Sharing information across patient subgroups to draw conclusions from sparse treatment networks
Theodoros Evrenoglou,
Silvia Metelli,
Johannes‐Schneider Thomas
et al.
Abstract:Network meta‐analysis (NMA) usually provides estimates of the relative effects with the highest possible precision. However, sparse networks with few available studies and limited direct evidence can arise, threatening the robustness and reliability of NMA estimates. In these cases, the limited amount of available information can hamper the formal evaluation of the underlying NMA assumptions of transitivity and consistency. In addition, NMA estimates from sparse networks are expected to be imprecise and possib… Show more
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