Network meta-analysis (NMA) has become an increasingly used tool to compare multiple treatments simultaneously by synthesizing direct and indirect evidence in clinical research. However, many existing studies did not properly report the evidence of treatment comparisons and show the comparison structure to audience. In addition, nearly all treatment networks presented only direct evidence, not overall evidence that can reflect the benefit of performing NMAs. This article classifies treatment networks into three types under different assumptions; they include networks with each treatment comparison's edge width proportional to the corresponding number of studies, sample size, and precision. In addition, three new measures (ie, the effective number of studies, the effective sample size, and the effective precision) are proposed to preliminarily quantify overall evidence gained in NMAs. They permit audience to intuitively evaluate the benefit of performing NMAs, compared with pairwise meta-analyses based on only direct evidence. We use four case studies, including one illustrative example, to demonstrate their derivations and interpretations. Treatment networks may look fairly differently when different measures are used to present the evidence. The proposed measures provide clear information about overall evidence of all treatment comparisons, and they also imply the additional number of studies, sample size, and precision obtained from indirect evidence. Some comparisons may benefit little from NMAs. Researchers are encouraged to present overall evidence of all treatment comparisons, so that audience can preliminarily evaluate the quality of NMAs.
Keywords: direct and indirect evidence; effective number of studies; effective precision; effective sample size; network meta-analysis.
© 2018 John Wiley & Sons, Ltd.