| Summary: | In this document we describe methods to detect inconsistency in a network meta-analysis. Inconsistency can be thought of as a conflict between "direct" evidence on a comparison between treatments B and C, and "indirect" evidence gained from AC and AB trials. Like heterogeneity, inconsistency is caused by effect-modifiers, and specifically by an imbalance in the distribution of effect modifiers in the direct and indirect evidence. Checking for inconsistency therefore logically comes alongside a consideration of the extent of heterogeneity and its sources, and the possibility of adjustment by meta-regression or bias adjustment (see TSD3). We emphasise that while tests for inconsistency must be carried out, they are inherently underpowered, and will often fail to detect it. Investigators must therefore also ask whether, if inconsistency is not detected, conclusions from combining direct and indirect evidence can be relied upon
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