Description
Meta-analyses are often used to synthesise evidence from multiple studies in order to decide which treatment is most effective (or cost-effective) out of several alternatives. Often, more than two treatments are available and several measures are used to assess patients’ response to treatment (outcomes). It is common for randomised trials to report more than one outcome of interest, but different trials may report a different combination of outcomes. Separate meta-analyses of each pair of treatments by outcome, each typically using different sets of randomised controlled trials, is data- and time-inefficient and can lead to conflicting conclusions. Network meta-analysis (NMA) has been proposed to compare multiple treatments for a single outcome and is now common in clinical applications. However, models that combine related outcomes in a single, coherent analysis are seldom considered.We will discuss the underlying data relationships that are assumed by NMA (which combine multiple treatments in a single analysis) and propose models that incorporate what is known about the relationships between different relative treatment effects across outcomes. This will be illustrated by some key examples where more precise and coherent estimates of treatment effects are obtained when all relevant evidence is included in a joint analysis.
The availability of individual participant data (IPD) allows estimation of the within-study relationships between different outcomes for the same participant, leading to potentially better inferences.
The implications of a framework that makes best use of all available evidence (i.e. including all relevant treatments and outcomes) for the usual process of systematic review and meta-analysis will be discussed.
Period | 7 May 2021 |
---|---|
Event title | Management of Urinary Tract Infections in the Practice: How to achieve the best use of evidence? |
Event type | Conference |
Location | Wurzburg, GermanyShow on map |
Degree of Recognition | International |
Documents & Links
Related content
-
Projects
-
HOD1: Inferring relative treatment effects from combined randomised and observational data
Project: Research project (funded) › Research