Define the review question and eligibility criteriaДЄ well-formulated, clearly defined, answerable research question guides the eligibility criteria and the overall research protocol. The following sections discuss methodologic challenges and research opportunities for network meta-analysis relevant to each aspect of the systematic review process. Aspects of designing and conducting the systematic review include defining the review question, specifying eligibility criteria, searching for and selecting studies, assessing risk of bias and quality of evidence, conducting a meta-analysis, and interpreting and reporting findings.

To minimize error and ensure validity of findings from meta-analyses, the systematic review, whether it involves a standard, pair-wise meta-analysis or a network meta-analysis, must be designed rigorously and conducted carefully.

Using statistical methods to combine findings from individual studies in a systematic review can provide useful information for clinical decision-making. But as for a conventional pair-wise meta-analysis, the methodology for network meta-analysis must be carefully developed and rigorously evaluated before the technique is applied widely. Many assumptions behind network meta-analysis methods appear to be similar to those made in standard pair-wise meta-analysis. Data structure of this type can be extended to k-comparisons to facilitate simultaneous inference regarding all available treatments, and to provide evidence for selecting the best of several treatment options. When both direct and indirect evidence are available, the two sources of information can be combined as a weighted average when appropriate. Indirect evidence can be obtained from RCTs of either A or C versus a common comparator B (Figure 1), keeping intact the randomized comparisons within the RCTs. In the simplest case, one may be interested in comparing two interventions A and C. When the comparative effectiveness of a range of interventions is of interest, appropriate statistical methodology must be used for analysis.ДЄlso called mixed treatments comparison or multiple treatments comparison meta-analysis, network meta-analysis expands the scope of a conventional pair-wise meta-analysis by analyzing simultaneously both direct comparisons of interventions within randomized controlled trials (RCTs) and indirect comparisons across trials based on a common comparator (e.g., placebo or some standard treatment). Some systematic reviews compare only two interventions, in which a conventional pair-wise meta-analysis may be conducted, while others examine the comparative effectiveness of many or all available interventions for a given condition. When appropriate, systematic reviews may include a meta-analysis, that is, the statistical combination of results from two or more separate studies.

Systematic reviews use explicit, pre-specified methods to identify, appraise, and synthesize all available evidence related to a clinical question. Since this commentary reflects the discussion at that meeting, it is not intended to provide an overview of the field. This commentary summarizes the methodologic challenges and research opportunities for network meta-analysis relevant to each aspect of the systematic review process based on discussions at a network meta-analysis methodology meeting we hosted in May 2010 at the Johns Hopkins Bloomberg School of Public Health. Aspects of designing and conducting a systematic review for network meta-analysis include defining the review question, specifying eligibility criteria, searching for and selecting studies, assessing risk of bias and quality of evidence, conducting a network meta-analysis, interpreting and reporting findings. To ensure validity of findings from network meta-analyses, the systematic review must be designed rigorously and conducted carefully. Network meta-analysis, in the context of a systematic review, is a meta-analysis in which multiple treatments (that is, three or more) are being compared using both direct comparisons of interventions within randomized controlled trials and indirect comparisons across trials based on a common comparator.

Comprehensive meta analysis v3