Stability of additive treatment effects in multiple treatment comparison meta-analysis: a simulation study

Many medical interventions are administered in the form of treatment combinations involving two or more individual drugs (eg, drug A + drug B). When the individual drugs and drug combinations have been compared in a number of randomized clinical trials, it is possible to quantify the comparative effectiveness of all drugs simultaneously in a multiple treatment comparison (MTC) meta-analysis. However, current MTC models ignore the dependence between drug combinations (eg, A + B) and the individual drugs that are part of the combination. In particular, current models ignore the possibility that drug effects may be additive, ie, the property that the effect of A and B combined is equal to the sum of the individual effects of A and B. Current MTC models may thus be suboptimal for analyzing data including drug combinations when their effects are additive or approximately additive. However, the extent to which the additivity assumption can be violated before the conventional model becomes the more optimal approach is unknown. The objective of this study was to evaluate the comparative statistical performance of the conventional MTC model and the additive effects MTC model in MTC scenarios where additivity holds true, is mildly violated, or is strongly violated.