blog_19_10_2020

Clinical research requires various specialized tools of analysis. One of the most common or popular forms of analysis used to systemic reviews that use explicit, pre-specified methods to identify, appraise, and synthesize available evidence related to a clinical question. Meta-analysis evaluation is a type of systemic analysis that play an important role in clinical decision making. Some meta-analysis research compares only two interventions where a conventional pair-wise meta-analysis may be conducted(ranging from a 2-D to a multidimensional analytical framework); while network meta-analysis is resorted to examining the comparative effectiveness of many or all available interventions for a given condition.

What is Network meta-analysis (NMA)?

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Network meta-analysis is known by various names such as MTC Meta-analysis, Multiple Treatment Meta-analysis, Mixed Treatments Comparison, Multiple Treatments Comparison, Pair-Wise Meta-analysis, Indirect Treatment Comparison, Multiple Treatment Comparison Meta-analysis, Live Cumulative Network Analysis. Basically, Network meta-analysis is used to compare multiple interventions simultaneously by analyzing studies making different comparisons in the same analysis. Network meta-analysis helps expand the scope of a conventional pair-wise meta-analysis by simultaneously analyzing both direct comparisons (interventions within Randomized Controlled Trials (RCTs)) and indirect comparisons (across trials based on a common comparator like placebo or some standard treatment).

Key features of NMA:

The key features of network meta-analysis are that it must be evidence-based and the reviewing process also should be designed and registered as per the guidelines at hand. Conventionally, the Bayesian framework is considered to be the most popular and accepted framework for NMA as it allows better robust modeling that can easily be adjusted for simpler evidence networks. The selection of studies is a critical part of NMA as any Network meta-analysis research with insufficient data or test cases does not give convincing results.

Pros and Cons of NMA

Network meta-analyses are best designed for:

  • Conditions with multiple interventions or many combinations of direct or indirect interactions
  • To make treatment estimates for an entire treatment network instead of scanning each individual pair-wise comparison
  • To give the “full picture” to clinicians who gain precision by considering all available evidence
  • Potential to more explicitly “rank” treatments using summary outputs

Some of the pitfalls to be wary of are:

  • Requires specialist statistical expertise and software for analysis
  • Assumes that all interventions included in the “network” are equally applicable to all populations and contexts of the studies included.
  • Maybe skewed as it risks introducing study selection bias.
  • It involves complex methodological approaches that may not be suitable for inexperienced researchers
  • Inexperienced researchers may fault in the limited interpretation of indirect evidence; limited interpretation of the ranking analysis
  • Only specific situations require the network meta-analysis and inappropriate use of network meta-analysis can lead to misleading results
  • It is still an evolving method and the norms are still being developed and finalized

As always, it is advisable to resort to professional Scientific Research services and Medical Writing Services while undertaking such complex exercises.

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