Abstract
Network meta-analysis is increasingly used to allow comparison of multiple treatment alternatives simultaneously, some of which may not have been compared directly in primary research studies. The majority of network meta-analyses published to date have incorporated data from randomized controlled trials (RCTs) only; however, inclusion of non-randomized studies may sometimes be considered. Non-randomized studies can complement RCTs or address some of their limitations, such as short follow-up time, small sample size, highly selected population, high cost, and ethical restrictions. In this paper, we discuss the challenges and opportunities of incorporating both RCTs and non-randomized comparative cohort studies into network meta-analysis for assessing the safety and effectiveness of medical treatments. Non-randomized studies with inadequate control of biases such as confounding may threaten the validity of the entire network meta-analysis. Therefore, identification and inclusion of non-randomized studies must balance their strengths with their limitations. Inclusion of both RCTs and non-randomized studies in network meta-analysis will likely increase in the future due to the growing need to assess multiple treatments simultaneously, the availability of higher quality non-randomized data and more valid methods, and the increased use of progressive licensing and product listing agreements requiring collection of data over the life cycle of medical products. Inappropriate inclusion of non-randomized studies could perpetuate the biases that are unknown, unmeasured, or uncontrolled. However, thoughtful integration of randomized and non-randomized studies may offer opportunities to provide more timely, comprehensive, and generalizable evidence about the comparative safety and effectiveness of medical treatments.
Highlights
Many medical conditions exist for which there are multiple treatment options
We describe network meta-analysis (NMA) involving both randomized controlled trials (RCTs) and non-randomized comparative cohort studies—defined as cohort studies that compare two or more treatment alternatives using observational data
In other situations, the findings reported in the non-randomized studies do not align with those reported in RCTs
Summary
Many medical conditions exist for which there are multiple treatment options. Meta-analysis is a widely used approach for aggregating results from multiple studies to provide more robust evidence on the safety and effectiveness of various treatments [1]. Incorporating both types of data allows assessments of multiple treatments simultaneously, including treatments that may not have been studied in randomized controlled trials.
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