Aggregation of clinical evidence using argumentation: A tutorial introduction

Abstract

In this tutorial, we describe a new framework for representing and synthesizing knowledge from clinical trials involving multiple outcome indicators. The framework offers a formal approach to aggregating clinical evidence. Based on the available evidence, arguments are generated for claiming that one treatment is superior, or equivalent, to another. Evidence comes from randomized clinical trials, systematic reviews, meta-analyses, network analyses, etc. Preference criteria over arguments are used that are based on the outcome indicators, and the magnitude of those outcome indicators, in the evidence. Meta-arguments attack (i.e. they are counterarguments to) arguments that are based on weaker evidence. An evaluation criterion is used to determine which are the winning arguments, and thereby the recommendations for which treatments are superior. Our approach has an advantage over meta analyses and network analyses in that they aggregate evidence according to a single outcome indicator, whereas our approach combines evidence according to multiple outcome indicators.