Argumentation for Aggregating Clinical Evidence
Anthony Hunter, Matthew Williams · 2010
Evidence-based decision making is becoming increasingly important in healthcare. Much valuable evidence is in the form of the results from clinical trials that compare the relative merits of treatments. For this, in previous papers, we have proposed a general framework for representing and synthesizing knowledge from clinical trials involving the same outcome indicator. Now, in this paper, we present a new framework for representing and synthesizing knowledge from clinical trials involving multiple outcome indicators. In this framework, evidence from randomized clinical trials, systematic reviews, meta-analyses, network analyses, etc., comparing a pair of treatments τ1and τ2according to desired and/or undesired outcomes is aggregated to give an overall evaluation of the treatments saying τ1is superior to τ2, or τ1is equivalent to τ2, or τ1is inferior to τ2. Our general framework incorporates inference rules for generating arguments and counterarguments for claiming that one treatment is superior to another based on the available evidence, and preference rules for specifying which arguments are preferred. In this paper, we also present a new version of this framework that incorporates utility-theoretic criteria for defining specific preference rules over arguments.