Journal Article

Causal inference and adjustment for reference-arm risk in indirect treatment comparison meta-analysis

Swallow, Elyse, Ayyagari, Rajeev, Pelletier, Corey, Patterson-Lomba, Oscar, Signorovitch, James, Mehta, Rina

2020

Overview

To illustrate that bias associated with indirect treatment comparison and network meta-analyses can be reduced by adjusting for outcomes on common reference arms. Approaches to adjusting for reference-arm effects are presented within a causal inference framework. Bayesian and Frequentist approaches are applied to three real data examples. Reference-arm adjustment can significantly impact estimated treatment differences, improve model fit and align indirectly estimated treatment effects with those observed in randomized trials. Reference-arm adjustment can possibly reverse the direction of estimated treatment effects. Accumulating theoretical and empirical evidence underscores the importance of adjusting for reference-arm outcomes in indirect treatment comparison and network meta-analyses to make full use of data and reduce the risk of bias in estimated treatments effects. Indirect treatment comparisons (ITCs) and network meta-analyses (NMAs) can help decision makers compare therapies that lack head-to-head randomized trials. However, these estimates are vulnerable to biases due to cross-trial differences in patient characteristics and other factors. In this study, we outline methods to reduce biases associated with ITC/NMA and apply them to three real-world examples (antiretroviral therapy for human immunodeficiency virus, treatments for Type 2 diabetes and biological treatments for psoriasis). Our results show that reference-arm adjustment can have a significant impact on indirectly estimated treatment effects and can improve consistency between indirect evidence and gold-standard evidence from randomized trials. ITC and NMA without reference-arm adjustment present an avoidable risk of misleading or biased treatment effects. We argue that reference-arm adjustment should always be considered and reported when feasible in ITC and NMA.

• Publisher: Future Medicine Ltd
• Subject: Bayes Theorem / Bayesian approach / Bias / causal inference / Clinical trials / Delivery of Health Care - standards / Estimates / Frequentist approach / Humans / indirect treatment comparison / Meta-analysis / Models, Theoretical / network meta-analysis / Network Meta-Analysis As Topic / reference-arm adjustment / Research Design - standards / treatment effect / Treatment Outcome