Algorithmic parameterization of mixed treatment comparisons

摘要

Mixed Treatment Comparisons (MTCs) enable the simultaneous meta-analysis (data pooling) of networks of clinical trials comparing >2 alternative treatments. In-consistency models are critical in MTC to assess the over-all consistency between evidence sources. Only in the ab-sence of considerable inconsistency can the results of an MTC (consistency) model be trusted. However, inconsis-tency model specification is non-trivial when multi-arm tri-als are present in the evidence structure. In this paper, we define the parameterization problem for inconsistency mod-els in mathematical terms and provide an algorithm for the generation of inconsistency models. We evaluate running-time of the algorithm by generating models for 15 published evidence structures.