Evidence synthesis for decision making 1: introduction

Abstract

We introduce the series of 7 tutorial papers on evidence synthesis methods for decision making, based on the Technical Support Documents in Evidence Synthesis prepared for the National Institute for Health and Clinical Excellence (NICE) Decision Support Unit. Although oriented to NICE's Technology Appraisal process, which examines new pharmaceutical products in a cost-effectiveness framework, the methods presented throughout the tutorials are equally relevant to clinical guideline development and to comparisons between medical devices, or public health interventions. Detailed guidance is given on how to use the other tutorials in the series, which propose a single evidence synthesis framework that covers fixed and random effects models, pairwise meta-analysis, indirect comparisons, and network meta-analysis, and where outcomes expressed in several different reporting formats can be analyzed without recourse to normal approximations. We describe the principles of evidence synthesis required by the 2008 revision of the NICE Guide to the Methods of Technology Appraisal and explain how the approach proposed in these tutorials was designed to conform to those requirements. We finish with some suggestions on how to present the evidence, the synthesis methods, and the results.

Keywords: Bayesian meta-analysis; cost-effectiveness analysis; systematic reviews.

Figure 1

Disconnected treatment network. Lines represent a comparison of the connected treatments in at least one trial. The network formed by treatments A, B, and C is not connected to the network formed by treatments X and Y.

Figure 2

Treatment network in which the treatments relevant for the decision and for synthesis differ. Lines represent a comparison of the connected treatments in at least one trial. Treatments relevant to the decision are in bold. (a) Treatment X has been added to the synthesis because it links treatment C to the rest of the network (dashed lines); (b) Treatment Y also links treatment C to the network and needs to be added to the synthesis (long-dashed lines).

Figure 3

Parkinson network. Each edge represents a treatment, and connecting lines indicate pairs of treatments that have been directly compared in randomized trials. The numbers on the lines indicate the numbers of trials making that comparison, and the numbers in brackets represent the treatment coding used in the analysis.

Figure 4

Mean lost work-time reduction on treatments for Parkinson’s disease relative to placebo. The horizontal lines represent the 95% credible intervals with the dot representing the posterior mean relative treatment effect. The vertical line represents no treatment effect.