Network meta-analysis: users’ guide for pediatricians

Abstract

BackgroundNetwork meta-analysis (NMA) is a powerful analytic tool that allows simultaneous comparison between several management/treatment alternatives even when direct comparisons of the alternatives (such as the case in which treatments are compared against placebo and have not been compared against each other) are unavailable. Though there are still a limited number of pediatric NMAs published, the rapid increase in NMAs in other areas suggests pediatricians will soon be frequently facing this new form of evidence summary.DiscussionEvaluating the NMA evidence requires serial judgments on the creditability of the process of NMA conduct, and evidence quality assessment. First clinicians need to evaluate the basic standards applicable to any meta-analysis (e.g. comprehensive search, duplicate assessment of eligibility, risk of bias, and data abstraction). Then evaluate specific issues related to NMA including precision, transitivity, coherence, and rankings.ConclusionsIn this article we discuss how clinicians can evaluate the credibility of NMA methods, and how they can make judgments regarding the quality (certainty) of the evidence. We illustrate the concepts using recent pediatric NMA publications.

Do osteoconductive bone substitutes result in similar bone regeneration for maxillary sinus augmentation when compared to osteogenic and osteoinductive bone grafts? A systematic review and frequentist network meta-analysis

“…Statistically, a NMA can be conducted using either a frequentist or Bayesian approach [15][16][17] . The frequentist NMA is what researchers will commonly encounter in single randomized controlled trials (RCTs) and conventional direct metaanalyses.…”

The relative effectiveness of psychotherapeutic techniques and delivery modalities for chronic pain: a protocol for a systematic review and network meta-analysis.

“…Pooled SMDs and 95% confidence intervals will respectively be used to quantify the magnitude of difference between each intervention type and the uncertainty surrounding these differences. Direct estimates will be generated based on interventions directly compared in trials, indirect estimates will be generated based on the results of direct estimates where intervention types that have not been directly compared share a common comparator, and network estimates will be generated through combining direct and indirect estimates ( Al Khalifah et al , 2018 ). A network forest plot and interval plot will be created to graphically represent the effect size of each included study.…”

Comparative effectiveness and safety of interventions for acute diarrhea and gastroenteritis in children: A systematic review and network meta-analysis

“…Heterogeneity, for the whole network, which considers the extent of inconsistency of results within each of the direct comparisons, was measured with the Tau 2 statistic. Transitivity is the assumption that an indirect comparison is a valid method to compare two treatments, because the studies are sufficiently similar in important clinical and methodological characteristics; in other words, that they are similar in their distributions of effect modifiers[27,28]. Coherence (also called consistency in NMA) is the assumption that the direct effect estimates and the calculated indirect estimates for a given comparison are similar[28,29].…”

“…Transitivity is the assumption that an indirect comparison is a valid method to compare two treatments, because the studies are sufficiently similar in important clinical and methodological characteristics; in other words, that they are similar in their distributions of effect modifiers[27,28]. Coherence (also called consistency in NMA) is the assumption that the direct effect estimates and the calculated indirect estimates for a given comparison are similar[28,29]. We explored potential causes of important heterogeneity, transitivity and incoherence via meta-regression assuming common fixed coefficient across comparisons for interventions vs. placebo/standard treatment (STND), sensitivity analyses and subgroup analysis.…”