Network Meta-Analysis for Decision-Making

8Meta-Regression for Relative Treatment Effects

8.1 Introduction

Heterogeneity in relative treatment effects is an indication of the presence of effect-modifying covariates, in other words of interactions between the treatment effect and trial-level or patient-level variables whose distribution might vary across included trials. A distinction is usually made between (i) true clinical variability in treatment effects due to variation between patient populations, protocols or settings across trials and (ii) biases related to methodological flaws in the way in which trials were conducted.

Clinical variability in relative treatment effects is said to represent a threat to the external validity of trials (Rothman et al., 2012) and limits the extent to which one can generalise trial results from one situation to another. The trial may deliver an unbiased estimate of the treatment effect in a certain setting, but it may be ‘biased’ with respect to the target population in a specific decision problem (Chapter 1). Careful consideration of inclusion and exclusion criteria can help to minimise this type of bias, but often at the expense of having little or no evidence to base decisions on. That is, if inclusion criteria are too strict, the majority, or even all, of the evidence may be discarded as ‘not relevant’, leaving no synthesis option. On the other hand, inclusion criteria that are too broad risk pooling populations with very different relative treatment effects, thus inducing a ...