparisons, presentation of findings in a concise and comprehensible way is challenging. Graphical Tools for Network Meta-Analysis in STATA Anna Chaimani1, Julian P. T. Higgins2,3, Dimitris Mavridis1,4, Panagiota Spyridonos5, Georgia Salanti1* 1Department of Hygiene and Epidemiology, School of Medicine, University of Ioannina, Ioannina, Greece, 2School of Social and Community Medicine, University of Statistics in Medicine 2011; 30: 24812498. As an example, in the dietary advice network (Figure 11.2.a) suppose that most of the evidence involved in the indirect comparison (i.e. The situation is illustrated in Figure 11.2.a, where the solid straight lines depict available evidence. Recently, the IMP framework was extended into meta-analyses with continuous outcomes. A common view of the two approaches is that they do not support the idea of downgrading indirect evidence by default. From these dimensions, we developed a system with five categories , ranging from interventions that provide generic information through a single channel, e.g. Evaluation of networks of randomized trials. Once incoherence is detected, possible explanations should be sought. Review authors should consider the confidence intervals for incoherence factors and decide whether they include values that are sufficiently large to suggest clinically important discrepancies between direct and indirect evidence. Previous work on models for networ Global incoherence in a network can be evaluated and detected via incoherence models. PloS One 2010; 5: e11054. Note that the package requires the latest versions of metan, mvmeta and network and is compatible with Stata versions 13, 14 and 15. Consequently, we need to assign values 1 and 1 to the dummies dietitian versus doctor and dietitian versus nurse, respectively. The method is implemented in the network macro available for Stata (White 2015). The equation that considers within-study . Also, the network meta-analysis results are more precise (narrower confidence intervals) than the pair-wise meta-analysis results for two comparisons (Mirena versus first generation hysteroscopic techniques and Second generation non-hysteroscopic techniques versus Mirena). Methodology from electrical networks and graphic theory also can be used to fit network meta-analysis and is outlined in by Rcker (Rcker 2012). Download data from various applications of Network Meta-Analysis here, Stata software for pairwise and network meta-analysis, Allowing for informative missingness in aggregate data meta-analysis with continuous or binary outcomes: Extensions to metamiss, Allowing for uncertainty due to missing continuous outcome data in pairwise and network meta-analysis. Detailed descriptions of hierarchical models for network meta-analysis can be found elsewhere (Lu and Ades 2004, Salanti et al 2008, Dias et al 2018). The distinction between the decision set and the wider synthesis comparator set (all interventions included in the analysis) should be made in the protocol of the review. Schnelle Lieferung Kostenloser Versand Unbegrenzter Rabatt Riley RD, Higgins JPT, Deeks JJ. For each multi-arm study with T number of arms there are observations (with the same study ID) equal to the number of pairwise comparisons that this study provides. We introduced indirect comparisons in Section 11.2.1 in the context of subgroup analysis, where the subgroups are defined by the comparisons. It is closely related to the statistical notion of coherence (see Section 11.2.3.2); the distinction is a little like that between diversity and (statistical) heterogeneity in pairwise meta-analysis (see Chapter 10, Section 10.10.1). Third, assuming common heterogeneity makes model estimation computationally easier than assuming comparison-specific heterogeneity (Lu and Ades 2009). For example, in the dietary advice network containing only three intervention nodes (see Section 11.2.1, Figure 11.2.a) the dummy variable might be used to indicate the comparison dietitian versus nurse. Annals of Internal Medicine 2013; 159: 130137. Statistics in Medicine 2013; 32: 2539. The idea is similar to a subgroup analysis: the different subgroups could have a common heterogeneity or different heterogeneities. Sobieraj DM, Cappelleri JC, Baker WL, Phung OJ, White CM, Coleman CI. It is common to assume that the amount of heterogeneity is the same for every comparison in the network (Higgins and Whitehead 1996). Jackson D, Barrett JK, Rice S, White IR, Higgins JPT. Close collaboration between the statistician and the content area expert is essential to ensure that the studies selected for a network meta-analysis are similar except for the interventions being compared (see Section 11.2.2). For networks including many competing interventions and multiple different study designs, network diagrams might not be the most appropriate tool for presenting the data. BMC Medical Research Methodology 2013; 13: 35. 12. BMJ Open2016;6:e011841. What is a Diagnostic Test Accuracy Review? efficacy and acceptability) might conflict with respect to which interventions work best. Synthesis:Statistical analysis when possible (heterogeneity a potential problem with indirect comparisons)--uses different statistical methods than a systematic review. This means that studies comparing doctor versus nurse inform us about the difference between the two comparisons already in the analysis. Song F, Clark A, Bachmann MO, Maas J. Simulation evaluation of statistical properties of methods for indirect and mixed treatment comparisons. An extension of this model has been suggested where incoherence measures the disagreement when an effect size is measured in studies that involve different sets of interventions (termed design incoherence) (Higgins et al 2012). In this section, we summarize and highlight key issues that are pertinent to systematic review with a network meta-analysis. It all depends on the distribution of effect modifiers. Incoherence occurs when different sources of information for a particular relative effect are in disagreement (Song et al 2003, Lu and Ades 2006, Salanti 2012). Figure 11.2.d Example of valid and invalid indirect comparisons when the severity of disease acts as effect modifier and its distribution differs between the two direct comparisons. Thicker lines correspond to greater average age within the respective comparison. Example of a published Treatment Network for the Drugs Considered in the Example Multiple Treatment Comparison on Generalized Anxiety Disorder, Mills, Edward J., John P. A. Ioannidis, Kristian Thorlund, Holger J. Schnemann, Milo A. Puhan, and Gordon H. Guyatt. The results from evaluating global incoherence can be summarized in the P value of the Chi2 statistic incoherence test and the I2 statistic for incoherence (see Chapter 10, Section 10.10.2). Section 11.4 briefly describes the available statistical methods for synthesizing the data, estimating the relative ranking and assessing coherence in a network of interventions. stataNMAstata, Graphs to Enhance Understanding & Improve Interpretability of the Evidence from Network Meta-Analysis, Network Meta-Analysis&example datasets from , Cipriani A, Barbui C, Salanti G, Rendell J, Brown R, Stockton S, et al. To see the help files for any routine type help and the name of the command. Higgins JPT, Thompson SG, Spiegelhalter DJ. These are the connections between a pair of interventions of interest that involve exactly one common comparator. Care needs to be taken using this method because it is more statistically complex than a standard meta-analysis. BMC Medicine 2013; 11: 159. Inconsistency Salanti and colleagues propose to create a common domain to consider jointly both types of inconsistency that may occur: heterogeneity within direct comparisons and incoherence. Journal of Clinical Epidemiology 2011; 64: 163171. Any set of studies that links three or more interventions via direct comparisons forms a network of interventions. It then introduces the notion of transitivity (and its statistical analogue, coherence) as the core assumption underlying the validity of an indirect comparison. Background. Each line connects the estimated probabilities of being at a particular rank for every intervention. The relative ranking for two (competing) outcomes can be presented jointly in a two-dimensional scatterplot (Chaimani et al 2013). Transitivity requires that intervention A is similar when it appears in A versus B studies and A versus C studies with respect to characteristics (effect modifiers) that may affect the two relative effects (Salanti et al 2009). Journal of Clinical Epidemiology 1997; 50: 683691. We sought advice from experts in smoking cessation on the key dimensions that would influence the effectiveness of smoking cessation programmes. We obtain estimates for the other comparisons after the analysis using the coherence equations (see Section 11.2.3.2). a study that does not include the common reference intervention), a technique known as data augmentation can be used to allow the appropriate parameterization (White et al 2012). Sources and searches:Requires a large search to locate all of the trials using transparent & reproducible methods. This has three advantages compared with assuming comparison-specific heterogeneities. 2009). Acknowledgements: Lorne Becker contributed important insights in the discussion of separating Overview from Intervention Reviews with network meta-analysis. The two available approaches to evaluating confidence in evidence from a network meta-analysis acknowledge that the confidence in each combined comparison depends on the confidence in the direct and indirect comparisons that contribute to it, and that the confidence in each indirect comparison in turn depends on the confidence in the pieces of direct evidence that contribute to it. These have been implemented in the package netmeta in R (Schwarzer et al 2015). You would be better asking for advices on particular issues instead of presenting a whole reserch task that you seemingly expect others to perform. Abstract: Network meta-analysis involves synthesising the scientific literature comparing several treatments. Missing outcome data are a common threat to the validity of randomized trials and their meta-analysis, as they require making untestable assumptions. Annals of Internal Medicine 2015; 162: 777784. Network meta-analysis can yield estimates between any pairs of interventions, including those that have never been compared directly against each other. Meta-analysis is a statistical technique for combining the results from several sim. A detailed description of the concepts and the implementation of this approach is available (White et al 2012). 2011. However, it is usually the case that several, perhaps even numerous, competing interventions are available for any given condition. Higgins JPT, Whitehead A. In such cases, excluding placebo would result in ignoring a considerable amount of indirect evidence. Research Synthesis Methods 2012; 3: 161176. Emphasis is placed on practical issues of applying and presenting NMA. Then, the variables in the analysis should be specified by typing the command < network setup d n, studyvar (study) trtvar (trt) ref (A)> . Assessing the Feasibility of a Network Meta-Analysis (. Sometimes these characteristics are associated with the effect of an intervention. Figure 11.4.a Network graph of four interventions for heavy menstrual bleeding (Middleton et al 2010). In large networks, many loops with comparable influence may exist and it is not clear how many of those equally influential loops should be considered under this approach. Ades AE, Caldwell DM, Reken S, Welton NJ, Sutton AJ, Dias S. Evidence synthesis for decision making 7: a reviewers checklist. Sometimes observational data from non-randomized studies may form a useful source of evidence (see Chapter 24). This can be formally tested via a Chi2 statistic test which is available in Stata in the network macro (White 2015). Hysterectomy versus first generation hysteroscopic techniques), the heterogeneity among studies in the network as a whole is larger than the heterogeneity within the direct comparison, and therefore some uncertainty is added in the network estimates (see Section 11.4.3.2). In this paper we aim to make the methodology accessible to non-statisticians by presenting and explaining a series of graphical tools via worked examples.
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