Combining randomized and non‐randomized evidence in network meta‐analysis

• Published in: Statistics in medicine Vol. 36; no. 8; pp. 1210 - 1226
• Main Authors: Efthimiou, Orestis, Mavridis, Dimitris, Debray, Thomas P. A., Samara, Myrto, Belger, Mark, Siontis, George C. M., Leucht, Stefan, Salanti, Georgia
• Format: Journal Article
• Language: English
• Published: England Wiley Subscription Services, Inc 15.04.2017
• Subjects: Clinical medicine; Clinical Trials as Topic - statistics & numerical data; cohort studies; Data Interpretation, Statistical; Humans; Medical statistics; Meta-analysis; mixed treatment comparison; Models, Statistical; multiple treatments meta‐analysis; Network Meta-Analysis as Topic; observational data; observational evidence; observational studies; Randomized Controlled Trials as Topic - statistics & numerical data; Statistics as Topic; Treatment Outcome; cohort studies; observational evidence; mixed treatment comparison; observational data; observational studies; multiple treatments meta-analysis
• ISSN: 0277-6715; 1097-0258
• DOI: 10.1002/sim.7223

Non‐randomized studies aim to reveal whether or not interventions are effective in real‐life clinical practice, and there is a growing interest in including such evidence in the decision‐making process. We evaluate existing methodologies and present new approaches to using non‐randomized evidence in a network meta‐analysis of randomized controlled trials (RCTs) when the aim is to assess relative treatment effects. We first discuss how to assess compatibility between the two types of evidence. We then present and compare an array of alternative methods that allow the inclusion of non‐randomized studies in a network meta‐analysis of RCTs: the naïve data synthesis, the design‐adjusted synthesis, the use of non‐randomized evidence as prior information and the use of three‐level hierarchical models. We apply some of the methods in two previously published clinical examples comparing percutaneous interventions for the treatment of coronary in‐stent restenosis and antipsychotics in patients with schizophrenia. We discuss in depth the advantages and limitations of each method, and we conclude that the inclusion of real‐world evidence from non‐randomized studies has the potential to corroborate findings from RCTs, increase precision and enhance the decision‐making process. Copyright © 2017 John Wiley & Sons, Ltd.